6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Substitution mutational signatures in whole-genome–sequenced cancers in the UK population

      1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 3 , 4 , 1 , 2 , 1 , 2 , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Genomics England Research Consortium†
      Science
      American Association for the Advancement of Science (AAAS)

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Whole-genome sequencing (WGS) permits comprehensive cancer genome analyses, revealing mutational signatures, imprints of DNA damage, and repair processes that have arisen in each patient’s cancer. We performed mutational signature analyses on 12,222 whole-genome–sequenced tumor-normal matched pairs from patients recruited via the UK National Health Service (NHS). We contrasted our results with two independent cancer WGS datasets—from the International Cancer Genome Consortium (ICGC) and the Hartwig Medical Foundation (HMF)—involving 18,640 whole-genome–sequenced cancers in total. Our analyses add 40 single and 18 double substitution signatures to the current mutational signature tally. We show for each organ that cancers have a limited number of common signatures and a long tail of rare signatures, and we provide a practical solution for applying this concept of common versus rare signatures to future analyses.

          A signature accomplishment

          Tumor development is associated with the accumulation of mutations in the genome. Depending on the causes of a given cancer, such as environmental exposures or DNA repair abnormalities, these mutations can form a specific pattern called a mutational signature. Many mutational signatures have already been reported in cancer, but by performing whole-genome sequencing on a particularly large collection of cancer samples, Degasperi et al . not only confirmed previously reported signatures, but also discovered many rarer ones (see the Perspective by Szüts). The authors characterized these signatures, tried to elucidate the underlying biology where possible, and then provided an algorithm for applying these findings to individual patients to help personalize cancer treatments. —YN

          Abstract

          A large whole-genome sequenced cancer effort advances the understanding of common and rare mutational signatures and their analysis.

          Abstract

          INTRODUCTION

          Mutational signatures—imprints of DNA damage and repair processes that have been operative during tumorigenesis—provide insights into environmental and endogenous causes of each patient’s cancer. Cancer genome sequencing studies permit exploration of mutational signatures. We investigated a very large number of whole-genome–sequenced cancers of many tumor types, substantially more than in previous efforts, to comprehensively reinforce our understanding of mutational signatures.

          RATIONALE

          We present mutational signature analyses of 12,222 whole-genome–sequenced cancers collected prospectively via the UK National Health Service (NHS) for the 100,000 Genomes Project. We identified single-base substitution (SBS) and double-base substitution (DBS) signatures independently in each organ. Exploiting this unusually large cohort, we developed a method to enhance discrimination of common mutational processes from rare, lower-frequency mutagenic processes. We validated our findings by independently performing analyses with data from two publicly available cohorts: 3001 primary cancers from the International Cancer Genome Consortium (ICGC) and 3417 metastatic cancers from the Hartwig Medical Foundation. We produced a set of reference signatures by comparing and contrasting the independently derived tissue-specific signatures and performing clustering analysis to unite mutational signatures from different tissues that could be due to similar processes. We included additional quality control measures such as dimensionality reduction of mixed signatures and gathered evidence that could help elucidate mechanisms and etiologies such as transcriptional and replication strand bias, associations with somatic drivers, and germline predisposition mutations. We also investigated additional mutation context and examined past clinical and treatment histories when possible, to explore potential etiologies.

          RESULTS

          Each organ contained a limited number of common SBS signatures (typically between 5 and 10). The number of common signatures was independent of cohort size. By contrast, the number of rare signatures was dependent on sample size, as the likelihood of detecting a rare signature is a function of its population prevalence. The same biological process produced slightly different signatures in diverse tissues, reinforcing that mutational signatures are tissue specific.

          Across organs, we clustered all tissue-specific signatures to ascertain mutational processes that were equivalent but occurring in different tissues (i.e., reference signatures). We obtained 82 high-confidence SBS reference signatures and 27 high-confidence DBS reference signatures. We compared these with previously reported mutational signatures, revealing 40 and 18 previously unidentified SBS and DBS signatures, respectively.

          Because we are cognizant of increasing complexity in mutational signatures and want to enable general users, we developed an algorithm called Signature Fit Multi-Step (FitMS) that seeks signatures in new samples while taking advantage of our recent findings. In a first step, FitMS detects common, organ-specific signatures; in a second step, it determines whether an additional rare signature is also present.

          CONCLUSION

          Mutational signature analysis of 18,640 cancers, the largest cohort of whole-genome–sequenced samples to date, has required methodological advances, permitting knowledge expansion. We have identified many previously unreported signatures and established the concept of common and rare signatures. The FitMS algorithm has been designed to exploit these advances to aid users in accurately identifying mutational processes in new samples.

          Related collections

          Most cited references43

          • Record: found
          • Abstract: found
          • Article: not found

          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Signatures of mutational processes in human cancer

            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 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 etiology, prevention and therapy.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade

              The genomes of cancers deficient in mismatch repair contain exceptionally high numbers of somatic mutations. In a proof-of-concept study, we previously showed that colorectal cancers with mismatch repair deficiency were sensitive to immune checkpoint blockade with antibodies to programmed death receptor-1 (PD-1). We have now expanded this study to evaluate the efficacy of PD-1 blockade in patients with advanced mismatch repair-deficient cancers across 12 different tumor types. Objective radiographic responses were observed in 53% of patients, and complete responses were achieved in 21% of patients. Responses were durable, with median progression-free survival and overall survival still not reached. Functional analysis in a responding patient demonstrated rapid in vivo expansion of neoantigen-specific T cell clones that were reactive to mutant neopeptides found in the tumor. These data support the hypothesis that the large proportion of mutant neoantigens in mismatch repair-deficient cancers make them sensitive to immune checkpoint blockade, regardless of the cancers' tissue of origin.
                Bookmark

                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Science
                Science
                American Association for the Advancement of Science (AAAS)
                0036-8075
                1095-9203
                April 22 2022
                April 22 2022
                : 376
                : 6591
                Affiliations
                [1 ]Academic Department of Medical Genetics, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK.
                [2 ]Early Cancer Institute, University of Cambridge, Cambridge CB2 0XZ, UK.
                [3 ]Genomics England, Queen Mary University of London, Dawson Hall, Charterhouse Square, London EC1M 6BQ, UK.
                [4 ]Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, UK.
                Article
                10.1126/science.abl9283
                35949260
                0afb7c4a-3c44-4356-87ba-c2de2aec0e12
                © 2022
                History

                Comments

                Comment on this article