Author
John W.M. Martens
Other affiliations: Erasmus University Medical Center
Bio: John W.M. Martens is an academic researcher from Erasmus University Rotterdam. The author has contributed to research in topics: Breast cancer & Cancer. The author has an hindex of 69, co-authored 283 publications receiving 21119 citations. Previous affiliations of John W.M. Martens include Erasmus University Medical Center.
Topics: Breast cancer, Cancer, Medicine, Circulating tumor cell, Metastasis
Papers published on a yearly basis
Papers
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Wellcome Trust Sanger Institute1, Flanders Institute for Biotechnology2, Katholieke Universiteit Leuven3, Norwich Research Park4, University of East Anglia5, Lund University6, Harvard University7, Oslo University Hospital8, King's College London9, Erasmus University Rotterdam10, University of British Columbia11, Curie Institute12, The Breast Cancer Research Foundation13, Medical Research Council14, Cambridge University Hospitals NHS Foundation Trust15, University of Cambridge16
TL;DR: This work generated catalogs of somatic mutation from 21 breast cancers and applied mathematical methods to extract mutational signatures of the underlying processes, finding a remarkable phenomenon of localized hypermutation, termed “kataegis,” was observed.
1,699 citations
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Wellcome Trust Sanger Institute1, Cambridge University Hospitals NHS Foundation Trust2, Lund University3, Erasmus University Medical Center4, Radboud University Nijmegen5, European Bioinformatics Institute6, University of Oslo7, Oslo University Hospital8, Gachon University9, Netherlands Cancer Institute10, Université libre de Bruxelles11, University of Antwerp12, Harvard University13, University of Amsterdam14, University of Ulsan15, Hanyang University16, Memorial Sloan Kettering Cancer Center17, University of Texas MD Anderson Cancer Center18, French Institute of Health and Medical Research19, Ninewells Hospital20, ICM Partners21, University of Queensland22, University of Iceland23, Curie Institute24, University of Cambridge25, King's College London26, Institute of Cancer Research27, University of Bergen28, Singapore General Hospital29
TL;DR: This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operative, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.
Abstract: We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.
1,696 citations
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Wellcome Trust Sanger Institute1, Wellcome Trust2, Katholieke Universiteit Leuven3, University of East Anglia4, Guy's and St Thomas' NHS Foundation Trust5, Academia Sinica6, Singapore General Hospital7, Netherlands Cancer Institute8, University of Queensland9, University of British Columbia10, Erasmus University Rotterdam11, Harvard University12, University of Cambridge13, Claude Bernard University Lyon 114, Curie Institute15, Royal Brisbane and Women's Hospital16, University of Amsterdam17, Université libre de Bruxelles18, The Breast Cancer Research Foundation19, Cambridge University Hospitals NHS Foundation Trust20, Oslo University Hospital21
TL;DR: Strong correlations between mutation number, age at which cancer was diagnosed and cancer histological grade are found, and multiple mutational signatures are observed, including one present in about ten per cent of tumours characterized by numerous mutations of cytosine at TpC dinucleotides.
Abstract: All cancers carry somatic mutations in their genomes. A subset, known as driver mutations, confer clonal selective advantage on cancer cells and are causally implicated in oncogenesis, and the remainder are passenger mutations. The driver mutations and mutational processes operative in breast cancer have not yet been comprehensively explored. Here we examine the genomes of 100 tumours for somatic copy number changes and mutations in the coding exons of protein-coding genes. The number of somatic mutations varied markedly between individual tumours. We found strong correlations between mutation number, age at which cancer was diagnosed and cancer histological grade, and observed multiple mutational signatures, including one present in about ten per cent of tumours characterized by numerous mutations of cytosine at TpC dinucleotides. Driver mutations were identified in several new cancer genes including AKT2, ARID1B, CASP8, CDKN1B, MAP3K1, MAP3K13, NCOR1, SMARCD1 and TBX3. Among the 100 tumours, we found driver mutations in at least 40 cancer genes and 73 different combinations of mutated cancer genes. The results highlight the substantial genetic diversity underlying this common disease.
1,606 citations
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TL;DR: The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.
Abstract: Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1,2,3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10,11,12,13,14,15,16,17,18.
1,600 citations
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TL;DR: A paired-end sequencing strategy is used to identify somatic rearrangements in breast cancer genomes and provides a new perspective on cancer genomes, highlighting the diversity of somatic upheavals and their potential contribution to cancer development.
Abstract: Multiple somatic rearrangements are often found in cancer genomes; however, the underlying processes of rearrangement and their contribution to cancer development are poorly characterized Here we use a paired-end sequencing strategy to identify somatic rearrangements in breast cancer genomes There are more rearrangements in some breast cancers than previously appreciated Rearrangements are more frequent over gene footprints and most are intrachromosomal Multiple rearrangement architectures are present, but tandem duplications are particularly common in some cancers, perhaps reflecting a specific defect in DNA maintenance Short overlapping sequences at most rearrangement junctions indicate that these have been mediated by non-homologous end-joining DNA repair, although varying sequence patterns indicate that multiple processes of this type are operative Several expressed in-frame fusion genes were identified but none was recurrent The study provides a new perspective on cancer genomes, highlighting the diversity of somatic rearrangements and their potential contribution to cancer development
838 citations
Cited by
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Wellcome Trust Sanger Institute1, Cambridge University Hospitals NHS Foundation Trust2, Wellcome Trust3, University of British Columbia4, University of Cambridge5, The Breast Cancer Research Foundation6, Oslo University Hospital7, University of Oslo8, University of Münster9, Université libre de Bruxelles10, German Cancer Research Center11, University of Iceland12, Erasmus University Rotterdam13, Paris Descartes University14, French Institute of Health and Medical Research15, University of Paris16, Broad Institute17, University of Bergen18, University of Oviedo19, University of Queensland20, University of Glasgow21, Harvard University22, United States Department of Veterans Affairs23, Netherlands Cancer Institute24, University of Kiel25, Radboud University Nijmegen26, King's College London27, Curie Institute28, University of New South Wales29, Bankstown Lidcombe Hospital30, University of Barcelona31
TL;DR: It is shown that hypermutation localized to small genomic regions, ‘kataegis’, is found in many cancer types, and this results reveal the diversity of mutational processes underlying the development of cancer.
Abstract: All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, 'kataegis', is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.
7,904 citations
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TL;DR: This work has revealed the genomic landscapes of common forms of human cancer, which consists of a small number of “mountains” (genes altered in a high percentage of tumors) and a much larger number of "hills" (Genes altered infrequently).
Abstract: Over the past decade, comprehensive sequencing efforts have revealed the genomic landscapes of common forms of human cancer. For most cancer types, this landscape consists of a small number of “mountains” (genes altered in a high percentage of tumors) and a much larger number of “hills” (genes altered infrequently). To date, these studies have revealed ~140 genes that, when altered by intragenic mutations, can promote or “drive” tumorigenesis. A typical tumor contains two to eight of these “driver gene” mutations; the remaining mutations are passengers that confer no selective growth advantage. Driver genes can be classified into 12 signaling pathways that regulate three core cellular processes: cell fate, cell survival, and genome maintenance. A better understanding of these pathways is one of the most pressing needs in basic cancer research. Even now, however, our knowledge of cancer genomes is sufficient to guide the development of more effective approaches for reducing cancer morbidity and mortality.
6,441 citations
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TL;DR: It is proposed that this "competing endogenous RNA" (ceRNA) activity forms a large-scale regulatory network across the transcriptome, greatly expanding the functional genetic information in the human genome and playing important roles in pathological conditions, such as cancer.
5,334 citations
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TL;DR: The results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome, and identify novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort.
Abstract: 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 cisand 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.
4,722 citations
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TL;DR: A fundamental problem with cancer genome studies is described: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds and the list includes many implausible genes, suggesting extensive false-positive findings that overshadow true driver events.
Abstract: Major international projects are underway that are aimed at creating a comprehensive catalogue of all the genes responsible for the initiation and progression of cancer. These studies involve the sequencing of matched tumour-normal samples followed by mathematical analysis to identify those genes in which mutations occur more frequently than expected by random chance. Here we describe a fundamental problem with cancer genome studies: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds. The list includes many implausible genes (such as those encoding olfactory receptors and the muscle protein titin), suggesting extensive false-positive findings that overshadow true driver events. We show that this problem stems largely from mutational heterogeneity and provide a novel analytical methodology, MutSigCV, for resolving the problem. We apply MutSigCV to exome sequences from 3,083 tumour-normal pairs and discover extraordinary variation in mutation frequency and spectrum within cancer types, which sheds light on mutational processes and disease aetiology, and in mutation frequency across the genome, which is strongly correlated with DNA replication timing and also with transcriptional activity. By incorporating mutational heterogeneity into the analyses, MutSigCV is able to eliminate most of the apparent artefactual findings and enable the identification of genes truly associated with cancer.
4,411 citations