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Grant Details

Grant Number: 5R01CA269919-02 Interpret this number
Primary Investigator: Carter, Hannah
Organization: University Of California, San Diego
Project Title: Comprehensive Identification of Germline-Somatic Interactions
Fiscal Year: 2023


Cancer remains a significant source of morbidity and mortality worldwide. Advances in next generation sequencing technologies have allowed extensive profiling of the genetic variants present in tumors and revealed daunting levels of inter-tumoral heterogeneity. Tumor genomic datasets have been extensively mined to reveal germline risk variants and to characterize heterogeneous patterns of somatic alteration that drive tumor progression. However, little attention has been given to interactions between genetic background and somatic changes, which could represent a major driver of heterogeneity. New evidence suggests that germline-somatic interactions are prevalent and our preliminary data support that some such interactions directly influence individual disease risk and potential to respond to therapies. This proposal will develop computational strategies to identify germline-somatic interactions and to characterize them in the context of molecular and clinical phenotypes, enabling new understanding of their role in inter-tumoral heterogeneity. Germline-somatic interactions have been challenging to study due to the limited amount of available data. To address this challenge, we have compiled tumor genomic data from public sources to boost our sample size to almost 45,000 tumor whole-exome and whole-genome sequences. Our analysis will focus on three major forces that shape the tumor genome: (i) the mutational processes that generate somatic mutations, (ii) the molecular organization of oncogenic pathways which determines the genes that can effectively drive cancer, and (iii) the immune system which acts as a selective force throughout tumor development. We will focus hypothesis testing with strict criteria for selecting germline variants and somatically altered genes likely to interact based on established tumor biology. To identify and characterize germline-somatic interactions we will: 1) Elucidate germline variants affecting the somatic mutational landscapes of human cancers 2) Reveal germline variants that modify somatic activation of hallmark oncogenic pathways 3) Establish the role of pathway-specific variant burden in cancer predisposition, overall survival, and response to immunotherapy Our team of co-investigators includes strong complementary expertise in analysis of mutational processes, genetic variation effects on molecular pathways and immunity, cancer biology, statistical methods and bioinformatic software dissemination. Careful attention will be given to statistical considerations including power, controlling false discovery rates, and validation in independent datasets. This proposal will produce A) novel bioinformatics tools designed specifically to detect and annotate germline-somatic interactions, B) new understanding of the contribution of germline variation to tumor progression, and C) a set of validated germline- somatic interactions affecting cancer risk, tumor evolution and immunotherapy response.


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Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator.
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Assigning mutational signatures to individual samples and individual somatic mutations with SigProfilerAssignment.
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Germline modifiers of the tumor immune microenvironment implicate drivers of cancer risk and immunotherapy response.
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Comprehensive analysis of mutational signatures reveals distinct patterns and molecular processes across 27 pediatric cancers.
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DNA damage and somatic mutations in mammalian cells after irradiation with a nail polish dryer.
Authors: Zhivagui M. , Hoda A. , Valenzuela N. , Yeh Y.Y. , Dai J. , He Y. , Nandi S.P. , Otlu B. , Van Houten B. , Alexandrov L.B. .
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Unraveling the impact of a germline heterozygous POLD1 frameshift variant in serrated polyposis syndrome.
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Differential regulation of TNFα and IL-6 expression contributes to immune evasion in prostate cancer.
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Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor.
Authors: Islam S.M.A. , Díaz-Gay M. , Wu Y. , Barnes M. , Vangara R. , Bergstrom E.N. , He Y. , Vella M. , Wang J. , Teague J.W. , et al. .
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Germline genetic biomarkers to stratify patients for personalized radiation treatment.
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Source: Journal of translational medicine, 2022-08-12; 20(1), p. 360.
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