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  • 1
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 13, No. 1 ( 2022-12-08)
    Type of Medium: Online Resource
    ISSN: 2041-1723
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
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  • 2
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 11, No. 1 ( 2020-02-05)
    Abstract: In cancer, the primary tumour’s organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium , we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types produced by the PCAWG Consortium. Our classifier achieves an accuracy of 91% on held-out tumor samples and 88% and 83% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced accuracy. Our results have clinical applicability, underscore how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of circulating tumour DNA.
    Type of Medium: Online Resource
    ISSN: 2041-1723
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
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  • 3
    In: Nature, Springer Science and Business Media LLC, Vol. 578, No. 7793 ( 2020-02-06), p. 94-101
    Abstract: Somatic mutations in cancer genomes are caused by multiple mutational processes, each of which generates a characteristic mutational signature 1 . Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium 2 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we characterized mutational signatures using 84,729,690 somatic mutations from 4,645 whole-genome and 19,184 exome sequences that encompass most types of cancer. We identified 49 single-base-substitution, 11 doublet-base-substitution, 4 clustered-base-substitution and 17 small insertion-and-deletion signatures. The substantial size of our dataset, compared with previous analyses 3–15 , enabled the discovery of new signatures, the separation of overlapping signatures and the decomposition of signatures into components that may represent associated—but distinct—DNA damage, repair and/or replication mechanisms. By estimating the contribution of each signature to the mutational catalogues of individual cancer genomes, we revealed associations of signatures to exogenous or endogenous exposures, as well as to defective DNA-maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes that contribute to the development of human cancer.
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
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    SSG: 11
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  • 4
    In: Nature, Springer Science and Business Media LLC
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
    RVK:
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 120714-3
    detail.hit.zdb_id: 1413423-8
    SSG: 11
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  • 5
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 11, No. 1 ( 2020-08-28)
    Abstract: Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research.
    Type of Medium: Online Resource
    ISSN: 2041-1723
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
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  • 6
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 13_Supplement ( 2017-07-01), p. LB-231-LB-231
    Abstract: Cancer genome studies have significantly contributed to the discovery of somatic mutations and processes that drive cancer. However, how these mutations accumulate in normal cells and contribute to early cancer development remains poorly understood. Recent studies have addressed this question by studying normal blood and a small number of skin samples, discovering both driver mutations as well as mutational processes observed in cancer. Here we extend these studies by analyzing RNA from ~7,000 samples across 30 normal tissues from ~600 individuals compared to their germline DNA, collected as part of the GTEx project. To accomplish this goal we first developed a new pipeline termed RNA-MuTect for calling somatic mutations directly from RNA-seq samples and their matched-normal DNA. RNA-MuTect includes multiple filtering steps designed specifically for analyzing RNA-seq. We first validated RNA-MuTect by analyzing TCGA samples where both DNA and RNA data are available. Comparing the set of mutations detected by RNA-MuTect to those identified in the DNA, we show that whenever there is sufficient coverage to detect the mutations in RNA, we have a high sensitivity. Most importantly, RNA-MuTect has a very low false-positive rate with specificity & gt;90%. We further demonstrate that we can discover most of the known driver genes in this cohort using the mutations detected based on the RNA data. Moreover, using the RNA data, we can detect the same mutational processes as identified in the DNA, including UV, aging, smoking and others. To study clonal expansion in normal tissues and investigate whether known cancer-related genes and processes can be identified, we applied RNA-MuTect to the GTEx dataset. As expected, multiple variants were detected across tissues, with skin, lung and esophagus having the highest number of somatic mutations. Overall, different cancer-related events were detected. Specifically: (1) we found 15 hotspot mutations in 6 different genes including TP53, KRAS and PIK3CA; (2) Mutated genes in 8 different tissues were found to be enriched with Cancer Gene Census genes; (3) Known cancer genes were found to be under positive selection in different tissues; (4) Known cancer-related mutational signatures were captured in normal tissues; (5) Cases of allelic imbalance were detected in various tissues. This study is the first to analyze a large number of samples across many tissues to explore the fundamental question of cancer initiation. Many cancer-related processes and events are discovered across different tissues, laying the foundation for studying the earliest stages of cancer development. Note: This abstract was not presented at the meeting. Citation Format: Keren Yizhak, Jaegil Kim, Francois Aguet, Julian Hess, Hailei Zhang, Eila Arich-Landkof, Noam Shoresh, Ayelet Segre, Chip Stewart, Dainel Rosebrock, Dimitri Livitz, Nicholas Haradhvala, Paz Polak, Tim Sullivan, Xiao Li, Kristin Ardlie, Gad Getz. Identifying cancer-related processes in normal tissues via RNA-seq [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-231. doi:10.1158/1538-7445.AM2017-LB-231
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
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  • 7
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 2727-2727
    Abstract: Despite increasing knowledge of tumorigenesis, the identity of the cancer cell-of-origin, i.e. the normal cell type that acquired the cancer-initiating event, remains largely unknown. Our approach of identifying the cell-of-origin is based on two observations: (1) the chromatin structure is cell-specific; and (2) the density of somatic mutations along the genome is associated with the regional profile of chromatin modifications. We have previously developed a method that quantifies the ability to predict the mutational distribution along the cancer genome from the profile of epigenetic modifications in different normal cell types. Here we present the largest application of our method using 2,550 whole genomes representing 32 distinct cancer types. To identify the cell-of-origin, we determined the correlation between the observed density of mutations along the genome and the predicted values based on chromatin modifications from 104 different normal tissue types. The normal cell type that showed the strongest correlation with a specific cancer mutational landscape was the candidate cell-of-origin. We found that in almost all cancer types the cell-of-origin can be characterized solely from DNA sequences. Interestingly, we found that the fallopian tube was the best match for high-grade serous ovarian cancer, providing independent evidence that this is the cancer’s site of origin. For breast cancer we found that the four distinct subtypes best-matched cells from the luminal cell lineage: basal-like breast cancer likely originates from luminal progenitors, whereas all other subtypes from luminal mature cells. This association holds true even when accounting for different alterations in the homologous recombination repair pathway, suggesting that subtypes are more determined by the cell-of-origin than the specific DNA repair defect. In addition, we found that we could identify the cell-of-origin using metastatic samples – a finding that may help in difficult clinical diagnoses. Moreover, we demonstrate that cancer drivers, both germline risk alleles and somatically mutated drivers, reside in active chromatin regions in the respective cell-of-origin. Taken together, our findings indicate that many of the somatic mutations accumulated while the cells maintained a chromatin structure similar to the cell-of-origin (likely occurring prior to transformation). Therefore, this historical record, captured in the DNA, can be used to identify, the often elusive, cancer cell-of-origin. Our approach can ultimately help better understand the potential of particular normal cell types to transform and initiate cancer, as well as the association of the cell-of-origin with tumor subtypes and sensitivity to treatment. Citation Format: Kirsten Kubler, Rosa Karlic, Nicholas J. Haradhvala, Kyungsik Ha, Jaegil Kim, Maja Kuzman, Wei Jiao, Sitanshu Gakkhar, Kent W. Mouw, Lior Z. Braunstein, Olivier Elemento, Andrew V. Biankin, Ilse Rooman, Mendy Miller, Christopher D. Nogiec, Edward Curry, Mari Mino-Kenudson, Leif W. Ellisen, Robert Brown, Alexander Gusev, Cristian Tomasetti, Hong-Gee Kim, Hwajin Lee, Kristian Vlahovicek, Charles Sawyers, Katherine A. Hoadley, Edwin Cuppen, Amnon Koren, Peter F. Arndt, David N. Louis, Lincoln Stein, William D. Foulkes, Paz Polak, Gad Getz. The premalignant state captured in the landscape of somatic mutations can reveal the cancer cell-of-origin [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2727.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
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  • 8
    In: Nature, Springer Science and Business Media LLC, Vol. 608, No. 7924 ( 2022-08-25), p. 724-732
    Abstract: The lymphocyte genome is prone to many threats, including programmed mutation during differentiation 1 , antigen-driven proliferation and residency in diverse microenvironments. Here, after developing protocols for expansion of single-cell lymphocyte cultures, we sequenced whole genomes from 717 normal naive and memory B and T cells and haematopoietic stem cells. All lymphocyte subsets carried more point mutations and structural variants than haematopoietic stem cells, with higher burdens in memory cells than in naive cells, and with T cells accumulating mutations at a higher rate throughout life. Off-target effects of immunological diversification accounted for approximately half of the additional differentiation-associated mutations in lymphocytes. Memory B cells acquired, on average, 18 off-target mutations genome-wide for every on-target IGHV mutation during the germinal centre reaction. Structural variation was 16-fold higher in lymphocytes than in stem cells, with around 15% of deletions being attributable to off-target recombinase-activating gene activity. DNA damage from ultraviolet light exposure and other sporadic mutational processes generated hundreds to thousands of mutations in some memory cells. The mutation burden and signatures of normal B cells were broadly similar to those seen in many B-cell cancers, suggesting that malignant transformation of lymphocytes arises from the same mutational processes that are active across normal ontogeny. The mutational landscape of normal lymphocytes chronicles the off-target effects of programmed genome engineering during immunological diversification and the consequences of differentiation, proliferation and residency in diverse microenvironments.
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
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  • 9
    In: Nature, Springer Science and Business Media LLC, Vol. 578, No. 7793 ( 2020-02-06), p. 129-136
    Abstract: Transcript alterations often result from somatic changes in cancer genomes 1 . Various forms of RNA alterations have been described in cancer, including overexpression 2 , altered splicing 3 and gene fusions 4 ; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) 5 . Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis , of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed ‘bridged’ fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
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    detail.hit.zdb_id: 1413423-8
    SSG: 11
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  • 10
    In: Nature Genetics, Springer Science and Business Media LLC, Vol. 52, No. 3 ( 2020-03-02), p. 342-352
    Abstract: Mitochondria are essential cellular organelles that play critical roles in cancer. Here, as part of the International Cancer Genome Consortium/The Cancer Genome Atlas Pan-Cancer Analysis of Whole Genomes Consortium, which aggregated whole-genome sequencing data from 2,658 cancers across 38 tumor types, we performed a multidimensional, integrated characterization of mitochondrial genomes and related RNA sequencing data. Our analysis presents the most definitive mutational landscape of mitochondrial genomes and identifies several hypermutated cases. Truncating mutations are markedly enriched in kidney, colorectal and thyroid cancers, suggesting oncogenic effects with the activation of signaling pathways. We find frequent somatic nuclear transfers of mitochondrial DNA, some of which disrupt therapeutic target genes. Mitochondrial copy number varies greatly within and across cancers and correlates with clinical variables. Co-expression analysis highlights the function of mitochondrial genes in oxidative phosphorylation, DNA repair and the cell cycle, and shows their connections with clinically actionable genes. Our study lays a foundation for translating mitochondrial biology into clinical applications.
    Type of Medium: Online Resource
    ISSN: 1061-4036 , 1546-1718
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 1494946-5
    SSG: 12
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