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Integrated genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF , chromatin modification, DNA repair and RNA processing. Expression analysis defined 4 subtypes: (1) squamous; (2) pancreatic progenitor; (3) immunogenic; and (4) aberrantly differentiated endocrine exocrine (ADEX) that correlate with histopathological characteristics. Squamous tumours are enriched for TP53 and KDM6A mutations, upregulation of the TP63∆N transcriptional network, hypermethylation of pancreatic endodermal cell-fate determining genes and have a poor prognosis. Pancreatic progenitor tumours preferentially express genes involved in early pancreatic development ( FOXA2/3 , PDX1 and MNX1 ). ADEX tumours displayed upregulation of genes that regulate networks involved in KRAS activation, exocrine ( NR5A2 and RBPJL ), and endocrine differentiation ( NEUROD1 and NKX2-2 ). Immunogenic tumours contained upregulated immune networks including pathways involved in acquired immune suppression. These data infer differences in the molecular evolution of pancreatic cancer subtypes and identify opportunities for therapeutic development. An integrated genomic analysis of 456 human pancreatic ductal adenocarcinomas identifies four subtypes defined by transcriptional expression profiles and show that these are associated with distinct histopathological characteristics and differential prognosis. Pancreatic cancer genomics Sean Grimmond and colleagues report integrated genomic analysis of 456 pancreatic ductal adenocarcinomas. They identify four subtypes defined by expression profiles, characterize their transcriptional networks, and show that these are associated with distinct histopathological characteristics and differential survival.

We analysed primary breast cancers by genomic DNA copy number arrays, DNA methylation, exome sequencing, messenger RNA arrays, microRNA sequencing and reverse-phase protein arrays. Our ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity. Somatic mutations in only three genes ( TP53 , PIK3CA and GATA3 ) occurred at >10% incidence across all breast cancers; however, there were numerous subtype-associated and novel gene mutations including the enrichment of specific mutations in GATA3 , PIK3CA and MAP3K1 with the luminal A subtype. We identified two novel protein-expression-defined subgroups, possibly produced by stromal/microenvironmental elements, and integrated analyses identified specific signalling pathways dominant in each molecular subtype including a HER2/phosphorylated HER2/EGFR/phosphorylated EGFR signature within the HER2-enriched expression subtype. Comparison of basal-like breast tumours with high-grade serous ovarian tumours showed many molecular commonalities, indicating a related aetiology and similar therapeutic opportunities. The biological finding of the four main breast cancer subtypes caused by different subsets of genetic and epigenetic abnormalities raises the hypothesis that much of the clinically observable plasticity and heterogeneity occurs within, and not across, these major biological subtypes of breast cancer. The Cancer Genome Atlas Network describe their multifaceted analyses of primary breast cancers, shedding light on breast cancer heterogeneity; although only three genes ( TP53 , PIK3CA and GATA3 ) are mutated at a frequency greater than 10% across all breast cancers, numerous subtype-associated and novel mutations were identified. Gene variation in breast cancer This Article from the Cancer Genome Atlas consortium describes a multifaceted analysis of primary breast cancers in 825 people. Exome sequencing, copy number variation, DNA methylation, messenger RNA arrays, microRNA sequencing and proteomic analyses were performed and integrated to shed light on breast-cancer heterogeneity. Just three genes — TP53 , PIK3CA and GATA3 — are mutated at greater than 10% frequency across all breast cancers. Many subtype-associated and novel mutations were identified, as well as two breast-cancer subgroups with specific signalling-pathway signatures. The analyses also suggest that much of the clinically observable plasticity and heterogeneity occurs within, and not across, the major subtypes of breast cancer.

Pancreatic cancer is not caused by a specific series of genetic alterations that occur sequentially but by one, or few, catastrophic events that result in simultaneous oncogenic genetic rearrangements, giving rise to highly aggressive tumours. Pancreatic cancer genome evolution Pancreatic cancer is a highly aggressive tumour type. With a view to examining the evolution of rapid tumour progression in this cancer, this paper presents an analysis of more than a hundred tumour-enriched whole-genome sequences from primary and metastatic pancreas cancers obtained from collaborating hospitals in Canada and the United States of America. Challenging a traditional model of progressive evolution based on ordered mutations in several genes, the authors find support for a role of complex rearrangements and chromothripsis in pancreatic cancer progression, which suggests that the genomic instability that marks this cancer may be explained by a punctuated equilibrium model. Pancreatic cancer, a highly aggressive tumour type with uniformly poor prognosis, exemplifies the classically held view of stepwise cancer development 1 . The current model of tumorigenesis, based on analyses of precursor lesions, termed pancreatic intraepithelial neoplasm (PanINs) lesions, makes two predictions: first, that pancreatic cancer develops through a particular sequence of genetic alterations 2 , 3 , 4 , 5 ( KRAS , followed by CDKN2A , then TP53 and SMAD4 ); and second, that the evolutionary trajectory of pancreatic cancer progression is gradual because each alteration is acquired independently. A shortcoming of this model is that clonally expanded precursor lesions do not always belong to the tumour lineage 2 , 5 , 6 , 7 , 8 , 9 , indicating that the evolutionary trajectory of the tumour lineage and precursor lesions can be divergent. This prevailing model of tumorigenesis has contributed to the clinical notion that pancreatic cancer evolves slowly and presents at a late stage 10 . However, the propensity for this disease to rapidly metastasize and the inability to improve patient outcomes, despite efforts aimed at early detection 11 , suggest that pancreatic cancer progression is not gradual. Here, using newly developed informatics tools, we tracked changes in DNA copy number and their associated rearrangements in tumour-enriched genomes and found that pancreatic cancer tumorigenesis is neither gradual nor follows the accepted mutation order. Two-thirds of tumours harbour complex rearrangement patterns associated with mitotic errors, consistent with punctuated equilibrium as the principal evolutionary trajectory 12 . In a subset of cases, the consequence of such errors is the simultaneous, rather than sequential, knockout of canonical preneoplastic genetic drivers that are likely to set-off invasive cancer growth. These findings challenge the current progression model of pancreatic cancer and provide insights into the mutational processes that give rise to these aggressive tumours.

A powerful way to discover key genes with causal roles in oncogenesis is to identify genomic regions that undergo frequent alteration in human cancers. Here we present high-resolution analyses of somatic copy-number alterations (SCNAs) from 3,131 cancer specimens, belonging largely to 26 histological types. We identify 158 regions of focal SCNA that are altered at significant frequency across several cancer types, of which 122 cannot be explained by the presence of a known cancer target gene located within these regions. Several gene families are enriched among these regions of focal SCNA, including the BCL2 family of apoptosis regulators and the NF-κΒ pathway. We show that cancer cells containing amplifications surrounding the MCL1 and BCL2L1 anti-apoptotic genes depend on the expression of these genes for survival. Finally, we demonstrate that a large majority of SCNAs identified in individual cancer types are present in several cancer types. Cancer genomics refined Two Articles in this issue add major data sets to the growing picture of the cancer genome. Bignell et al . analysed a large number of homozygous gene deletions in a collection of 746 publicly available cancer cell lines. Combined with information about hemizygous deletions of the same genes, the data suggest that many deletions found in cancer reflect the position of a gene at a fragile site in the genome, rather than as a recessive cancer gene whose loss confers a selective growth advantage. Beroukhim et al . present the largest data set to date on somatic copy-number variations across more than 3,000 specimens of human primary cancers. Many alterations are shared between multiple tumour types. Functional experiments demonstrate an oncogenic role for the apoptosis genes MCL1 and BCL2L1 that are associated with amplifications found in many cancers. One way of discovering genes with key roles in cancer development is to identify genomic regions that are frequently altered in human cancers. Here, high-resolution analyses of somatic copy-number alterations (SCNAs) in numerous cancer specimens provide an overview of regions of focal SCNA that are altered at significant frequency across several cancer types. An oncogenic function is also found for the anti-apoptosis genes MCL1 and BCL2L1 , which reside in amplified genome regions in many cancers.

Cancer-linked mutations A large-scale genetic analysis of more than 400 breast, lung, ovarian and prostate cancer samples has identified thousands of cancer-related mutations. Kan et al . analysed DNA from cancer patients and identified 2,576 somatic mutations across 1,507 coding genes. Of these, 77 are thought to be significantly mutated, implying possible pathogenic roles for protein kinases, G protein-coupled receptors and other potential therapeutic targets. These authors performed a large-scale study in which they identified 2,576 somatic mutations across 1,507 coding genes from 441 breast, lung, ovarian and prostate cancer types and subtypes. The study provides an overview of the mutational spectra across major human cancers, implies an expanded role for Gα subunits in multiple cancer types and identifies several potential therapeutic targets. The systematic characterization of somatic mutations in cancer genomes is essential for understanding the disease and for developing targeted therapeutics 1 . Here we report the identification of 2,576 somatic mutations across ∼1,800 megabases of DNA representing 1,507 coding genes from 441 tumours comprising breast, lung, ovarian and prostate cancer types and subtypes. We found that mutation rates and the sets of mutated genes varied substantially across tumour types and subtypes. Statistical analysis identified 77 significantly mutated genes including protein kinases, G-protein-coupled receptors such as GRM8 , BAI3 , AGTRL1 (also called APLNR ) and LPHN3 , and other druggable targets. Integrated analysis of somatic mutations and copy number alterations identified another 35 significantly altered genes including GNAS , indicating an expanded role for gα subunits in multiple cancer types. Furthermore, our experimental analyses demonstrate the functional roles of mutant GNAO1 (a Gα subunit) and mutant MAP2K4 (a member of the JNK signalling pathway) in oncogenesis. Our study provides an overview of the mutational spectra across major human cancers and identifies several potential therapeutic targets.

Mass-spectrometry-based proteomic profiling of human cancers has the potential for pan-cancer analyses to identify molecular subtypes and associated pathway features that might be otherwise missed using transcriptomics. Here, we classify 532 cancers, representing six tissue-based types (breast, colon, ovarian, renal, uterine), into ten proteome-based, pan-cancer subtypes that cut across tumor lineages. The proteome-based subtypes are observable in external cancer proteomic datasets surveyed. Gene signatures of oncogenic or metabolic pathways can further distinguish between the subtypes. Two distinct subtypes both involve the immune system, one associated with the adaptive immune response and T-cell activation, and the other associated with the humoral immune response. Two additional subtypes each involve the tumor stroma, one of these including the collagen VI interacting network. Three additional proteome-based subtypes—respectively involving proteins related to Golgi apparatus, hemoglobin complex, and endoplasmic reticulum—were not reflected in previous transcriptomics analyses. A data portal is available at UALCAN website. Mass-spectrometry-based profiling can be used to stratify tumours into molecular subtypes. Here, by classifying over 500 tumours, the authors show that this approach reveals proteomic subgroups which cut across tumour types.

The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ∼40% of genes, with the landscape dominated by cis - and trans -acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A , MTAP and MAP2K4 . Unsupervised analysis of paired DNA–RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis -acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans -acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the ‘CNA-devoid’ subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome. Integrative analysis of copy number and gene expression in 2,000 primary breast tumours with long-term clinical follow-up revealed putative cis -acting driver genes, novel subgroups and trans -acting aberration hotspots that modulate subgroup-specific gene networks.

Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers for responses to targeted agents. Here, to uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we screened a panel of several hundred cancer cell lines—which represent much of the tissue-type and genetic diversity of human cancers—with 130 drugs under clinical and preclinical investigation. In aggregate, we found that mutated cancer genes were associated with cellular response to most currently available cancer drugs. Classic oncogene addiction paradigms were modified by additional tissue-specific or expression biomarkers, and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. Unexpected relationships were revealed, including the marked sensitivity of Ewing’s sarcoma cells harbouring the EWS (also known as EWSR1 )- FLI1 gene translocation to poly(ADP-ribose) polymerase (PARP) inhibitors. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies. Human cancer cell lines are screened with drugs, undergoing clinical or preclinical investigation, to determine specific genomic alterations associated with response to therapeutic agents. Large-scale cancer cell line screening Cancer cell lines are widely used as preclinical models to gain mechanistic and therapeutic insight. Two manuscripts in this issue describe the large-scale genetic and pharmacological characterization of human cancer cell lines. Each group characterized collections of several-hundred cell lines using different platforms and analytical methods. Their results are complementary, and confirm that many human cell lines capture the genomic diversity of their respective cancers. Initial findings include the identification of a number of potential markers of drug sensitivity and resistance. For example, Garnett et al . report an association between EWS-FLI1 gene translocations, frequently found in Ewing's sarcoma, and sensitivity to PARP inhibitors, a class of drug currently in clinical trials for other cancer types. Barretina et al . report a possible association between SLFN11 expression and sensitivity to topoisomerase inhibitors.

Although a few cancer genes are mutated in a high proportion of tumours of a given type (>20%), most are mutated at intermediate frequencies (2–20%). To explore the feasibility of creating a comprehensive catalogue of cancer genes, we analysed somatic point mutations in exome sequences from 4,742 human cancers and their matched normal-tissue samples across 21 cancer types. We found that large-scale genomic analysis can identify nearly all known cancer genes in these tumour types. Our analysis also identified 33 genes that were not previously known to be significantly mutated in cancer, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Down-sampling analysis indicates that larger sample sizes will reveal many more genes mutated at clinically important frequencies. We estimate that near-saturation may be achieved with 600–5,000 samples per tumour type, depending on background mutation frequency. The results may help to guide the next stage of cancer genomics. Large-scale genomic analysis of somatic point mutations in exomes from tumour–normal pairs across 21 cancer types identifies most known cancer genes in these tumour types as well as 33 genes not known to be significantly mutated, and down-sampling analysis indicates that larger sample sizes will reveal many more genes mutated at clinically important frequencies. New cancer genes identified Most cancer genes are mutated at intermediate frequencies, appearing in less than one in five samples of a particular tumour type, so the accurate identification of cancer genes needs to be based on large-scale sampling in order to take account of this mutation-rate heterogeneity. This study presents a statistical analysis of 21 tumour types from more than 4,700 tumour–normal pairs. The authors identify 33 previously unknown genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Further analyses suggest that near-saturation may be achieved with between 600 and 5,000 samples for a given tumour type, depending on background mutation rate.

Exomes, transcriptomes and copy-number alterations in a sample of more than 70 primary human colonic tumours were analysed in an attempt to characterize the genomic landscape; in addition to finding alterations in genes associated with commonly mutated signalling pathways, recurrent gene fusions involving R-spondin family members were also found to occur in approximately 10% of colonic tumours, revealing a potential new therapeutic target. Defective proteins in colon cancer An analysis of exomes, transcriptomes and copy-number alterations in more than 70 primary human colon tumours and matched normal controls has identified more than 35,000 protein-altering somatic mutations, most of which have been validated. In addition to alterations in genes involved in the Wnt pathway, chromatin remodelling and receptor-tyrosine-kinase signalling, the authors identify recurrent gene fusions involving R-spondin family members that collectively occur in 10% of colon tumors; as such they may provide a potential therapeutic target. There is evidence to suggest that these fusions may have a role in the activation of Wnt signalling and tumorigenesis. Identifying and understanding changes in cancer genomes is essential for the development of targeted therapeutics 1 . Here we analyse systematically more than 70 pairs of primary human colon tumours by applying next-generation sequencing to characterize their exomes, transcriptomes and copy-number alterations. We have identified 36,303 protein-altering somatic changes that include several new recurrent mutations in the Wnt pathway gene TCF7L2 , chromatin-remodelling genes such as TET2 and TET3 and receptor tyrosine kinases including ERBB3 . Our analysis for significantly mutated cancer genes identified 23 candidates, including the cell cycle checkpoint kinase ATM . Copy-number and RNA-seq data analysis identified amplifications and corresponding overexpression of IGF2 in a subset of colon tumours. Furthermore, using RNA-seq data we identified multiple fusion transcripts including recurrent gene fusions involving R-spondin family members RSPO2 and RSPO3 that together occur in 10% of colon tumours. The RSPO fusions were mutually exclusive with APC mutations, indicating that they probably have a role in the activation of Wnt signalling and tumorigenesis. Consistent with this we show that the RSPO fusion proteins were capable of potentiating Wnt signalling. The R-spondin gene fusions and several other gene mutations identified in this study provide new potential opportunities for therapeutic intervention in colon cancer.