Somatic mutation and selection at epidemiological scale

Comprehensive Mutational Analysis of Juvenile Myelomonocytic Leukemia Using Whole-Genome Sequencing

Driver mutations are the genetic variants responsible for oncogenesis, but how specific somatic mutational events arise in cells remains poorly understood. Mutational signatures derive from the frequency of mutated trinucleotides in a given cancer sample, and they provide an avenue for investigating the underlying mutational processes that operate in cancer. Here we analyse somatic mutations from 7,815 cancer exomes from The Cancer Genome Atlas (TCGA) across 26 cancer types. We curate a list of 50 known cancer driver mutations by analysing recurrence in our cohort and annotations of known cancer-associated genes from the Cancer Gene Census, IntOGen database and Cancer Genome Interpreter. We then use these datasets to perform binary univariate logistic regression and establish the statistical relationship between individual driver mutations and known mutational signatures across different cancer types. Our analysis led to the identification of 39 significant associations between driver mutations and mutational signatures (P < 0.004, with a false discovery rate of < 5%). We first validate our methodology by establishing statistical links for known and novel associations between driver mutations and the mutational signature arising from Polymerase Epsilon proofreading deficiency. We then examine associations between driver mutations and mutational signatures for AID/APOBEC enzyme activity and deficient mismatch repair. We also identify negative associations (odds ratio < 1) between mutational signatures and driver mutations, and here we examine the role of aging and cigarette smoke mutagenesis in the generation of driver mutations in IDH1 and KRAS in brain cancers and lung adenocarcinomas respectively. Our study provides statistical foundations for hypothesised links between otherwise independent biological processes and we uncover previously unexplored relationships between driver mutations and mutagenic processes during cancer development. These associations give insights into how cancers acquire advantageous mutations and can provide direction to guide further mechanistic studies into cancer pathogenesis.

In this review, we provide a survey and appraisal of research into somatic genomic events in endometriosis. Methodologies have evolved from conventional cytogenetics to next-generation sequencing, with findings ranging from chromosome imbalances to recurrent somatic cancer driver mutations. Somatic cancer driver mutations have been described in a range of endometriosis lesions, dominated by recurrent mutations in KRAS and PIK3CA as well as loss of PTEN and BAF250a (ARID1A). These somatic events appear to be largely restricted to the endometriosis glandular epithelium. Somatic mutations, particularly PTEN loss, have also been observed in eutopic (uterine) endometrium, although at lower mutant allele frequencies compared with ectopic lesions. Systematic studies of the potential clinical phenotype of these somatic genomic events have yet to be performed. Thus, we propose a framework to investigate the potential clinical phenotype associated with somatic genomic events in endometriosis. Technical requirements include pathology review of histological endometriosis, microdissection for tissue enrichment, orthogonal validation of whole genome/exome sequencing, and a germline sample for confirmation of somatic origin. Clinical requirements include annotation of surgical findings; patient demographics; cross-sectional and prospective data on pain and fertility; consideration of sampling multiple lesions in each patient, mutant allele frequency, and somatic events in the eutopic endometrium; and confirmation of any associations with mechanistic studies. Given the multifactorial nature of endometriosis-associated symptoms, it is likely that somatic events have small (or at most, moderate) effect sizes, and thus careful consideration will have to be given to future study design.

the development and progression of triple-negative breast cancer (TNBC) is driven by somatic driver mutations and the tumor-immune microenvironment. To date, data on somatic mutations has not been leveraged and integrated with information on the immune microenvironment to elucidate the possible oncogenic interactions and their potential effects on clinical outcomes. Here, we investigated possible oncogenic interactions between somatic mutations and the tumor-immune microenvironment, and their correlation with patient survival in TNBC. We performed analysis combining data on 7,875 somatic mutated genes with information on 1,751 immune-modulated genes, using gene-expression data as the intermediate phenotype, and correlated the resulting information with survival. We conducted functional analysis to identify immune-modulated molecular networks and signaling pathways enriched for somatic mutations likely to drive clinical outcomes. We discovered differences in somatic mutation profiles between patients who died and those who survived, and a signature of somatic mutated immune-modulated genes transcriptionally associated with TNBC, predictive of survival. In addition, we discovered immune-modulated molecular networks and signaling pathways enriched for somatic mutations. The investigation revealed possible oncogenic interactions between somatic mutations and the tumor-immune microenvironment in TNBC, likely to affect clinical outcomes.

BACKGROUND: Preliminary data has highlighted inherited predisposition to lung cancer related to certain genes. The frequency of pathogenic germline variants (PGV) PGV in patients (pts) with lung cancer according to the presence of an oncogenic driver is unknown. We studied the PGV of genes predisposing to cancer in pts with non-small cell lung cancer (NSCLC), and the somatic molecular profile of lung tumors. METHODS: Retrospective study of whole exome sequencing (WES) from tissue biopsies performed in pts with advanced NSCLC enrolled, after signature of the inform consent, in the MOSCATO/MATCH-R trials between 2012 and 2018. Variants were considered as PGVs in the cancer predisposing genes (PMID: 29625052) if they satisfied the following criteria: (i) they had a “PASS” flag in HaplotypeCaller, (ii) were annotated as “Pathogenic” or “Likely Pathogenic” in ClinVar (PMID: 29165669) or InterVar (PMID: 28132688), or (iii) were truncating variants. Somatic driver mutations and Loss of Heterozygocity (LOH) of PGV harboring genes were further evaluated. The overlap to loss of heterozygocity regions was reported only when the variant allele frequency of the PGV was significantly higher than in the normal tissue. Cancer history, clinical and molecular data were retrospectively collected. The somatic mutations (m) in EGFR/BRAF/MET/HER2/KRAS and fusions in ALK/ROS1/RET were also considered for analysis. RESULTS: Among 134 pts, 48% were women, median age was 61 (range 24-83), 45% were nonsmokers, 74% had adenocarcinoma. The most common somatic oncogenic driver alterations were: EGFRm in 44 pts (33%), KRASm in 19 pts (14%), BRAFm in 12 pts (9%) and ALK in 12 pts (9%).PGV were found in 22 out of 152 (15%) cancer-predisposing genes; 4 pts had additional somatic mutations (2) or LOHs (2) in the same genes. 77% of PGVs were in genes which are part of DNA repair pathways including 3.6% nucleotide excision repair (ERCC1/2/3, XPA), 6.5% homologous recombination/Fanconi Anemia: (FANC/A/C/M/D2, BRCA1, RECQL), 2.1% base excision repair (MUTYH, NTHL1), while the others were represented by genes related to cell signaling and metabolism (NF1, MET, ELANE, PRDM9, TRIM37).In the 22 PGV-carriers, 68% had a somatic oncogene-driven alteration (15/22) : EGFRm (n=7; 5 ex19del, 2 ex21(L858R)), KRASm (n=3; 2 G12D, 1 G12V), METm (n=2), HER2m (n=1), ROS1 (n=1) and RET (n=1). PGV were observed in 16% of EGFRm (7/44), 67% of METm (2/3), 15% in KRASm (3/19), 33% of HER2m (1/3), 25% of ROS1 (1/4), 50% of RET (1/2); but no PGV was identified in pts with BRAFVm (12) or ALK (12). CONCLUSION: In our cohort, 15% of pts with NSCLC were PGV-carriers; 68% of PGV-carriers had oncogene-driven tumors, particularly with somatic EGFR mutations. PGV and oncogene-driven lung carcinogenesis need further evaluation. Citation Format: Laura Mezquita, Andrei Iurchenko, Jose Carlos Benitez, Maria Baz, Sergey Nikolaev, David Planchard, Felix Blanc-Durand, Mihaela Aldea, Patricia Martín-Romano, Yohann Loriot, Claudio Nicotra, Maud Ngocamus, Jean-Yves Scoazec, Stefan Michiels, Sophie Postel-Vinay, Julien Viot, Luc Friboulet, Antoine Italiano, Fabrice Andre, Christophe Massard, Jean-Charles Soria, Etienne Rouleau, Daniel Gautheret, Benjamin Besse. High prevalence of pathogenic germline variants in patients with oncogene-driven non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 448.

Polygenic Germline Risk of Common Haematological Traits Drives Clonal Selection on <i>JAK2</i>V617F and Development of Myeloproliferative Neoplasms

scATAC-seq data presents unprecedented opportunities to identify somatic mutations in regulatory regions. However, existing tools struggle to reliably detect somatic mutations from scATAC-seq data due to the unbalanced coverage between tumor and normal cells. To address this, we developed scVar, a pipeline designed to detect somatic mutations from scATAC-seq data. Applying scVar to snATAC-Seq data from about 200 tumor samples spanning 10 cancer types, we identified over 70, 000 somatic mutations, with 95% located in non-coding regions. Comparison with bulk WGS and WXS data demonstrated that scVar achieves high accuracy in detecting somatic mutations. Notably, scVar effectively recaptured the UV mutational signature in skin cancer. Variant allele frequency (VAF) analysis revealed an increase in VAF in snATAC-seq data compared to WXS data. For tumor suppressor genes such as TP53, VHL, BAP1, CDH1, CBFB, TGIF1, and ZNF750, homozygous mutations with VAFs approaching 1 were consistently detected in snATAC-seq data, emphasizing the critical role of biallelic variants in tumor initiation. We also observed recurrent TERT promoter mutations across 20 samples, with VAFs close to 1, which were associated with increased chromatin accessibility and expression in glioblastoma, but not in skin cancer. Additionally, novel promoter mutations, such as in CDK12, were linked to increased gene expression. These findings highlight the utility of scVar in uncovering somatic mutations and their functional effects in non-coding regions from scATAC-seq data. Citation Format: Song Cao, Liting Zhang, Alla Karpova, Fernanda M. Rodrigues, Yingduo Song, Nadezhda V. Terekhanova, Benjamin J. Raphael, Ryan C. Fields, Feng Chen, Li Ding. Discovery of non-coding somatic driver mutations in single-cell chromatin accessibility data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2385.

The identification of somatic driver mutations in cancer has enabled therapeutic advances by identifying drug targets critical to disease causation. However, such genomic discoveries in oncology have not translated into...

Genetic Testing in Pancreatic Ductal Adenocarcinoma: Implications for Prevention and Treatment

Angioimmunoblastic T-cell lymphoma (AITL) is a subtype of peripheral T-cell lymphoma with a poor prognosis: the 5-year survival rate is approximately 30%. Somatic driver mutations have been found in TET2, IDH2, DNMT3A, RHOA, FYN, PLCG1, and CD28, whereas germline susceptibility to AITL has to our knowledge not been studied. The homogenous Finnish population is well suited for studies on genetic predisposition. Here, we performed an exome-wide rare variant analysis in 23 AITL patients. No germline mutations were found in the driver genes, implying that they are not frequently involved in genetic AITL predisposition. Potentially pathogenic variants present in at least two patients and showing significant (p < 0.01) enrichment in our sample set were found in ten genes: POLK, PRKCB, ZNF676, PRRC2B, PCDHGB6, GNL3L, TTC36, OTOG, OSGEPL1, and RASSF9. The most significantly enriched variants, causing p.Lys469Ter in a splice variant of POLK and p.Pro588His in PRKCB, are intriguing candidates as Polk deficient mice display a spontaneous mutator phenotype, whereas PRKCB was recently shown to be somatically mutated in 33% of another peripheral T-cell lymphoma, adult T-cell lymphoma. If validated, our findings would provide new insight into the pathogenesis of AITL, as well as tools for early detection in susceptible individuals.

Motivation: The number of missense mutations being identified in cancer genomes has greatly increased as a consequence of technological advances and the reduced cost of whole-genome/whole-exome sequencing methods. However, a high proportion of the amino acid substitutions detected in cancer genomes have little or no effect on tumour progression (passenger mutations). Therefore, accurate automated methods capable of discriminating between driver (cancer-promoting) and passenger mutations are becoming increasingly important. In our previous work, we developed the Functional Analysis through Hidden Markov Models (FATHMM) software and, using a model weighted for inherited disease mutations, observed improved performances over alternative computational prediction algorithms. Here, we describe an adaptation of our original algorithm that incorporates a cancer-specific model to potentiate the functional analysis of driver mutations.Results: The performance of our algorithm was evaluated using two separate benchmarks. In our analysis, we observed improved performances when distinguishing between driver mutations and other germ line variants (both disease-causing and putatively neutral mutations). In addition, when discriminating between somatic driver and passenger mutations, we observed performances comparable with the leading computational prediction algorithms: SPF-Cancer and TransFIC.Availability and implementation: A web-based implementation of our cancer-specific model, including a downloadable stand-alone package, is available at http://fathmm.biocompute.org.uk.Contact:fathmm@biocompute.org.ukSupplementary information:Supplementary data are available at Bioinformatics online.

Philadelphia-negative (Ph−) classical myeloproliferative neoplasms (MPNs) include polycythemia vera, essential thrombocythemia (ET), and primary myelofibrosis. Somatic driver mutations in the JAK2, CALR, and MPL genes serve as major diagnostic criteria of the Ph− MPNs and these mutations occur in a mutually exclusive manner. In this report, we describe the first case of ET harboring double mutations in JAK2 V617F and MPL. For MPL, the patient had multiple clones of MPL mutations: c.1543_1546delinsAGGG (p.Trp515_Gln516delinsArgGlu) and c.1546C>G (p.Gln516Glu). The JAK2 V617F allele burden in our patient is very low (4%) compared to the relatively high (17%–78%) allele frequency of MPL mutations. The low JAK2 mutant burden might be explained by preexisting clonal hematopoiesis before overt signs of MPNs, followed by the acquisition of a second oncogenic mutation of CALR or MPL leading to the MPN phenotype. This highlights that screening for a second driver mutation should be considered in patients with a low JAK2 mutant burden by reporting a 57-year-old Korean man with ET.

Intracranial aneurysms (IAs) are a major cause of subarachnoidal hemorrhage (SAH) which can have a significant morbidity and mortality. The processes underlying the aneurysm development remains unclear. We performed whole exome sequencing of DNA derived from 20 saccular cerebral aneurysms of 20 patients, followed by somatic variant calling. Eleven (55%) of the 20 patients had detectable nonsynonymous somatic mutations and in total, 48 mutations were detected in the aneurysm samples. The mutations were highly enriched in cancer-related genes and 77% were predictably deleterious. A p.Tyr562Asp somatic mutation was detected in the PDGFRB gene; somatic mutations at the same codon have been reported in fusiform cerebral aneurysms. These results widen the concept on the role of somatic mutations in cerebral aneurysms, indicating their possible role in the more common saccular aneurysm, similarly to the rarer fusiform aneurysm.

Cancer-Type Somatic Mutations in Saccular Cerebral Aneurysms

I come from a family in which there have been no scientists or doctors. I was interested, however, in biology at school and started my scientific career by training in medicine at Oxford University and Guys Hospital, London. Practising as a doctor reinforced my curiosity about the biological processes underlying human disease. As a consequence, I pursued a clinical vocation in histopathology, a discipline that couples exposure to the sights and smells of the autopsy room with a daily journey into the often beautiful, sometimes ugly world of healthy and diseased human tissues under the microscope. After an introduction to general histopathology in Nick Wright's department at the Hammersmith Hospital, London, I completed my postgraduate medical training in neuropathology with Peter Lantos at the Maudsley Hospital, London.Peering at the nuclei of cancer cells under the microscope, for me it was a matter of fascination that hidden within them were the key events converting normal cells into cancer cells, and frustration because they were out of reach. Many of the tissue samples examined by pathologists are from cancers. The clonal theory of cancer development and the general role of DNA mutations in generating cancer cell clones had been established by 1986 when I was working as a junior pathologist. Indeed, the first mutated cancer gene, HRAS , had recently been identified through application of the, then new, technologies of recombinant DNA technology. Peering at the nuclei of cancer cells under the microscope, for me it was a matter of fascination that hidden within them were the key events converting normal cells into cancer cells, and frustration because they were out of reach. So, I took 3 years break from medicine to study for a PhD, learning the methods and thinking of molecular oncology in Colin Cooper's laboratory at the Institute …