Author
Ludmil B. Alexandrov
Other affiliations: Beth Israel Deaconess Medical Center, University of California, Berkeley, Wellcome Trust Sanger Institute ...read more
Bio: Ludmil B. Alexandrov is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 60, co-authored 117 publications receiving 28167 citations. Previous affiliations of Ludmil B. Alexandrov include Beth Israel Deaconess Medical Center & University of California, Berkeley.
Topics: Medicine, Biology, Cancer, Germline mutation, Genome
Papers
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Wellcome Trust Sanger Institute1, Wellcome Trust2, Cambridge University Hospitals NHS Foundation Trust3, University of British Columbia4, University of Cambridge5, Oslo University Hospital6, The Breast Cancer Research Foundation7, University of Oslo8, University of Münster9, Université libre de Bruxelles10, German Cancer Research Center11, University of Iceland12, Erasmus University Rotterdam13, French Institute of Health and Medical Research14, Paris Descartes University15, 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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Wellcome Trust Sanger Institute1, Katholieke Universiteit Leuven2, Flanders Institute for Biotechnology3, 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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Cambridge University Hospitals NHS Foundation Trust1, Wellcome Trust Sanger Institute2, 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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University of California, San Diego1, Broad Institute2, Harvard University3, National University of Singapore4, Baylor College of Medicine5, National Institutes of Health6, Pompeu Fabra University7, Catalan Institution for Research and Advanced Studies8, Wellcome Trust Sanger Institute9, National Centre for Biological Sciences10, University of Helsinki11
TL;DR: The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet- base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development.
Abstract: Somatic mutations in cancer genomes are caused by multiple mutational processes, each of which generates a characteristic mutational signature1. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium2 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 analyses3–15, 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. The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet-base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development.
1,521 citations
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TL;DR: Across 234 biopsies of sun-exposed eyelid epidermis from four individuals, the burden of somatic mutations averaged two to six mutations per megabase per cell, similar to that seen in many cancers, and exhibited characteristic signatures of exposure to ultraviolet light.
Abstract: How somatic mutations accumulate in normal cells is central to understanding cancer development but is poorly understood. We performed ultradeep sequencing of 74 cancer genes in small (0.8 to 4.7 square millimeters) biopsies of normal skin. Across 234 biopsies of sun-exposed eyelid epidermis from four individuals, the burden of somatic mutations averaged two to six mutations per megabase per cell, similar to that seen in many cancers, and exhibited characteristic signatures of exposure to ultraviolet light. Remarkably, multiple cancer genes are under strong positive selection even in physiologically normal skin, including most of the key drivers of cutaneous squamous cell carcinomas. Positively selected mutations were found in 18 to 32% of normal skin cells at a density of ~140 driver mutations per square centimeter. We observed variability in the driver landscape among individuals and variability in the sizes of clonal expansions across genes. Thus, aged sun-exposed skin is a patchwork of thousands of evolving clones with over a quarter of cells carrying cancer-causing mutations while maintaining the physiological functions of epidermis.
1,312 citations
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01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.
10,141 citations
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Wellcome Trust Sanger Institute1, Wellcome Trust2, Cambridge University Hospitals NHS Foundation 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, Bankstown Lidcombe Hospital29, University of New South Wales30, 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: The following Clinical Practice Guidelines will give up-to-date advice for the clinical management of patients with hepatocellular carcinoma, as well as providing an in-depth review of all the relevant data leading to the conclusions herein.
7,851 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: Treatment efficacy was associated with a higher number of mutations in the tumors, and a tumor-specific T cell response paralleled tumor regression in one patient, suggesting that the genomic landscape of lung cancers shapes response to anti–PD-1 therapy.
Abstract: Immune checkpoint inhibitors, which unleash a patient’s own T cells to kill tumors, are revolutionizing cancer treatment. To unravel the genomic determinants of response to this therapy, we used whole-exome sequencing of non–small cell lung cancers treated with pembrolizumab, an antibody targeting programmed cell death-1 (PD-1). In two independent cohorts, higher nonsynonymous mutation burden in tumors was associated with improved objective response, durable clinical benefit, and progression-free survival. Efficacy also correlated with the molecular smoking signature, higher neoantigen burden, and DNA repair pathway mutations; each factor was also associated with mutation burden. In one responder, neoantigen-specific CD8+ T cell responses paralleled tumor regression, suggesting that anti–PD-1 therapy enhances neoantigen-specific T cell reactivity. Our results suggest that the genomic landscape of lung cancers shapes response to anti–PD-1 therapy.
6,215 citations