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Grant Details

Grant Number: 1U01CA243483-01A1 Interpret this number
Primary Investigator: Amos, Christopher
Organization: Baylor College Of Medicine
Project Title: Sequencing Familial Lung Cancer
Fiscal Year: 2020


Lung cancer (LC) is the leading cause of cancer mortality in the U.S. Although tobacco smoking and some environmental exposures contribute substantially to lung cancer risk, family studies show an additional strong contribution from genetic factors. The Genetic Epidemiology of Lung Cancer Consortium (GELCC) has been collecting samples and data from individuals with a strong family history of LC for the last 20 years, and has assembled a unique resource of specimens and data. We have cancer phenotypes, smoking exposure data and biological specimens available on multiple relatives in over 150 highly aggregated LC families (high-risk familial lung cancer families, HRFLC cases/families) as well as phenotype, genotype and smoking data on over 800 additional lung cancer cases who have a family history of at least one first or second degree relative with lung cancer but for whom biospecimens were not available from additional relatives (familial cases from biospecimen limited families, FLC cases). The goal of this research application is to identify genetic factors that confer a high risk for lung cancer and to perform research to characterize further the mechanisms by which these factors influence lung cancer risk. Identifying genetic factors for lung cancer provides insight into the specific causes and pathways underlying its development. In addition, if high-risk individuals can be identified they will reap the greatest benefit from screening modalities. We propose three aims. In aim 1 we will identify genetic factors conferring a high-risk of lung cancer development.. In this aim, we will complete analyses of WES data from 33 HRFLC families comprising 291 individuals along with 114 FLC cases and case/control analyses of 1084 lung cancer cases compared with 919 controls. We will use these data along with linkage analysis to prioritize uncommon variants that have a strong effect on lung cancer risk. In Aim 2 we will extend and validate findings to a broader population. We will also collect additional samples from LC cases in HRLFC. We will sequence the most strongly associated variants and genes from Aim 1 in additional affected and unaffected individuals in the sequenced families and an additional set of FLC cases and frequency matched controls. This aim will allow us to a) validate findings from aim 1 using a larger collection of cases with a family history of lung cancer and controls and b) assess the impact on risk in families according to smoking behavior and genetic contributions. In Aim 3 we will study the impact that variants found in aims 1 and 2 have on cellular biology. We will study the effect that specific mutations have on cellular phenotypes identified in aims 1 and 2 using CRISPR technology. We will begin by studying mutations in PARK2 that we recently identified in 5 HRLFC families and in E2A we previously studied. The proposed research will bring new insights into the etiology of lung cancer.


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PMID: 38180474
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Heritable Traits and Lung Cancer Risk: A Two-Sample Mendelian Randomization Study.
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Source: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2023-10-02; 32(10), p. 1421-1435.
PMID: 37530747
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A rare FGF5 candidate variant (rs112475347) for predisposition to nonsquamous, nonsmall-cell lung cancer.
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A comprehensive analysis of lung cancer highlighting epidemiological factors and psychiatric comorbidities from the All of Us Research Program.
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p53 and ovarian carcinoma survival: an Ovarian Tumor Tissue Analysis consortium study.
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PMID: 36948887
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Functional studies of lung cancer GWAS beyond association.
Authors: Long E. , Patel H. , Byun J. , Amos C.I. , Choi J. .
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Genome-wide interaction analysis identified low-frequency variants with sex disparity in lung cancer risk.
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Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer.
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Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples.
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SNP characteristics and validation success in genome wide association studies.
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PMID: 34981173
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Identification of lung cancer drivers by comparison of the observed and the expected numbers of missense and nonsense mutations in individual human genes.
Authors: Gorlova O.Y. , Kimmel M. , Tsavachidis S. , Amos C.I. , Gorlov I.P. .
Source: Oncotarget, 2022; 13, p. 756-767.
EPub date: 2022-05-25.
PMID: 35634240
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Advancing NGS quality control to enable measurement of actionable mutations in circulating tumor DNA.
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Source: Cell reports methods, 2021-11-22; 1(7), p. 100106.
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PMID: 35475002
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Genetic Variation and Recurrent Haplotypes on Chromosome 6q23-25 Risk Locus in Familial Lung Cancer.
Authors: Musolf A.M. , Simpson C.L. , Moiz B.A. , Pikielny C.W. , Middlebrooks C.D. , Mandal D. , de Andrade M. , Cole M.D. , Gaba C. , Yang P. , et al. .
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Rare deleterious germline variants and risk of lung cancer.
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Gene-Based Association Testing of Dichotomous Traits With Generalized Functional Linear Mixed Models Using Extended Pedigrees: Applications to Age-Related Macular Degeneration.
Authors: Jiang Y. , Chiu C.Y. , Yan Q. , Chen W. , Gorin M.B. , Conley Y.P. , Lakhal-Chaieb M.L. , Cook R.J. , Amos C.I. , Wilson A.F. , et al. .
Source: Journal of the American Statistical Association, 2021; 116(534), p. 531-545.
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Whole Exome Sequencing of Highly Aggregated Lung Cancer Families Reveals Linked Loci for Increased Cancer Risk on Chromosomes 12q, 7p, and 4q.
Authors: Musolf A.M. , Moiz B.A. , Sun H. , Pikielny C.W. , Bossé Y. , Mandal D. , de Andrade M. , Gaba C. , Yang P. , Li Y. , et al. .
Source: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2020 Feb; 29(2), p. 434-442.
EPub date: 2019-12-11.
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