Approaches to treat immune hot, altered and cold tumours with combination immunotherapies

Abstract

Immunotherapies are the most rapidly growing drug class and have a major impact in oncology and on human health. It is increasingly clear that the effectiveness of immunomodulatory strategies depends on the presence of a baseline immune response and on unleashing of pre-existing immunity. Therefore, a general consensus emerged on the central part played by effector T cells in the antitumour responses. Recent technological, analytical and mechanistic advances in immunology have enabled the identification of patients who are more likely to respond to immunotherapy. In this Review, we focus on defining hot, altered and cold tumours, the complexity of the tumour microenvironment, the Immunoscore and immune contexture of tumours, and we describe approaches to treat such tumours with combination immunotherapies, including checkpoint inhibitors. In the upcoming era of combination immunotherapy, it is becoming critical to understand the mechanisms responsible for hot, altered or cold immune tumours in order to boost a weak antitumour immunity. The impact of combination therapy on the immune response to convert an immune cold into a hot tumour will be discussed.

Introduction

The remarkable results achieved in the past few years with the advent of cancer immunotherapies and checkpoint inhibitors have revolutionized the field of oncology by putting the host immune response under the spotlight as a target for anticancer therapeutic interventions. The founding principles of the immunotherapy of cancer are threefold: first, the demonstration of immuno-surveillance using immune-deficient mouse models1,2; second, the demonstration of the major importance of pre-existing immunity and natural intratumoural T cells in humans3; and third, the unleashing of pre-existing immunity via inhibition of checkpoint receptors on T cells in human cancers4,5,6,7,8. Insight knowledge of the basic mechanisms responsible for the establishment and development of tumours, on the basis of their interaction with and control of the host immune system, has enabled us to draw a more comprehensive picture of the possible points of intervention and has provided us with reasons that might account for therapeutic failure. An update in the current guidelines for tumour classification and subsequent treatment is therefore becoming a pressing necessity. The recent yet unofficial classification of tumours into two categories, ‘hot’ and ‘cold’, has been increasingly advocated. In this Review, we aim to suggest a more comprehensive main four-category classification of tumours — hot, altered-excluded, altered-immunosuppressed and cold — and to provide an overview of both current and potential therapeutic strategies to best target these four categories of tumour, which in most cases involve combinatorial immunotherapy strategies. We believe that a rational, standardized and harmonized approach embracing the central role of the immune system must be adopted to guide therapeutic decisions. This adoption will require a general consensus and a large collective effort, as anything of great value.

Definition of hot and cold tumours

Current knowledge of the tumour–immune system interaction has already set the foundations for a rationally guided stratification of patients and therapeutic strategies. A powerful concept for patient stratification came with the observation that the type, density and location of immune cells within the tumour site could predict survival in colorectal cancer (CRC) more accurately than the classical TNM system for the first time in any type of cancer9. This concept led to the development and implementation of the Immunoscore3,10,11,12,13 — a robust, consensus, standardized scoring system based on the quantification of two lymphocyte populations (CD3 and CD8) both at the tumour centre and the invasive margin14,15. The Immunoscore ranges from Immunoscore 0 (I0, for low densities, such as absence of both cell types in both regions) to I4 (high immune cell densities in both locations). By classifying cancers according to their immune infiltration, the system proposed for the first time an immune-based, rather than a cancer-based, classification of tumours3, de facto introducing the notion of ‘hot’ (highly infiltrated, Immunoscore I4) and ‘cold’ (non-infiltrated, Immunoscore I0) tumours (Fig. 1). Tumour progression (T stage) and invasion (N stage) were dependent on the pre-existing adaptive intratumour immunity3,9. The consensus Immunoscore has been validated globally in colon cancer and has a greater relative prognostic value than pathologic T (pT) stage, pN stage, lymphovascular invasion, tumour differentiation and microsatellite instability (MSI) status16.

Fig. 1: Defining ‘hot’, ‘altered’ and ‘cold’ immune tumours — Immunoscore as a new approach for the classification of cancer.
figure1

a | Illustrative example of hot, altered and cold immune tumours. Brown (3,3ʹ-diaminobenzidine (DAB)) staining represents CD3+ T cells and blue (alkaline phosphatase) counterstaining provides homogeneous tissue background staining. The level and spatial distribution of CD3+ and CD8+ T cell infiltration differentiates four distinct solid tumour phenotypes: hot (or inflamed); altered, which can be excluded or immunosuppressed; and cold (or non-inflamed). These tumour phenotypes are characterized by high, intermediate and low Immunoscore, respectively. b | Schematic representation of the four subtypes of immune tumour. Of note, in altered-excluded tumours, CD3+ and CD8+ T cell infiltrates are low at the tumour centre and high at the invasive margin, resulting overall in an intermediate Immunoscore. Altered-immunosuppressed tumours display instead a more uniform pattern of (low) CD3+ and CD8+ T cell infiltration. CT, centre of tumour; Hi, high; IM, invasive margin; Lo, low.

On the basis of these findings, the novel concept of ‘immune contexture’ was proposed13 and adopted to refer to the combination of immune variables associating the nature, density, immune functional orientation and distribution of immune cells within the tumour13. These immune contexture parameters are associated with long-term survival and prediction of response to treatments10. In 2009, Camus et al. first described three major immune coordination profiles (hot, altered and cold) observed within primary CRCs, which enabled classification according to the balance between tumour escape and immune coordination17. The 2-year risk of relapse for these three types of tumour was 10%, 50% and 80%, respectively. The altered phenotype was further divided into two distinct patterns — ‘excluded’ and ‘immunosuppressed’17. In some cases, T cells are found at the edge of tumour sites (invasive margin) without being able to infiltrate them. This ‘excluded’ phenotype reflects the intrinsic ability of the host immune system to effectively mount a T cell-mediated immune response and the ability of the tumour to escape such response by physically hindering T cell infiltration (Fig. 1a). In other cases, tumour sites display a low degree of immune infiltration (Fig. 1a), which suggests the absence of physical barriers and the presence of an immunosuppressive environment that limits further recruitment17 and expansion18; this can be defined as an ‘immunosuppressed’ phenotype17. By more suitably simplifying the complexity of the tumour phenotype spectrum, these four characteristic subgroups can potentially represent a practical tool to direct therapeutic intervention (Box 1; Fig. 1b). Immunoscore proved to be a better prognostic tool for patients with CRC than MSI19, which is currently tested to predict the response of these patients to anti-programmed cell death protein 1 (PD-1) therapy20. A worldwide consensus Immunoscore study validated the prediction of risk of recurrence and survival on the basis of the three main subtypes of tumour — the immune hot, altered and cold tumours15,16.

Currently, the terms ‘hot’ and ‘cold’ are routinely used to refer to T cell-infiltrated, inflamed but non-infiltrated, and non-inflamed tumours, reflecting well the higher (I4) and lower (I0) Immunoscore categories3 (Fig. 1). This immune classification has been validated in other cancer types such as melanoma21. Apart from the presence of tumour-infiltrating lymphocytes (TILs), additional features such as the expression of anti-programmed death-ligand 1 (PD-L1) on tumour-associated immune cells, possible genomic instability and the presence of a pre-existing antitumour immune response have been described as characteristics of hot tumours22. Conversely, apart from being poorly infiltrated, cold tumours have also been described to be immunologically ignorant (scarcely expressing PD-L1) and characterized by high proliferation with low mutational burden (low expression of neoantigens) and low expression of antigen presentation machinery markers such as major histocompatibility complex class I (MHC I)22. In an attempt to propose a more simplistic yet comprehensive classification, the four proposed types of tumour (hot, excluded, immunosuppressed and cold), based on Immunoscore, could be the first routine immune parameters to evaluate at the time of diagnosis. Recently, a novel theory of cancer evolution at the metastatic stage was demonstrated and highlighted a model of tumour evolution in which a parallel immune selection exists, with a major role of Immunoscore and T cells in this process23. The fact that T cells are currently widely recognized as the key fighters in the antitumour battle makes the use of the Immunoscore an attractive option to help in guiding treatment selection. Of course, this option does not exclude the possible use of additional parameters, which in fact are required to gain further insights into the specifics of each case, but its routine incorporation into clinical practice could definitely relieve the existing, urging need for therapeutic guidance. The limitations associated with the current techniques for immune monitoring are discussed in Box 2.

Beyond hot, altered and cold tumours

The distinction between hot, altered (excluded and immunosuppressed) and cold tumours is based on the cytotoxic T cell landscape within a tumour. This powerful simplification reflects the outcome of a tremendously complex interplay between the tumour and the immune system. For instance, apart from T cells, high expression of markers of B and follicular helper T (TFH) cells was also correlated with a significantly prolonged disease-free survival time in patients with CRCs24. By secreting CXC-chemokine ligand 13 (CXCL13), TFH cells activate a positive loop that involves increased densities of B, TFH, T helper 1 (TH1), cytotoxic and memory T cells in breast cancer25 and CRC24. Acquisition of a memory phenotype by these adaptive immune cells long term can extend the survival of patients24.

The immune functional orientation associated with the immune contexture was first described in CRC and showed the major importance of T cells (TH1 and cytotoxic T cells) and associated factors (interferon-γ (IFNγ), granulysin (GNLY), perforin (PRF1) and granzymes (GZMs)3). These immune signatures were associated with prolonged survival and validated in other cancer types26,27,28,29,30,31. A similar T cell-inflamed gene expression profile exhibited predictive utility in identifying responders to treatment with an anti-PD-1 antibody32. These observations support the notion that these signatures are both prognostic and predictive10.

Activated lymphocytes, such as cytotoxic T cells, are among the main sources of IFNγ. By increasing MHC I and immunoproteasome expression in tumour cells, IFNγ enhances antigen presentation and subsequent immunosurveillance33. IFNγ also attenuates cancer cell growth, and it may exert pro-apoptotic and anti-proliferative effects via induction of several interferon-stimulated genes (ISGs)33,34, although these effects seem to be dose-dependent35. It should be noted that IFNγ can exert both antitumour and pro-tumour functions, depending on the cellular, microenvironmental and/or molecular context35,36,37. Furthermore, prolonged IFNγ signalling and enduring antigen exposure may also have an immunosuppressive role38,39, leading to T cell exhaustion and resistance to immune checkpoint blockade39.

CD4+ T cells also contribute to antitumour immunity. By expressing the transcription factor T-bet (also known as T-box transcription factor TBX21) and producing IFNγ, TH1 cells hinder neo-angiogenesis by inhibiting vascular endothelial growth factor (VEGF)-producing tumour-associated macrophages40 and promote the recruitment of CD8+ T cells41. A fine regulation of the genetic and epigenetic networks controlling TH1 responses is required for optimal T cell functioning42.

A series of immunosuppressive mechanisms also occur in the tumour microenvironment (TME), which hinder not only the natural host immune responses but also the efficacy of cancer immunotherapies. Two types of immunosuppression mechanism operate in the TME — a tumour-intrinsic and a local adaptive immunosuppression43. The former may be induced by genetic alterations of the tumour and involves the activation of various oncogenic pathways, including the WNT–β-catenin44,45, mitogen-activated protein kinase (MAPK)46,47, Janus kinase (JAK)–signal transducer and activator of transcription 3 (STAT3)48 and nuclear factor-κB (NF-κB)49 signalling pathways. The engagement of these pathways results in the expression of cytokines and chemokines that ultimately mediate the exclusion of T cells from the TME43, or, alternatively, the repression of factors that facilitate T cell recruitment44. Depending on the specifics of the case, the tumour-intrinsic immunosuppression can result in a cold or an altered (either excluded or immunosuppressed) tumour. In turn, the local adaptive immunosuppression is triggered by tumour-specific T cells that are infiltrated in combinations being tested in cold immune tumou tumours. By producing IFNγ, TILs can induce immune checkpoint molecules (such as PD-L1) or immunosuppressive factors such as indoleamine-pyrrole 2,3-dioxygenase 1 (IDO1). Thus, local adaptive immunosuppression can generate hot or immunosuppressed tumours, depending on the power of the driving mechanisms.

Great diversity in the TME composition exists across different cancer types but also among patients with the same cancer and even in different tumour sites within the same patient50,51. This diversity results from the combination of a multitude of factors, including the occurrence of specific driver mutations and deregulation of oncogenes in cancer cells44,52; the load and quality of passenger mutations in cancer cells19,53; the presence of immunosuppressive components in the TME, whether soluble (such as transforming growth factor-β (TGFβ)54) or cell-associated (such as PD-1 and/or PD-L1 (ref.55)); the presence of factors directing immune attraction24,56,57; and the presence of factors (such as interleukin 15 (IL-15)) that mediate the expansion and proliferation of cytotoxic CD8+ T cells18. This complex scenario is further complicated by the fact that the TME evolves with disease progression and recurrence24. Future studies will have to reveal advanced biomarkers to groups of patients who display similar features, thereby creating specific models that can guide the choice of therapeutic regimen as well as therapeutic development. Some of the challenges associated with the approaches used to characterize the TME are discussed in Box 2.

Unleashing the pre-existing immunity

Effectiveness of immunomodulatory strategies depends on the presence of a baseline antitumour immune response, involving either tumour-associated6,7,10,58,59,60,61,62 or circulating immune components8. Clinical response of human melanoma following treatment with monoclonal antibody (mAb) anti-PD-1 was dependent on immune reinvigoration of circulating exhausted CD8+ T cells (implying the pre-existence of an antitumour immune response) and pretreatment tumour burden8. This finding shows that even when in peripheral blood, pre-existing antitumour T cells can predict response. Immune checkpoint blockade inhibitors (ICIs) may trigger changes in the T cell receptor (TCR) repertoire and the expansion of specific clones of tumour-reactive T cells63. In patients with melanoma who responded to anti-PD-1 treatment, the comparison of the TCR repertoire before and after treatment revealed the emergence of TCR Vß subfamilies — which specifically recognize the melanoma antigen recognized by T cells 1 (MART1; also known as Melan-A) — that were undetectable before treatment64. This emergence could be due to an insufficient sensitivity to detect lowly expressed clones or to a de novo second wave of immune activation, with subsequent emergence of mutant neo-epitope-targeting T cells65. Preclinical studies demonstrated that PD-1 blockade cannot unleash antitumour T cell responses in the absence of fully primed and committed antigen-specific T cells66, and the presence of functionally impaired PD-1high tumour antigen-specific CD8+ T cells infiltrating the tumour has been described58. Furthermore, TCR β chain (TCRβ) deep sequencing revealed that clonally expanded tumour-reactive CD8+ TILs express PD-1 (ref.59). Altogether, this evidence strongly supports the existence of an in situ and/or peripheral antitumour immunity that confers clinical efficacy to subsequent checkpoint blockade.

There seems to be a general consensus on the central part played by effector T cells in the antitumour responses67. Upon recognition of antigenic peptides presented on the surface of cancer cells by MHC I–β2-microglobulin (β2m) complexes, CD8+ T cells kill target cells mainly by releasing cytotoxic factors such as PRF1, GNLY and GZM68. TBX21, STAT1, STAT4 and interferon regulatory factor 1 (IRF1) are among the main signalling molecules and transcription factors that regulate the production of these mediators that result ultimately in tumour rejection68,69. High T cell infiltrates in primary CRCs are associated with decreased metastatic invasion and increased overall survival70,71, and T cells are crucial for the clinical benefit of current immunotherapies. For example, the presence of CD8+ T cells at the tumour invasive margin is a prerequisite for the therapeutic success of PD-1 blockade in metastatic melanoma6, and proliferation of said CD8+ T cells in responding patients directly correlates with reduction in tumour size6. Furthermore, a high mutational burden in the TME correlated with the response to anti-PD-1 and anti-PD-L1 in melanoma, lung, MSI-positive CRC7,72 and several other cancer types32. By breaking tolerance, ICIs allow unleashing a pre-existing immune response to reject the tumour. However, they fail to reject the tumour in the absence of such a pre-existing response (for example, in excluded or cold tumours)6,73,74. Of note, the ‘quality’ of this pre-existing immunity also affects the response to ICI. For instance, the upregulation of alternative immune checkpoints (such as hepatitis A virus cellular receptor 2, HAVcr-2, also known as TIM3) following anti-PD-1 treatment confers adaptive resistance to therapy75,76. Indeed, in patients with renal cell carcinoma (RCC), inhibition of PD-1 alone could not rescue the functionality of CD8+ T cells that co-expressed PD-1 and TIM3 (ref.77).

As single agents, ICIs have response rates in the range 10–35%78. Indeed, at the time of diagnosis, most stage IV solid cancers are poorly infiltrated in primary tumours, if not non-infiltrated by T cells, possibly explaining the limited response to ICIs73. When used as adjuvant therapy for high-risk stage III melanoma, the anti-PD-1 mAb pembrolizumab resulted in significantly longer recurrence-free survival79. In an attempt to achieve increased clinical benefit of ICIs, an impressive amount of studies and clinical trials testing combinations of various immunotherapy agents, as well as combinations of immunotherapy agents with standard-of-care treatments, are currently under evaluation67 (Fig. 2). These have different likelihood of response based on pre-existing hot, altered or cold immune tumours (Fig. 1b).

Fig. 2: Overview of more than 2,000 immuno-oncology agents currently tested or in use.
figure2

a | Numbers of ongoing trials assessing therapies in combination with anti-programmed cell death protein 1 (PD-1) and/or PD-1 ligand (PD-L1). With ‘multi-combo’, we designate triple combinations, specifically, PD-1 and/or PD-L1 combined with radiochemotherapy, chemotherapy and targeted therapy, chemotherapy and immunotherapy, targeted therapy and immunotherapy or radiotherapy and immunotherapy (source: https://clinicaltrials.gov/). b | Number of immune-oncology (IO) agents currently in development, from preclinical phase to regulatory approval. c | Number of IO drugs in clinical trials sorted by mechanism of action and identifying six categories of IO agent. The ‘immune microenvironment agents’ category includes any immune modulator that does not belong to any other indicated category (for example, innate immune cell modulators). d | IO agents efficient in hot immune tumours (red circle), IO agent combinations likely efficient in altered immune tumours (yellow circle) and IO agent combinations being tested in cold immune tumours (blue circle). Nine (1–9) single or combinatorial approaches are illustrated to possibly treat hot, altered and cold tumours. Combo, combinational therapy.

Treating hot tumours with immunotherapy

T cell-targeting immunotherapies

By displaying a high degree of T cell infiltration, hot tumours represent a fertile ground for effective ICI-based monotherapy or combination therapy (Box 3; Fig. 3). Exhausted or dysfunctional TILs express a number of inhibitory receptors, most notably cytotoxic T lymphocyte-associated antigen 4 (CTLA4) and PD-1. CTLA4 inhibits T cells’ early activation and differentiation (typically in the lymph nodes) whereas PD-1 modulates their effector functions (mostly within tumours), which can lead to T cell exhaustion78,80. Strategies used to target CTLA4 and PD-1 and/or PD-L1 have now been approved by the US Food and Drug Administration (FDA) for the treatment of multiple cancers (Box 3). Hot (infiltrated) TME, TH1 immune signature and PD-L1 expression are features associated with increased response to anti-PD-1 or anti-PD-L1 monotherapy6,81,82. The non-redundant nature of CTLA4 and PD-1 makes them good targets for dual checkpoint blockade; indeed, anti-CTLA4–PD-1 dual therapy has been successful in the treatment of advanced-stage melanoma83, RCC84 and non-small-cell lung cancer (NSCLC)85, resulting in regulatory approval. It can be postulated that such combinations would be effective only in the context of hot or immunosuppressed tumours as they rely on a certain degree of T cell infiltration.

Fig. 3: The tumour–immune classification cycle as a tool to direct anticancer therapy.
figure3

Tumours can be classified into four main subtypes (hot, altered-excluded, altered-immunosuppressed and cold) according to their associated T cell (CD3+ and CD8+) presence and distribution. Hot tumours are defined by the simultaneous presence of immune contexture parameters: the cell type (CD3+, CD8+, follicular helper T (TFH), T helper 1 (TH1), memory and exhausted T cells); the location (invasive margin, tumour core and tertiary lymphoid structures); the density (immune density and quantity); and the functional immune orientation (chemokines, cytokines, cytotoxic factors, adhesion, attraction and TH1)10. The main components, pathways and features (in green trapezoids) of the immunogram have been identified and may represent potential targets (in blue). One or more of these features can be present at once in a specific tumour. Immunogenicity and adjuvanticity are tumour-intrinsic core characteristics that contribute to the shaping of the tumour-associated T cell landscape; we postulate that they are strikingly low or absent in cold tumours, although they may contribute to a certain extent to other subtypes. By representing a tool for the classification of a cancer into one of the four categories together with the identification of a specific defect or deregulated pathway, the spin chart could prove instrumental for building the most successful therapeutic scheme, and, conversely, narrow down the list of possible therapies by excluding potentially inefficient ones. ADORA2A, A2A adenosine receptor; β2m, β2-microglobulin; BET, bromodomain and extra-terminal motif proteins; BTLA, B and T lymphocyte attenuator; CAR T cell, chimeric antigen receptor T cell; CCR, CC-chemokine receptor; CIN, chromosomal instability, CSF1R, colony-stimulating factor 1 receptor; CTLA4, cytotoxic T lymphocyte-associated antigen; CXCL, CXC-chemokine ligand; DDR, DNA damage response; ECM, extracellular matrix; EMT, epithelial–mesenchymal transition; FDA, US Food and Drug Administration; FGFR3, fibroblast growth factor receptor 3; FOXP3, forkhead box P3; GITR, glucocorticoid-induced TNFR-related protein; GM-CSF, granulocyte–macrophage colony-stimulating factor; HDAC, histone deacetylase; HIF1α, hypoxia-inducible factor 1-α; HLA, human leukocyte antigen; HMA, hypomethylating agent; IAP, inhibitors of apoptosis family (also known as XIAP); ICAM1, intercellular adhesion molecule 1; ICD, immunogenic cell death; ICOS, inducible T cell co-stimulator; ICP, immune checkpoint; IDO, indoleamine 2,3-dioxygenase; IFN, interferon; IL, interleukin; LAG3, lymphocyte activation gene 3; LIGHT, tumour necrosis factor superfamily member 14; MAdCAM1, mucosal addressin cell adhesion molecule 1; MCL1, induced myeloid leukaemia cell differentiation protein Mcl1; MDSCs, myeloid-derived suppressor cells; MEK, mitogen-activated protein kinase kinase; MET, mesenchymal–epithelial transition; MSI, microsatellite instability; NK, natural killer; NOS1, nitric oxide synthase 1; PD-1, programmed cell death protein 1; PD-L1, PD-1 ligand; PI3Kγ, phosphoinositide 3-kinase-γ; PPARγ, peroxisome proliferator-activated receptor-γ; SIGLEC9, sialic acid-binding Ig-like lectin 9; STING, stimulator of interferon genes; TDO, tryptophan 2,3-dioxygenase; TGFβ, transforming growth factor-β; TIGIT, T cell immunoglobulin and ITIM domain; TIM3, T cell immunoglobulin and mucin domain-containing 3; TKI, tyrosine kinase inhibitor; TLR, Toll-like receptor; Treg cells, regulatory T cells; VCAM1, vascular cell adhesion molecule 1; VEGF, vascular endothelial growth factor; VISTA, V-domain Ig suppressor of T cell activation; XCL1, lymphotactin; XCR1, chemokine XC receptor 1. Lower case i following any acronym or abbreviation indicates inhibitor; lower case a following any acronym or abbreviation indicates agonist.

Another promising target to be considered in association with anti-PD-1 and PD-L1 strategies is lymphocyte activation gene 3 (LAG3), a co-inhibitory receptor on T cells that, among other functions, enhances activity of regulatory T (Treg) cells and regulates T cell proliferation, differentiation and effector function78. Whereas LAG3 blockade yields only modest efficacy as a monotherapy, its combination with anti-PD-1 has synergistic potential in preclinical models78. Other likely targets to combine with existing ICIs include additional co-inhibitory receptors such as TIM3 (a marker for exhausted T cells86); T cell immunoglobulin and ITIM domain (TIGIT, which counterbalances the co-stimulatory function of CD226, that is rapidly induced following T cell activation87); B and T lymphocyte attenuator (BTLA; also known as CD272), which is expressed by T cells and synergizes with herpesvirus entry mediator (HVEM; also known as TNFRSF14), expressed on antigen-presenting cells (APCs)88; V-domain Ig suppressor of T cell activation (VISTA, which mediates a compensatory inhibitory pathway following anti-CTLA4 therapy in prostate cancer89); and sialic acid-binding Ig-like lectin 9 (SIGLEC9), which is upregulated in TILs and possibly determines a subclass of tumour-specific CD8+ TILs90.

Alternatively, ICIs could be combined with co-stimulatory checkpoint molecules, such as OX40 antigen (also known as TNFRSF4 (or CD134)), TNFRSF7 (also known as CD27), CD28, TNFRSF9 (also known as 4-1BB ligand receptor or CD137) and glucocorticoid-induced TNFR-related protein (GITR), all of which enhance T cell expansion and effector functions while controlling Treg cell suppressive functions78,91. The notion that CD28 conveys the second signal required to complete T cell activation upon TCR engagement has been known for over three decades92. Recently, CD28, and not the TCR, has been shown to be the target of PD-1 signalling93 and thus to be required for efficient PD-1 therapies94. Apart from enhancing effector T function, CD28 blocks the suppressive function of Treg cells92, which suggests its potential as an anticancer therapy95. The first-in-human clinical trial testing a CD28 super-agonist was associated with a life-threatening cytokine release syndrome in all six subjects receiving the drug96, illustrating the need to fine-tune the dose and scheduling of these powerful immunotherapies. Another co-stimulatory immune checkpoint molecule, inducible T cell co-stimulator (ICOS), could also be a candidate owing to its expression on activated T cells. However, despite showing a promising profile in tumour mouse models97, its concomitant expression on Treg cells98 might limit its clinical impact. On the basis of preclinical evidence, the requirement for combinatorial immune checkpoint blockade could be bypassed by inhibiting the chronic interferon response, shown to mediate resistance to ICIs39. Altogether, albeit promising, the use of co-stimulatory molecules could be limited clinically by systemic toxicity due to important off-tumour effects.

Microbiome modulation

Antibiotics can inhibit the clinical benefit of ICIs in patients with advanced-stage cancer, and a correlation between clinical responses to ICIs and the relative abundance of the Gram-negative commensal bacterium Akkermansia muciniphila has been demonstrated99. Therefore, selective modulation of gut microbiome composition might overcome resistance to ICIs99,100. Abundance of ‘good’ bacteria, including those belonging to the Faecalibacterium genus101, correlated with a higher number of effector CD4+ and CD8+ T cells in peripheral blood and with response to anti-PD-1 mAbs in patients with melanoma101. Conversely, non-responders had a higher abundance of members of the Bacteroidales order, which correlated with higher frequencies of Treg cells and myeloid-derived suppressor cells (MDSCs) in the systemic circulation101. Mice that received faecal microbiota transplantation from responding patients showed an upregulation of PD-L1, which suggested that the ‘right’ microbiota could help in the development of a hot TME101. Another study on metastatic melanoma demonstrated the significant association between commensal microbial composition and clinical response to anti-PD-1-based immunotherapy102.

It is unlikely that the modulation of the microbiota alone would work in an altered or cold tumour; nonetheless, the presented evidence suggests that fairly simple lifestyle changes and/or oral supplementation of good bacteria could shape a favourable stage for subsequent immune-based therapies, which could be effective in the context of hot tumours or possibly in combination with other agents in altered or cold tumours.

Treatment of immune-altered tumours

T cell trafficking modulators

In excluded tumours, an accumulation of CD8+ T cells occurs at the tumour borders. This phenomenon indicates the ability of the host to mount a T cell-mediated immune response and the physical inability of the T cells to reach the tumour bed (Fig. 1). Many explanations for this phenotype can be proposed. One reason for T cell exclusion could be the lack of T cell-recruiting signals, such as chemokines directing T cell trafficking, including CXCL9, CXCL10, CXCL11, CXCL13, CX3C-chemokine ligand 1 (CX3CL1), CC-chemokine ligand 2 (CCL2) and CCL5 (refs57,103). This shortage of chemokines may result from the modulation of the oncogenic, genetic and epigenetic pathways that control their expression104. Histone modification and DNA methylation can repress the expression of TH1-derived CXCL9 and CXCL10 in ovarian105 and colon cancer106. Therapeutic epigenetic modulation promoted tumour infiltration of effector T cells, slowed tumour progression and improved the efficacy of PD-L1 blockade in preclinical models106,107. In metastatic melanoma, constitutive activation of the β-catenin pathway resulted in defective recruitment of CD103+ dendritic cells (DCs) into the TME and subsequent absence of CD103+ DC-derived CXCL9 and CXCL10 in hot tumours44. Of note, the cited studies rely on the more simplistic distinction of T cell-inflamed (hot) versus non-T cell-inflamed (cold) tumours. Therefore, it can be only postulated that between these two types, there could be cases of excluded tumours; however, it is tempting to speculate that these represent the cases in which the association of T cell tracking modulators with immunotherapy yields clinical benefit.

Activation of tumour-oncogenic pathways correlating with T cell exclusion has been described in muscle-invasive urothelial bladder cancer (MIUBC)108, usually characterized by poor outcome. Non-surprisingly, genes encoding PD-L1, IDO, FOXP3 (forkhead box P3; the master regulator of Treg cells), TIM3 and LAG3 were upregulated in T cell-inflamed MIUBCs, whereas an activation of β-catenin, peroxisome proliferator-activated receptor-γ (PPARγ) and fibroblast growth factor receptor 3 (FGFR3) pathways was found in the most common non-T cell-inflamed MIUBCs108.

A ‘sufficient’ T cell infiltration in mice tumour sites, rather than a differential PD-L1 expression, is critical for the response to anti-PD-L1 therapy109. On the basis of this assumption, it can be envisaged that strategies that facilitate the recruitment of T cells to excluded tumours could overcome tumour resistance to checkpoint blockade109. TNFSF14 (also known as LIGHT, or HVEM ligand) is an activator of lymphotoxin β-receptor signalling, which triggers the production of T cell-targeting chemokines, thereby creating a T cell-inflamed microenvironment109. Accordingly, the use of an antibody-guided LIGHT modulated the recruitment of T cells to the tumour site and overcame tumour resistance to ICIs109.

In summary, the epigenetic modulation of TH1-derived chemokines, as well as a blockade of β-catenin signalling, could turn excluded tumours into hot tumours, thus increasing the likelihood of success of concomitant immunotherapy.

Physical barrier breakers

Another explanation for the inability of T cells to penetrate tumour sites could be the presence of physical barriers. The development of abnormal structural features is a hallmark of cancer progression. Many extracellular matrix proteins are significantly deregulated during the progression of cancer, causing both biochemical and biomechanical changes possibly inhibiting immunity and promoting the metastatic cascade110. Changes in the tumour-associated vasculature (both blood and lymphatic) have been extensively described, as well as the resulting hypoxic milieu111,112. Tumour vasculature acts as an important barrier to T cells via the deregulation of adhesion molecules (such as intercellular adhesion molecule 1 (ICAM1), vascular cell adhesion protein 1 (VCAM1) and mucosal addressin cell adhesion molecule 1 (MAdCAM1)) required for T cell extravasation113,114. Hypoxia favours the establishment of an immunosuppressed TME, and ultimately cancer progression and treatment resistance, mostly acting through the hypoxia-inducible factor (HIF) family of transcription factors115. Among these, HIF1α not only can drive the expression of PD-L1 but also can increase adenosine generation and signalling116. The enzymatic activity of two ecto-nucleotidases, CD39 (also known as NTPDase I) and CD73 (also known as 5ʹ-nucleotidase), is responsible for the conversion of extracellular ATP to adenosine117. Adenosine accumulation in the TME exerts a plethora of pro-cancer effects117,118. CD73 blockade in several in vivo models significantly reduced tumour growth and metastatic spread119, and combination of CD73 blockade with ICIs has been proposed as an exploitable therapeutic strategy120. In turn, CD39 blockade prolonged survival in a lethal metastatic patient-derived sarcoma model121. However, deletion of CD39 resulted in autochthonous liver cancer in mice122, suggesting caution when using CD39 blocking agents. Nonetheless, agents that target CD39 are currently in the preclinical stage, whereas CD73 inhibitors are already being assessed in clinical trials123. Blocking the A2A adenosine receptor ADORA2A can restore immune competence and T cell proliferation in chronic lymphocytic leukaemia116. Therefore, HIF (mostly HIF1α and HIF2α) as well as CD73, CD39 and adenosine receptor inhibitors and/or mAbs have been developed as possible anticancer therapeutics, although thus far, no agent has reached regulatory approval123,124,125.

Hypoxia also exerts systemic effects via the secretion of growth factors and cytokines altering immune cell proliferation, differentiation and function111. One of these factors is the pro-angiogenic cytokine VEGF, which has been targeted by various pharmacological and immune-based antitumour strategies in the past decade112,126. VEGF-dependent effects extend beyond its angiogenic capabilities. For example, high expression of VEGFA inhibits the maturation of DCs, modulates TCR signalling and counteracts the beneficial effects of TH1 cells and cytotoxic T cells by suppressing the expression of IRF1 and GNLY, respectively127. Nonetheless, anti-VEGF and other angiogenesis inhibitors have not been successful as single agents, mostly owing to the development of a compensatory mechanism128. Furthermore, these inhibitors resulted in some cases in a somewhat counterintuitive increase in metastatic spread129,130. Despite these setbacks, evidence exists in support of the complementary therapeutic value of the normalization of the vascular abnormalities112, or vessel normalization. Vessel normalization is characterized by increased pericyte coverage, improved tumour vessel perfusion, reduced vascular permeability and subsequent reduced hypoxia131. Infiltration and activity of TH1 lymphocytes correlate with vessel normalization. In addition, TH1 activation by ICIs increased vessel normalization in various mouse models of breast cancer132, suggesting that a synergistic effect can be achieved by combining anti-angiogenic therapies with ICIs.

Soluble factor inhibitors

In the case of immunosuppressed tumours, tumour sites display a modest, insufficient degree of immune infiltration (Fig. 1), suggesting that the presence of an immunosuppressive environment, rather than that of physical barriers, limits further T cell recruitment17 and expansion18. IL-10 and TGFβ are among the best-characterized tumour-derived soluble factors impairing the development of an antitumour immune response133,134. As a matter of fact, IL-10 and TGFβ display both pro-tumour and antitumour abilities. This apparent contradiction can be explained by their numerous, yet not fully characterized, functions as well as by their different local versus systemic effects135,136. Therefore, they would not seem to constitute optimal molecular targets. Nevertheless, the recent evaluation of the combined inhibition of TGFβ and PD-L1 in multiple tumour types showed clinical benefit137. One of the characterized functions of IL-10 and TGFβ is their ability to disrupt DC differentiation, migration and antigen presentation, some of the crucial mechanisms required to mount an effective antitumour T cell response138,139. In the presence of this type of immunosuppression, CD40-activated B cells were suggested as alternative APCs owing to their resistance to IL-10, TGFβ and VEGF138.

A new therapeutic strategy aiming at improving the effector functions of T cells is based on the ionic reprogramming of tumour-specific T cells140. Tissue necrosis, common in solid tumours, releases potassium (usually intracellular) into the extracellular milieu, suppressing T cell effector functions141. This effect was mediated by a subsequent increase in intracellular potassium levels, inhibiting the TCR-driven AKT–mTOR pathway in a protein phosphatase 2-dependent manner140. By lowering intracellular potassium, the overexpression of the potassium channel Kv1.3 restored T cell effector functions, tumour clearance and survival in a melanoma mouse model140. These results show the potential of this alternative type of intervention as a further promising anticancer strategy.

Cellular modulators of local adaptive immunity

Two key cellular mediators of local adaptive immune suppression in the TME are MDSCs and Treg cells67. As both favour tumour progression, it is not surprising that strategies aiming at reducing their number are currently being explored. This seems to be somewhat feasible for MDSCs and has indeed been achieved by blocking their main suppressive pathways (IDO142, arginine, tryptophan and nitric-oxide-related pathways143,144,145), by regulating myelopoiesis or by preventing their trafficking67. Nonetheless, the recent failure of the phase III, randomized, double-blind study involving the combination of an IDO inhibitor plus a PD-1 blocking agent to yield greater clinical benefit than anti-PD-1 alone in unresectable or metastatic melanoma raises questions on the efficacy of these strategies146.

The selective targeting of the γ-isoform of phosphoinositide 3-kinase (PI3Kγ), highly expressed in myeloid cells, successfully reshaped the TME and promoted cytotoxic-T cell-mediated tumour regression in preclinical mouse models for several cancers147. The combination of this pharmacological approach with PD-1 blockade is currently under investigation in clinical trials147.

Blockade of colony-stimulating factor 1 receptor (CSF1R) could deplete the pro-tumoural macrophage population, in particular the M2 subtype, thus favouring the induction of a cytotoxic antitumour T cell response following PD-L1 blockade148. Clinical trials are ongoing to test the clinical activity of a combined treatment associating antibodies against CSF1R andanti-PD-L1 in patients with metastatic cancers148. Another example of modulation of tumour-associated myeloid cells can be found in the study by Nakhlé et al. on bladder tumours. In mouse models, targeting S100A9 — a zinc and calcium protein with a prominent role in the regulation of inflammatory processes and immune response — with tasquinimod, a regulator of MDSC accumulation, resulted in a re-education of tumour-infiltrating myeloid cells from a pro-tumoural M2 phenotype towards an antitumoural M1 phenotype149. The parallel increase in PD-L1 expression could explain the lack of tumour growth inhibition following treatment with tasquinimod as single therapy149 while simultaneously providing a solution to overcome this obstacle. Indeed, the combination of tasquinimod with an anti-PD-L1 antibody enhanced the antitumour immune response in preclinical bladder tumour models149. Along the same lines, the depletion of MDSCs induced a CD8+ T cell-dependent tumour rejection in mouse models of head and neck squamous cell carcinoma (HNSCC) when combined with anti-CTLA4 therapy150. The same study revealed the existence of an MDSC-rich gene expression profile with a T cell-inflamed phenotype in > 60% of patients in an HNSCC cancer cohort150. This observation reiterates the idea that a comprehensive characterization of the TME and its key components could prove to be tremendously useful in pinpointing the most promising therapeutic strategy.

The targeting and reduction of tumour-associated Treg cells remain quite challenging to achieve. Importantly, Treg cells express high levels of PD-1, which acts as a stimulatory receptor, rather than inhibitory, in these cells67, which may therefore reduce the benefits of an eventual anti–PD-1 antibody-based therapy67. Clinical approaches for Treg cell depletion have also not been very successful, having the downside of also reducing the tumour-suppressive Treg cells, critical for preventing autoimmunity. Crucially, Treg cells in the TME are not dysfunctional, in contrast to other TILs67.

A third, less characterized population of pro-cancer cells is represented by cancer stem cells, which are discussed in Box 4.

Innate immune response modulators

The lack of adequate innate immune response could constitute a limiting factor restraining the development of an effective adaptive, antitumour response, therefore originating an immunosuppressed tumour or contributing to the establishment of a cold tumour. One of the first indications of the activation of innate immune pathways in tumour settings came with the correlation between the expression of ISGs and T cell-associated transcripts in metastases from melanoma151. Indeed, a type I interferon signature predicted favourable clinical outcome in breast carcinoma following treatment with cancer vaccines152 and classic chemotherapy153. Type I interferons in tumours derive mostly from the activation of the stimulator of interferon genes (STING) pathway by cytosolic tumour-derived DNA within conventional, basic leucine zipper ATF-like transcription factor 3 (BATF3)-expressing, tumour-associated DCs. The pattern-recognition receptor cyclic GMP-AMP synthase (cGAS) recognizes cytosolic DNA, thereby stimulating the formation of the STING ligand cyclic-GMP-AMP154. These events culminate in the promotion of tumour-specific antigen (TSA) cross-presentation and T cell cross-priming by these cells155,156,157. Regression of established tumours and systemic antitumour responses were observed in preclinical models following intratumoural injection of a STING agonist158. Therefore, STING agonists are currently being tested in clinical trials159.

The modulation of the innate immune landscape within the TME represents a possible point of intervention in the case of T cell-infiltrated tumours that do not respond to ICI (such as immunosuppressed tumours). The local injection of a STING agonist in the tumour site, followed by treatment with an anti-PD-L1 antibody, was able to control, or completely reject, T cell-inflamed tumours in a mouse model of HNSCC149. Again, as the study refers to only hot and cold tumours, we can only assume that this case may fall into the category of an immunosuppressed tumour rather than that of a hot tumour. STING activation triggered the production of type I and II interferons and the accumulation of DCs in tumour-draining lymph nodes, boosting the T cell-mediated response; this came with a concomitant increase in the expression of PD-L1 in the TME149. The subsequent addition of an anti-PD-L1 mAb successfully removed the immunosuppressive status, thereby allowing the establishment of a local, as well as systemic, T cell-mediated antitumour activity149. Of note, the STING-agonist-mediated induction of type I interferon and accumulation of DCs in draining lymph nodes were not enough to mount an adaptive immune response in a parallel model of non-T cell-inflamed (cold) tumour149. Poor antigenicity or an intrinsic insensitivity to T cell killing in this model were proposed as possible explanations for these findings149. The potential of STING as an immune adjuvant that promotes the priming of tumour antigen-specific CD8 T cells has also been shown in murine tolerogenic HER2+ breast tumours160. In this study, the injection of a STING agonist in combination with PD-L1 blockade and OX40 activation resulted in tumour regression by providing priming and overcoming antigen-enforced immune tolerance160. It should be noted that also persistent type I interferons, just as IFNγ, can confer resistance to immune checkpoint blockade39, thereby suggesting possible setbacks of this therapeutic strategy.

Apart from the DNA sensor cGAS, various other pattern-recognition receptors, such as Toll-like receptors (TLRs), RNA helicase RIG-I-like receptors and NOD-like receptors have a role in endogenous stress signal recognition occurring in tumours161,162. Therefore, they are being investigated for their anticancer potential. TLRs are highly expressed by tumour-infiltrating immune cells, notably APCs, leading to their activation upon ligand stimulation. The upregulation of MHC II, CD80 and CD86 by TLR-stimulated APCs and their conversion from tolerogenic to immunogenic have been demonstrated in murine and human TMEs163,164. TLRs can also be expressed by tumour cells, in which they can exert direct cytotoxic effects upon stimulation165. Intratumoural injection of a TLR9 agonist reverted resistance to PD-1 blockade, resulting in durable and systemic tumour rejection in mouse models166. Similarly, intratumoural injection of TLR7 and TLR9 agonists, in combination with PD-1 blockade, suppressed primary tumour growth and prevented metastatic spread in HNSCC models167. Finally, intratumoural injection of a TLR9 ligand, combined with administration of an anti-OX40 antibody, successfully mediated regression even of a variety of histological tumour types, including that of spontaneous breast cancers168. The efficacy of TLR agonists has been investigated in multiple clinical trials169,170,171,172,173. When used as monotherapies, these agents yielded limited success174; however, combination strategies (for example, with anticancer vaccines) seem to be quite promising175,176,177.

Modulation of APC activation can be achieved by using agonist anti-CD40 mAbs. CD40 is a TNFRSF member mostly expressed on APCs. By interacting with its ligand on activated TH cells, it triggers APC activation and subsequent induction of adaptive immunity178. Agonistic anti-CD40 antibodies performed remarkably well in preclinical models of B cell lymphomas179 and bladder tumours180. There are multiple ongoing clinical trials involving CD40 agonists, and potential combinations with ICIs are being evaluated181.

The chemokine XC receptor 1 (XCR1) and its ligand lymphotactin (XCL1) regulate migration and function of CD103+CD11b DCs182,183,184. Intratumoural natural killer (NK) cells produce CCL5 and XCL1, thereby promoting DC recruitment in multiple human cancers and affecting patient survival184. Future anticancer strategies exploiting these newly discovered axes could prove successful.

The treatment of immune cold tumours

Cold tumours, characterized by low Immunoscore, are the most challenging to eradicate and are invariably associated with poor prognosis. A proposed approach to overcome the lack of a pre-existing immune response — and ultimately to turn cold tumours into hot tumours — is to combine a priming therapy that enhances T cell responses (such as vaccines, adoptive T cell transfer (ACT) or strategies that turn the tumour into a vaccine) with the removal of co-inhibitory signals (through approaches such as ICIs or MDSC depletion) and/or the supply of co-stimulatory signals (such as anti-OX40 or anti-GITR)67. The concern with this type of approach would be the concurrent increase in undesired side effects67, which is the case of most combinatorial therapies, surely requiring careful evaluation. In principle, it would make sense that a priming therapy would be beneficial in the case of non-inflamed, cold tumours, whereas inflamed, hot tumours would benefit more from immune interventions that counteract the tumour-induced T cell dysfunctions22,67. However, this black and white distinction of hot versus cold tumour is an oversimplification of an incredibly complex scenario. The introduction of the altered categories (excluded and immunosuppressed) may more suitably represent intermediate phenotypes. Hence, it is possible that some of the proposed approaches could in fact be effective only in the case of altered tumours. It is likely that the parallel occurrence of multiple pro-tumour mechanisms ultimately leads to the establishment of a cold tumour and combinatorial approaches are likely needed to achieve clinical benefit.

Radiotherapy

A promising priming therapy to be associated with subsequent immunotherapy is ionizing radiotherapy67,73. The currently achievable precise delivery of radiotherapy and the resulting induction of immunogenic cell death (ICD) pathways can potentially convert the tumour into an in situ vaccine67. The consequences of this approach not only involve the irradiated tumour site itself but can possibly contribute to the achievement of systemic tumour control through the so-called ‘abscopal effect67. The DNA released following the radiation-induced cell damage might trigger a STING-mediated type I interferon production, possibly by tumour-infiltrating CD8α+CD103+ DCs in mice (or their human counterpart CD141+ DCs185), a DC subset specialized in antigen cross-presentation186; this will then fuel a T cell-mediated antitumour immune response186,187. This process relies on a certain degree of infiltration of CD103+ DCs, which could be a limiting factor in cold tumours but may be effective in excluded tumours. A recently developed mouse melanoma model that lacks intratumoural CD8α+CD103+ DCs44 could shed light onto the ability of radiotherapy to prime T cell responses in non-infiltrated tumours. The combination of radiotherapy with further anti-immunosuppressive strategies could potentially increase the frequency of the abscopal effect. Indeed, combining radiotherapy with anti-CTLA4 mAbs in melanoma and NSCLC (which normally does not respond to anti-CTLA4) significantly improved the therapeutic outcome67. Additionally, maximal anti-CTLA4 therapy-driven abscopal responses in a mouse melanoma model was dependent on STING signalling188, further supporting the key role of STING and type I interferons in this context. The same study revealed a possible reason for the observed time frame (days rather than minutes) in which the radiation-induced inflammatory responses occur. In a classical model, the cGAS recognizes cytosolic DNA, then stimulates the formation of the STING ligand cyclic-GMP-AMP154. The revised model adds an extra level of complexity by showing that pattern recognitions occur within cGAS-containing micronuclei, which form and accumulate only following cell cycle progression through mitosis188. This dependence on actively cycling cells could possibly explain the observed delayed onset of inflammatory signalling upon radiotherapy and other DNA double-stranded-breaking therapies188.

By being readily available and free from patent rights, radiotherapy presents the risk of being used as a simple add-on to any immunotherapy, without a rationale defining dose, fractionation, sequencing and timing. A deeper knowledge on the molecular mechanisms triggered by different regimens of radiotherapy within the TME needs to be gained to carefully design efficient therapeutic schemes73. There are evident limitations in studying the effect of radiotherapy in mouse models, including the intrinsic radiosensitivity and immunogenicity differences and the choice of tumour implantation site73. Nonetheless, abscopal effects were observed in patients treated with anti-CTLA4 mAbs and undergoing radiation regimens similar to those regimes used in mice, highlighting the translational potential of mice studies in this context73. As tumours can develop different immune-evasion strategies, the choice of radiation regimen should be made according to the specifics of the case. For example, as a low dose of radiation promoted vascular normalization, such an approach could be useful in excluded tumours73.

A promising strategy to promote T cell infiltration into a cold tumour and convert it into a hot one came from a study by Zheng et al. on a pancreatic cancer mouse model189. Patients with CD8+Tlo PD-L1hi pancreatic cancer respond poorly to treatment with ICIs, vaccine or their combination, as well as to radiotherapy. The development of a murine model that mimicked CD8+ Tlo PD-L1hi pancreatic tumours enabled the demonstration that the sequential combination of radiotherapy, vaccination (with live cells expressing a model immunodominant antigen) and checkpoint inhibition (anti-PD-L1 mAb) resulted in tumour regression and improved survival compared with individual treatments or radiotherapy plus vaccination189. It is likely that the radiation enabled the recruitment of vaccine-primed T cells, which could exert their antitumour effects in a no-longer immunosuppressive microenvironment.

Despite the growing amount of information, the lack of sufficient preclinical data impedes a guided design of clinical trials, the results of which are often inconclusive in attributing a therapeutic benefit to radiotherapy. It would be challenging, yet crucial, to demonstrate unequivocally the contribution of radiation to immunotherapy response. An optimal integration of radiation biology with tumour immunology could give rise to potentially great clinical benefits190.

Chemotherapy

Anticancer agents can augment the immunogenicity of tumour cells through two main routes — the antigenicity191 and the adjuvanticity191,192 (Fig. 4). Genotoxic chemotherapies can induce mutations leading to the generation of neo-epitopes (therefore increasing the antigenicity). However, such neoantigens may be lowly expressed on tumour cells, thus having a modest impact on the immune response193. Nonetheless, chemotherapies that trigger an ICD — such as anthracyclines, cyclophosphamide, oxaliplatin and taxanes — can concomitantly increase the adjuvanticity by releasing damage-associated molecular patterns (DAMPs)194,195 and activating apoptotic or necroptotic pathways196. The calreticulin exposure at the membrane provides an ‘eat-me’ signal that favours the transfer of tumour-associated antigens (TAAs) to DCs197. Dying tumour cells can also stimulate a TLR3-dependent, cancer-cell-autonomous type I interferon response, which induces the local production of CXCL10, attracting T cells and memory T cells to the tumour bed56,153,198. Even if these ICD pathways have been elucidated only in mouse models, they might be clinically relevant. Indeed, chemotherapy modified the local immune microenvironment in patients with breast cancer199. Following neoadjuvant chemotherapy (NAC), these patients had an increased ratio of intratumoural CD8+ T cells to FOXP3+ cells200. This event was accompanied by a clonal expansion of antitumour T cells that correlated with response to NAC, followed by a complete pathological response200. After chemotherapy, the absence of autophagy-related protein LC3B (LC3B+) puncta and a low CD8+ to FOXP3+ cells ratio were associated with a bad prognosis in patients with breast cancer201,202. Low calreticulin levels on tumour cells correlated with a weaker immunosurveillance in ovarian cancer204 and NSCLC203,204. Low levels of antigen-specific circulating T cells were associated with poor clinical outcome in patients with acute myeloid leukaemia205,206. In CRC, neoadjuvant chemotherapy increased the adaptive immune response, and there was a significantly higher frequency of high Immunoscore metastases in patients achieving pathological and radiological responses50. Chemotherapy might also stimulate the activation of immune effectors through off-target effects, resulting in general immune stimulation207. Agents such as 5-fluorouracil deplete intratumour MDSCs208, whereas cyclophosphamide depletes Treg cells209 and triggers the translocation of immunostimulatory bacteria from the gut lumen to the damaged epithelium210. Effector T cells abrogate stroma-mediated chemoresistance in ovarian cancer211. IFNγ-producing CD8+ T cells may block cysteine and glutathione (both of which confer resistance to platinum-based chemotherapy) synthesis by fibroblast-associated tumour cells211. Altogether, these observations support the ever-growingly endorsed hypothesis that chemotherapy is not simply tumour suppressive but is also involved in the positive modulation of the immune system. It could be postulated that the beneficial effect of chemotherapy depends on the presence of an adaptive pre-existing immunity. In such a case, hot and altered immune tumours as measured by Immunoscore may be more susceptible to chemotherapy (as well as radiotherapy) than cold tumours212. Furthermore, this would constitute the rationale for coupling chemotherapy with ICIs. The success of the combination of anti-PD-1 therapy plus chemotherapy in metastatic NSCLC213 demonstrates the strength of this dual approach.

Fig. 4: Schematic representation of treatments of immune cold tumours.
figure4

The key factors or processes to be tackled to achieve clinical benefit are the following: priming the immune response (for example, with a neo-epitope cancer vaccine) (a); modulating the immune response (for example, with transforming growth factor-β (TGFβ) inhibitors) (b); expanding cytotoxic T cell proliferation (for example, with interleukin-15 (IL-15)) (c); inducing recruitment of cytotoxic immune cells (for example, by epigenetic modulation or the use of dendritic or T cell-recruiting chemokines) (d); breaking tolerance (using agents such as anti-programmed cell death protein 1 (PD-1) and/or PD-1 ligand (PD-L1) therapy) (e); inducing immunogenicity (for example, with an instability inducer, such as an inhibitor of MutL homologue 1 (MLH1)) (f); inducing immunological cell death (for example, by means of chemotherapy) (g); and inducing adjuvanticity (with an oncolytic virus) (h). CTL, cytotoxic T lymphocyte; MDSC, myeloid-derived suppressor cell; NK, natural killer; TAA, tumour-associated antigen; TFH, follicular helper T cell; TLS, tertiary lymphoid structure; Treg cell, regulatory T cell.

Targeted therapies

An insufficient TAA load could in principle impair the mounting of an efficient T cell-mediated immune response. Therefore, therapies that increase the antigenicity could prove beneficial in promoting the recruitment of T cells to tumour sites and the subsequent elimination of tumour cells (Fig. 4). Tumour antigenicity can be enhanced by therapies that favour the re-expression of TAAs, for example, DNA-demethylating agents (such as 5-azacytidine (AZA)) or epidermal growth factor receptor (EGFR) and MEK inhibitors214. AZA is a cytosine analogue and a potent DNA methyltransferase inhibitor that has been used for many years to treat myelodysplastic syndromes. The fact that it induced a late clinical response in some patients suggested the possible implication of the immune system in its mode of action215. In fact, AZA upregulated MHC I, β2m and cancer testis antigen genes, as well as genes involved in IFNγ signalling216. In ovarian cancer, AZA also induces a cytosolic double-stranded RNA-dependent type I interferon response by increasing the expression of DNA hypermethylated endogenous retroviruses (ERVs)217. AZA-induced ERV transcripts were found in melanoma218 and endometrial cancer cells219. Patients can be stratified according to their basal ERV levels and antiviral gene. A high antiviral gene signature was significantly associated with durable clinical responses in patients with melanoma treated with anti-CTLA4 therapy217.

Inhibitors of EGFR, RET kinase and MEK are broadly used in the current clinical routine, despite the lack of knowledge on their detailed molecular mechanisms of action. Their role as negative regulators of MHC I expression and antigen presentation machinery in multiple cancer types was revealed by a pooled short hairpin RNA interference-based analysis of the human kinome214. In vivo studies demonstrated that activated MAPK signalling inhibited components of MHC I and the antigen presentation machinery214. The use of MAPK inhibitors indeed enhanced the T cell-mediated killing of tumour cells214.

Proteins that prevent tumour cell apoptosis, including members of the inhibitor of apoptosis protein family220, MCL1 (ref.221) and mTOR222 (as well as IL-6 (ref.223)), represent further possible targets. Overall, given their ability to increase tumour antigenicity, these treatments may sensitize patients to further immunotherapies. This approach might be a well-suited option in the case of immunosuppressed tumours, which show potential for infiltration (no physical barriers) but insufficient T cell response. However, it may be not the most suitable choice in the case of cold tumours. In support of this hypothesis, a study by Spranger et al. in patients with melanoma demonstrated that no difference exists between inflamed and non-inflamed tumours in terms of antigenic load and/or mutational burden108. In this particular study, the lack of BATF3-lineage DCs may have been the cause for the ‘cold’ TME. An assessment of the mutational load within the tumour could provide a rational basis for the use of antigenicity-enhancing therapies.

The proteasomal machinery, which leads to the processing of peptides and their presentation on human leukocyte antigen (HLA) class I (MHC I) molecules, has been pinpointed as a novel exploitable point of intervention to increase antigenicity224. The set of epitopes presented for CD8 recognition are collectively termed the ‘immunopeptidome’. However, compelling evidence indicates that the proteasome hosts a more complex mechanism of epitope splicing, defined as proteasome-catalysed peptide splicing, by which the fusion of two non-contiguous peptidic segments generates novel epitopes224. The proteasome-generated spliced peptide pool accounts for one-third of the entire HLA class I immunopeptidome in terms of diversity and one-fourth in terms of abundance224. Intriguingly, this newly identified pool represents a unique set of antigens that bear distinguishing immunological characteristics224, which makes it an attractive target for future therapeutic manipulations.

DNA-repair-based therapy

High mutational and putative neoantigen load correlate with clinical benefit from immune checkpoint blockade therapy in lung cancer and melanoma225. Therefore, strategies that increase the burden of neoantigens in tumour cells could in principle be used in combination with subsequent checkpoint inhibition. This notion is supported by a recent mouse study by Germano et al. that involved the genetic inactivation of DNA mismatch repair (MMR) protein MutL homologue 1 (MLH1) in colorectal, breast and pancreatic cancer cells, ultimately inactivating the cellular DNA MMR mechanisms, thus inducing genomic instability and triggering immune surveillance226. Apart from highlighting the importance of neoantigen burden, this study points out the potential impact of strategies inhibiting the DNA damage response (DDR) in tumour cells226. The inhibition of the DDR has been previously proposed to sensitize cervical cancer cells to subsequent chemotherapy and/or radiotherapy, thereby contributing to the success of such treatments227. Numerous agents blocking DDR components, such as ATR serine/threonine kinase, ATM (ataxia telangiectasia mutated), checkpoint kinase 1 (CHK1), DNA-dependent protein kinase (DNA-PK), p38 MAPK and MAPK-activated protein kinase 2 (MK2), are currently being evaluated preclinically and clinically228.

Adoptive cell therapy

Engineered T cells that express artificial chimeric antigen receptors (CARs) targeting a tumour cell surface molecule were first produced in 1993 (ref.229), but only since 2010 have they revealed their true potential as anticancer agents230. CAR-T cell-based therapies rely on the isolation, ex vivo manipulation and expansion of antigen-specific T cells, which are subsequently transferred to the same patient (through adoptive cell therapy)231. This method has shown several potential advantages over conventional therapies, including specificity, rapidity, high success rate and long-lasting effects232. The two presently approved therapies, as well as most of the current clinical trials based on this technology, are directed against CD19, a classical B cell malignancy-associated antigen.

Typically, CARs are transduced into T cells from the patient using randomly integrating vectors233, which is a limitation of this system as it may lead to undesired effects such as oncogenic transformation, variable expression levels and transcriptional silencing234,235. To circumvent these limitations, Eyquem et al. directed a CD19-specific CAR to the TCR α constant (TRAC) locus by using CRISPR–Cas9-mediated genome editing, yielding a uniform CAR expression in human peripheral blood T cells236. By enhancing tumour rejection, such optimization of the CAR-T cell-based technology is an attractive option to adopt for future therapeutic designs.

A further optimization strategy to enhance the efficacy of adoptive T cell therapy was suggested by Hervas-Stubbs et al., and it relies on priming of naive CD8+ T cells with type I interferon237. Specifically, IFNα-primed CD8+ T cells show enhanced ability to persist and to mount a robust recall response compared with naive CD8+ T cells while preserving a low differentiation profile; in addition, they display heightened responsiveness to IL-15 and IL-7, which mediate T cell expansion and activation237. It could be envisaged that combing IFNα-primed ACT with subsequent cytokine (IL-15 and/or IL-7) administration might constitute a successful combinatorial therapy. Despite most studies on CAR T cells focusing on targeting CD19 (that is, B cell malignancies), a significant effort is being directed at identifying alternative candidates given the more limited success against solid tumours. TSAs would constitute ideal targets because their cognate T cells, unlike T cells targeting TAAs, would not trigger undesirable autoimmune reactions238. Epitopes carrying driver somatic mutations would be the best candidates as they are TSAs and are critically involved in the process of malignant transformation238. However, their limited mutation frequency and the restrictions offered by all the steps of the antigen presentation pathway make these tumour-specific mutated epitopes hard to target. The enlarged immunopeptidome spectrum recently revealed with the existence of spliced epitopes might therefore have a profound impact on the adoptive T cell therapy field238.

In a study by Verdegaal et al. that included two patients with stage IV melanoma, tumour-specific T cells were expanded by repeated stimulation with cell lines established from the resected lesion239. Albeit laborious, ACT proved to be effective, as both patients were long-term survivors. It should be noted that melanoma represents the solid cancer type with the best response to ACT thus far43. The ACT was also useful to analyse the stability of neoantigen-specific T cell responses and the antigens they are directed against239. The study revealed a highly dynamic environment, in which the T cell-recognized neoantigens selectively disappeared from the tumour cell population, with a concomitant development of neoantigen-specific T cells among the TILs239. Importantly, the authors suggested the occurrence of T cell-mediated neoantigen immunoediting; therefore, a broad neoantigen-specific T cell response should be sought to avoid tumour resistance239. In fact, this is a concept that should be considered in all strategies aiming at inducing neoantigen-specific immune responses — the broader, the better.

The crucial question at this point is whether ACT therapies will be able to overcome failed spontaneous T cell priming and convert cold into hot tumours. This question was addressed in a non-T cell-inflamed β-catenin-expressing murine melanoma model by Spranger et al.240. The study revealed failed trafficking of tumour-specific effector T cells that had been adoptively transferred into tumours owing to the absence of the T cell-recruiting chemokines CXCL9 and CXCL10 (ref.240). The same question was also addressed in patients with non-Hodgkin lymphoma undergoing anti-CD19 CAR-T cell therapy in a multicentre trial (ZUMA-1) and revealed that a stronger immune contexture predicted increased likelihood of response, supporting the notion that CAR-T cell therapy may not be enough by itself to treat patients with cold tumours241.

Taken together, these results further reiterate the idea that a deeper analysis of the TME and a consequent tumour classification are required before and/or during any therapeutic intervention.

Oncolytic therapy

Despite being known for nearly a century, the ability of viruses to kill tumour cells, and hence their therapeutic benefit in cancer patients, has been documented only recently in several clinical trials242. Oncolytic viruses are native or genetically modified viruses that selectively infect and replicate within tumour cells, eventually leading to tumour cell lysis242. Alongside this direct and local antitumour activity, oncolytic viruses can also induce a potent, systemic and potentially durable antitumour immunity242. The dying tumour cells release TAAs and additional DAMPs, thereby eliciting an efficient antitumour immune response242. In fact, the power of this approach lies in the ultimate engagement of systemic immunity, which results in therapeutic responses not only at the site of injection but also at distant tumour sites242.

Cancer cells represent a fertile environment for viral replication owing to their intrinsic abnormalities in the signalling pathways involved in cell stress and homeostasis and, possibly, in the antiviral machinery. The latter should be carefully considered in individual patients as disease-induced deregulation of the host-antiviral mechanisms can influence the therapeutic activity of the oncolytic viruses. For example, protein kinase R (PKR), which helps in the clearing of intracellular viruses, may be differentially expressed and/or activated in different cancer types242,243.

In order to be used therapeutically, oncolytic viruses have to be devoid of virulence factors yet retain their immunostimulatory abilities. Many viruses have been engineered accordingly and assessed in clinical trials, including adenoviruses, poxviruses, herpes simplex virus type 1 (HSV-1), coxsackieviruses, poliovirus, measles virus, Newcastle disease virus (NDV) and reovirus242. Many of the currently evaluated oncolytic viruses have a natural tropism for cell surface proteins overexpressed by cancer cells. Two examples are CD46 and HVEM, which are cell entry receptors for the Edmonton strain of measles virus and HSV-1, respectively242.

Talimogene laherparepvec (T-VEC) represents the first FDA-approved virotherapeutic approach for the localized treatment of patients with unresectable melanoma. As mentioned above, a potentially therapeutic strategy to ‘heat up’ cold tumours could lie in the use of an oncolytic virus as priming therapy, combined with the removal of co-inhibitory signals (Fig. 4). Indeed, T-VEC administration in combination with ipilimumab (an anti–CTLA4 antibody) in patients with unresectable stage IIIB–IV melanoma yielded greater antitumour activity than ipilimumab alone244. A phase Ib study using T-VEC followed by the anti-PD-1 antibody pembrolizumab in patients with advanced melanoma resulted in an outstanding response rate of 62%245. Patients who responded to treatment with T-VEC displayed increased CD8+ T cells, high mutational burden and high expression of PD-L1 protein and IFNG in several cell subsets in tumours245, suggesting the need for a pre-existing tumour-specific T cell pool for the anti-PD-1 therapy to be effective246. Importantly, this improved antitumour activity did not come at the expense of the safety profile244,245. Despite being highly encouraging, the percentage of responders to the combination treatment shows still room for improvement and further points of interventions should be envisaged. A possible reason for therapeutic failure could lie in the possible poor antigenicity (low TAAs) of cold tumours; in this case, virion-mediated lysis of cancer cells may not release enough TAAs to prime antitumour T cell responses. Vaccine-based therapy (discussed in the next section) may represent a more suitable option in this context.

Another intratumour therapeutic approach to achieve an abscopal effect is offered by the use of oncolytic peptides. The nine amino acid residue (9-mer) oncolytic peptide LTX-315 acts on both drug-resistant and drug-sensitive cancer cells, rather than healthy cells, thereby causing the lysis of their plasma and organelle membranes, which act as danger signals initiating an innate and subsequent systemic adaptive immune response247. The intratumour injection of LTX-315 resulted in a complete rejection of fibrosarcomas established in a rat model. This tumour rejection relied on T cell infiltration in both injected and distal tumour sites247.

Physical barriers (including necrosis, calcification, hypoxia, acidosis, increased proteolytic activity, high interstitial pressure, poor vascularization and/or dense extracellular matrix) may reduce the spread of oncolytic viruses, limiting their biodistribution and consequent therapeutic efficacy242. Although this limitation can be overcome in physically accessible tumours by intratumoural injections, the same factors could limit T cell trafficking and the establishment of a successful immune response. In other words, it is reasonable to hypothesize the existence of cases in which such priming therapy only ‘promotes’ a tumour to an altered (excluded in this example) phenotype; this will then additionally require not only an ICI but also an additional strategy (such as anti-VEGF) to become hot.

Vaccine-based therapy

After an initial identification of neoantigens from tumour cells, putative antigen or antigenic epitope or epitopes can be presented through a variety of platforms, such as whole tumour cell preparations, through MHC-specific peptides, whole or partial proteins encoded by RNA or DNA, or in recombinant viral or bacterial vectors expressed in DCs248. The use of additional vaccine adjuvants, such as TLR agonists, could boost the immune response against TAAs. Despite seemingly valuable, anticancer vaccines turned out to be quite disappointing, as proved by the low overall objective response rate obtained in numerous clinical trials248 (Fig. 2c). However, this lack of success translated into a quest for the reasons underlying this ineffectiveness. A key aspect to consider is that anticancer vaccines were tested in patients with established cancers, in which immunosuppressive mechanisms were already in place. Therefore, the increase in ICIs brought along a renewed interest in these therapeutic approaches248. Indeed, studies on ICIs highlighted the positive correlation of the somatic mutation burden and consequent emergence of neoantigens with clinical benefit225,249, providing a rationale for combination therapies involving ICIs and T cell priming anticancer vaccines (Fig. 4). ICIs would de facto play the part of vaccine adjuvants. It is tempting to speculate that future studies involving the combination of T cell boosting tumour vaccines with the T cell suppression-preventing ICIs may translate into clinical benefit in patients with cold tumours.

A challenging aspect of anticancer vaccination is finding the optimal antigen for vaccination. Among the possible candidates are overexpressed self-proteins (such as prostate-specific antigen (PSA)), differentiation antigens (such as protein Melan-A or gp100 (ref.250)) and mutated antigens (neoantigens)248. Thus far, there is only one FDA-approved vaccine, sipuleucel-T, for the treatment of asymptomatic or minimally symptomatic hormone-refractory prostate cancer. Sipuleucel-T consists of autologous DCs loaded with recombinant human fusion protein encoding the prostatic acid phosphatase (PAP) antigen (the expression of which increases with prostate cancer progression) and granulocyte–macrophage colony-stimulating factor (GM-CSF) to sustain DC maturation.

The selective detection of cytomegalovirus (CMV) antigens in certain types of tumour (such as glioblastoma (GBM)) but not in normal tissue suggested the opportunity to use immunological interventions that target these viral proteins. Accordingly, vaccination with CMV pp65 RNA-pulsed DCs was developed to treat GBM251. Unfortunately, this approach did not translate into higher clinical benefit than the standard of care251,252. However, a clear clinical benefit was observed when preconditioning the vaccine site with tetanus–diphtheria (Td) toxoid; such a potent recall antigen significantly improved lymph node homing and the efficacy of tumour antigen-specific DCs251. Interestingly, the blinded interim data of the overall patient population enrolled in a phase III randomized, double-blind, placebo-controlled clinical trial of an autologous tumour lysate-pulsed DC vaccine (DCVax-L) for newly diagnosed GBM revealed extended survival253. Saying that tumour vaccines could per se provide sufficient basis to convert a cold into a hot tumour is an overstatement, as this example clearly shows. Notwithstanding, it shows once again the power of a multifactorial approach and opens the intriguing perspective of exploiting past vaccinations against infectious diseases.

Other vaccines targeting defined tumours or TAAs are currently being evaluated as they present obvious advantages, including the possibility of mass production, easy monitoring of immune responses and a generally tolerable safety profile248.

The broad range of neoantigens and their positive association with improved clinical responses suggested their possible use for vaccination. Furthermore, as new epitopes appear continuously during tumour progression, immune editing and T cell suppression seem unlikely as they require time248. A neoantigen fitness model, which measured the likelihood of neoantigen presentation by the MHC and subsequent recognition by T cells, predicted survival in patients with melanoma treated with anti-CTLA4 therapy and patients with lung cancer treated with PD-1 blockade254. Newly identified low-fitness neoantigens could constitute ideal targets for developing novel cancer vaccines254. A difficulty of this approach is its intrinsic personalized nature — hence the bench-to-bedside time frame. Nonetheless, the development and optimization of high-throughput screening techniques and epitope-predicting algorithms may allow for such strategy. The recently reported RNA-based poly-neo-epitope approach used in 13 patients with melanoma made the concept of individualized mutanome vaccines a promising reality255. All patients completed treatment with a maximum of 20 neo-epitope vaccine doses, which were well tolerated, and developed T cell responses against at least three mutations, resulting in sustained progression-free survival255. This strategy identified a patient in which the combination of the vaccine and PD-1 blockade yielded a complete response. Another study demonstrated the feasibility, safety and immunogenicity of a vaccine that targets up to 20 predicted personal tumour neoantigens. Of six vaccinated patients, four had no recurrence at 25 months after vaccination, whereas two with recurrent disease were subsequently treated with anti-PD-1 treatment and experienced complete tumour regression, with expansion of the repertoire of neoantigen-specific T cells256. Apart from the undoubted merit of paving the way to personalized vaccine-based immunotherapy, this study supplied evidence of the potential of the combinatorial therapeutic approach with current immunotherapies.

T cell immunomodulators

Several cytokines (such as IL-2, IL-7, IL-15, IL-21, IL-12, GM-CSF and IFNα) are known to modulate T cell expansion, survival and/or function and were or are being tested in clinical trials as potential anticancer agents, in monotherapy or in combination257. IL-2 was the first cytokine to be characterized as a ‘T cell growth factor’ (TCGF) in 1976 (ref.258). IL-2 became an early candidate for cancer immunotherapy and showed promising results as a single agent in metastatic RCC and melanoma258. However, its pleiotropic effects on the immune system (notably, the targeting of Treg cells) as well as the severe associated side effects greatly reduced its importance as a single anticancer agent258. Combinations with traditional anticancer therapies as well as immunotherapies, including ACTs, have since been investigated but displayed similar limitations to the monotherapy. A renewed interest in IL-2 came with the development of a strategy to redirect the specificity of IL-2 towards adoptively transferred T cells259. By using orthogonal IL-2 cytokine–receptor pairs (mutant IL-2 and IL-2 receptor (IL-2R)), this approach enables selective expansion of desired T cells, with negligible off-target effects and toxicity259.

The IL-2-related cytokine IL-15 has lately attracted attention in the cancer immunotherapy field as it does not target Treg cells but NK cells and lacks other undesired features of IL-2 (ref.260). Reduced IL-15 expression due to chromosomal instability impaired the intratumoural T and B cell proliferation and correlated with higher risk of tumour recurrence and reduced survival of patients with CRC18, providing a clear indication of its key anticancer role. Current efforts aim at ensuring sufficient bioavailability, which is low at present owing to rapid renal clearance260. ALT-803 is a super-agonist of the IL-15–IL-15Rα complex that successfully prolonged the half-life of IL-15 and promoted enhanced immune activation in vivo261. ALT-803 was well tolerated and resulted in clinical responses in patients with haematological malignancies who relapsed after allogeneic haematopoietic cell transplantation261.

IL-7 is yet another potent growth, activation and survival factor for CD8+ T cells that could improve antitumour CD8+ T cell responses262. Owing to its features, it is not surprising that recombinant IL-7 (rIL-7) was considered as a tool to improve ACT263. Indeed, an ACT mouse model demonstrated the efficacy of rIL-7 in inducing CD8+ T cell proliferation and differentiation, and tumour rejection, in an IL-7R-dependent manner263. Combining T cell-modulating cytokines with other approaches could improve the therapeutic success. This possibility was demonstrated by an in vivo study that featured a modified NDV that co-expressed IL15 and IL7 (ref.264). Such a tumour vaccine displayed improved antitumour activity compared with a non-modified vaccine264.

IL-21 is a promoter of T cell responses265 and could be exploited for its potential antitumour activity. IL-21 counteracts the in vitro TGFβ1-induced FOXP3 expression in purified naive CD4 T cells, confirming its known additional ability to alleviate Treg-mediated immunosuppression in several cancers266. Apart from targeting T cells, IL-21 also regulates TFH (ref.267) and B cells265. Together with CXCL13, IL-21 is a crucial element regulating the TFH–B cell axis within the TME in CRC, and its presence correlated with increased patient survival24. In addition, Lewis et al. demonstrated the synergistic antitumour activity of IL-21 and anti-CTLA4 and/or anti-PD-1 therapy in various tumour models268. The decreased percentages of intratumour CD4+CD25+FOXP3+ T cells were accompanied by increased CD8+ T cell infiltrates, CD8+ T cell proliferation, increased levels of effector memory T cells and overall enhanced antitumour activity268. Combining the adoptive transfer of IL-21-primed, melanoma-reactive CD8+ T cells with anti-CTLA4 therapy controlled refractory metastatic melanoma in a patient269, showing the potential of IL-21 in combinatorial anticancer therapies.

Concluding remarks

The concept of personalized cancer immunotherapies has been ever-growingly advocated in recent years. Possibly the biggest challenge impeding the achievement of such an ambitious approach lies in the lack of a comprehensive knowledge of the cancer–immune interaction parameters; even when this knowledge is available, standardized methods of measuring most parameters are lacking. Accurate measurement of parameters is quite crucial, as their relative ‘weight’ varies considerably among individual patients62. It is clear that the identification of key features, immune-related or tumour-related, at the moment of diagnosis is needed to build a solid classification strategy supporting subsequent therapy. Here, we provide a panel of therapeutic strategies to be deployed or developed (if not yet available) against hot, altered and cold tumours. It is reasonable to assume that the colder the tumour is, the more approaches are needed. Interestingly, all proposed therapeutic designs ultimately involve combinations with immunotherapies to achieve maximal efficiency. Given the pivotal role of T cells against cancer, the careful assessment of the pre-existing T cell landscape and of the immune microenvironment should be routinely used to differentiate specific cases, not only in the clinical setting but also at the preclinical stage. This information could help in the translation of study findings in clinical indications.

References

  1. 1.

    Shankaran, V. et al. IFNgamma and lymphocytes prevent primary tumour development and shape tumour immunogenicity. Nature 410, 1107–1111 (2001).

  2. 2.

    Schreiber, R. D., Old, L. J. & Smyth, M. J. Cancer immunoediting: integrating immunity’s roles in cancer suppression and promotion. Science 331, 1565–1570 (2011).

  3. 3.

    Galon, J. et al. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science 313, 1960–1964 (2006). This article is the first demonstration of the dependence of tumour progression and invasion on the intratumoural adaptive immunity. T cell infiltrates and IFNγ signatures have predictive value superior to TNM with respect to the natural history of primary cancers.

  4. 4.

    Hodi, F. S. et al. Improved survival with ipilimumab in patients with metastatic melanoma. N. Engl. J. Med. 363, 711–723 (2010).

  5. 5.

    Topalian, S. L. et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N. Engl. J. Med. 366, 2443–2454 (2012).

  6. 6.

    Tumeh, P. C. et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 515, 568–571 (2014). This article shows that the baseline density and location at the invasive margin of T cells in metastatic melanomas predicts the treatment outcome of patients receiving PD-1-targeting therapies.

  7. 7.

    Van Allen, E. M. et al. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science 350, 207–211 (2015). This article is the first to show that patients with metastatic melanoma with high mutational burden, neoantigen load and expression of cytolytic markers in their tumours are more likely to respond to anti-CTLA4 immunotherapy.

  8. 8.

    Huang, A. C. et al. T cell invigoration to tumour burden ratio associated with anti-PD-1 response. Nature 545, 60–65 (2017).

  9. 9.

    Mlecnik, B. et al. Histopathologic-based prognostic factors of colorectal cancers are associated with the state of the local immune reaction. J. Clin. Oncol. 29, 610–618 (2011).

  10. 10.

    Galon, J., Angell, H. K., Bedognetti, D. & Marincola, F. M. The continuum of cancer immunosurveillance: prognostic, predictive, and mechanistic signatures. Immunity 39, 11–26 (2013).

  11. 11.

    Angell, H. & Galon, J. From the immune contexture to the Immunoscore: the role of prognostic and predictive immune markers in cancer. Curr. Opin. Immunol. 25, 261–267 (2013).

  12. 12.

    Galluzzi, L. et al. Trial watch: dendritic cell-based interventions for cancer therapy. Oncoimmunology 1, 1111–1134 (2012).

  13. 13.

    Galon, J., Fridman, W. H. & Pages, F. The adaptive immunologic microenvironment in colorectal cancer: a novel perspective. Cancer Res. 67, 1883–1886 (2007).

  14. 14.

    Pages, F. et al. In situ cytotoxic and memory T cells predict outcome in patients with early-stage colorectal cancer. J. Clin. Oncol. 27, 5944–5951 (2009).

  15. 15.

    Galon, J. et al. Towards the introduction of the ‘Immunoscore’ in the classification of malignant tumours. J. Pathol. 232, 199–209 (2014).

  16. 16.

    Pages, F. et al. International validation of the consensus Immunoscore for the classification of colon cancer: a prognostic and accuracy study. Lancet 391, 2128–2139 (2018). This article validates Immunoscore as a consensus and standardized cytotoxic T cell assay that defines immune hot, altered and cold tumours and has a greater prognostic value in CRC than T stage, N stage, lymphovascular invasion, tumour differentiation and MSI status.

  17. 17.

    Camus, M. et al. Coordination of intratumoral immune reaction and human colorectal cancer recurrence. Cancer Res. 69, 2685–2693 (2009). This paper presents the first description of the immune hot (optimal), altered-excluded, altered-immunosuppressed and cold (absent) tumours.

  18. 18.

    Mlecnik, B. et al. Functional network pipeline reveals genetic determinants associated with in situ lymphocyte proliferation and survival of cancer patients. Sci. Transl Med. 6, 228ra37 (2014).

  19. 19.

    Mlecnik, B. et al. Integrative analyses of colorectal cancer show Immunoscore is a stronger predictor of patient survival than microsatellite instability. Immunity 44, 698–711 (2016).

  20. 20.

    Boland, C. R. & Goel, A. Microsatellite instability in colorectal cancer. Gastroenterology 138, 2073–2087 (2010).

  21. 21.

    Gajewski, T. F. et al. Cancer immunotherapy targets based on understanding the T cell-inflamed versus non-T cell-inflamed tumor microenvironment. Adv. Exp. Med. Biol. 1036, 19–31 (2017).

  22. 22.

    Hegde, P. S., Karanikas, V. & Evers, S. The where, the when, and the how of immune monitoring for cancer immunotherapies in the era of checkpoint inhibition. Clin. Cancer Res. 22, 1865–1874 (2016).

  23. 23.

    Angelova, M. et al. Evolution of metastases in space and time under immune selection. Cell 175, 601 (2018).

  24. 24.

    Bindea, G. et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity 39, 782–795 (2013). This article is the first to describe the immunome from immune signatures of purified immune cell subpopulations applied to human tumours. Immune infiltrate composition changes at each tumour stage and T, B and T FH cells have a major impact on survival.

  25. 25.

    Gu-Trantien, C. et al. CXCL13-producing TFH cells link immune suppression and adaptive memory in human breast cancer. JCI Insight 2, 91487 (2017).

  26. 26.

    Chew, V. et al. Chemokine-driven lymphocyte infiltration: an early intratumoural event determining long-term survival in resectable hepatocellular carcinoma. Gut 61, 427–438 (2012).

  27. 27.

    Gajewski, T. F., Schreiber, H. & Fu, Y. X. Innate and adaptive immune cells in the tumor microenvironment. Nat. Immunol. 14, 1014–1022 (2013).

  28. 28.

    Goc, J. et al. Dendritic cells in tumor-associated tertiary lymphoid structures signal a Th1 cytotoxic immune contexture and license the positive prognostic value of infiltrating CD8+T cells. Cancer Res. 74, 705–715 (2014).

  29. 29.

    Ingels, A. et al. T-helper 1 immunoreaction influences survival in muscle-invasive bladder cancer: proof of concept. Ecancermedicalscience 8, 486 (2014).

  30. 30.

    Mulligan, A. M., Pinnaduwage, D., Tchatchou, S., Bull, S. B. & Andrulis, I. L. Validation of intratumoral T-bet+lymphoid cells as predictors of disease-free survival in breast cancer. Cancer Immunol. Res. 4, 41–48 (2016).

  31. 31.

    Mulligan, A. M. et al. Tumoral lymphocytic infiltration and expression of the chemokine CXCL10 in breast cancers from the Ontario Familial Breast Cancer Registry. Clin. Cancer Res. 19, 336–346 (2013).

  32. 32.

    Cristescu, R. et al. Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy. Science 362, eaar3593 (2018).

  33. 33.

    Cheon, H., Borden, E. C. & Stark, G. R. Interferons and their stimulated genes in the tumor microenvironment. Semin. Oncol. 41, 156–173 (2014).

  34. 34.

    Lin, C. F. et al. Escape from IFN-gamma-dependent immunosurveillance in tumorigenesis. J. Biomed. Sci. 24, 10 (2017).

  35. 35.

    Zaidi, M. R. & Merlino, G. The two faces of interferon-gamma in cancer. Clin. Cancer Res. 17, 6118–6124 (2011).

  36. 36.

    Mandai, M. et al. Dual faces of IFNgamma in cancer progression: a role of PD-L1 induction in the determination of pro- and antitumor immunity. Clin. Cancer Res. 22, 2329–2334 (2016).

  37. 37.

    Snell, L. M., McGaha, T. L. & Brooks, D. G. Type I interferon in chronic virus infection and cancer. Trends Immunol. 38, 542–557 (2017).

  38. 38.

    Minn, A. J. & Wherry, E. J. Combination cancer therapies with immune checkpoint blockade: convergence on interferon signaling. Cell 165, 272–275 (2016).

  39. 39.

    Benci, J. L. et al. Tumor interferon signaling regulates a multigenic resistance program to immune checkpoint blockade. Cell 167, 1540–1554 (2016).

  40. 40.

    Sun, T. et al. Inhibition of tumor angiogenesis by interferon-gamma by suppression of tumor-associated macrophage differentiation. Oncol. Res. 21, 227–235 (2014).

  41. 41.

    Kim, H. J. & Cantor, H. CD4 T cell subsets and tumor immunity: the helpful and the not-so-helpful. Cancer Immunol. Res. 2, 91–98 (2014).

  42. 42.

    Placek, K., Coffre, M., Maiella, S., Bianchi, E. & Rogge, L. Genetic and epigenetic networks controlling T helper 1 cell differentiation. Immunology 127, 155–162 (2009).

  43. 43.

    Kato, D. et al. Prospects for personalized combination immunotherapy for solid tumors based on adoptive cell therapies and immune checkpoint blockade therapies. Nihon Rinsho Meneki Gakkai Kaishi 40, 68–77 (2017).

  44. 44.

    Spranger, S., Bao, R. & Gajewski, T. F. Melanoma-intrinsic beta-catenin signalling prevents anti-tumour immunity. Nature 523, 231–235 (2015). This article shows that a melanoma cell-intrinsic oncogenic pathway (active β-catenin signalling) contributes to a lack of T cell infiltration in tumour sites and resistance to anti-PD-L1 and/or anti-CTLA4 mAb therapy.

  45. 45.

    Yaguchi, T. et al. Immune suppression and resistance mediated by constitutive activation of Wnt/beta-catenin signaling in human melanoma cells. J. Immunol. 189, 2110–2117 (2012).

  46. 46.

    Sumimoto, H., Imabayashi, F., Iwata, T. & Kawakami, Y. The BRAF-MAPK signaling pathway is essential for cancer-immune evasion in human melanoma cells. J. Exp. Med. 203, 1651–1656 (2006).

  47. 47.

    Sumimoto, H. et al. Inhibition of growth and invasive ability of melanoma by inactivation of mutated BRAF with lentivirus-mediated RNA interference. Oncogene 23, 6031–6039 (2004).

  48. 48.

    Iwata-Kajihara, T. et al. Enhanced cancer immunotherapy using STAT3-depleted dendritic cells with high Th1-inducing ability and resistance to cancer cell-derived inhibitory factors. J. Immunol. 187, 27–36 (2011).

  49. 49.

    Nishio, H. et al. Immunosuppression through constitutively activated NF-kappaB signalling in human ovarian cancer and its reversal by an NF-kappaB inhibitor. Br. J. Cancer 110, 2965–2974 (2014).

  50. 50.

    Mlecnik, B. et al. Comprehensive intrametastatic immune quantification and major impact of immunoscore on survival. J. Natl Cancer Inst. 110, 97–108 (2018).

  51. 51.

    Zhang, A. W. et al. Interfaces of malignant and immunologic clonal dynamics in ovarian cancer. Cell 173, 1755–1769 (2018).

  52. 52.

    Yoshida, M. et al. Modification of the tumor microenvironment in KRAS or c-MYC-induced ovarian cancer-associated peritonitis. PLOS ONE 11, e0160330 (2016).

  53. 53.

    McFarland, C. D. et al. The damaging effect of passenger mutations on cancer progression. Cancer Res. 77, 4763–4772 (2017).

  54. 54.

    Tauriello, D. V. F. et al. TGFbeta drives immune evasion in genetically reconstituted colon cancer metastasis. Nature 554, 538–543 (2018).

  55. 55.

    Zitvogel, L. & Kroemer, G. Targeting PD-1/PD-L1 interactions for cancer immunotherapy. Oncoimmunology 1, 1223–1225 (2012).

  56. 56.

    Mlecnik, B. et al. Biomolecular network reconstruction identifies T cell homing factors associated with survival in colorectal cancer. Gastroenterology 138, 1429–1440 (2010).

  57. 57.

    van der Woude, L. L., Gorris, M. A. J., Halilovic, A., Figdor, C. G. & de Vries, I. J. M. Migrating into the tumor: a roadmap for T cells. Trends Cancer 3, 797–808 (2017).

  58. 58.

    Ahmadzadeh, M. et al. Tumor antigen-specific CD8 T cells infiltrating the tumor express high levels of PD-1 and are functionally impaired. Blood 114, 1537–1544 (2009).

  59. 59.

    Gros, A. et al. PD-1 identifies the patient-specific CD8(+) tumor-reactive repertoire infiltrating human tumors. J. Clin. Invest. 124, 2246–2259 (2014).

  60. 60.

    Ji, R. R. et al. An immune-active tumor microenvironment favors clinical response to ipilimumab. Cancer Immunol. Immunother. 61, 1019–1031 (2012).

  61. 61.

    Eroglu, Z. et al. High response rate to PD-1 blockade in desmoplastic melanomas. Nature 553, 347–350 (2018).

  62. 62.

    Blank, C. U., Haanen, J. B., Ribas, A. & Schumacher, T. N. The “cancer immunogram”. Science 352, 658–660 (2016).

  63. 63.

    Wieland, A. et al. T cell receptor sequencing of activated CD8 T cells in the blood identifies tumor-infiltrating clones that expand after PD-1 therapy and radiation in a melanoma patient. Cancer Immunol. Immunother. 67, 1767–1776 (2018).

  64. 64.

    Simon, S. et al. Emergence of high-avidity Melan-A-specific clonotypes as a reflection of anti-PD-1 clinical efficacy. Cancer Res. 77, 7083–7093 (2017).

  65. 65.

    Riaz, N. et al. Tumor and microenvironment evolution during immunotherapy with nivolumab. Cell 171, 934–949 (2017).

  66. 66.

    Fife, B. T. et al. Insulin-induced remission in new-onset NOD mice is maintained by the PD-1–PD-L1 pathway. J. Exp. Med. 203, 2737–2747 (2006).

  67. 67.

    Whiteside, T. L., Demaria, S., Rodriguez-Ruiz, M. E., Zarour, H. M. & Melero, I. Emerging opportunities and challenges in cancer immunotherapy. Clin. Cancer Res. 22, 1845–1855 (2016).

  68. 68.

    Weng, N. P., Araki, Y. & Subedi, K. The molecular basis of the memory T cell response: differential gene expression and its epigenetic regulation. Nat. Rev. Immunol. 12, 306–315 (2012).

  69. 69.

    Durgeau, A., Virk, Y., Corgnac, S. & Mami-Chouaib, F. Recent advances in targeting CD8 T-Cell immunity for more effective cancer immunotherapy. Front. Immunol. 9, 14 (2018).

  70. 70.

    Mlecnik, B. et al. The tumor microenvironment and Immunoscore are critical determinants of dissemination to distant metastasis. Sci. Transl Med. 8, 327ra26 (2016).

  71. 71.

    Pages, F. et al. Effector memory T cells, early metastasis, and survival in colorectal cancer. N. Engl. J. Med. 353, 2654–2666 (2005).

  72. 72.

    Church, S. E. & Galon, J. Tumor microenvironment and immunotherapy: the whole picture is better than a glimpse. Immunity 43, 631–633 (2015).

  73. 73.

    Demaria, S., Coleman, C. N. & Formenti, S. C. Radiotherapy: changing the game in immunotherapy. Trends Cancer 2, 286–294 (2016).

  74. 74.

    Sharma, P. & Allison, J. P. The future of immune checkpoint therapy. Science 348, 56–61 (2015).

  75. 75.

    Koyama, S. et al. Adaptive resistance to therapeutic PD-1 blockade is associated with upregulation of alternative immune checkpoints. Nat. Commun. 7, 10501 (2016).

  76. 76.

    Shayan, G. et al. Adaptive resistance to anti-PD1 therapy by Tim-3 upregulation is mediated by the PI3K-Akt pathway in head and neck cancer. Oncoimmunology 6, e1261779 (2017).

  77. 77.

    Granier, C. et al. Tim-3 expression on tumor-infiltrating PD-1(+)CD8(+) T cells correlates with poor clinical outcome in renal cell carcinoma. Cancer Res. 77, 1075–1082 (2017).

  78. 78.

    Hellmann, M. D., Friedman, C. F. & Wolchok, J. D. Combinatorial cancer immunotherapies. Adv. Immunol. 130, 251–277 (2016).

  79. 79.

    Eggermont, A. M. M. et al. Adjuvant pembrolizumab versus placebo in resected stage III melanoma. N. Engl. J. Med. 378, 1789–1801 (2018).

  80. 80.

    Buchbinder, E. I. & Desai, A. CTLA-4 and PD-1 pathways: similarities, differences, and implications of their inhibition. Am. J. Clin. Oncol. 39, 98–106 (2016).

  81. 81.

    Taube, J. M. Unleashing the immune system: PD-1 and PD-Ls in the pre-treatment tumor microenvironment and correlation with response to PD-1/PD-L1 blockade. Oncoimmunology 3, e963413 (2014).

  82. 82.

    Taube, J. M. et al. Implications of the tumor immune microenvironment for staging and therapeutics. Mod. Pathol. 31, 214–234 (2018).

  83. 83.

    Wolchok, J. D. et al. Overall survival with combined nivolumab and ipilimumab in advanced melanoma. N. Engl. J. Med. 377, 1345–1356 (2017).

  84. 84.

    Motzer, R. J. et al. Nivolumab plus ipilimumab versus sunitinib in advanced renal-cell carcinoma. N. Engl. J. Med. 378, 1277–1290 (2018).

  85. 85.

    Hellmann, M. D. et al. Nivolumab plus ipilimumab in lung cancer with a high tumor mutational burden. N. Engl. J. Med. 378, 2093–2104 (2018).

  86. 86.

    Du, W. et al. TIM-3 as a target for cancer immunotherapy and mechanisms of action. Int. J. Mol. Sci. 18, E645 (2017).

  87. 87.

    Manieri, N. A., Chiang, E. Y. & Grogan, J. L. TIGIT: a key inhibitor of the cancer immunity cycle. Trends Immunol. 38, 20–28 (2017).

  88. 88.

    Sedy, J. R. et al. B and T lymphocyte attenuator regulates T cell activation through interaction with herpesvirus entry mediator. Nat. Immunol. 6, 90–98 (2005).

  89. 89.

    Gao, J. et al. VISTA is an inhibitory immune checkpoint that is increased after ipilimumab therapy in patients with prostate cancer. Nat. Med. 23, 551–555 (2017).

  90. 90.

    Stanczak, M. A. et al. Self-associated molecular patterns mediate cancer immune evasion by engaging Siglecs on T cells. J. Clin. Invest. https://doi.org/10.1172/JCI120612 (2018).

  91. 91.

    Buchan, S. L., Rogel, A. & Al-Shamkhani, A. The immunobiology of CD27 and OX40 and their potential as targets for cancer immunotherapy. Blood 131, 39–48 (2018).

  92. 92.

    Esensten, J. H., Helou, Y. A., Chopra, G., Weiss, A. & Bluestone, J. A. CD28 costimulation: from mechanism to therapy. Immunity 44, 973–988 (2016).

  93. 93.

    Hui, E. et al. T cell costimulatory receptor CD28 is a primary target for PD-1-mediated inhibition. Science 355, 1428–1433 (2017).

  94. 94.

    Kamphorst, A. O. et al. Rescue of exhausted CD8 T cells by PD-1-targeted therapies is CD28-dependent. Science 355, 1423–1427 (2017).

  95. 95.

    Sanmamed, M. F. et al. Agonists of co-stimulation in cancer immunotherapy directed against CD137, OX40, GITR, CD27, CD28, and ICOS. Semin. Oncol. 42, 640–655 (2015).

  96. 96.

    Hunig, T. The storm has cleared: lessons from the CD28 superagonist TGN1412 trial. Nat. Rev. Immunol. 12, 317–318 (2012).

  97. 97.

    Elpek, K. et al. Efficacy of anti-ICOS agonist monoclonal antibodies in preclinical tumor models provides a rationale for clinical development as cancer immunotherapeutics. Cancer Immunol. Res. 4, A059 (2016).

  98. 98.

    Chaudhary, B. & Elkord, E. Regulatory T cells in the tumor microenvironment and cancer progression: role and therapeutic targeting. Vaccines 4, E28 (2016).

  99. 99.

    Routy, B. et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 359, 91–97 (2017).

  100. 100.

    Snyder, A., Pamer, E. & Wolchok, J. Could microbial therapy boost cancer immunotherapy? Science 350, 1031–1032 (2015).

  101. 101.

    Gopalakrishnan, V. et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science 359, 97–103 (2017).

  102. 102.

    Matson, V. et al. The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients. Science 359, 104–108 (2018).

  103. 103.

    Nolz, J. C. Molecular mechanisms of CD8(+) T cell trafficking and localization. Cell. Mol. Life Sci. 72, 2461–2473 (2015).

  104. 104.

    Nagarsheth, N., Wicha, M. S. & Zou, W. Chemokines in the cancer microenvironment and their relevance in cancer immunotherapy. Nat. Rev. Immunol. 17, 559–572 (2017).

  105. 105.

    Peng, D. et al. Epigenetic silencing of TH1-type chemokines shapes tumour immunity and immunotherapy. Nature 527, 249–253 (2015).

  106. 106.

    Nagarsheth, N. et al. PRC2 epigenetically silences Th1-type chemokines to suppress effector T-cell trafficking in colon cancer. Cancer Res. 76, 275–282 (2016).

  107. 107.

    Huang, Y. et al. CD4+and CD8+T cells have opposing roles in breast cancer progression and outcome. Oncotarget 6, 17462–17478 (2015).

  108. 108.

    Sweis, R. F. et al. Molecular drivers of the non-T cell-inflamed tumor microenvironment in urothelial bladder cancer. Cancer Immunol. Res. 4, 563–568 (2016).

  109. 109.

    Tang, H. et al. Facilitating T cell infiltration in tumor microenvironment overcomes resistance to PD-L1 blockade. Cancer Cell 29, 285–296 (2016).

  110. 110.

    Venning, F. A., Wullkopf, L. & Erler, J. T. Targeting ECM disrupts cancer progression. Front. Oncol. 5, 224 (2015).

  111. 111.

    Huang, Y., Goel, S., Duda, D. G., Fukumura, D. & Jain, R. K. Vascular normalization as an emerging strategy to enhance cancer immunotherapy. Cancer Res. 73, 2943–2948 (2013).

  112. 112.

    Carmeliet, P. & Jain, R. K. Principles and mechanisms of vessel normalization for cancer and other angiogenic diseases. Nat. Rev. Drug Discov. 10, 417–427 (2011).

  113. 113.

    Lanitis, E., Irving, M. & Coukos, G. Targeting the tumor vasculature to enhance T cell activity. Curr. Opin. Immunol. 33, 55–63 (2015).

  114. 114.

    Tan, L. Y. et al. Control of immune cell entry through the tumour vasculature: a missing link in optimising melanoma immunotherapy? Clin. Transl Immunol. 6, e134 (2017).

  115. 115.

    Wigerup, C., Pahlman, S. & Bexell, D. Therapeutic targeting of hypoxia and hypoxia-inducible factors in cancer. Pharmacol. Ther. 164, 152–169 (2016).

  116. 116.

    Serra, S. et al. Adenosine signaling mediates hypoxic responses in the chronic lymphocytic leukemia microenvironment. Blood Adv. 1, 47–61 (2016).

  117. 117.

    Stagg, J. & Smyth, M. J. Extracellular adenosine triphosphate and adenosine in cancer. Oncogene 29, 5346–5358 (2010).

  118. 118.

    Antonioli, L., Blandizzi, C., Pacher, P. & Hasko, G. Immunity, inflammation and cancer: a leading role for adenosine. Nat. Rev. Cancer 13, 842–857 (2013).

  119. 119.

    Stagg, J. et al. CD73-deficient mice have increased antitumor immunity and are resistant to experimental metastasis. Cancer Res. 71, 2892–2900 (2011).

  120. 120.

    Antonioli, L., Yegutkin, G. G., Pacher, P., Blandizzi, C. & Hasko, G. Anti-CD73 in cancer immunotherapy: awakening new opportunities. Trends Cancer 2, 95–109 (2016).

  121. 121.

    Hayes, G. M. et al. CD39 is a promising therapeutic antibody target for the treatment of soft tissue sarcoma. Am. J. Transl Res. 7, 1181–1188 (2015).

  122. 122.

    Sun, X. et al. Disordered purinergic signaling and abnormal cellular metabolism are associated with development of liver cancer in Cd39/ENTPD1 null mice. Hepatology 57, 205–216 (2013).

  123. 123.

    Leone, R. D. & Emens, L. A. Targeting adenosine for cancer immunotherapy. J. Immunother. Cancer 6, 57 (2018).

  124. 124.

    Yu, T., Tang, B. & Sun, X. Development of inhibitors targeting hypoxia-inducible factor 1 and 2 for cancer therapy. Yonsei Med. J. 58, 489–496 (2017).

  125. 125.

    Leone, R. D., Lo, Y. C. & Powell, J. D. A2aR antagonists: next generation checkpoint blockade for cancer immunotherapy. Comput. Struct. Biotechnol. J. 13, 265–272 (2015).

  126. 126.

    Cardones, A. R. & Banez, L. L. VEGF inhibitors in cancer therapy. Curr. Pharm. Des. 12, 387–394 (2006).

  127. 127.

    Fridman, W. H., Pages, F., Sautes-Fridman, C. & Galon, J. The immune contexture in human tumours: impact on clinical outcome. Nat. Rev. Cancer 12, 298–306 (2012).

  128. 128.

    Rajabi, M. & Mousa, S. A. The role of angiogenesis in cancer treatment. Biomedicines 5, 34 (2017).

  129. 129.

    Ebos, J. M. et al. Accelerated metastasis after short-term treatment with a potent inhibitor of tumor angiogenesis. Cancer Cell 15, 232–239 (2009).

  130. 130.

    Paez-Ribes, M. et al. Antiangiogenic therapy elicits malignant progression of tumors to increased local invasion and distant metastasis. Cancer Cell 15, 220–231 (2009).

  131. 131.

    Goel, S., Wong, A. H. & Jain, R. K. Vascular normalization as a therapeutic strategy for malignant and nonmalignant disease. Cold Spring Harb. Perspect. Med. 2, a006486 (2012).

  132. 132.

    Tian, L. et al. Mutual regulation of tumour vessel normalization and immunostimulatory reprogramming. Nature 544, 250–254 (2017).

  133. 133.

    Sabat, R. et al. Biology of interleukin-10. Cytokine Growth Factor Rev. 21, 331–344 (2010).

  134. 134.

    Yang, L. TGFbeta a potent regulator of tumor microenvironment and host immune response, implication for therapy. Curr. Mol. Med. 10, 374–380 (2010).

  135. 135.

    Zhang, H., Wang, Y., Hwang, E. S. & He, Y. W. Interleukin-10: an immune-activating cytokine in cancer immunotherapy. J. Clin. Oncol. 34, 3576–3578 (2016).

  136. 136.

    Neuzillet, C. et al. Targeting the TGFbeta pathway for cancer therapy. Pharmacol. Ther. 147, 22–31 (2015).

  137. 137.

    Lan, Y. et al. Enhanced preclinical antitumor activity of M7824, a bifunctional fusion protein simultaneously targeting PD-L1 and TGF-beta. Sci. Transl Med. 10, eaan5488 (2018).

  138. 138.

    Shimabukuro-Vornhagen, A. et al. The immunosuppressive factors IL-10, TGF-beta, and VEGF do not affect the antigen-presenting function of CD40-activated B cells. J. Exp. Clin. Cancer Res. 31, 47 (2012).

  139. 139.

    Gabrilovich, D. Mechanisms and functional significance of tumour-induced dendritic-cell defects. Nat. Rev. Immunol. 4, 941–952 (2004).

  140. 140.

    Eil, R. et al. Ionic immune suppression within the tumour microenvironment limits T cell effector function. Nature 537, 539–543 (2016).

  141. 141.

    Richards, C. H., Mohammed, Z., Qayyum, T., Horgan, P. G. & McMillan, D. C. The prognostic value of histological tumor necrosis in solid organ malignant disease: a systematic review. Future Oncol. 7, 1223–1235 (2011).

  142. 142.

    Holmgaard, R. B. et al. Tumor-expressed IDO recruits and activates MDSCs in a Treg-dependent manner. Cell Rep. 13, 412–424 (2015).

  143. 143.

    Timosenko, E., Hadjinicolaou, A. V. & Cerundolo, V. Modulation of cancer-specific immune responses by amino acid degrading enzymes. Immunotherapy 9, 83–97 (2017).

  144. 144.

    Kumar, V., Patel, S., Tcyganov, E. & Gabrilovich, D. I. The nature of myeloid-derived suppressor cells in the tumor microenvironment. Trends Immunol. 37, 208–220 (2016).

  145. 145.

    Raber, P. L. et al. Subpopulations of myeloid-derived suppressor cells impair T cell responses through independent nitric oxide-related pathways. Int. J. Cancer 134, 2853–2864 (2014).

  146. 146.

    Long, G. V. et al. Epacadostat (E) plus pembrolizumab (P) versus pembrolizumab alone in patients (pts) with unresectable or metastatic melanoma: results of the phase 3 ECHO-301/KEYNOTE-252 study. J. Clin. Oncol. 36, 108 (2018).

  147. 147.

    De Henau, O. et al. Overcoming resistance to checkpoint blockade therapy by targeting PI3Kgamma in myeloid cells. Nature 539, 443–447 (2016).

  148. 148.

    Cannarile, M. A. et al. Colony-stimulating factor 1 receptor (CSF1R) inhibitors in cancer therapy. J. Immunother. Cancer 5, 53 (2017).

  149. 149.

    Moore, E. et al. Established T cell-inflamed tumors rejected after adaptive resistance was reversed by combination STING activation and PD-1 pathway blockade. Cancer Immunol. Res. 4, 1061–1071 (2016).

  150. 150.

    Clavijo, P. E. et al. Resistance to CTLA-4 checkpoint inhibition reversed through selective elimination of granulocytic myeloid cells. Oncotarget 8, 55804–55820 (2017).

  151. 151.

    Harlin, H. et al. Chemokine expression in melanoma metastases associated with CD8+T cell recruitment. Cancer Res. 69, 3077–3085 (2009).

  152. 152.

    Ulloa-Montoya, F. et al. Predictive gene signature in MAGE-A3 antigen-specific cancer immunotherapy. J. Clin. Oncol. 31, 2388–2395 (2013).

  153. 153.

    Sistigu, A. et al. Cancer cell-autonomous contribution of type I interferon signaling to the efficacy of chemotherapy. Nat. Med. 20, 1301–1309 (2014).

  154. 154.

    Cai, X., Chiu, Y. H. & Chen, Z. J. The cGAS-cGAMP-STING pathway of cytosolic DNA sensing and signaling. Mol. Cell 54, 289–296 (2014).

  155. 155.

    Corrales, L., McWhirter, S. M., Dubensky, T. W. Jr & Gajewski, T. F. The host STING pathway at the interface of cancer and immunity. J. Clin. Invest. 126, 2404–2411 (2016).

  156. 156.

    Sanchez-Paulete, A. R. et al. Antigen cross-presentation and T cell cross-priming in cancer immunology and immunotherapy. Ann. Oncol. 28, xii44–xii55 (2017).

  157. 157.

    Zitvogel, L., Galluzzi, L., Kepp, O., Smyth, M. J. & Kroemer, G. Type I interferons in anticancer immunity. Nat. Rev. Immunol. 15, 405–414 (2015).

  158. 158.

    Corrales, L. et al. Direct activation of STING in the tumor microenvironment leads to potent and systemic tumor regression and immunity. Cell Rep. 11, 1018–1030 (2015).

  159. 159.

    Huck, B. R., Kotzner, L. & Urbahns, K. Small molecules drive big improvements in immuno-oncology therapies. Angew. Chem. Int. Ed. 57, 4412–4428 (2018).

  160. 160.

    Foote, J. B. et al. A STING agonist given with OX40 receptor and PD-L1 modulators primes immunity and reduces tumor growth in tolerized mice. Cancer Immunol. Res. 5, 468–479 (2017).

  161. 161.

    Shekarian, T. et al. Pattern recognition receptors: immune targets to enhance cancer immunotherapy. Ann. Oncol. 28, 1756–1766 (2017).

  162. 162.

    Elion, D. L. & Cook, R. S. Harnessing RIG-I and intrinsic immunity in the tumor microenvironment for therapeutic cancer treatment. Oncotarget 9, 29007–29017 (2018).

  163. 163.

    Le Mercier, I. et al. Tumor promotion by intratumoral plasmacytoid dendritic cells is reversed by TLR7 ligand treatment. Cancer Res. 73, 4629–4640 (2013).

  164. 164.

    Kim, Y. H. et al. In situ vaccination against mycosis fungoides by intratumoral injection of a TLR9 agonist combined with radiation: a phase 1/2 study. Blood 119, 355–363 (2012).

  165. 165.

    Li, J. et al. Lymphoma immunotherapy with CpG oligodeoxynucleotides requires TLR9 either in the host or in the tumor itself. J. Immunol. 179, 2493–2500 (2007).

  166. 166.

    Wang, S. et al. Intratumoral injection of a CpG oligonucleotide reverts resistance to PD-1 blockade by expanding multifunctional CD8+ T cells. Proc. Natl Acad. Sci. USA 113, E7240–E7249 (2016).

  167. 167.

    Sato-Kaneko, F. et al. Combination immunotherapy with TLR agonists and checkpoint inhibitors suppresses head and neck cancer. JCI Insight 2, 93397 (2017).

  168. 168.

    Sagiv-Barfi, I. et al. Eradication of spontaneous malignancy by local immunotherapy. Sci. Transl Med. 10, eaan4488 (2018).

  169. 169.

    Marin-Acevedo, J. A., Soyano, A. E., Dholaria, B., Knutson, K. L. & Lou, Y. Cancer immunotherapy beyond immune checkpoint inhibitors. J. Hematol. Oncol. 11, 8 (2018).

  170. 170.

    Wilkinson, R. W. & Leishman, A. J. Further advances in cancer immunotherapy: going beyond checkpoint blockade. Front. Immunol. 9, 1082 (2018).

  171. 171.

    Frank, M. J. et al. In situ vaccination with a TLR 9 agonist and local low dose radiation induces systemic responses in untreated indolent lymphoma. Cancer Discov. https://doi.org/10.1158/2159-8290.CD-18-0743 (2018).

  172. 172.

    Chow, L. Q. M. et al. Phase Ib trial of the toll-like receptor 8 agonist, motolimod (VTX-2337), combined with cetuximab in patients with recurrent or metastatic SCCHN. Clin. Cancer Res. 23, 2442–2450 (2017).

  173. 173.

    Marabelle, A., Kohrt, H., Caux, C. & Levy, R. Intratumoral immunization: a new paradigm for cancer therapy. Clin. Cancer Res. 20, 1747–1756 (2014).

  174. 174.

    Ridnour, L. A. et al. Molecular pathways: toll-like receptors in the tumor microenvironment—poor prognosis or new therapeutic opportunity. Clin. Cancer Res. 19, 1340–1346 (2013).

  175. 175.

    Huang, L., Xu, H. & Peng, G. TLR-mediated metabolic reprogramming in the tumor microenvironment: potential novel strategies for cancer immunotherapy. Cell. Mol. Immunol. 15, 428–437 (2018).

  176. 176.

    Li, J. K., Balic, J. J., Yu, L. & Jenkins, B. TLR agonists as adjuvants for cancer vaccines. Adv. Exp. Med. Biol. 1024, 195–212 (2017).

  177. 177.

    Iribarren, K. et al. Trial watch: immunostimulation with toll-like receptor agonists in cancer therapy. Oncoimmunology 5, e1088631 (2016).

  178. 178.

    Vonderheide, R. H. & Glennie, M. J. Agonistic CD40 antibodies and cancer therapy. Clin. Cancer Res. 19, 1035–1043 (2013).

  179. 179.

    Tutt, A. L. et al. T cell immunity to lymphoma following treatment with anti-CD40 monoclonal antibody. J. Immunol. 168, 2720–2728 (2002).

  180. 180.

    Mangsbo, S. M. et al. The human agonistic CD40 antibody ADC-1013 eradicates bladder tumors and generates T cell-dependent tumor immunity. Clin. Cancer Res. 21, 1115–1126 (2015).

  181. 181.

    Beatty, G. L., Li, Y. & Long, K. B. Cancer immunotherapy: activating innate and adaptive immunity through CD40 agonists. Expert Rev. Anticancer Ther. 17, 175–186 (2017).

  182. 182.

    Ohta, T. et al. Crucial roles of XCR1-expressing dendritic cells and the XCR1-XCL1 chemokine axis in intestinal immune homeostasis. Sci. Rep. 6, 23505 (2016).

  183. 183.

    Krummel, M. F., Bartumeus, F. & Gerard, A. T cell migration, search strategies and mechanisms. Nat. Rev. Immunol. 16, 193–201 (2016).

  184. 184.

    Bottcher, J. P. et al. NK cells stimulate recruitment of cDC1 into the tumor microenvironment promoting cancer immune control. Cell 172, 1022–1037 (2018).

  185. 185.

    Villadangos, J. A. & Shortman, K. Found in translation: the human equivalent of mouse CD8+dendritic cells. J. Exp. Med. 207, 1131–1134 (2010).

  186. 186.

    Woo, S. R. et al. STING-dependent cytosolic DNA sensing mediates innate immune recognition of immunogenic tumors. Immunity 41, 830–842 (2014). This article shows that innate immune sensing of cancer occurs via the host STING pathway and subsequent type I interferon production. Spontaneous CD8 + T cell priming against tumours depends on STING.

  187. 187.

    Deng, L. et al. STING-dependent cytosolic DNA sensing promotes radiation-induced type I interferon-dependent antitumor immunity in immunogenic tumors. Immunity 41, 843–852 (2014).

  188. 188.

    Harding, S. M. et al. Mitotic progression following DNA damage enables pattern recognition within micronuclei. Nature 548, 466–470 (2017).

  189. 189.

    Zheng, W. et al. Combination of radiotherapy and vaccination overcomes checkpoint blockade resistance. Oncotarget 7, 43039–43051 (2016).

  190. 190.

    Bonvalot, S. et al. First-in-human study testing a new radioenhancer using nanoparticles (NBTXR3) activated by radiation therapy in patients with locally advanced soft tissue sarcomas. Clin. Cancer Res. 23, 908–917 (2017).

  191. 191.

    Beatty, G. L. & Gladney, W. L. Immune escape mechanisms as a guide for cancer immunotherapy. Clin. Cancer Res. 21, 687–692 (2015).

  192. 192.

    Zitvogel, L., Kepp, O. & Kroemer, G. Decoding cell death signals in inflammation and immunity. Cell 140, 798–804 (2010).

  193. 193.

    McGranahan, N. et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science 351, 1463–1469 (2016). This article demonstrates that a relationship exists between clonal neoantigen burden and overall survival in primary lung adenocarcinomas. Sensitivity to PD-1 and CTLA4 blockade in patients with advanced NSCLC and melanoma was enhanced in tumours enriched for clonal neoantigens.

  194. 194.

    Krysko, D. V. et al. Immunogenic cell death and DAMPs in cancer therapy. Nat. Rev. Cancer 12, 860–875 (2012).

  195. 195.

    Kroemer, G., Galluzzi, L., Kepp, O. & Zitvogel, L. Immunogenic cell death in cancer therapy. Annu. Rev. Immunol. 31, 51–72 (2013).

  196. 196.

    Galluzzi, L., Buque, A., Kepp, O., Zitvogel, L. & Kroemer, G. Immunogenic cell death in cancer and infectious disease. Nat. Rev. Immunol. 17, 97–111 (2017).

  197. 197.

    Obeid, M. et al. Calreticulin exposure dictates the immunogenicity of cancer cell death. Nat. Med. 13, 54–61 (2007).

  198. 198.

    Vacchelli, E. et al. Chemotherapy-induced antitumor immunity requires formyl peptide receptor 1. Science 350, 972–978 (2015).

  199. 199.

    Ruffell, B. et al. Leukocyte composition of human breast cancer. Proc. Natl Acad. Sci. USA 109, 2796–2801 (2012).

  200. 200.

    Park, J. H. et al. Clonal expansion of antitumor T cells in breast cancer correlates with response to neoadjuvant chemotherapy. Int. J. Oncol. 49, 471–478 (2016).

  201. 201.

    Ladoire, S. et al. Combined evaluation of LC3B puncta and HMGB1 expression predicts residual risk of relapse after adjuvant chemotherapy in breast cancer. Autophagy 11, 1878–1890 (2015).

  202. 202.

    Ladoire, S. et al. The presence of LC3B puncta and HMGB1 expression in malignant cells correlate with the immune infiltrate in breast cancer. Autophagy 12, 864–875 (2016).

  203. 203.

    Fucikova, J. et al. Calreticulin expression in human non-small cell lung cancers correlates with increased accumulation of antitumor immune cells and favorable prognosis. Cancer Res. 76, 1746–1756 (2016).

  204. 204.

    Stoll, G. et al. Calreticulin expression: interaction with the immune infiltrate and impact on survival in patients with ovarian and non-small cell lung cancer. Oncoimmunology 5, e1177692 (2016).

  205. 205.

    Wemeau, M. et al. Calreticulin exposure on malignant blasts predicts a cellular anticancer immune response in patients with acute myeloid leukemia. Cell Death Dis. 1, e104 (2010).

  206. 206.

    Fucikova, J. et al. Calreticulin exposure by malignant blasts correlates with robust anticancer immunity and improved clinical outcome in AML patients. Blood 128, 3113–3124 (2016).

  207. 207.

    Galluzzi, L., Buque, A., Kepp, O., Zitvogel, L. & Kroemer, G. Immunological effects of conventional chemotherapy and targeted anticancer agents. Cancer Cell 28, 690–714 (2015).

  208. 208.

    Vincent, J. et al. 5-Fluorouracil selectively kills tumor-associated myeloid-derived suppressor cells resulting in enhanced T cell-dependent antitumor immunity. Cancer Res. 70, 3052–3061 (2010).

  209. 209.

    Ghiringhelli, F. et al. Metronomic cyclophosphamide regimen selectively depletes CD4+CD25+ regulatory T cells and restores T and NK effector functions in end stage cancer patients. Cancer Immunol. Immunother. 56, 641–648 (2007).

  210. 210.

    Viaud, S. et al. The intestinal microbiota modulates the anticancer immune effects of cyclophosphamide. Science 342, 971–976 (2013).

  211. 211.

    Wang, W. et al. Effector T cells abrogate stroma-mediated chemoresistance in ovarian cancer. Cell 165, 1092–1105 (2016).

  212. 212.

    Anitei, M. G. et al. Prognostic and predictive values of the immunoscore in patients with rectal cancer. Clin. Cancer Res. 20, 1891–1899 (2014).

  213. 213.

    Gandhi, L. et al. Pembrolizumab plus chemotherapy in metastatic non-small-cell lung cancer. N. Engl. J. Med. 378, 2078–2092 (2018).

  214. 214.

    Brea, E. J. et al. Kinase regulation of human MHC class I molecule expression on cancer cells. Cancer Immunol. Res. 4, 936–947 (2016).

  215. 215.

    Gang, A. O. et al. 5-Azacytidine treatment sensitizes tumor cells to T cell mediated cytotoxicity and modulates NK cells in patients with myeloid malignancies. Blood Cancer J. 4, e197 (2014).

  216. 216.

    de Charette, M., Marabelle, A. & Houot, R. Turning tumour cells into antigen presenting cells: the next step to improve cancer immunotherapy? Eur. J. Cancer 68, 134–147 (2016).

  217. 217.

    Chiappinelli, K. B. et al. Inhibiting DNA methylation causes an interferon response in cancer via dsRNA including endogenous retroviruses. Cell 162, 974–986 (2015).

  218. 218.

    Stengel, S., Fiebig, U., Kurth, R. & Denner, J. Regulation of human endogenous retrovirus-K expression in melanomas by CpG methylation. Genes Chromosomes Cancer 49, 401–411 (2010).

  219. 219.

    Strissel, P. L. et al. Reactivation of codogenic endogenous retroviral (ERV) envelope genes in human endometrial carcinoma and prestages: emergence of new molecular targets. Oncotarget 3, 1204–1219 (2012).

  220. 220.

    Sharma, S., Kaufmann, T. & Biswas, S. Impact of inhibitor of apoptosis proteins on immune modulation and inflammation. Immunol. Cell Biol. 95, 236–243 (2017).

  221. 221.

    Kotschy, A. et al. The MCL1 inhibitor S63845 is tolerable and effective in diverse cancer models. Nature 538, 477–482 (2016).

  222. 222.

    Yea, S. S. & Fruman, D. A. Achieving cancer cell death with PI3K/mTOR-targeted therapies. Ann. NY Acad. Sci. 1280, 15–18 (2013).

  223. 223.

    Kumari, N., Dwarakanath, B. S., Das, A. & Bhatt, A. N. Role of interleukin-6 in cancer progression and therapeutic resistance. Tumour Biol. 37, 11553–11572 (2016).

  224. 224.

    Liepe, J. et al. A large fraction of HLA class I ligands are proteasome-generated spliced peptides. Science 354, 354–358 (2016).

  225. 225.

    Lauss, M. et al. Mutational and putative neoantigen load predict clinical benefit of adoptive T cell therapy in melanoma. Nat. Commun. 8, 1738 (2017).

  226. 226.

    Germano, G. et al. Inactivation of DNA repair triggers neoantigen generation and impairs tumour growth. Nature 552, 116–120 (2017). This article shows that inactivation of DNA MMR mechanisms increased mutational load, promoted continuous renewal of neoantigens in human CRCs and triggered immune surveillance in mouse models.

  227. 227.

    Wieringa, H. W., van der Zee, A. G., de Vries, E. G. & van Vugt, M. A. Breaking the DNA damage response to improve cervical cancer treatment. Cancer Treat. Rev. 42, 30–40 (2016).

  228. 228.

    Hemann, M. T. From breaking bad to worse: exploiting homologous DNA repair deficiency in cancer. Cancer Discov. 4, 516–518 (2014).

  229. 229.

    Yang, Y. Cancer immunotherapy: harnessing the immune system to battle cancer. J. Clin. Invest. 125, 3335–3337 (2015).

  230. 230.

    Rosenbaum, L. Tragedy, perseverance, and chance — the story of CAR-T therapy. N. Engl. J. Med. 377, 1313–1315 (2017).

  231. 231.

    Jensen, M. C. & Riddell, S. R. Designing chimeric antigen receptors to effectively and safely target tumors. Curr. Opin. Immunol. 33, 9–15 (2015).

  232. 232.

    Gomes-Silva, D. & Ramos, C. A. Cancer immunotherapy using CAR-T cells: from the research bench to the assembly line. Biotechnol. J. 13, 1700097 (2018).

  233. 233.

    Wang, X. & Riviere, I. Clinical manufacturing of CAR T cells: foundation of a promising therapy. Mol. Ther. Oncolyt. 3, 16015 (2016).

  234. 234.

    von Kalle, C., Deichmann, A. & Schmidt, M. Vector integration and tumorigenesis. Hum. Gene Ther. 25, 475–481 (2014).

  235. 235.

    Wright, A. V., Nunez, J. K. & Doudna, J. A. Biology and applications of CRISPR systems: harnessing nature’s toolbox for genome engineering. Cell 164, 29–44 (2016).

  236. 236.

    Eyquem, J. et al. Targeting a CAR to the TRAC locus with CRISPR/Cas9 enhances tumour rejection. Nature 543, 113–117 (2017).

  237. 237.

    Hervas-Stubbs, S. et al. CD8 T cell priming in the presence of IFN-alpha renders CTLs with improved responsiveness to homeostatic cytokines and recall antigens: important traits for adoptive T cell therapy. J. Immunol. 189, 3299–3310 (2012).

  238. 238.

    Mishto, M. & Liepe, J. Post-translational peptide splicing and T cell responses. Trends Immunol. 38, 904–915 (2017).

  239. 239.

    Verdegaal, E. M. et al. Neoantigen landscape dynamics during human melanoma-T cell interactions. Nature 536, 91–95 (2016).

  240. 240.

    Spranger, S., Dai, D., Horton, B. & Gajewski, T. F. Tumor-residing Batf3 dendritic cells are required for effector T cell trafficking and adoptive T cell therapy. Cancer Cell 31, 711–723 (2017).

  241. 241.

    Galon, J. et al. Characterization of anti-CD19 chimeric antigen receptor (CAR) T cell-mediated tumor microenvironment immune gene profile in a multicenter trial (ZUMA-1) with axicabtagene ciloleucel (axi-cel, KTE-C19). J. Clin. Oncol. 35, 3025 (2017).

  242. 242.

    Kaufman, H. L., Kohlhapp, F. J. & Zloza, A. Oncolytic viruses: a new class of immunotherapy drugs. Nat. Rev. Drug Discov. 14, 642–662 (2015).

  243. 243.

    Pataer, A., Swisher, S. G., Roth, J. A., Logothetis, C. J. & Corn, P. G. Inhibition of RNA-dependent protein kinase (PKR) leads to cancer cell death and increases chemosensitivity. Cancer Biol. Ther. 8, 245–252 (2009).

  244. 244.

    Chesney, J. et al. Randomized, open-label phase II study evaluating the efficacy and safety of talimogene laherparepvec in combination with ipilimumab versus ipilimumab alone in patients with advanced, unresectable melanoma. J. Clin. Oncol. 36, 1658–1667 (2018). This paper presents the first randomized trial evaluating the combination of an oncolytic virus with a checkpoint inhibitor and showing a significantly higher objective response rate for T-VEC plus ipilimumab versus ipilimumab alone.

  245. 245.

    Ribas, A. et al. Oncolytic virotherapy promotes intratumoral T cell infiltration and improves anti-PD-1 immunotherapy. Cell 170, 1109–1119 (2017). This article shows that oncolytic virotherapy with T-VEC in patients with advanced melanoma increased the cytotoxic T cell infiltration and therapeutic efficacy of an anti-PD-1 antibody.

  246. 246.

    Haanen, J. Converting cold into hot tumors by combining immunotherapies. Cell 170, 1055–1056 (2017).

  247. 247.

    Nestvold, J. et al. Oncolytic peptide LTX-315 induces an immune-mediated abscopal effect in a rat sarcoma model. Oncoimmunology 6, e1338236 (2017).

  248. 248.

    Patel, A., Kaufman, H. L. & Disis, M. L. Next generation approaches for tumor vaccination. Chin. Clin. Oncol. 6, 19 (2017).

  249. 249.

    Gibney, G. T., Weiner, L. M. & Atkins, M. B. Predictive biomarkers for checkpoint inhibitor-based immunotherapy. Lancet Oncol. 17, e542–e551 (2016).

  250. 250.

    Vigneron, N. Human tumor antigens and cancer immunotherapy. Biomed. Res. Int. 2015, 948501 (2015).

  251. 251.

    Mitchell, D. A. et al. Tetanus toxoid and CCL3 improve dendritic cell vaccines in mice and glioblastoma patients. Nature 519, 366–369 (2015).

  252. 252.

    Stupp, R. et al. Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N. Engl. J. Med. 352, 987–996 (2005).

  253. 253.

    Liau, L. M. et al. First results on survival from a large phase 3 clinical trial of an autologous dendritic cell vaccine in newly diagnosed glioblastoma. J. Transl Med. 16, 142 (2018).

  254. 254.

    Luksza, M. et al. A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy. Nature 551, 517–520 (2017).

  255. 255.

    Sahin, U. et al. Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer. Nature 547, 222–226 (2017). This paper presents the development and successful application of a personalized vaccine-based immunotherapy exploiting the concept of an individualized mutanome and computational prediction of neo-epitopes.

  256. 256.

    Ott, P. A. et al. An immunogenic personal neoantigen vaccine for patients with melanoma. Nature 547, 217–221 (2017). This article provides a strong rationale for further development of neo-epitope vaccines, alone and in combination with checkpoint blockade or other immunotherapies.

  257. 257.

    Garcia-Martinez, E. et al. Trial watch: immunostimulation with recombinant cytokines for cancer therapy. Oncoimmunology 7, e1433982 (2018).

  258. 258.

    Jiang, T., Zhou, C. & Ren, S. Role of IL-2 in cancer immunotherapy. Oncoimmunology 5, e1163462 (2016).

  259. 259.

    Sockolosky, J. T. et al. Selective targeting of engineered T cells using orthogonal IL-2 cytokine-receptor complexes. Science 359, 1037–1042 (2018).

  260. 260.

    Ochoa, M. C. et al. Interleukin-15 in gene therapy of cancer. Curr. Gene Ther. 13, 15–30 (2013).

  261. 261.

    Romee, R. et al. First-in-human phase 1 clinical study of the IL-15 superagonist complex ALT-803 to treat relapse after transplantation. Blood 131, 2515–2527 (2018).

  262. 262.

    Mazzucchelli, R. & Durum, S. K. Interleukin-7 receptor expression: intelligent design. Nat. Rev. Immunol. 7, 144–154 (2007).

  263. 263.

    Deiser, K., Stoycheva, D., Bank, U., Blankenstein, T. & Schuler, T. Interleukin-7 modulates anti-tumor CD8+T cell responses via its action on host cells. PLOS ONE 11, e0159690 (2016).

  264. 264.

    Xu, X., Sun, Q., Mei, Y., Liu, Y. & Zhao, L. Newcastle disease virus co-expressing interleukin 7 and interleukin 15 modified tumor cells as a vaccine for cancer immunotherapy. Cancer Sci. 109, 279–288 (2018).

  265. 265.

    Al-Chami, E., Tormo, A., Khodayarian, F. & Rafei, M. Therapeutic utility of the newly discovered properties of interleukin-21. Cytokine 82, 33–37 (2016).

  266. 266.

    Kannappan, V. et al. Interleukin 21 inhibits cancer-mediated FOXP3 induction in naive human CD4 T cells. Cancer Immunol. Immunother. 66, 637–645 (2017).

  267. 267.

    Spolski, R. & Leonard, W. J. IL-21 and T follicular helper cells. Int. Immunol. 22, 7–12 (2010).

  268. 268.

    Lewis, K. E. et al. Interleukin-21 combined with PD-1 or CTLA-4 blockade enhances antitumor immunity in mouse tumor models. Oncoimmunology 7, e1377873 (2017).

  269. 269.

    Chapuis, A. G. et al. Combined IL-21-primed polyclonal CTL plus CTLA4 blockade controls refractory metastatic melanoma in a patient. J. Exp. Med. 213, 1133–1139 (2016).

  270. 270.

    Kaiser, J. ‘Liquid biopsy’ for cancer promises early detection. Science 359, 259 (2018).

  271. 271.

    Tavare, R. et al. An effective immuno-PET imaging method to monitor CD8-dependent responses to immunotherapy. Cancer Res. 76, 73–82 (2016).

  272. 272.

    Ali, H. R., Chlon, L., Pharoah, P. D., Markowetz, F. & Caldas, C. Patterns of immune infiltration in breast cancer and their clinical implications: a gene-expression-based retrospective study. PLOS Med. 13, e1002194 (2016).

  273. 273.

    Newman, A. M. et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods 12, 453–457 (2015).

  274. 274.

    Rooney, M. S., Shukla, S. A., Wu, C. J., Getz, G. & Hacohen, N. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell 160, 48–61 (2015).

  275. 275.

    Gentles, A. J. et al. The prognostic landscape of genes and infiltrating immune cells across human cancers. Nat. Med. 21, 938–945 (2015).

  276. 276.

    Aran, D., Hu, Z. & Butte, A. J. xCell: digitally portraying the tissue cellular heterogeneity landscape. Genome Biol. 18, 220 (2017).

  277. 277.

    Li, T. et al. TIMER: a web server for comprehensive analysis of tumor-infiltrating immune cells. Cancer Res. 77, e108–e110 (2017).

  278. 278.

    Thorsson, V. et al. The immune landscape of cancer. Immunity 48, 812–830 (2018).

  279. 279.

    Zappia, L., Phipson, B. & Oshlack, A. Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database. PLOS Comput. Biol. 14, e1006245 (2018).

  280. 280.

    Chen, X., Sun, Y. C., Church, G. M., Lee, J. H. & Zador, A. M. Efficient in situ barcode sequencing using padlock probe-based BaristaSeq. Nucleic Acids Res. 46, e22 (2018).

  281. 281.

    Herbst, R. S. et al. Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature 515, 563–567 (2014).

  282. 282.

    Topalian, S. L., Drake, C. G. & Pardoll, D. M. Targeting the PD-1/B7-H1(PD-L1) pathway to activate anti-tumor immunity. Curr. Opin. Immunol. 24, 207–212 (2012).

  283. 283.

    Ayers, M. et al. IFN-gamma-related mRNA profile predicts clinical response to PD-1 blockade. J. Clin. Invest. 127, 2930–2940 (2017).

  284. 284.

    Davoli, T., Uno, H., Wooten, E. C. & Elledge, S. J. Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy. Science 355, eaaf8399 (2017).

  285. 285.

    Papaccio, F. et al. Concise review: cancer cells, cancer stem cells, and mesenchymal stem cells: influence in cancer development. Stem Cells Transl Med. 6, 2115–2125 (2017).

  286. 286.

    Jolly, M. K., Ware, K. E., Gilja, S., Somarelli, J. A. & Levine, H. EMT and MET: necessary or permissive for metastasis? Mol. Oncol. 11, 755–769 (2017).

  287. 287.

    Moustakas, A. & de Herreros, A. G. Epithelial-mesenchymal transition in cancer. Mol. Oncol. 11, 715–717 (2017).

  288. 288.

    Terry, S. et al. New insights into the role of EMT in tumor immune escape. Mol. Oncol. 11, 824–846 (2017).

Download references

Acknowledgements

The authors thank the following institutions for their financial support: the National Cancer Institute of France (INCa), the Plan Cancer, the Canceropole Ile de France, INSERM, Cancer Research for Personalized Medicine (CARPEM), the Paris Alliance of Cancer Research Institutes (PACRI), H2020 PHC-32-2014 APERIM grant number EEAA15006DDA, MedImmune (grant number RVE15004DSA) and LabEx Immuno-oncology.

Author information

The authors contributed equally to all aspects of the article.

Correspondence to Jérôme Galon.

Ethics declarations

Competing interests

Immunoscore is a registered trademark from INSERM. J.G. is co-founder and chairman of the scientific advisory board of HalioDx. J.G. has patents associated with an ‘in vitro method for the prognosis of progression of a cancer’ (PCT/IB2006/003168 and PCT/EP2013/062405). J.G. established Collaborative Research Agreement (grants) with Perkin-Elmer, IO Biotech, MedImmune, Astra Zeneca, Janssen, Imcheck Therapeutics. J.G. participated to Scientific Advisory Boards of BMS, MedImmune, Astra Zeneca, Novartis, Definiens, Merck Serono, IO Biotech, ImmunID, Nanostring, Illumina, Northwest Biotherapeutics, Actelion, Amgen, Kite Pharma and Merck MSD. J.G. was a consultant for BMS, Roche, GSK, Compugen, Mologen and Sanofi.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Glossary

TNM system

The tumour-node-metastasis (TNM) staging system is a globally recognized classification of tumours based on their anatomical extent. T refers to the size and extent of the primary tumour, N refers to the involvement of regional lymph nodes and M describes the presence of distant metastases.

Pathologic T (pT) stage

The staging assigned post-surgery to guide treatment stratification, patient selection for clinical trials and prognosis prediction (as opposed to clinical staging that relies on physical exams and imaging tests).

Immunoproteasome

Proteasome isoform constitutively expressed in haematopoietic cells and induced in non-immune cells following exposure to interferon-γ (IFNγ) and other pro-inflammatory cytokines (type I interferons and tumour necrosis factor (TNF)). It is involved in antigen processing and in the expansion, maintenance and differentiation of T cell populations during an immune response.

T cell receptor (TCR) repertoire

The variety of the TCR diversity, as generated by the somatic recombination of the germ line V, D and J gene segments and the deletion and insertion of nucleotides at the V(D)J junctions. Such variety is required to recognize a wide spectrum of antigens.

TCR Vß subfamilies

Human TCR ß locus is on chromosome 7, comprising nine multimember V subfamilies plus additional elements on chromosome 9. The presence of multiple subfamilies is due to evolutionary duplication events.

Tumour-specific antigen

(TSA). Antigen not encoded in the normal genome, expressed exclusively by tumour cells.

Antigenicity

Presence of tumour-associated antigens (TAAs) capable of engaging with T cell receptors or antibodies (B cell receptors), thereby driving adaptive immunity.

Abscopal effect

Phenomenon characterized by the regression of metastases outside the field of radiation after irradiation of one tumour site. Although rarely detected, it is well documented in patients with more immunogenic tumours.

Adjuvanticity

Presence of damage-associated molecular patterns (DAMPs) and stress signals driving the innate immunity.

Genotoxic chemotherapies

Chemical agents that cause DNA damage, such as single-strand and double-strand breaks, loss of excision repair, crosslinking, alkali-labile sites, point mutations and structural and numerical chromosomal aberrations.

Damage-associated molecular patterns

(DAMPs). Intracellular molecules that are hidden from immune recognition under physiological conditions. These molecules are secreted, exposed or released upon cellular stress or tissue injury and recognized by pattern-recognition receptors expressed on innate immune cells.

Tumour-associated antigens

(TAAs). Antigens that are preferentially expressed by tumour cells but they can also be found in normal tissues (except for the TSAs, which are exclusively expressed by tumour cells). They can be broadly categorized into aberrantly expressed self-antigens, mutated self-antigens and TSAs.

(LC3B+) puncta

LC3 is a protein involved in the formation of autophagosomes and autolysosomes. Punctate (as opposed to diffused) LC3 staining indicates autophagy, as determined by fluorescence microscopy.

Differentiation antigens

Antigens derived from proteins that are expressed in a given type of tumour and the corresponding healthy tissue, often in lower amounts.

Neoantigen fitness

The likelihood of a peptide to be immunogenic, as measured by its binding affinity to major histocompatibility complex (MHC) and subsequent recognition by T cells.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Further reading