The TCGA collaboration is committed to the rapid distribution of data to the research community. The findings can be assessed for their usefulness in prevention, early diagnosis, prognosis and therapeutic targeting.

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The cancer genomics horizon promises to bring even more expansive data sets and powerful technologies. In the coming year, thousands of whole-genome sequences will be available, setting the stage for important new analyses beyond the current Pan-Cancer work, which focused primarily on variants detectable in the coding exome. The sequence of entire genomes will enable more thorough investigations into mobile DNA elements associated with tumorigenesis, such as viruses. It will enable the detection of potential mutations in promoter and enhancer sequences that currently go undetected and will allow the construction of a more detailed map of the structural changes that chromosomes undergo during tumor evolution, providing a more detailed view of subclonality.

As isolation technologies improve and smaller quantities of material can be sequenced, new avenues will be opened. TCGA has focused almost exclusively on primary tumors. However, it is most often cancer metastases that disrupt the body and present a lethal hazard. Microfluidic and nanotechnologies will allow small quantities of tissue to be assayed so that the same analytic tools used on primary tumors can be brought to bear on metastatic samples. We can then find out what genomic determinants allow subclones in the primary tumors to branch off, invade tissue, resist treatment and set up in new niches.

The major achievement of consortia (TCGA and the International Cancer Genome Consortium (ICGC)) characterizing cancer genomes is that they have created a framework in which the key genes and pathways that contribute to cancer can be identified in a collaborative fashion. This framework will allow these groups to quickly leverage existing methods to attack the new questions on the horizon and comes with a commitment to the rapid distribution of data to the research community. The usefulness of the findings can thus be assessed in terms of prevention, early diagnosis, prognosis and therapeutic targeting. This multifaceted profiling at the DNA, RNA, protein and epigenetic levels is at once scientifically powerful and intensely practical in the long term for individuals with cancer.

The Cancer Genome Atlas Pan-Cancer Analysis project

The Cancer Genome Atlas Research Network et al.Nature Genetics 10.1038/ng.2764

The Pan-Cancer project represents one of the first of what will surely be many efforts to coordinate analysis across the molecular landscape of cancer, especially as additional tumor types are investigated in large numbers. Further increasing the number of samples per tumor type and the variety of tumor types will improve our ability to detect rare driver events in heterogeneous tumor samples. But the true power will come from a detailed analysis across tumor types—with links to high-quality clinical outcomes and eventual experimental validation and clinical trials to test the hypotheses that emerge.

Clone-level and other types of studies may identify even more connections among tumor types. Longitudinal genomic studies on primary resected tumors paired with their local recurrences and/or metastases will be undertaken by large consortium efforts, which have heretofore been restricted to primary disease and have lacked information about response to treatment. The characteristics of primary tumors may change markedly when they metastasize to distant sites, particularly bone and brain. Analysis of metastasis across tumor types will therefore be highly informative.

The power of cross-tumor analysis will increase as technologies for monitoring individual tumor cells at high resolution come into play. Now that the price of genome sequencing has fallen, the next Pan-Cancer enterprise will be able to analyze large numbers of whole-genome sequences across tumor types. Whole-genome analysis will complement the current studies by shedding light on mutational processes in the noncoding parts of the genome, which have not been as well explored so far. This expanded analysis will bring focus to disruptions in promoter and enhancer sites and aberrations in noncoding RNAs, as well as the genomic integration processes at work in tumor evolution that result from mobile endogenous and exogenous DNA elements such as retrotransposons and viruses. Whole-genome sequencing will create a backdrop against which genome-wide association studies can relate inherited predispositions to particular forms of cancer.

(For consortium analysis of genetic susceptibility to cancer, see http://www.nature.com/icogs/).

The Cancer Genome Atlas Pan-Cancer Analysis project

The Cancer Genome Atlas Research Network et al.Nature Genetics 10.1038/ng.2764

From many tumors to the individual

The hope is that investigations across tumor type such as the Pan-Cancer project will ultimately inform clinical decision-making. We hope such studies will enable the discovery of novel therapeutic agents that can be tested clinically—perhaps in novel adaptive, biomarker-based clinical trials that cross boundaries between tumor types. Toward this end, TCGA Pan-Cancer data sets have been made available publicly in one location. Although coordination remains a challenge, the data sets comprise an unequalled resource for the integrative analysis of cancer in its many forms.

A key challenge is the development of clinical trial strategies for connecting subsets of tumors from different tissues in terms of molecular signatures. Recent analyses of pharmacological profiling experiments across a diverse panel of cancer cell lines has suggested that common genetic alterations can sometimes predict response to therapy across multiple cell lineages39–42.

Until recently, most research on the molecular, pathological and clinical natures of cancers has been 'siloed' by tumor type26. One has only to glance at the directory of oncology departments in any major cancer center to realize that medical and surgical cancer care are, for the most part, also divided by disease as defined by organ of origin. This framework has made sense for generations, but the results of molecular analysis are now calling this view into question; cancers of disparate organs have many shared features, whereas, conversely, cancers from the same organ are often quite distinct.

Pan-cancer analyses will establish catalogs of genes that may provide powerful new targets for personalized treatment. In the near future, versions of these lists including druggable targets should be derived. New cancer antigens could be collected by intersecting such lists with known and predicted surface proteins. Further bioinformatics will then be required to determine which peptides are specific to cancer cell populations by eliminating those detected in normal tissues from online atlases such as the Human Protein Atlas.

The Cancer Genome Atlas Pan-Cancer Analysis project

The Cancer Genome Atlas Research Network et al.Nature Genetics 10.1038/ng.2764

Biomarker-based design of clinical trials can increase statistical power, greatly decreasing the size, expense and duration of clinical trials. The number and size of omic data sets on cancer available to the research community for mining and exploring continue to expand rapidly, and computational tools to derive insights into the fundamental causes of cancer are becoming more powerful. It is important to note that the full potential of the enterprise will be realized only over time and with broader efforts.

Mutational landscape and significance across 12 major cancer types

Cyriac Kandoth, Michael McLellan et al.Nature 10.1038/nature12634 (2013)

Although a common set of driver mutations exists in each cancer, the combination of driver mutations within a cancer type and their distribution within the founding clone and subclones is variable for individual patients. This suggests that knowing the clonal architecture of each patient's tumor will be critical to optimize treatment.

We have successfully applied the MuSiC suite and Dendrix to perform systematic analysis of the TCGA Pan-Cancer mutation dataset and revealed some key insights in cancer genomes as shown in Extended Data Figure 9.

Emerging landscape of oncogenic signatures across human cancers

Giovanni Ciriello et al.Nature Genetics 10.1038/ng.2762

The observed cross-cancer distribution of targetable alterations presents an opportunity to design tumor treatment strategies tailored to subsets of tumors characterized by particular sets of functional events.

To explore the relationship between functional alterations and therapeutic interventions in more detail, we first assessed the distribution of potentially actionable alterations in different tissue-specific tumor types, focusing on a subset of the ∼500 SFEs with well-characterized roles in pathways (Fig. 4).

The systematic identification of genomic subclasses presented here is intended as a step toward this goal across a larger number of tumor types than was previously possible. With more than 3,000 tumors analyzed, genomic subclasses were found to be characterized not only by single oncogenic events but also by specific combinations of events (Fig. 5 and Supplementary Fig. 11). Such concurrent alterations may be targetable by combination therapies (Fig. 5). For example, subsets of lung and head and neck squamous cell carcinomas may benefit from concurrent blockade of the cell cycle and PI3K-AKT signaling (Fig. 5, subclasses C3 and C4), whereas inhibition of PARP and Aurora kinase A may be beneficial for subsets of BRCA1- or BRCA2-mutant ovarian and basal breast tumors (Fig. 5, subclasses C13 and C14).

figure 1

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figure 2

Genes [...] encoding components of four major oncogenic pathways (RTK-RAS-RAF, PI3K-AKT-mTOR, cell cycle and p53–DNA repair; shown schematically in the pathway column) are affected by selected functional events [...] across tissue-specific tumor types. [...] A sizable fraction of these alterations are directly or indirectly therapeutically actionable given the current availability of anticancer drugs (the column with drug family information shows the targets of specific inhibitors).

figure 3

In these examples of oncogenic signature subclasses, functional events distinctive for a tumor subclass nominate potential combination therapy when these alterations are either directly or indirectly targetable.