Sir Peter MacCallum Department of Oncology - Research Publications

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    Genomic footprints of activated telomere maintenance mechanisms in cancer
    Sieverling, L ; Hong, C ; Koser, SD ; Ginsbach, P ; Kleinheinz, K ; Hutter, B ; Braun, DM ; Cortes-Ciriano, I ; Xi, R ; Kabbe, R ; Park, PJ ; Eils, R ; Schlesner, M ; Brors, B ; Rippe, K ; Jones, DTW ; Feuerbach, L (NATURE PORTFOLIO, 2020-02-05)
    Cancers require telomere maintenance mechanisms for unlimited replicative potential. They achieve this through TERT activation or alternative telomere lengthening associated with ATRX or DAXX loss. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we dissect whole-genome sequencing data of over 2500 matched tumor-control samples from 36 different tumor types aggregated within the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium to characterize the genomic footprints of these mechanisms. While the telomere content of tumors with ATRX or DAXX mutations (ATRX/DAXXtrunc) is increased, tumors with TERT modifications show a moderate decrease of telomere content. One quarter of all tumor samples contain somatic integrations of telomeric sequences into non-telomeric DNA. This fraction is increased to 80% prevalence in ATRX/DAXXtrunc tumors, which carry an aberrant telomere variant repeat (TVR) distribution as another genomic marker. The latter feature includes enrichment or depletion of the previously undescribed singleton TVRs TTCGGG and TTTGGG, respectively. Our systematic analysis provides new insight into the recurrent genomic alterations associated with telomere maintenance mechanisms in cancer.
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    High-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations
    Zhang, Y ; Chen, F ; Fonseca, NA ; He, Y ; Fujita, M ; Nakagawa, H ; Zhang, Z ; Brazma, A ; Creighton, CJ (NATURE PUBLISHING GROUP, 2020-02-05)
    The impact of somatic structural variants (SVs) on gene expression in cancer is largely unknown. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole-genome sequencing data and RNA sequencing from a common set of 1220 cancer cases, we report hundreds of genes for which the presence within 100 kb of an SV breakpoint associates with altered expression. For the majority of these genes, expression increases rather than decreases with corresponding breakpoint events. Up-regulated cancer-associated genes impacted by this phenomenon include TERT, MDM2, CDK4, ERBB2, CD274, PDCD1LG2, and IGF2. TERT-associated breakpoints involve ~3% of cases, most frequently in liver biliary, melanoma, sarcoma, stomach, and kidney cancers. SVs associated with up-regulation of PD1 and PDL1 genes involve ~1% of non-amplified cases. For many genes, SVs are significantly associated with increased numbers or greater proximity of enhancer regulatory elements near the gene. DNA methylation near the promoter is often increased with nearby SV breakpoint, which may involve inactivation of repressor elements.
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    Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing
    Cortes-Ciriano, I ; Lee, JJ-K ; Xi, R ; Jain, D ; Jung, YL ; Yang, L ; Gordenin, D ; Klimczak, LJ ; Zhang, C-Z ; Pellman, DS ; Park, PJ ; Akdemir, KC ; Alvarez, EG ; Baez-Ortega, A ; Beroukhim, R ; Boutros, PC ; Bowtell, DDL ; Brors, B ; Burns, KH ; Campbell, PJ ; Chan, K ; Chen, K ; Dueso-Barroso, A ; Dunford, AJ ; Edwards, PA ; Estivill, X ; Etemadmoghadam, D ; Feuerbach, L ; Fink, JL ; Frenkel-Morgenstern, M ; Garsed, DW ; Gerstein, M ; Gordenin, DA ; Haan, D ; Haber, JE ; Hess, JM ; Hutter, B ; Imielinski, M ; Jones, DTW ; Ju, YS ; Kazanov, MD ; Koh, Y ; Korbel, JO ; Kumar, K ; Lee, EA ; Li, Y ; Lynch, AG ; Macintyre, G ; Markowetz, F ; Martincorena, I ; Martinez-Fundichely, A ; Miyano, S ; Nakagawa, H ; Navarro, FCP ; Ossowski, S ; Pearson, J ; Puiggros, M ; Rippe, K ; Roberts, ND ; Roberts, SA ; Rodriguez-Martin, B ; Schumacher, SE ; Scully, R ; Shackleton, M ; Sidiropoulos, N ; Sieverling, L ; Stewart, C ; Torrents, D ; Tubio, JMC ; Villasante, I ; Waddell, N ; Wala, JA ; Weischenfeldt, J ; Yao, X ; Yoon, S-S ; Zamora, J (NATURE PORTFOLIO, 2020-03)
    Chromothripsis is a mutational phenomenon characterized by massive, clustered genomic rearrangements that occurs in cancer and other diseases. Recent studies in selected cancer types have suggested that chromothripsis may be more common than initially inferred from low-resolution copy-number data. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we analyze patterns of chromothripsis across 2,658 tumors from 38 cancer types using whole-genome sequencing data. We find that chromothripsis events are pervasive across cancers, with a frequency of more than 50% in several cancer types. Whereas canonical chromothripsis profiles display oscillations between two copy-number states, a considerable fraction of events involve multiple chromosomes and additional structural alterations. In addition to non-homologous end joining, we detect signatures of replication-associated processes and templated insertions. Chromothripsis contributes to oncogene amplification and to inactivation of genes such as mismatch-repair-related genes. These findings show that chromothripsis is a major process that drives genome evolution in human cancer.
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    Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer
    Akdemir, KC ; Le, VT ; Chandran, S ; Li, Y ; Verhaak, RG ; Beroukhim, R ; Campbell, PJ ; Chin, L ; Dixon, JR ; Futreal, PA ; Alvarez, EG ; Baez-Ortega, A ; Beroukhim, R ; Boutros, PC ; Bowtell, DDL ; Brors, B ; Burns, KH ; Chan, K ; Chen, K ; Cortes-Ciriano, I ; Dueso-Barroso, A ; Dunford, AJ ; Edwards, PA ; Estivill, X ; Etemadmoghadam, D ; Feuerbach, L ; Fink, JL ; Frenkel-Morgenstern, M ; Garsed, DW ; Gerstein, M ; Gordenin, DA ; Haan, D ; Haber, JE ; Hess, JM ; Hutter, B ; Imielinski, M ; Jones, DTW ; Ju, YS ; Kazanov, MD ; Klimczak, LJ ; Koh, Y ; Korbel, JO ; Kumar, K ; Lee, EA ; Lee, JJ-K ; Lynch, AG ; Macintyre, G ; Markowetz, F ; Martincorena, I ; Martinez-Fundichely, A ; Meyerson, M ; Miyano, S ; Nakagawa, H ; Navarro, FCP ; Ossowski, S ; Park, PJ ; Pearson, JV ; Puiggros, M ; Rippe, K ; Roberts, ND ; Roberts, SA ; Rodriguez-Martin, B ; Schumacher, SE ; Scully, R ; Shackleton, M ; Sidiropoulos, N ; Sieverling, L ; Stewart, C ; Torrents, D ; Tubio, JMC ; Villasante, I ; Waddell, N ; Wala, JA ; Weischenfeldt, J ; Yang, L ; Yao, X ; Yoon, S-S ; Zamora, J ; Zhang, C-Z (NATURE PORTFOLIO, 2020-03)
    Chromatin is folded into successive layers to organize linear DNA. Genes within the same topologically associating domains (TADs) demonstrate similar expression and histone-modification profiles, and boundaries separating different domains have important roles in reinforcing the stability of these features. Indeed, domain disruptions in human cancers can lead to misregulation of gene expression. However, the frequency of domain disruptions in human cancers remains unclear. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), which aggregated whole-genome sequencing data from 2,658 cancers across 38 tumor types, we analyzed 288,457 somatic structural variations (SVs) to understand the distributions and effects of SVs across TADs. Notably, SVs can lead to the fusion of discrete TADs, and complex rearrangements markedly change chromatin folding maps in the cancer genomes. Notably, only 14% of the boundary deletions resulted in a change in expression in nearby genes of more than twofold.
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    Cancer LncRNA Census reveals evidence for deep functional conservation of long noncoding RNAs in tumorigenesis
    Carlevaro-Fita, J ; Lanzos, A ; Feuerbach, L ; Hong, C ; Mas-Ponte, D ; Pedersen, JS ; Johnson, R ; Abascal, F ; Amin, SB ; Bader, GD ; Barenboim, J ; Beroukhim, R ; Bertl, J ; Boroevich, KA ; Brunak, S ; Campbell, PJ ; Carlevaro-Fita, J ; Chakravarty, D ; Chan, CWY ; Chen, K ; Choi, JK ; Deu-Pons, J ; Dhingra, P ; Diamanti, K ; Feuerbach, L ; Fink, JL ; Fonseca, NA ; Frigola, J ; Gambacorti-Passerini, C ; Garsed, DW ; Gerstein, M ; Getz, G ; Gonzalez-Perez, A ; Guo, Q ; Gut, IG ; Haan, D ; Hamilton, MP ; Haradhvala, NJ ; Harmanci, AO ; Helmy, M ; Herrmann, C ; Hess, JM ; Hobolth, A ; Hodzic, E ; Hong, C ; Hornshoj, H ; Isaev, K ; Izarzugaza, JMG ; Johnson, TA ; Juul, M ; Juul, RI ; Kahles, A ; Kahraman, A ; Kellis, M ; Khurana, E ; Kim, J ; Kim, JK ; Kim, Y ; Komorowski, J ; Korbel, JO ; Kumar, S ; Lanzos, A ; Larsson, E ; Lawrence, MS ; Lee, D ; Lehmann, K-V ; Li, S ; Li, X ; Lin, Z ; Liu, EM ; Lochovsky, L ; Lou, S ; Madsen, T ; Marchal, K ; Martincorena, I ; Martinez-Fundichely, A ; Maruvka, YE ; McGillivray, PD ; Meyerson, W ; Muinos, F ; Mularoni, L ; Nakagawa, H ; Nielsen, MM ; Paczkowska, M ; Park, K ; Park, K ; Pedersen, JS ; Pich, O ; Pons, T ; Pulido-Tamayo, S ; Raphael, BJ ; Reimand, J ; Reyes-Salazar, I ; Reyna, MA ; Rheinbay, E ; Rubin, MA ; Rubio-Perez, C ; Sabarinathan, R ; Sahinalp, SC ; Saksena, G ; Salichos, L ; Sander, C ; Schumacher, SE ; Shackleton, M ; Shapira, O ; Shen, C ; Shrestha, R ; Shuai, S ; Sidiropoulos, N ; Sieverling, L ; Sinnott-Armstrong, N ; Stein, LD ; Stuart, JM ; Tamborero, D ; Tiao, G ; Tsunoda, T ; Umer, HM ; Uuskula-Reimand, L ; Valencia, A ; Vazquez, M ; Verbeke, LPC ; Wadelius, C ; Wadi, L ; Wang, J ; Warrell, J ; Waszak, SM ; Weischenfeldt, J ; Wheeler, DA ; Wu, G ; Yu, J ; Zhang, J ; Zhang, X ; Zhang, Y ; Zhao, Z ; Zou, L ; von Mering, C (NATURE PUBLISHING GROUP, 2020-02-05)
    Long non-coding RNAs (lncRNAs) are a growing focus of cancer genomics studies, creating the need for a resource of lncRNAs with validated cancer roles. Furthermore, it remains debated whether mutated lncRNAs can drive tumorigenesis, and whether such functions could be conserved during evolution. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we introduce the Cancer LncRNA Census (CLC), a compilation of 122 GENCODE lncRNAs with causal roles in cancer phenotypes. In contrast to existing databases, CLC requires strong functional or genetic evidence. CLC genes are enriched amongst driver genes predicted from somatic mutations, and display characteristic genomic features. Strikingly, CLC genes are enriched for driver mutations from unbiased, genome-wide transposon-mutagenesis screens in mice. We identified 10 tumour-causing mutations in orthologues of 8 lncRNAs, including LINC-PINT and NEAT1, but not MALAT1. Thus CLC represents a dataset of high-confidence cancer lncRNAs. Mutagenesis maps are a novel means for identifying deeply-conserved roles of lncRNAs in tumorigenesis.
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    Integrative pathway enrichment analysis of multivariate omics data
    Paczkowska, M ; Barenboim, J ; Sintupisut, N ; Fox, NS ; Zhu, H ; Abd-Rabbo, D ; Mee, MW ; Boutros, PC ; Reimand, J (NATURE PUBLISHING GROUP, 2020-02-05)
    Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations.
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    Patterns of somatic structural variation in human cancer genomes
    Li, Y ; Roberts, ND ; Wala, JA ; Shapira, O ; Schumacher, SE ; Kumar, K ; Khurana, E ; Waszak, S ; Korbel, JO ; Haber, JE ; Imielinski, M ; Weischenfeldt, J ; Beroukhim, R ; Campbell, PJ ; Akdemir, KC ; Alvarez, EG ; Baez-Ortega, A ; Boutros, PC ; Bowtell, DDL ; Brors, B ; Burns, KH ; Chan, K ; Chen, K ; Cortes-Ciriano, I ; Dueso-Barroso, A ; Dunford, AJ ; Edwards, PA ; Estivill, X ; Etemadmoghadam, D ; Feuerbach, L ; Fink, JL ; Frenkel-Morgenstern, M ; Garsed, DW ; Gerstein, M ; Gordenin, DA ; Haan, D ; Hess, JM ; Hutter, B ; Jones, DTW ; Ju, YS ; Kazanov, MD ; Klimczak, LJ ; Koh, Y ; Lee, EA ; Lee, JJ-K ; Lynch, AG ; Macintyre, G ; Markowetz, F ; Martincorena, I ; Martinez-Fundichely, A ; Meyerson, M ; Miyano, S ; Nakagawa, H ; Navarro, FCP ; Ossowski, S ; Park, PJ ; Pearson, J ; Puiggros, M ; Rippe, K ; Roberts, SA ; Rodriguez-Martin, B ; Scully, R ; Shackleton, M ; Sidiropoulos, N ; Sieverling, L ; Stewart, C ; Torrents, D ; Tubio, JMC ; Villasante, I ; Waddell, N ; Yang, L ; Yao, X ; Yoon, S-S ; Zamora, J ; Zhang, C-Z (NATURE PORTFOLIO, 2020-02-06)
    A key mutational process in cancer is structural variation, in which rearrangements delete, amplify or reorder genomic segments that range in size from kilobases to whole chromosomes1-7. Here we develop methods to group, classify and describe somatic structural variants, using data from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), which aggregated whole-genome sequencing data from 2,658 cancers across 38 tumour types8. Sixteen signatures of structural variation emerged. Deletions have a multimodal size distribution, assort unevenly across tumour types and patients, are enriched in late-replicating regions and correlate with inversions. Tandem duplications also have a multimodal size distribution, but are enriched in early-replicating regions-as are unbalanced translocations. Replication-based mechanisms of rearrangement generate varied chromosomal structures with low-level copy-number gains and frequent inverted rearrangements. One prominent structure consists of 2-7 templates copied from distinct regions of the genome strung together within one locus. Such cycles of templated insertions correlate with tandem duplications, and-in liver cancer-frequently activate the telomerase gene TERT. A wide variety of rearrangement processes are active in cancer, which generate complex configurations of the genome upon which selection can act.
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    Reconstructing evolutionary trajectories of mutation signature activities in cancer using TrackSig
    Rubanova, Y ; Shi, R ; Harrigan, CF ; Li, R ; Wintersinger, J ; Sahin, N ; Deshwar, A ; PCAWG Evolution and Heterogeneity Working Group, ; Morris, Q ; PCAWG Consortium, (Nature Research (part of Springer Nature), 2020-02-05)
    The type and genomic context of cancer mutations depend on their causes. These causes have been characterized using signatures that represent mutation types that co-occur in the same tumours. However, it remains unclear how mutation processes change during cancer evolution due to the lack of reliable methods to reconstruct evolutionary trajectories of mutational signature activity. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole-genome sequencing data from 2658 cancers across 38 tumour types, we present TrackSig, a new method that reconstructs these trajectories using optimal, joint segmentation and deconvolution of mutation type and allele frequencies from a single tumour sample. In simulations, we find TrackSig has a 3-5% activity reconstruction error, and 12% false detection rate. It outperforms an aggressive baseline in situations with branching evolution, CNA gain, and neutral mutations. Applied to data from 2658 tumours and 38 cancer types, TrackSig permits pan-cancer insight into evolutionary changes in mutational processes.
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    Combined burden and functional impact tests for cancer driver discovery using DriverPower
    Shuai, S ; Gallinger, S ; Stein, L (NATURE PORTFOLIO, 2020-02-05)
    The discovery of driver mutations is one of the key motivations for cancer genome sequencing. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumour types, we describe DriverPower, a software package that uses mutational burden and functional impact evidence to identify driver mutations in coding and non-coding sites within cancer whole genomes. Using a total of 1373 genomic features derived from public sources, DriverPower's background mutation model explains up to 93% of the regional variance in the mutation rate across multiple tumour types. By incorporating functional impact scores, we are able to further increase the accuracy of driver discovery. Testing across a collection of 2583 cancer genomes from the PCAWG project, DriverPower identifies 217 coding and 95 non-coding driver candidates. Comparing to six published methods used by the PCAWG Drivers and Functional Interpretation Working Group, DriverPower has the highest F1 score for both coding and non-coding driver discovery. This demonstrates that DriverPower is an effective framework for computational driver discovery.
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    Analyses of non-coding somatic drivers in 2,658 cancer whole genomes
    Rheinbay, E ; Nielsen, MM ; Abascal, F ; Wala, JA ; Shapira, O ; Tiao, G ; Hornshoj, H ; Hess, JM ; Juul, RI ; Lin, Z ; Feuerbach, L ; Sabarinathan, R ; Madsen, T ; Kim, J ; Mularoni, L ; Shuai, S ; Lanzos, A ; Herrmann, C ; Maruvka, YE ; Shen, C ; Amin, SB ; Bandopadhayay, P ; Bertl, J ; Boroevich, KA ; Busanovich, J ; Carlevaro-Fita, J ; Chakravarty, D ; Chan, CWY ; Craft, D ; Dhingra, P ; Diamanti, K ; Fonseca, NA ; Gonzalez-Perez, A ; Guo, Q ; Hamilton, MP ; Haradhvala, NJ ; Hong, C ; Isaev, K ; Johnson, TA ; Juul, M ; Kahles, A ; Kahraman, A ; Kim, Y ; Komorowski, J ; Kumar, K ; Kumar, S ; Lee, D ; Lehmann, K-V ; Li, Y ; Liu, EM ; Lochovsky, L ; Park, K ; Pich, O ; Roberts, ND ; Saksena, G ; Schumacher, SE ; Sidiropoulos, N ; Sieverling, L ; Sinnott-Armstrong, N ; Stewart, C ; Tamborero, D ; Tubio, JMC ; Umer, HM ; Uuskula-Reimand, L ; Wadelius, C ; Wadi, L ; Yao, X ; Zhang, C-Z ; Zhang, J ; Haber, JE ; Hobolth, A ; Imielinski, M ; Kellis, M ; Lawrence, MS ; von Mering, C ; Nakagawa, H ; Raphael, BJ ; Rubin, MA ; Sander, C ; Stein, LD ; Stuart, JM ; Tsunoda, T ; Wheeler, DA ; Johnson, R ; Reimand, J ; Gerstein, M ; Khurana, E ; Campbell, PJ ; Lopez-Bigas, N ; Weischenfeldt, J ; Beroukhim, R ; Martincorena, I ; Pedersen, JS ; Getz, G ; Bader, GD ; Barenboim, J ; Brunak, S ; Chen, K ; Choi, JK ; Deu-Pons, J ; Fink, JL ; Frigola, J ; Gambacorti-Passerini, C ; Garsed, DW ; Gut, IG ; Haan, D ; Harmanci, AO ; Helmy, M ; Hodzic, E ; Izarzugaza, JMG ; Kim, JK ; Korbel, JO ; Larsson, E ; Li, S ; Li, X ; Lou, S ; Marchal, K ; Martinez-Fundichely, A ; McGillivray, PD ; Meyerson, W ; Muinos, F ; Paczkowska, M ; Park, K ; Pons, T ; Pulido-Tamayo, S ; Reyes-Salazar, I ; Reyna, MA ; Rubio-Perez, C ; Sahinalp, SC ; Salichos, L ; Shackleton, M ; Shrestha, R ; Valencia, A ; Vazquez, M ; Verbeke, LPC ; Wang, J ; Warrell, J ; Waszak, SM ; Wu, G ; Yu, J ; Zhang, X ; Zhang, Y ; Zhao, Z ; Zou, L ; Akdemir, KC ; Alvarez, EG ; Baez-Ortega, A ; Boutros, PC ; Bowtell, DDL ; Brors, B ; Burns, KH ; Chan, K ; CortesCiriano, I ; Dueso-Barroso, A ; Dunford, AJ ; Edwards, PA ; Estivill, X ; Etemadmoghadam, D ; Frenkel-Morgenstern, M ; Gordenin, DA ; Hutter, B ; Jones, DTW ; Ju, YS ; Kazanov, MD ; Klimczak, LJ ; Koh, Y ; Lee, EA ; Lee, JJ-K ; Lynch, AG ; Macintyre, G ; Markowetz, F ; Meyerson, M ; Miyano, S ; Navarro, FCP ; Ossowski, S ; Park, PJ ; Pearson, J ; Puiggros, M ; Rippe, K ; Roberts, SA ; RodriguezMartin, B ; Scully, R ; Torrents, D ; Villasante, I ; Waddell, N ; Yang, L ; Yoon, S-S ; Zamora, J (NATURE RESEARCH, 2020-02-06)
    The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.