Evaluation of targeted therapies in advanced breast cancer: the need for large-scale molecular screening and transformative clinical trial designs

Subjects

Abstract

Breast cancer (BC) has been classified into four intrinsic subtypes through seminal studies employing gene expression profiling analysis of primary tumours, namely the luminal A and B subtypes, the human epidermal growth factor receptor 2-like subtype and the basal-like subtype. More recently, the emergence of high-throughput genomic sequencing techniques, such as next-generation or massive parallel sequencing has expanded our understanding of the complex genomic landscapes of BC, with marked intertumour heterogeneity seen among different patients. In addition, increasing evidence indicates intratumour heterogeneity, with molecular differences observed within one patient, both spatially and longitudinally. These phenomena have an impact on the clinical development of molecularly targeted agents, with the classical paradigm of population-based clinical trials being no longer efficient. In the era of genomically driven oncology, three complementary tools can accelerate the clinical development of targeted agents for advanced BC as follows: (i) the implementation of molecular profiling of metastatic tumour lesions, as exemplified by the AURORA (Aiming to Understand the Molecular Aberrations in Metastatic Breast Cancer) programme; (ii) serial assessments of circulating tumour DNA, allowing a more thorough molecular interrogation of metastatic tumour burden; and (iii) new innovative clinical trial designs able to address the challenges of the increasing molecular fragmentation of BC.

Introduction

Breast cancer (BC) is the second most common cancer in the world and the most frequent cancer among women. It is now the second cause of cancer-related death in the western world after lung cancer.1 Trastuzumab, a monoclonal antibody targeting the human epidermal growth factor receptor 2 (HER2), has profoundly changed the natural history of HER2-positive BC and was one of the first examples of the incorporation of genomic information into clinical decision-making.2 This success story exemplified the potential of clinical development of molecularly targeted agents within molecular segments of BC, defined by the molecular aberration under targeting by the respective blocking agent, opening the road to personalized cancer medicine in BC.3, 4

Seminal studies conducted more than 10 years ago, employing gene expression profiling of primary BC, led to the identification of four intrinsic subtypes, with different molecular and clinical characteristics as follows:5, 6, 7 (i) the luminal A and B subtypes, being hormone-receptor positive, with the latter showing increased proliferation rate as compared with their former counterparts and worse clinical outcome;8 (ii) the HER2-like subtype characterized by the increased expression of several genes of the ErbB2/HER2 amplicon, showing sensitivity to HER2-blocking agents;9, 10 and (iii) the basal-like subtype, which is predominantly oestrogen receptor negative, progesterone receptor negative and HER2 negative, characterized by aggressive clinical behaviour and lack of targeted therapeutic options.11, 12 More recently, additional BC subtypes have been identified. In the largest series reported so far, based on detailed characterization of 2000 primary BCs combining genomic and transcriptomic sequencing, the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) group identified 10 different molecular subtypes with distinct clinical outcomes.13

Subsequent studies interrogated further the genomic landscapes of BC through next-generation sequencing (NGS); numerous mutated and/or amplified genes have been identified, albeit mostly at low frequencies.14, 15, 16, 17, 18 Of note, some commonly found genomic aberrations are not currently targetable and cannot be therapeutically exploited through the administration of a molecularly targeted agent, as exemplified by TP53 mutations,19 whereas other ‘targetable’ aberrations are found at a low frequencies, such as ERBB2 mutations.20 Importantly, the functional significance of these aberrations is variable, with a binary classification having prevailed:21 (i) ‘driver’ events, corresponding to molecular aberrations that can initiate and support oncogenesis and tumour progression, respectively, and thus confer a growth advantage to the cancer cells bearing them and (ii) ‘passenger’ events, corresponding to aberrations without functional consequences. It is apparent that the former constitute potential therapeutic targets, with an increasing number of molecularly targeted agents undergoing clinical development for metastatic BC (Table 1).22

Table 1 Molecularly targeted agents under clinical development for patients with metastatic BC

The above-mentioned studies improved our understanding of the biology underlying BC; however, they all interrogated mainly the molecular landscapes of primary BC tumours. Emerging data indicate that there is a molecular evolution of BC over space and time, so that additional data need to be generated for the genomic aberrations in the metastatic setting. These data support differential mutation frequencies and structural variation patterns between primary tumours and their subsequent metastatic lesions.23, 24 Further data are needed to facilitate efficient clinical development of molecularly targeted agents in advanced disease.

In this study, we provide a short overview of the genomic landscapes of BC, as identified by recent studies. We argue that in the era of genomically driven oncology, three complementary tools can accelerate the clinical development of targeted agents for advanced BC: (i) the implementation of molecular profiling of metastatic tumour lesions, as exemplified by the AURORA (Aiming to Understand the Molecular Aberrations in Metastatic Breast Cancer) programme; (ii) the development of technologies allowing serial assessments of circulating tumour DNA, allowing a more thorough molecular interrogation of metastatic tumour burden; and (iii) new innovative clinical trial designs that are able to address the challenges of the increasing molecular fragmentation of BC.

Current knowledge of the landscape of genomic alterations in BC

As previously mentioned, four intrinsic subtypes of BC have been identified, with the respective classification, although by immunohistochemical surrogate markers, having prevailed in the clinical decision-making: the luminal A and B subtypes, the HER2-like subtype and the basal-like subtype. The rapid development of high information content assays including DNA sequencing and DNA methylation, and microRNA expression and proteomics methods provide unique opportunities to characterize more thoroughly the molecular background of BC.

The Cancer Genome Atlas study represents a systematic effort to provide comprehensive molecular portraits of BC across all four intrinsic subtypes of the disease.16 In addition to identifying nearly all genes previously implicated in BC (PIK3CA, PTEN, AKT1, TP53, GATA3, CDH1, RB1, MLL3, MAP3K1 and CDKN1B), a number of novel, significantly mutated genes were identified, including TBX3, RUNX1, CBFB, AFF2, PIK3R1, PTPN22, PTPRD, NF1, SF3B1 and CCND3. Significantly mutated genes were considerably more diverse and recurrent within the luminal A and luminal B tumours as compared with the basal-like and HER2-enriched subtypes.16 The luminal A subtype contains the most significantly mutated genes, with the most notable being PIK3CA (45%), which is a targetable aberration, followed by MAP3K1, GATA3, TP53, CDH1 and MAP2K. Luminal B cancers also display a significant number of mutated genes, with TP53 and PIK3CA being the most frequent. In addition, many potential copy-number-based drug targets are identified in this subgroup, such as FGFR, IFGR1 and CDK amplifications. The HER2 subtype, which has frequent ERBB2 amplification (80%), has a hybrid pattern with a high frequency of TP53 (72%) and PIK3CA (39%) mutations, and a much lower frequency of other significantly mutated genes including PIK3R1 (4%). Last, basal-like tumours show the highest rates for TP53 mutations (80%), followed by BRCA1 and BRCA2 mutations, found collectively in ~20% of the cases analysed. Interestingly, basal-like tumours show molecular similiraties with high-grade serous ovarian tumours.

Of note, The Cancer Genome Atlas data, corresponding to the largest collection of primary BCs with available multi-layer molecular profiling and clinical annotation, indicate several candidate molecular therapeutic targets across all BC subtypes. In addition, another approach could be to cluster several individual molecular alterations, such as gene mutations, amplifications and/or epigenetic changes, within signalling pathways. This approach could theoretically increase the number of patients for whom targeted agents might hold promise. In any case, the clinical utility of the aberrations listed in this catalogue of recurrent molecular aberrations still needs to be assessed; the understanding of the molecular heterogeneity underlying BC and the increasing number of targeted agents under development create challenges as are outlined in the following sections, where we propose strategies to tackle them.

The need for molecular profiling of metastatic BC and the AURORA initiative

The increasing evidence supporting a molecular evolution of BC during its life cycle indicate that deeper molecular characterization of metastatic BC tissue is needed.25 Indeed, there are data supporting the acquisition of new molecular aberrations and/or loss of pre-existing ones in metastatic BC lesions compared with matched primary tumours; this has been exemplified by discordances observed in the mutational status in the commonly mutated PIK3CA gene.26, 27 In addition, studies applying NGS to both primary breast tumours and their subsequent metastatic lesions showed that significant molecular evolution can occur as BC progresses from primary tumour to metastatic dissemination.24, 28 Acknowledging this need, the Breast International Group has set up an academic, multi-national, collaborative programme of molecular profiling of metastatic BC, called AURORA.29

Within AURORA, 1300 patients with either newly diagnosed metastatic BC or treated with no more than one line of systemic therapy will be recruited in over 80 leading European hospitals affiliated with groups from the Breast International Group network (Figure 1). This molecular profiling programme is supported by custom-developed IT tools, allowing the recording and tracking of biological samples, as well as the capturing and transfer of the high-volume clinical and genomic data that AURORA will generate. More specifically, these patients will undergo a metastatic lesion biopsy and sections of the primary tumour and blood samples will be collected. Targeted NGS for a panel of more than 400 cancer-related genes will be performed on all three biospecimens. Somatic mutations and copy-number alterations will be then reported to the treating physician on a real-time basis, as well as germline alterations if the patient provided consent for reporting of the latter ones. Furthermore, RNA sequencing will be performed at a subsequent timepoint, to provide a more thorough genomic characterization of the tumour samples analysed.

Figure 1
figure1

The AURORA initiative study design.

The patients entering AURORA will be prospectively followed, with information about the different types of treatment administered, and the respective efficacy/clinical outcome will be collected. AURORA is expected to improve the understanding of metastatic BC, with the following expected gains of knowledge as follows: (i) elucidation of the molecular evolution of BC, as it progresses from primary to metastatic disease, (ii) identification of potential prognostic biomarkers, for both early and advanced disease; and (iii) identification of potential predictive biomarkers, for both early and advanced disease. In regards to the latter, patients who will be deemed to be ‘clinical outliers’, that is, being either ‘exceptional responders’ or ‘rapid progressors’, will have their tumours subjected to whole-exome gene sequencing, in an effort to mine further the genomic landscape of their disease.

Of note, patients entering AURORA will be treated as per their physicians’ choice, receiving standard of care. Alternatively, they can enter downstream clinical trials developed to assess promising molecularly targeted agents by the Breast International Group. In the second scenario, the abundance of molecular profiling information generated through AURORA for both primary and metastatic BC holds the promise to accelerate successful clinical development of the investigational agents and identify putative predictive biomarkers. The extended collection of biospecimens will be subjected to further molecular interrogation in the future, thus expanding the potential of AURORA to lead to clinically meaningful conclusions for advanced BC. These downstream trials, however, if run in an old manner—namely following the ‘population-based’ paradigm of clinical trials—will face tremendous difficulties as we argue below; thus, a transformation in clinical trial design and conduct is urgently needed. Besides AURORA, there are other ongoing programmes assessing molecular profiling in different settings (Table 2).

Table 2 Ongoing efforts of molecular profiling in cancer diagnoses

Challenges for successful development of molecularly targeted agents

It should be noted that the success of this treating paradigm through the implementation of molecular profiling of tumour tissue will come from the successful clinical development of targeted agents for patients bearing tumours with specific molecular aberrations. This has been successfully exemplified in a preliminary, yet clear way, through the high antitumour activity seen for endocrine treatment and HER2 blockade for patients selected on the basis of hormone receptor and HER2 status, respectively. Several challenging issues need to be addressed, to increase the chances for further successful stories of molecularly targeted agents improving the clinical outcome of patients with BC, which can be summarized as follows: (i) the functional output of any given molecular aberration should be well evaluated and validated before its pursuit as therapeutic target. Indeed, functional annotation of gene mutations and/or copy-number aberrations seen through molecular profiling will be of crucial importance for the successful clinical development of molecularly targeted agents within specific genomic segments of BC. (ii) The allelic frequency of a ‘targetable’ molecular aberration should be taken into account, as such an aberration might be detected in a minor subclone of the disease, rendering its therapeutic blockade futile. (iii) Selection and/or prioritization of one ‘targetable’ aberration among several others that could be detected within one tumour tissue. (iv) Extensive molecular characterization applied for patients, in particular for those with metastatic disease, as the genomic landscape of the disease could be complex, already having aberrations that would mediate resistance to targeted therapeutics against other co-existing aberrations. In addition, this approach is more efficient in terms of sparing valuable tumour tissue. (v) Detailed serial monitoring of the evolving molecular landscapes of the disease, to follow the adaptive responses of cancer cells against targeted therapeutics applied. This could be achieved through the implementation of serial plasma-based monitoring, as it will be outlined in the following section. (vi) The translation of DNA-based alterations in consecutive alterations at the RNA and protein level should be rigorously assessed, as the targeted agents block proteins, and the DNA alterations we detect are not always translated at the protein level. Last, (vii) accurate knowledge of the pharmacology of the targeted agents under assessment, as well as thorough target validations processes in place, before matching targeted compounds for patients bearing specific molecular aberrations in their tumour.

Acquisition of genomic alterations during disease evolution and the promise of circulating tumour DNA

Discordances in oestrogen receptor, progesterone receptor and HER2 protein expression status between the primary tumour and the metastasic lesion have been known for several years. Mismatches have been identified in 10–40% of cases for hormone receptor expression and in nearly 10% of cases for HER2, with cases of both gains or losses.30, 31, 32, 33, 34, 35, 36 This phenomenon is a manifestation of temporal intratumour heterogeneity, indicating that we cannot extrapolate the molecular aberrations of metastatic disease on the basis of the molecular profile of its primary counterpart. Importantly, some of the studies that assessed the discordance rates of this triplet of markers in patients with BC indicate that this heterogeneity has prognostic implications, thus offering further arguments to support the need for assessment of the molecular background of the metastatic disease.37, 38 Thus, high-throughput molecular profiling techniques such as NGS need to be applied to metastatic lesions, to identify the most relevant aberrations for advanced disease. Indeed, more than 15 years ago a study assessed 29 primary BCs and their paired asynchronous metastases, using comparative genomic hybridization and fluorescence in situ hybridization.39 Interestingly, nine metastases (31%) were found to have an almost completely different genetic composition as compared with that of their paired primary tumours. Expanding further this approach, Desmedt et al.40 recently performed exome sequencing from an autopsy series of 10 BC patients in order to reconstruct the trajectories of metastatic BC progression. The authors observed that late relapses show additional genomic aberrations compared with the primary tumour, and that most distant metastases seem to arise from a first single seeding event, namely the ‘common metastatic precursor’, which may or may not be present in the primary tumour.40 Other recent genomic studies confirm that relapsing tumours often acquire new molecular aberrations and note differences across metastatic sites.28

These findings suggest that more than one metastatic lesion should ideally be biopsied at different time points of the disease, to capture the full genomic portrait of advanced BC. The advent of techniques that can detect circulating tumour DNA in plasma samples from patients with cancer is a promising alternative, to serve as both a diagnostic and monitoring tool for advanced disease.41 The detection of circulating tumour DNA could bridge the ‘gap’ between the genomic landscapes of primary and metastatic BC, offering a more thorough representation of the whole tumour burden in the metastatic setting, as compared with the molecular profile of a single metastatic biopsy.

An interesting proof-of-principle study was recently reported, based on a case study of a patient with metastatic disease, which used massively parallel sequencing for a panel of 300 cancer-related genes in both primary and metastatic tumour samples, as well as in the plasma.42 The results of this study indicated that there was significant heterogeneity in the mutational profiles of the primary and the metastatic tumour lesion; however, analysis of circulating tumour DNA did capture all mutations present in both tumour samples, thus indicating that plasma-based mutational profiling could substitute the molecular analysis of metastatic tumour tissue; however, confirmatory results are needed.

Another study reported results from NGS for a panel of 50 cancer-related genes from 69 tumour (primary and metastases) and 31 plasma samples originating from 17 patients with metastatic BC.43 In 13 of 17 (76%, 95% confidence interval: 50 to 93%) patients tumour and plasma provided concordant results, whereas in the remaining patients the results were discordant, providing complementary information. These are promising results; however, data to confirm the clinical utility of this approach still need to be generated. Furthermore, the analytical validity of the methods of assessment of circulating tumour DNA needs to be fixed, through the standardization of the techniques, as well as that of the samples collection.

In conclusion, there is increasing understanding of the genomic diversity of BC seen among different patients (intertumour heterogeneity) or within one patient (intratumour heterogeneity), spread in space and time. However, several questions remain unanswered: what are the dynamics of the tumour sub-clonal architecture over time? How is the genome landscape of the tumour impacted by our current drugs? Which ‘clones’ are going to have a major role in the lethal evolution of the disease? How to overcome the futility of targeting a sub-clonal driver at one site of the disease? Could the circulating tumour DNA substitute tumour tissue biopsies as a more thorough assessment of the genomic aberrations seen throughout the whole cancer burden in a patient?

The need for transformative clinical trial designs in the era of ‘genomic’ medicine

The traditional paradigm of clinical development of anticancer agents has consisted of single-arm phase II studies, which would be followed by randomized phase III trials, if deemed promising.44 In this classic scenario, patients would be selected on the basis of certain clinical and pathological characteristics of their disease, namely pretreatment history and oestrogen receptor/HER2 status. However, this approach has obvious limitations in the era of genomically driven oncology: on one hand, it cannot accommodate the rapidly increasing number of targeted anticancer agents in need of efficient clinical development and, on the other hand, it ignores the increasing molecular fragmentation of BC, with the realistic prediction that some of the novel targeted agents will achieve antitumour activity within specific molecularly defined BC subpopulations.45 Assuming that there is a targetable molecular aberration with a frequency of 1–2%, then for a single-arm phase II study 30–35 patients with advanced BC would be needed to confirm a decent antitumour activity of the corresponding targeted compound. This molecularly defined sample size would require a screening of more than 4000 patients, with even greater numbers needed for a registration phase III trial; the classical paradigm of clinical trials in oncology would be highly inefficient for such an agent.

To address these ever more frequently met challenges, new transformative clinical trial designs are needed. These study designs, described below, hold the promise to reduce the high attrition rates seen in oncology drugs’ development, as well as to keep the numbers of patients recruited in the respective trials at reasonable levels. To this end, statisticians have recommended integrated phase II/III designs that ‘save time’ in the drug development process.42

Longitudinal cohort studies with or without downstream clinical trials

This study design is exemplified among others by the AURORA programme described earlier. In short, this corresponds to a large-scale molecular profiling of patients with one particular cancer diagnosis being prospectively followed. Using this molecular profiling as the starting point, there can be ‘nested’ or ‘downstream’ clinical trials, making use of the molecular data generated,46 offering a dual benefit as follows: (i) facilitate the molecular pre-selection of patients eligible to be enroled in genotype-driven clinical trials and (ii) identify putative predictive biomarkers through the coupling of the molecular and clinical annotation. Additional benefits can be expected through this approach (Table 3).

Table 3 Expected benefits from prospective molecular profiling programmes of patients with metastatic BC

Master-protocol trials

This study design can assess different targeted agents in parallel within independent cohorts of patients defined by specific molecular aberrations that could predict sensitivity to the investigational agent under assessment (Figure 2). This approach reduces the percentage of screening failures, as patients with different aberrations can be enroled in one of the different molecularly defined cohorts. The Breast International Group and the North American Breast Cancer Group are currently designing such a study, assessing targeted agents in the setting of aggressive metastatic triple-negative BC. In particular, patients with this BC phenotype, who develop early systematic relapse will be eligible. Once metastatic tumour tissue has been subjected to NGS and on availability of these results, the patients will be entering one of the several parallel molecularly driven arms, randomized between standard of care or the respective targeted agent(s), dictated by the genotype of their disease. Of note, these trials face the difficulty of handling overlapping biomarkers and need to prioritize these as part of the protocol.

Figure 2
figure2

Hypothetical study design for a master protocol for patients with metastatic breast cancer. Patients with metastatic breast cancer undergo a metastatic biopsy. This tumour tissue and the archived primary tissue undergo NGS for molecular profiling. On availability of the results, they are directed to a molecular segment based on the aberrations found. They are randomized to receive matched targeted treatment or standard of care.

Basket trials

This is an innovative, histology agnostic trial design, where patients with tumours of different histologies can be enroled in the study protocol on the basis of the presence of a commonly shared molecular aberration. This study design has been implemented in a currently ongoing effort to develop a small molecule HER2-blocking agent within patients with ERBB2 mutated cancers (http://clinicaltrials.gov/ct2/show/NCT01953926). The main disadvantage in this approach is the different functional output and consecutively predictive impact a single molecular aberration can have among different types of cancer. This has been exemplified by the lack of antitumour efficacy of vemurafenib, a Braf-blocking agent, in the setting of BRAF-mutated metastatic colorectal cancer, contradicting the dramatic responses seen among patients with metastatic melanoma bearing the V600E Braf mutation.47

Adaptive trials

Adaptive trials constitute another innovative study design, recently employed by the BATTLE (Biomarker-integrated Approaches of Targeted Therapy for Lung Cancer Elimination)-1 and -2 clinical trials for patients with metastatic non-small cell lung cancer,48 or the I-SPY (The Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Biomarker Analysis)-1 and -2 trials in the neoadjuvant setting of BC.49, 50, 51 These are dynamically evolving trials, with the defining characteristic being that in the initial phase of the adaptive study patients are being recruited in the different arms at equal ratios; however, as the recruitment proceeds and efficacy data are being pooled from the different biomarker-driven arms, the adaptive phase follows, where randomization ratios can be re-adapted and treatment arms can be dropped and/or added if specific thresholds of efficacy are not reached or new promising data emerge, respectively.49

N-of-1 trials

This is a study design that has been more pursued in fields of clinical research other than oncology, such as trials in the context of musculoskeletal or pulmonary conditions.52, 53 The main characteristic is the recruitment of individual patients exposed to different experimental agents or placebo in different sequences and with washout periods in between.54 This allows each involved patient to serve as his/her own comparator, through the comparison of the efficacy seen for the different experimental agents that the patient receives during his/her participation in the trial. In oncology, a modified N-of-1 study design was reported some years ago, which assessed the antitumour activity of different targeted agents, matched to the molecular profile of the patients.55 In this trial, 86 patients with different types of advanced tumours had molecular profiling and 66 of them were treated according to these results. In terms of efficacy, 18 patients had a progression-free survival ratio of 1.3 (95% confidence interval: 17 to 38%; one-sided, one-sample P=0.007), meeting the primary endpoint, which was the comparison of the progression-free survival obtained by the targeted treatment with the progression-free survival achieved by the previous systemic treatment within each individual patient. This approach could be helpful in cases where a molecular aberration with a really low frequency defines a specific patient subpopulation of interest, for which randomized studies would be extremely challenging.

Window-of-opportunity trials

These trials are based on the administration of an investigational agent over a short period of time, typically in the neoadjuvant setting that enables serial tumour biopsies, although such studies can be conducted in the metastatic setting as well.56, 57 These trials do not have, by definition, an efficacy endpoint given the short drug exposure but they can assess in vivo the biological effects of the experimental agent administered in human patients, evaluating the pharmacologic modulation of the therapeutic target. An ongoing study using this innovative design is the D-Beyond trial, a pre-operative window study evaluating Denosumab, a RANK ligand inhibitor, and its biological effects for premenopausal women with early BC (https://clinicaltrials.gov/ct2/show/NCT01864798). In this trial, patients receive pre-operatively two doses of denosumab 120 mg subcutaneously 1 week apart followed by surgery. Ten to 21 days after the first injection, surgery was performed, with the primary objective being the antiproliferative effect exerted by Denosumab, as measured by Ki67 immunohistochemistry. Another window-of-opportunity trial ready to recruit patients is the RHEA (Biomarker Research Study for PF-03084014 in chemoresistant triple-negative BC). This is a single-arm, phase 2, open-label preoperative study of PF-03084014, a NOTCH inhibitor, administered for 9 days after the completion of neoadjuvant chemotherapy in patients with chemo-resistant BC of the triple-negative phenotype.

Conclusions

There is still much to be learned about the clonal evolution of BC and the molecular heterogeneity of advanced disease. Initiatives to ‘scale up’ molecular screening need to be encouraged, so that we can gain clarity on the genomic landscape of metastatic BC. Of note, SAFIR01, an initiative of precision medicine conducted in the setting of BC illustrated how challenging the implementation of molecular profiling can be; indeed, in this programme only 55 patients out of 423 could get access to a targeted agent matched to a molecular aberration found.58 However, the implementation of more extensive panels of genes assessed, as will be the case for AURORA or SAFIR02, as well as the increasing list of targeted compounds aiming different aberrations can improve this performance. In addition, the implementation of systematic assessment of plasma-based biomarkers can complement the information we derive from tumour tissue biopsies or even replace the latter ones. However, establishment of the analytic and clinical validity of the methods used followed by the demonstration of their clinical utility is also needed before their implementation in the clinical setting. Finally, there is a clear realization that next to the technological revolution that facilitates the molecular interrogation of metastatic BC, further innovative approaches are needed in the field of clinical trial designs; such approaches should accommodate the increasing molecular fragmentation of BC, minimizing the number of patients needed to be screened and subsequently involved in trials assessing molecularly targeted agents. For all this to become a reality, large collaborative networks will be of paramount importance to achieve personalized cancer medicine.

References

  1. 1

    Ferlay J, Soerjomataram I, Ervik M, Dikshit R, Eser S, Mathers C et al GLOBOCAN 2012 v1.0, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 11 (Internet). International Agency for Research on Cancer: Lyon, France; 2013. Available from: http://globocan.iarc.fr.

  2. 2

    Hudis CA . Trastuzumab — mechanism of action and use in clinical practice. N Engl J Med 2007; 357: 39–51.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  3. 3

    Ades F, Zardavas D, Aftimos P, Awada A . Anticancer drug development: moving away from the old habits. Curr Opin Oncol 2014; 26: 334–339.

    Article  PubMed  Google Scholar 

  4. 4

    Zardavas D, Pugliano L, Piccart M . Personalized therapy for breast cancer: a dream or a reality? Future Oncol 2013; 9: 1105–1119.

    CAS  Article  PubMed  Google Scholar 

  5. 5

    Perou CM, Sørlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA et al. Molecular portraits of human breast tumours. Nature 2000; 406: 747–752.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  6. 6

    Sorlie T, Tibshirani R, Parker J, Hastie T, Marron JS, Nobel A et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA 2003; 100: 8418–8423.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  7. 7

    Sotiriou C, Neo SY, McShane LM, Korn EL, Long PM, Jazaeri A et al. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci USA 2003; 100: 10393–10398.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  8. 8

    Ades F, Zardavas D, Bozovic-Spasojevic I, Pugliano L, Fumagalli D, de Azambuja E et al. Luminal B breast cancer: molecular characterization, clinical management, and future perspectives. J Clin Oncol 2014; 32: 2794–2803.

    Article  PubMed  Google Scholar 

  9. 9

    Arteaga CL, Sliwkowski MX, Osborne CK, Perez EA, Puglisi F, Gianni L . Treatment of HER2-positive breast cancer: current status and future perspectives. Nat Rev Clin Oncol 2011; 9: 16–32.

    Article  PubMed  Google Scholar 

  10. 10

    Zardavas D, Cameron D, Krop I, Piccart M . Beyond trastuzumab and lapatinib: new options for HER2-positive breast cancer. Am Soc Clin Oncol Educ Book 2013 doi:10.1200/EdBook_AM.2013.33.e2.

    Article  Google Scholar 

  11. 11

    Foulkes WD, Smith IE, Reis-Filho JS . Triple-negative breast cancer. N Engl J Med 2010; 363: 1938–1948.

    CAS  Article  PubMed  Google Scholar 

  12. 12

    Badve S, Dabbs DJ, Schnitt SJ, Baehner FL, Decker T, Eusebi V et al. Basal-like and triple-negative breast cancers: a critical review with an emphasis on the implications for pathologists and oncologists. Mod Pathol 2011; 24: 157–167.

    Article  PubMed  Google Scholar 

  13. 13

    Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ et alMETABRIC Group. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 2012; 486: 346–352.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  14. 14

    Banerji S, Cibulskis K, Rangel-Escareno C, Brown KK, Carter SL, Frederick AM et al. Sequence analysis of mutations and translocations across breast cancer subtypes. Nature 2012; 486: 405–409.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  15. 15

    Ellis MJ, Ding L, Shen D, Luo J, Suman VJ, Wallis JW et al. Whole-genome analysis informs breast cancer response to aromatase inhibition. Nature 2012; 486: 353–360.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  16. 16

    Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature 2012; 490: 61–70.

    Article  Google Scholar 

  17. 17

    Shah SP, Roth A, Goya R, Oloumi A, Ha G, Zhao Y et al. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature 2012; 486: 395–399.

    CAS  Article  PubMed  Google Scholar 

  18. 18

    Stephens PJ, Tarpey PS, Davies H, Van Loo P, Greenman C, Wedge DC et al. The landscape of cancer genes and mutational processes in breast cancer. Nature 2012; 486: 400–404.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  19. 19

    Muller PA, Vousden KH . Mutant p53 in cancer: new functions and therapeutic opportunities. Cancer Cell 2014; 25: 304–317.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  20. 20

    Yan M, Parker BA, Schwab R, Kurzrock R . HER2 aberrations in cancer: implications for therapy. Cancer Treat Rev 2014; 40: 770–780.

    CAS  Article  PubMed  Google Scholar 

  21. 21

    Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA Jr, Kinzler KW . Cancer genome landscapes. Science 2013; 339: 1546–1558.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  22. 22

    Zardavas D, Baselga J, Piccart M . Emerging targeted agents in metastatic breast cancer. Nat Rev Clin Oncol 2013; 10: 191–210.

    CAS  Article  PubMed  Google Scholar 

  23. 23

    Eirew P, Steif A, Khattra J, Ha G, Yap D, Farahani H et al. Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution. Nature 2015; 518: 422–426.

    CAS  Article  PubMed  Google Scholar 

  24. 24

    Shah SP, Morin RD, Khattra J, Prentice L, Pugh T, Burleigh A et al. Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution. Nature 2009; 461: 809–813.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  25. 25

    Zardavas D, Irrthum A, Swanton C, Piccart M . Clinical management of breast cancer heterogeneity. Nat Rev Clin Oncol 2015, e-pub print of head 21 April 2015 doi:10.1038/nrclinonc.2015.73.

    CAS  Article  PubMed  Google Scholar 

  26. 26

    Gonzalez-Angulo AM, Ferrer-Lozano J, Stemke-Hale K, Sahin A, Liu S, Barrera JA et al. PI3K pathway mutations and PTEN levels in primary and metastatic breast cancer. Mol Cancer Ther 2011; 10: 1093–1101.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  27. 27

    Dupont Jensen J, Laenkholm AV, Knoop A, Ewertz M, Bandaru R, Liu W et al. PIK3CA mutations may be discordant between primary and corresponding metastatic disease in breast cancer. Clin Cancer Res 2011; 17: 667–677.

    CAS  Article  PubMed  Google Scholar 

  28. 28

    Ding L, Ellis MJ, Li S, Larson DE, Chen K, Wallis JW et al. Genome remodelling in a basal-like breast cancer metastasis and xenograft. Nature 2010; 464: 999–1005.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  29. 29

    Zardavas D, Maetens M, Irrthum A, Goulioti T, Engelen K, Fumagalli D et al. The AURORA initiative for metastatic breast cancer. Br J Cancer 2014; 111: 1881–1887.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  30. 30

    Curigliano G, Bagnardi V, Viale G, Fumagalli L, Rotmensz N, Aurilio G et al. Should liver metastases of breast cancer be biopsied to improve treatment choice? Ann Oncol 2011; 22: 2227–2233.

    CAS  Article  PubMed  Google Scholar 

  31. 31

    Curtit E, Nerich V, Mansi L, Chaigneau L, Cals L, Villanueva C et al. Discordances in estrogen receptor status, progesterone receptor status, and HER2 status between primary breast cancer and metastasis. Oncologist 2013; 18: 667–674.

    Article  PubMed  PubMed Central  Google Scholar 

  32. 32

    de Dueñas EM, Hernández AL, Zotano AG, Carrión RM, López-Muñiz JI, Novoa SA et al. Prospective evaluation of the conversion rate in the receptor status between primary breast cancer and metastasis: results from the GEICAM 2009-03 ConvertHER study. Breast Cancer Res Treat 2014; 143: 507–515.

    Article  PubMed  PubMed Central  Google Scholar 

  33. 33

    Duchnowska R, Dziadziuszko R, Trojanowski T, Mandat T, Och W, Czartoryska-Arłukowicz B et alPolish Brain Metastasis Consortium. Conversion of epidermal growth factor receptor 2 and hormone receptor expression in breast cancer metastases to the brain. Breast Cancer Res 2012; 14: R119.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  34. 34

    Macfarlane R, Seal M, Speers C, Woods R, Masoudi H, Aparicio S et al. Molecular alterations between the primary breast cancer and the subsequent locoregional/metastatic tumor. Oncologist 2012; 17: 172–178.

    Article  PubMed  PubMed Central  Google Scholar 

  35. 35

    Nedergaard L, Haerslev T, Jacobsen GK . Immunohistochemical study of estrogen receptors in primary breast carcinomas and their lymph node metastases including comparison of two monoclonal antibodies. APMI 1995; 103: 20–24.

    CAS  Article  Google Scholar 

  36. 36

    Simmons C, Miller N, Geddie W, Gianfelice D, Oldfield M, Dranitsaris G et al. Does confirmatory tumor biopsy alter the management of breast cancer patients with distant metastases? Ann Oncol 2009; 20: 1499–1504.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  37. 37

    Wilking U, Karlsson E, Skoog L, Hatschek T, Lidbrink E, Elmberger G et al. HER2 status in a population-derived breast cancer cohort: discordances during tumor progression. Breast Cancer Res Treat 2011; 125: 553–561.

    CAS  Article  PubMed  Google Scholar 

  38. 38

    Lindström LS, Karlsson E, Wilking UM, Johansson U, Hartman J, Lidbrink EK et al. Clinically used breast cancer markers such as estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 are unstable throughout tumor progression. J Clin Oncol 2012; 30: 2601–2608.

    Article  PubMed  Google Scholar 

  39. 39

    Kuukasjärvi T, Karhu R, Tanner M, Kähkönen M, Schäffer A, Nupponen N et al. Genetic heterogeneity and clonal evolution underlying development of asynchronous metastasis in human breast cancer. Cancer Res 1997; 57: 1597–1604.

    PubMed  Google Scholar 

  40. 40

    Desmedt C, Brown D, Szekely B, Smeets D, Szasz MA, Adnet PY et al Unraveling Breast Cancer Progression Through Geographical and Temporal Sequencing. AACR: San Diego, 2014, Abstract number 986.

    Google Scholar 

  41. 41

    De Mattos-Arruda L, Cortes J, Santarpia L, Vivancos A, Tabernero J, Reis-Filho JS et al. Circulating tumour cells and cell-free DNA as tools for managing breast cancer. Nat Rev Clin Oncol 2013; 10: 377–389.

    CAS  Article  PubMed  Google Scholar 

  42. 42

    De Mattos-Arruda L, Weigelt B, Cortes J, Won HH, Ng CK, Nuciforo P et al. Capturing intra-tumor genetic heterogeneity by de novo mutation profiling of circulating cell-free tumor DNA: a proof-of-principle. Ann Oncol 2014; 25: 1729–1735.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  43. 43

    Rothé F, Laes JF, Lambrechts D, Smeets D, Vincent D, Maetens M et al. Plasma circulating tumor DNA as an alternative to metastatic biopsies for mutational analysis in breast cancer. Ann Oncol 2014; 25: 1959–1965.

    Article  PubMed  Google Scholar 

  44. 44

    Hunsberger S, Zhao Y, Simon R . A comparison of phase II study strategies. Clin Cancer Res 2009; 15: 5950–5955.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  45. 45

    Sleijfer S, Bogaerts J, Siu LL . Designing transformative clinical trials in the cancer genome era. J Clin Oncol 2013; 31: 1834–1841.

    Article  PubMed  Google Scholar 

  46. 46

    Rodón J, Saura C, Dienstmann R, Vivancos A, Ramón y Cajal S, Baselga J et al. Molecular prescreening to select patient population in early clinical trials. Nat Rev Clin Oncol 2012; 9: 359–366.

    Article  PubMed  Google Scholar 

  47. 47

    Corcoran RB, Ebi H, Turke AB, Coffee EM, Nishino M, Cogdill AP et al. EGFR-mediated re-activation of MAPK signaling contributes to insensitivity of BRAF mutant colorectal cancers to RAF inhibition with vemurafenib. Cancer Discov 2012; 2: 227–235.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  48. 48

    Kim ES, Herbst RS, Wistuba II, Lee JJ, Blumenschein GR Jr, Tsao A et al. The BATTLE trial: personalizing therapy for lung cancer. Cancer Discov 2011; 1: 44–53.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  49. 49

    Esserman LJ, Berry DA, DeMichele A, Carey L, Davis SE, Buxton M et al. Pathologic complete response predicts recurrence-free survival more effectively by cancer subset: results from the I-SPY 1 TRIAL—CALGB 150007/150012, ACRIN 6657. J Clin Oncol 2012; 30: 3242–3249.

    Article  PubMed  PubMed Central  Google Scholar 

  50. 50

    Printz C . I-SPY 2 may change how clinical trials are conducted: researchers aim to accelerate approvals of cancer drugs. Cancer 2013; 119: 1925–1927.

    Article  PubMed  Google Scholar 

  51. 51

    Positive results for drug combo in I-SPY 2 trial. Cancer Discov 2014; 4: OF2.

  52. 52

    Louly PG, Medeiros-Souza P, Santos-Neto L . N-of-1 double-blind, randomized controlled trial of tramadol to treat chronic cough. Clin Ther 2009; 31: 1007–1013.

    CAS  Article  PubMed  Google Scholar 

  53. 53

    Scudeller L, Del Fante C, Perotti C, Pavesi CF, Coscia D, Scotti V et al. N of 1, two contemporary arm, randomised controlled clinical trial for bilateral epicondylitis: a new study design. BMJ 2011; 343: d7653.

    Article  PubMed  PubMed Central  Google Scholar 

  54. 54

    Duan N, Kravitz RL, Schmid CH . Single-patient (n-of-1) trials: a pragmatic clinical decision methodology for patient-centered comparative effectiveness research. J Clin Epidemiol 2013; 66: S21–S28.

    Article  PubMed  PubMed Central  Google Scholar 

  55. 55

    Von Hoff DD, Stephenson JJ Jr, Rosen P, Loesch DM, Borad MJ, Anthony S et al. Pilot study using molecular profiling of patients’ tumors to find potential targets and select treatments for their refractory cancers. J Clin Oncol 2010; 28: 4877–4883.

    CAS  Article  PubMed  Google Scholar 

  56. 56

    Bjarnadottir O, Romero Q, Bendahl PO, Jirström K, Rydén L, Loman N et al. Targeting HMG-CoA reductase with statins in a window-of-opportunity breast cancer trial. Breast Cancer Res Treat 2013; 138: 499–508.

    CAS  Article  PubMed  Google Scholar 

  57. 57

    Hadad S, Iwamoto T, Jordan L, Purdie C, Bray S, Baker L et al. Evidence for biological effects of metformin in operable breast cancer: a pre-operative, window-of-opportunity, randomized trial. Breast Cancer Res Treat 2011; 128: 783–794.

    CAS  Article  PubMed  Google Scholar 

  58. 58

    André F, Bachelot T, Commo F, Campone M, Arnedos M, Dieras V et al. Comparative genomic hybridisation array and DNA sequencing to direct treatment of metastatic breast cancer: a multicentre, prospective trial (SAFIR01/UNICANCER). Lancet Oncol 2014; 15: 267–274.

    Article  PubMed  Google Scholar 

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Fadoukhair, Z., Zardavas, D., Chad, M. et al. Evaluation of targeted therapies in advanced breast cancer: the need for large-scale molecular screening and transformative clinical trial designs. Oncogene 35, 1743–1749 (2016). https://doi.org/10.1038/onc.2015.249

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