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Blechter B, Wong JYY, Chien LH, Shiraishi K, Shu XO, Cai Q, Zheng W, Ji BT, Hu W, Rahman ML, Jiang HF, Tsai FY, Huang WY, Gao YT, Han X, Steinwandel MD, Yang G, Daida YG, Liang SY, Gomez SL, DeRouen MC, Diver WR, Reddy AG, Patel AV, Le Marchand L, Haiman C, Kohno T, Cheng I, Chang IS, Hsiung CA, Rothman N, Lan Q. Age at lung cancer diagnosis in females versus males who never smoke by race and ethnicity. Br J Cancer 2024; 130:1286-1294. [PMID: 38388856 PMCID: PMC11014844 DOI: 10.1038/s41416-024-02592-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Revised: 01/17/2024] [Accepted: 01/19/2024] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND We characterized age at diagnosis and estimated sex differences for lung cancer and its histological subtypes among individuals who never smoke. METHODS We analyzed the distribution of age at lung cancer diagnosis in 33,793 individuals across 8 cohort studies and two national registries from East Asia, the United States (US) and the United Kingdom (UK). Student's t-tests were used to assess the study population differences (Δ years) in age at diagnosis comparing females and males who never smoke across subgroups defined by race/ethnicity, geographic location, and histological subtypes. RESULTS We found that among Chinese individuals diagnosed with lung cancer who never smoke, females were diagnosed with lung cancer younger than males in the Taiwan Cancer Registry (n = 29,832) (Δ years = -2.2 (95% confidence interval (CI):-2.5, -1.9), in Shanghai (n = 1049) (Δ years = -1.6 (95% CI:-2.9, -0.3), and in Sutter Health and Kaiser Permanente Hawai'i in the US (n = 82) (Δ years = -11.3 (95% CI: -17.7, -4.9). While there was a suggestion of similar patterns in African American and non-Hispanic White individuals. the estimated differences were not consistent across studies and were not statistically significant. CONCLUSIONS We found evidence of sex differences for age at lung cancer diagnosis among individuals who never smoke.
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Affiliation(s)
- Batel Blechter
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
| | - Jason Y Y Wong
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Li-Hsin Chien
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
- Department of Applied Mathematics, Chung-Yuan Christian University, Chung-Li, Taiwan
| | - Kouya Shiraishi
- Division of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan
- Department of Clinical Genomics, National Cancer Center Research Institute, Tokyo, Japan
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, TN, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, TN, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, TN, USA
| | - Bu-Tian Ji
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Wei Hu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Mohammad L Rahman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Hsin-Fang Jiang
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - Fang-Yu Tsai
- National Institute of Cancer Research, National Health Research Institutes, Zhunan, Taiwan
| | - Wen-Yi Huang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China
| | - Xijing Han
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Mark D Steinwandel
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Gong Yang
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, TN, USA
| | - Yihe G Daida
- Center for Integrated Health Care Research, Kaiser Permanente Hawai'i, Honolulu, HI, USA
| | - Su-Ying Liang
- Palo Alto Medical Foundation Research Institute, Sutter Health, Palo Alto, CA, USA
| | - Scarlett L Gomez
- Greater Bay Area Cancer Registry, University of California, San Francisco, CA, USA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA
| | - Mindy C DeRouen
- Greater Bay Area Cancer Registry, University of California, San Francisco, CA, USA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA
| | - W Ryan Diver
- Department of Population Science, American Cancer Society, Kennesaw, GA, USA
| | - Ananya G Reddy
- Department of Population Science, American Cancer Society, Kennesaw, GA, USA
| | - Alpa V Patel
- Department of Population Science, American Cancer Society, Kennesaw, GA, USA
| | | | - Christopher Haiman
- Greater Bay Area Cancer Registry, University of California, San Francisco, CA, USA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA
| | - Takashi Kohno
- Division of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan
| | - Iona Cheng
- Greater Bay Area Cancer Registry, University of California, San Francisco, CA, USA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA
| | - I-Shou Chang
- National Institute of Cancer Research, National Health Research Institutes, Zhunan, Taiwan
| | - Chao Agnes Hsiung
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
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Shi J, Wen W, Long J, Gamazon ER, Tao R, Cai Q. Genetic correlation and causal associations between psychiatric disorders and lung cancer risk. J Affect Disord 2024; 356:647-656. [PMID: 38657774 DOI: 10.1016/j.jad.2024.04.080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 04/04/2024] [Accepted: 04/21/2024] [Indexed: 04/26/2024]
Abstract
BACKGROUND Patients with certain psychiatric disorders have increased lung cancer incidence. However, establishing a causal relationship through traditional epidemiological methods poses challenges. METHODS Available summary statistics of genome-wide association studies of cigarette smoking, lung cancer, and eight psychiatric disorders, including attention deficit/hyperactivity disorder (ADHD), autism, depression, major depressive disorder, bipolar disorder, insomnia, neuroticism, and schizophrenia (range N: 46,350-1,331,010) were leveraged to estimate genetic correlations using Linkage Disequilibrium Score Regression and assess causal effect of each psychiatric disorder on lung cancer using two-sample Mendelian randomization (MR) models, comprising inverse-variance weighted (IVW), weighted median, MR-Egger, pleiotropy residual sum and outlier testing (MR-PRESSO), and a constrained maximum likelihood approach (cML-MR). RESULTS Significant positive correlations were observed between each psychiatric disorder and both smoking and lung cancer (all FDR < 0.05), except for the correlation between autism and lung cancer. Both univariable and the cML-MA MR analyses demonstrated that liability to schizophrenia, depression, ADHD, or insomnia was associated with an increased risk of overall lung cancer. Genetic liability to insomnia was linked specifically to squamous cell carcinoma (SCC), while genetic liability to ADHD was associated with an elevated risk of both SCC and small cell lung cancer (all P < 0.05). The later was further supported by multivariable MR analyses, which accounted for smoking. LIMITATIONS Participants were constrained to European ancestry populations. Causal estimates from binary psychiatric disorders may be biased. CONCLUSION Our findings suggest appropriate management of several psychiatric disorders, particularly ADHD, may potentially reduce the risk of developing lung cancer.
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Affiliation(s)
- Jiajun Shi
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Eric R Gamazon
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37203, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37203, USA; Data Science Institute, Vanderbilt University Medical Center, Nashville, TN 37203, USA; Clare Hall, University of Cambridge, Cambridge CB3 9AL, UK; MRC Epidemiology Unit, University of Cambridge, Cambridge CB2 0SL, UK
| | - Ran Tao
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37203, USA; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN 37203, USA.
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Zhang L, Xiong Y, Zhang J, Feng Y, Xu A. Systematic proteome-wide Mendelian randomization using the human plasma proteome to identify therapeutic targets for lung adenocarcinoma. J Transl Med 2024; 22:330. [PMID: 38576019 PMCID: PMC10993587 DOI: 10.1186/s12967-024-04919-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 01/21/2024] [Indexed: 04/06/2024] Open
Abstract
BACKGROUND Lung adenocarcinoma (LUAD) is the predominant histological subtype of lung cancer and the leading cause of cancer-related mortality. Identifying effective drug targets is crucial for advancing LUAD treatment strategies. METHODS This study employed proteome-wide Mendelian randomization (MR) and colocalization analyses. We collected data on 1394 plasma proteins from a protein quantitative trait loci (pQTL) study involving 4907 individuals. Genetic associations with LUAD were derived from the Transdisciplinary Research in Cancer of the Lung (TRICL) study, including 11,245 cases and 54,619 controls. We integrated pQTL and LUAD genome-wide association studies (GWASs) data to identify candidate proteins. MR utilizes single nucleotide polymorphisms (SNPs) as genetic instruments to estimate the causal effect of exposure on outcome, while Bayesian colocalization analysis determines the probability of shared causal genetic variants between traits. Our study applied these methods to assess causality between plasma proteins and LUAD. Furthermore, we employed a two-step MR to quantify the proportion of risk factors mediated by proteins on LUAD. Finally, protein-protein interaction (PPI) analysis elucidated potential links between proteins and current LUAD medications. RESULTS We identified nine plasma proteins significantly associated with LUAD. Increased levels of ALAD, FLT1, ICAM5, and VWC2 exhibited protective effects, with odds ratios of 0.79 (95% CI 0.72-0.87), 0.39 (95% CI 0.28-0.55), 0.91 (95% CI 0.72-0.87), and 0.85 (95% CI 0.79-0.92), respectively. Conversely, MDGA2 (OR, 1.13; 95% CI 1.08-1.19), NTM (OR, 1.12; 95% CI 1.09-1.16), PMM2 (OR, 1.35; 95% CI 1.18-1.53), RNASET2 (OR, 1.15; 95% CI 1.08-1.21), and TFPI (OR, 4.58; 95% CI 3.02-6.94) increased LUAD risk. Notably, none of the nine proteins showed evidence of reverse causality. Bayesian colocalization indicated that RNASET2, TFPI, and VWC2 shared the same variant with LUAD. Furthermore, NTM and FLT1 demonstrated interactions with targets of current LUAD medications. Additionally, FLT1 and TFPI are currently under evaluation as therapeutic targets, while NTM, RNASET2, and VWC2 are potentially druggable. These findings shed light on LUAD pathogenesis, highlighting the tumor-promoting effects of RNASET2, TFPI, and NTM, along with the protective effects of VWC2 and FLT1, providing a significant biological foundation for future LUAD therapeutic targets. CONCLUSIONS Our proteome-wide MR analysis highlighted RNASET2, TFPI, VWC2, NTM, and FLT1 as potential drug targets for further clinical investigation in LUAD. However, the specific mechanisms by which these proteins influence LUAD remain elusive. Targeting these proteins in drug development holds the potential for successful clinical trials, providing a pathway to prioritize and reduce costs in LUAD therapeutics.
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Affiliation(s)
- Long Zhang
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yajun Xiong
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Jie Zhang
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yuying Feng
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Aiguo Xu
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
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Chen T, Pham G, Fox L, Zhang J, Byun J, Han Y, Saunders GRB, Liu D, Bray MJ, Ramsey AT, McKay J, Bierut L, Amos CI, Hung RJ, Lin X, Zhang H, Chen LS. Genomic Insights for Personalized Care: Motivating At-Risk Individuals Toward Evidence-Based Health Practices. medRxiv 2024:2024.03.19.24304556. [PMID: 38562690 PMCID: PMC10984046 DOI: 10.1101/2024.03.19.24304556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Lung cancer and tobacco use pose significant global health challenges and require a comprehensive translational roadmap for improved prevention strategies. We propose the GREAT care paradigm ( G enomic Informed Care for Motivating High R isk Individuals E ligible for Evidence-b a sed Prevention), which employs polygenic risk scores (PRSs) to stratify disease risk and personalize interventions, such as lung cancer screening and tobacco treatment. We developed PRSs using large-scale multi-ancestry genome-wide association studies and adjusted for genetic ancestry for standardized risk stratification across diverse populations. We applied our PRSs to over 340,000 individuals of diverse ethnic background and found significant odds ratios for lung cancer and difficulty quitting smoking. These findings enable the evaluation of PRS-based interventions in ongoing trials aimed at motivating health behavior changes in high-risk patients. This pioneering approach enhances primary care with genomic insights, promising improved outcomes in cancer prevention and tobacco treatment, and is currently under assessment in clinical trials.
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Chen Y, Xie Y, Ci H, Cheng Z, Kuang Y, Li S, Wang G, Qi Y, Tang J, Liu D, Li W, Yang Y. Plasma metabolites and risk of seven cancers: a two-sample Mendelian randomization study among European descendants. BMC Med 2024; 22:90. [PMID: 38433226 PMCID: PMC10910673 DOI: 10.1186/s12916-024-03272-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 01/22/2024] [Indexed: 03/05/2024] Open
Abstract
BACKGROUND While circulating metabolites have been increasingly linked to cancer risk, the causality underlying these associations remains largely uninterrogated. METHODS We conducted a comprehensive 2-sample Mendelian randomization (MR) study to evaluate the potential causal relationship between 913 plasma metabolites and the risk of seven cancers among European-ancestry individuals. Data on variant-metabolite associations were obtained from a genome-wide association study (GWAS) of plasma metabolites among 14,296 subjects. Data on variant-cancer associations were gathered from large-scale GWAS consortia for breast (N = 266,081), colorectal (N = 185,616), lung (N = 85,716), ovarian (N = 63,347), prostate (N = 140,306), renal cell (N = 31,190), and testicular germ cell (N = 28,135) cancers. MR analyses were performed with the inverse variance-weighted (IVW) method as the primary strategy to identify significant associations at Bonferroni-corrected P < 0.05 for each cancer type separately. Significant associations were subjected to additional scrutiny via weighted median MR, Egger regression, MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and reverse MR analyses. Replication analyses were performed using an independent dataset from a plasma metabolite GWAS including 8,129 participants of European ancestry. RESULTS We identified 94 significant associations, suggesting putative causal associations between 66 distinct plasma metabolites and the risk of seven cancers. Remarkably, 68.2% (45) of these metabolites were each associated with the risk of a specific cancer. Among the 66 metabolites, O-methylcatechol sulfate and 4-vinylphenol sulfate demonstrated the most pronounced positive and negative associations with cancer risk, respectively. Genetically proxied plasma levels of these two metabolites were significantly associated with the risk of lung cancer and renal cell cancer, with an odds ratio and 95% confidence interval of 2.81 (2.33-3.37) and 0.49 (0.40-0.61), respectively. None of these 94 associations was biased by weak instruments, horizontal pleiotropy, or reverse causation. Further, 64 of these 94 were eligible for replication analyses, and 54 (84.4%) showed P < 0.05 with association patterns consistent with those shown in primary analyses. CONCLUSIONS Our study unveils plausible causal relationships between 66 plasma metabolites and cancer risk, expanding our understanding of the role of circulating metabolites in cancer genetics and etiology. These findings hold promise for enhancing cancer risk assessment and prevention strategies, meriting further exploration.
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Affiliation(s)
- Yaxin Chen
- Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yufang Xie
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Hang Ci
- Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China
| | - Zhengpei Cheng
- Center for Public Health Genomics, Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, 560 Ray C. Hunt Dr., Rm 4408, Charlottesville, VA, USA
| | - Yongjie Kuang
- Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Shuqing Li
- Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China
| | - Gang Wang
- Innovation Laboratory for Precision Diagnostics, Precision Medicine Research Center, Precision Medicine Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yawen Qi
- Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China
| | - Jun Tang
- Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China
| | - Dan Liu
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Weimin Li
- Institute of Respiratory Health, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Guoxue Alley 37, Chengdu, Sichuan, China.
- Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Yaohua Yang
- Center for Public Health Genomics, Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, 560 Ray C. Hunt Dr., Rm 4408, Charlottesville, VA, USA.
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6
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Li Y, Xiao X, Li J, Han Y, Cheng C, Fernandes GF, Slewitzke SE, Rosenberg SM, Zhu M, Byun J, Bossé Y, McKay JD, Albanes D, Lam S, Tardon A, Chen C, Bojesen SE, Landi MT, Johansson M, Risch A, Bickeböller H, Wichmann HE, Christiani DC, Rennert G, Arnold SM, Goodman GE, Field JK, Davies MP, Shete S, Marchand LL, Liu G, Hung RJ, Andrew AS, Kiemeney LA, Sun R, Zienolddiny S, Grankvist K, Johansson M, Caporaso NE, Cox A, Hong YC, Lazarus P, Schabath MB, Aldrich MC, Schwartz AG, Gorlov I, Purrington KS, Yang P, Liu Y, Bailey-Wilson JE, Pinney SM, Mandal D, Willey JC, Gaba C, Brennan P, Xia J, Shen H, Amos CI. Lung Cancer in Ever- and Never-Smokers: Findings from Multi-Population GWAS Studies. Cancer Epidemiol Biomarkers Prev 2024; 33:389-399. [PMID: 38180474 PMCID: PMC10905670 DOI: 10.1158/1055-9965.epi-23-0613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 08/03/2023] [Accepted: 01/03/2024] [Indexed: 01/06/2024] Open
Abstract
BACKGROUND Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer. METHODS We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer. RESULTS Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P < 5 × 10-8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear > 20). Different risk patterns were observed for the variants among the different groups by smoking behavior. CONCLUSIONS We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies. IMPACT Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly cancer.
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Affiliation(s)
- Yafang Li
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Xiangjun Xiao
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas
| | - Jianrong Li
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas
| | - Younghun Han
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Chao Cheng
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Gail F. Fernandes
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas
| | - Shannon E. Slewitzke
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas
| | - Susan M. Rosenberg
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas
| | - Meng Zhu
- Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, P.R. China
| | - Jinyoung Byun
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Yohan Bossé
- Institut universitaire de cardiologie et de pneumologie de Québec, Department of Molecular Medicine, Laval University, Quebec City, Canada
| | - James D. McKay
- Section of Genetics, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Demetrios Albanes
- Division of Cancer Epidemiology and Genetics, NCI, NIH, Bethesda, Maryland
| | - Stephen Lam
- Department of Integrative Oncology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Adonina Tardon
- Public Health Department, University of Oviedo, ISPA and CIBERESP, Asturias, Spain
| | - Chu Chen
- Program in Epidemiology, Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Stig E. Bojesen
- Department of Clinical Biochemistry, Copenhagen University Hospital, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Maria T. Landi
- Division of Cancer Epidemiology and Genetics, NCI, NIH, Bethesda, Maryland
| | - Mattias Johansson
- Section of Genetics, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Angela Risch
- Thoraxklinik at University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC-H), Heidelberg, Germany
- University of Salzburg and Cancer Cluster Salzburg, Salzburg, Austria
| | - Heike Bickeböller
- Department of Genetic Epidemiology, University Medical Center, Georg-August-University Göttingen, Göttingen, Germany
| | | | - David C. Christiani
- Departments of Environmental Health and Epidemiology, Harvard TH Chan School of Public Health, Boston, Massachusetts
| | - Gad Rennert
- Clalit National Cancer Control Center at Carmel Medical Center and Technion Faculty of Medicine, Haifa, Israel
| | | | | | - John K. Field
- Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom
| | - Michael P.A. Davies
- Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom
| | - Sanjay Shete
- Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, Texas
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Geoffrey Liu
- University Health Network- The Princess Margaret Cancer Centre, Toronto, California
| | - Rayjean J. Hung
- Luenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Canada
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Canada
| | - Angeline S. Andrew
- Departments of Epidemiology and Community and Family Medicine, Dartmouth College, Hanover, New Hampshire
| | | | - Ryan Sun
- Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | | | - Kjell Grankvist
- Department of Medical Biosciences, Umeå University, Umeå, Sweden
| | | | - Neil E. Caporaso
- Division of Cancer Epidemiology and Genetics, NCI, NIH, Bethesda, Maryland
| | - Angela Cox
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, United Kingdom
| | - Yun-Chul Hong
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of South Korea
| | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington
| | - Matthew B. Schabath
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Melinda C. Aldrich
- Department of Thoracic Surgery, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Ann G. Schwartz
- Department of Oncology, Wayne State University School of Medicine, Detroit, Michigan
- Karmanos Cancer Institute, Detroit, Michigan
| | - Ivan Gorlov
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Kristen S. Purrington
- Department of Oncology, Wayne State University School of Medicine, Detroit, Michigan
- Karmanos Cancer Institute, Detroit, Michigan
| | - Ping Yang
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Yanhong Liu
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | | | - Susan M. Pinney
- University of Cincinnati College of Medicine, Cincinnati, Ohio
| | - Diptasri Mandal
- Louisiana State University Health Sciences Center, New Orleans, Louisiana
| | - James C. Willey
- College of Medicine and Life Sciences, University of Toledo, Toledo, Ohio
| | - Colette Gaba
- The University of Toledo College of Medicine, Toledo, Ohio
| | - Paul Brennan
- Institut universitaire de cardiologie et de pneumologie de Québec, Department of Molecular Medicine, Laval University, Quebec City, Canada
| | - Jun Xia
- Creighton University School of Medicine, Omaha, Nebraska
| | - Hongbing Shen
- Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, P.R. China
| | - Christopher I. Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
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7
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Hua T, Zhang C, Fu Y, Qin N, Liu S, Chen C, Gong L, Ma H, Ding Y, Wei X, Jin C, Jin C, Zhu M, Zhang E, Dai J, Ma H. Integrative analyses of N6-methyladenosine-associated single-nucleotide polymorphisms (m6A-SNPs) identify tumor suppressor gene AK9 in lung cancer. Mol Carcinog 2024; 63:538-548. [PMID: 38051288 DOI: 10.1002/mc.23669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 11/21/2023] [Accepted: 11/25/2023] [Indexed: 12/07/2023]
Abstract
N6 -methyladenosine (m6 A) modification has been identified as one of the most important epigenetic regulation mechanisms in the development of human cancers. However, the association between m6 A-associated single-nucleotide polymorphisms (m6 A-SNPs) and lung cancer risk remains largely unknown. Here, we identified m6 A-SNPs and examined the association of these m6 A-SNPs with lung cancer risk in 13,793 lung cancer cases and 14,027 controls. In silico functional annotation was used to identify causal m6 A-SNPs and target genes. Furthermore, methylated RNA immunoprecipitation and quantitative real-time polymerase chain reaction (MeRIP-qPCR) assay was performed to assess the m6 A modification level of different genotypes of the causal SNP. In vitro assays were performed to validate the potential role of the target gene in lung cancer. A total of 8794 m6 A-SNPs were detected, among which 397 SNPs in nine susceptibility loci were associated with lung cancer risk, including six novel loci. Bioinformatics analyses indicated that rs1321328 in 6q21 was located around the m6 A modification site of AK9 and significantly reduced AK9 expression (β = -0.15, p = 2.78 × 10-8 ). Moreover, AK9 was significantly downregulated in lung cancer tissues than that in adjacent normal tissues of samples from the Cancer Genome Atlas and Nanjing Lung Cancer Cohort. MeRIP-qPCR assay suggested that C allele of rs1321328 could significantly decrease the m6 A modification level of AK9 compared with G allele. In vitro assays verified the tumor-suppressing role of AK9 in lung cancer. These findings shed light on the pathogenic mechanism of lung cancer susceptibility loci linked with m6 A modification.
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Affiliation(s)
- Tingting Hua
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Chang Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou Second People's Hospital, Changzhou Medical Center, Nanjing Medical University, Nanjing, China
| | - Yating Fu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Na Qin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Su Liu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Congcong Chen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Linnan Gong
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Huimin Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yue Ding
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xiaoxia Wei
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Chenying Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Chen Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Erbao Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
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8
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Li H, Du S, Dai J, Jiang Y, Li Z, Fan Q, Zhang Y, You D, Zhang R, Zhao Y, Christiani DC, Shen S, Chen F. Proteome-wide Mendelian randomization identifies causal plasma proteins in lung cancer. iScience 2024; 27:108985. [PMID: 38333712 PMCID: PMC10850776 DOI: 10.1016/j.isci.2024.108985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 11/17/2023] [Accepted: 01/17/2024] [Indexed: 02/10/2024] Open
Abstract
Plasma proteins are promising biomarkers and potential drug targets in lung cancer. To evaluate the causal association between plasma proteins and lung cancer, we performed proteome-wide Mendelian randomization meta-analysis (PW-MR-meta) based on lung cancer genome-wide association studies (GWASs), protein quantitative trait loci (pQTLs) of 4,719 plasma proteins in deCODE and 4,775 in Fenland. Further, causal-protein risk score (CPRS) was developed based on causal proteins and validated in the UK Biobank. 270 plasma proteins were identified using PW-MR meta-analysis, including 39 robust causal proteins (both FDR-q < 0.05) and 78 moderate causal proteins (FDR-q < 0.05 in one and p < 0.05 in another). The CPRS had satisfactory performance in risk stratification for lung cancer (top 10% CPRS:Hazard ratio (HR) (95%CI):4.33(2.65-7.06)). The CPRS [AUC (95%CI): 65.93 (62.91-68.78)] outperformed the traditional polygenic risk score (PRS) [AUC (95%CI): 55.71(52.67-58.59)]. Our findings offer further insight into the genetic architecture of plasma proteins for lung cancer susceptibility.
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Affiliation(s)
- Hongru Li
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Sha Du
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Jinglan Dai
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yunke Jiang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Zaiming Li
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Qihan Fan
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yixin Zhang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Dongfang You
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- China International Cooperation Center of Environment and Human Health, Nanjing Medical University, Nanjing 211166, China
| | - Ruyang Zhang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Key Laboratory of Biomedical Big Data of Nanjing Medical University, Nanjing 211166, China
| | - Yang Zhao
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Key Laboratory of Biomedical Big Data of Nanjing Medical University, Nanjing 211166, China
| | - David C. Christiani
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
- Pulmonary and Critical Care Division, Massachusetts General Hospital, Department of Medicine, Harvard Medical School, Boston, MA 02114, USA
| | - Sipeng Shen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
- Key Laboratory of Biomedical Big Data of Nanjing Medical University, Nanjing 211166, China
| | - Feng Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
- China International Cooperation Center of Environment and Human Health, Nanjing Medical University, Nanjing 211166, China
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9
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Wang X, Zhang Z, Ding Y, Chen T, Mucci L, Albanes D, Landi MT, Caporaso NE, Lam S, Tardon A, Chen C, Bojesen SE, Johansson M, Risch A, Bickeböller H, Wichmann HE, Rennert G, Arnold S, Brennan P, McKay JD, Field JK, Shete SS, Le Marchand L, Liu G, Andrew AS, Kiemeney LA, Zienolddiny-Narui S, Behndig A, Johansson M, Cox A, Lazarus P, Schabath MB, Aldrich MC, Hung RJ, Amos CI, Lin X, Christiani DC. Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification. Genome Med 2024; 16:22. [PMID: 38317189 PMCID: PMC10840262 DOI: 10.1186/s13073-024-01298-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 01/26/2024] [Indexed: 02/07/2024] Open
Abstract
BACKGROUND Although polygenic risk score (PRS) has emerged as a promising tool for predicting cancer risk from genome-wide association studies (GWAS), the individual-level accuracy of lung cancer PRS and the extent to which its impact on subsequent clinical applications remains largely unexplored. METHODS Lung cancer PRSs and confidence/credible interval (CI) were constructed using two statistical approaches for each individual: (1) the weighted sum of 16 GWAS-derived significant SNP loci and the CI through the bootstrapping method (PRS-16-CV) and (2) LDpred2 and the CI through posteriors sampling (PRS-Bayes), among 17,166 lung cancer cases and 12,894 controls with European ancestry from the International Lung Cancer Consortium. Individuals were classified into different genetic risk subgroups based on the relationship between their own PRS mean/PRS CI and the population level threshold. RESULTS Considerable variances in PRS point estimates at the individual level were observed for both methods, with an average standard deviation (s.d.) of 0.12 for PRS-16-CV and a much larger s.d. of 0.88 for PRS-Bayes. Using PRS-16-CV, only 25.0% of individuals with PRS point estimates in the lowest decile of PRS and 16.8% in the highest decile have their entire 95% CI fully contained in the lowest and highest decile, respectively, while PRS-Bayes was unable to find any eligible individuals. Only 19% of the individuals were concordantly identified as having high genetic risk (> 90th percentile) using the two PRS estimators. An increased relative risk of lung cancer comparing the highest PRS percentile to the lowest was observed when taking the CI into account (OR = 2.73, 95% CI: 2.12-3.50, P-value = 4.13 × 10-15) compared to using PRS-16-CV mean (OR = 2.23, 95% CI: 1.99-2.49, P-value = 5.70 × 10-46). Improved risk prediction performance with higher AUC was consistently observed in individuals identified by PRS-16-CV CI, and the best performance was achieved by incorporating age, gender, and detailed smoking pack-years (AUC: 0.73, 95% CI = 0.72-0.74). CONCLUSIONS Lung cancer PRS estimates using different methods have modest correlations at the individual level, highlighting the importance of considering individual-level uncertainty when evaluating the practical utility of PRS.
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Affiliation(s)
- Xinan Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, 667 Huntington Ave, Boston, MA, 02115, USA
| | - Ziwei Zhang
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Yi Ding
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, USA
| | - Tony Chen
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Lorelei Mucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Demetrios Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Neil E Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Stephen Lam
- Department of Medicine, British Columbia Cancer Agency, University of British Columbia, Vancouver, Canada
| | - Adonina Tardon
- Faculty of Medicine, University of Oviedo and CIBERESP, Oviedo, Spain
| | - Chu Chen
- Department of Epidemiology, University of Washington School of Public Health, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Stig E Bojesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Denmark
| | - Mattias Johansson
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France
| | - Angela Risch
- Department of Biosciences and Medical Biology, Allergy-Cancer-BioNano Research Centre, University of Salzburg, and Cancer Cluster Salzburg, Salzburg, Austria
| | - Heike Bickeböller
- Department of Genetic Epidemiology, University Medical Center, Georg August University Göttingen, Göttingen, Germany
| | - H-Erich Wichmann
- Institute of Medical Informatics, Biometry and Epidemiology, Ludwig Maximilians University, Munich, Germany
| | - Gadi Rennert
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Carmel, Haifa, Israel
| | - Susanne Arnold
- Markey Cancer Center, University of Kentucky, Lexington, KY, USA
| | - Paul Brennan
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France
| | - James D McKay
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France
| | - John K Field
- Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Sanjay S Shete
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Geoffrey Liu
- Princess Margaret Cancer Centre, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Angeline S Andrew
- Department of Epidemiology, Department of Community and Family Medicine, Dartmouth Geisel School of Medicine, Hanover, NH, USA
| | - Lambertus A Kiemeney
- Department for Health Evidence, Department of Urology, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Annelie Behndig
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | | | - Angie Cox
- Department of Oncology and Metabolism, The Medical School, University of Sheffield, Sheffield, UK
| | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy, Washington State University, Spokane, WA, USA
| | - Matthew B Schabath
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida, USA
| | - Melinda C Aldrich
- Department of Medicine, Department of Biomedical Informatics and Department of Thoracic Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Rayjean J Hung
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Christopher I Amos
- Institute for Clinical and Translational Research, Department of Medicine, Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - David C Christiani
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, 667 Huntington Ave, Boston, MA, 02115, USA.
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
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10
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Shiraishi K, Takahashi A, Momozawa Y, Daigo Y, Kaneko S, Kawaguchi T, Kunitoh H, Matsumoto S, Horinouchi H, Goto A, Honda T, Shimizu K, Torasawa M, Takayanagi D, Saito M, Saito A, Ohe Y, Watanabe S, Goto K, Tsuboi M, Tsuchihara K, Takata S, Aoi T, Takano A, Kobayashi M, Miyagi Y, Tanaka K, Suzuki H, Maeda D, Yamaura T, Matsuda M, Shimada Y, Mizuno T, Sakamoto H, Yoshida T, Goto Y, Yoshida T, Yamaji T, Sonobe M, Toyooka S, Yoneda K, Masago K, Tanaka F, Hara M, Fuse N, Nishizuka SS, Motoi N, Sawada N, Nishida Y, Kumada K, Takeuchi K, Tanno K, Yatabe Y, Sunami K, Hishida T, Miyazaki Y, Ito H, Amemiya M, Totsuka H, Nakayama H, Yokose T, Ishigaki K, Nagashima T, Ohtaki Y, Imai K, Takasawa K, Minamiya Y, Kobayashi K, Okubo K, Wakai K, Shimizu A, Yamamoto M, Iwasaki M, Matsuda K, Inazawa J, Shiraishi Y, Nishikawa H, Murakami Y, Kubo M, Matsuda F, Kamatani Y, Hamamoto R, Matsuo K, Kohno T. Identification of telomere maintenance gene variations related to lung adenocarcinoma risk by genome-wide association and whole genome sequencing analyses. Cancer Commun (Lond) 2024; 44:287-293. [PMID: 37882647 PMCID: PMC10876189 DOI: 10.1002/cac2.12498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 10/06/2023] [Accepted: 10/15/2023] [Indexed: 10/27/2023] Open
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Abstract
The field of oncology has witnessed an extraordinary surge in the application of big data and artificial intelligence (AI). AI development has made multiscale and multimodal data fusion and analysis possible. A new era of extracting information from complex big data is rapidly evolving. However, challenges related to efficient data curation, in-depth analysis, and utilization remain. We provide a comprehensive overview of the current state of the art in big data and computational analysis, highlighting key applications, challenges, and future opportunities in cancer research. By sketching the current landscape, we seek to foster a deeper understanding and facilitate the advancement of big data utilization in oncology, call for interdisciplinary collaborations, ultimately contributing to improved patient outcomes and a profound understanding of cancer.
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Affiliation(s)
- Xifeng Wu
- Department of Big Data in Health Science, School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; National Institute for Data Science in Health and Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Wenyuan Li
- Department of Big Data in Health Science, School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Huakang Tu
- Department of Big Data in Health Science, School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; Cancer Center, Zhejiang University, Hangzhou, Zhejiang, China
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12
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Mao F, Cheung LC, Cook RJ. Two-phase designs with failure time processes subject to nonsusceptibility. Biometrics 2024; 80:ujad038. [PMID: 38446442 DOI: 10.1093/biomtc/ujad038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 12/05/2023] [Accepted: 12/21/2023] [Indexed: 03/07/2024]
Abstract
Epidemiological studies based on 2-phase designs help ensure efficient use of limited resources in situations where certain covariates are prohibitively expensive to measure for a full cohort. Typically, these designs involve 2 steps: In phase I, data on an outcome and inexpensive covariates are acquired, and in phase II, a subsample is chosen in which the costly variable of interest is measured. For right-censored data, 2-phase designs have been primarily based on the Cox model. We develop efficient 2-phase design strategies for settings involving a fraction of long-term survivors due to nonsusceptibility. Using mixture models accommodating a nonsusceptible fraction, we consider 3 regression frameworks, including (a) a logistic "cure" model, (b) a proportional hazards model for those who are susceptible, and (c) regression models for susceptibility and failure time in those susceptible. Importantly, we introduce a novel class of bivariate residual-dependent designs to address the unique challenges presented in scenario (c), which involves 2 parameters of interest. Extensive simulation studies demonstrate the superiority of our approach over various phase II subsampling schemes. We illustrate the method through applications to the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial.
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Affiliation(s)
- Fangya Mao
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Rockville, MD 20852, United States
| | - Li C Cheung
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Rockville, MD 20852, United States
| | - Richard J Cook
- Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada
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13
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Enjo-Barreiro JR, Ruano-Ravina A, Pérez-Ríos M, Kelsey K, Barros-Dios JM, Varela-Lema L. Genome Wide Association Studies in Small-Cell Lung Cancer. A Systematic Review. Clin Lung Cancer 2024; 25:9-17. [PMID: 37940411 DOI: 10.1016/j.cllc.2023.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 08/28/2023] [Accepted: 10/09/2023] [Indexed: 11/10/2023]
Abstract
Small cell lung cancer (SCLC) is one of the deadliest forms of lung cancer, but few information exists regarding the role of genetics, particularly on Genome Wide Association Studies (GWAS). The aim of the study is to explore the evidence available obtained through GWAS studies for SCLC using a systematic review. We performed a literature search in the main databases until July 31st, 2023. We included all human based studies on GWAS for lung cancer which presented results for SCLC. Only studies with participants diagnosed of SCLC with anatomopathological confirmation were included. Fourteen studies were identified; 8 studies showed a relationship between ASCL1 overexpression and SCLC, which may regulate CHRNA5/A3/B4 cluster, producing a consequent nAChR overexpression. Nine papers, including 8 of the previous, found a positive association between SNPs located in chromosome 15 and SCLC. The most important cluster of genes found is CHRNA5/A3/B4 but the mechanism for the role of these genes is unclear. Kyoto Encyclopaedia of Genes and Genome (KEGG) shows that these receptors were found to be overexpressed where nicotine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and N'-Nitrosonornicotine (NNN) acts, involving different routes in SCLC carcinogenesis.
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Affiliation(s)
- José Ramón Enjo-Barreiro
- Department of Preventive Medicine, University of Santiago de Compostela, Santiago de Compostela, Spain; Service of Preventive Medicine, A Coruña University Teaching Hospital Complex, A Coruña, Spain
| | - Alberto Ruano-Ravina
- Department of Preventive Medicine, University of Santiago de Compostela, Santiago de Compostela, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Santiago de Compostela, Spain; Health Research Institute of Santiago de Compostela (Instituto de Investigación Sanitaria de Santiago de Compostela - IDIS), Santiago de Compostela, Spain.
| | - Mónica Pérez-Ríos
- Department of Preventive Medicine, University of Santiago de Compostela, Santiago de Compostela, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Santiago de Compostela, Spain; Health Research Institute of Santiago de Compostela (Instituto de Investigación Sanitaria de Santiago de Compostela - IDIS), Santiago de Compostela, Spain
| | - Karl Kelsey
- Department of Epidemiology, Brown School of Public Health, Brown University, Providence, RI
| | - Juan Miguel Barros-Dios
- Department of Preventive Medicine, University of Santiago de Compostela, Santiago de Compostela, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Santiago de Compostela, Spain; Health Research Institute of Santiago de Compostela (Instituto de Investigación Sanitaria de Santiago de Compostela - IDIS), Santiago de Compostela, Spain
| | - Leonor Varela-Lema
- Department of Preventive Medicine, University of Santiago de Compostela, Santiago de Compostela, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Santiago de Compostela, Spain; Health Research Institute of Santiago de Compostela (Instituto de Investigación Sanitaria de Santiago de Compostela - IDIS), Santiago de Compostela, Spain
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Long E, Zhang J. Evidence for the role of selection for reproductively advantageous alleles in human aging. Sci Adv 2023; 9:eadh4990. [PMID: 38064565 PMCID: PMC10708185 DOI: 10.1126/sciadv.adh4990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 11/07/2023] [Indexed: 12/18/2023]
Abstract
The antagonistic pleiotropy hypothesis posits that natural selection for pleiotropic mutations that confer earlier or more reproduction but impair the post-reproductive life causes aging. This hypothesis of the evolutionary origin of aging is supported by case studies but lacks unambiguous genomic evidence. Here, we genomically test this hypothesis using the genotypes, reproductive phenotypes, and death registry of 276,406 U.K. Biobank participants. We observe a strong, negative genetic correlation between reproductive traits and life span. Individuals with higher polygenetic scores for reproduction (PGSR) have lower survivorships to age 76 (SV76), and PGSR increased over birth cohorts from 1940 to 1969. Similar trends are seen from individual genetic variants examined. The antagonistically pleiotropic variants are often associated with cis-regulatory effects across multiple tissues or on multiple target genes. These and other findings support the antagonistic pleiotropy hypothesis of aging in humans and point to potential molecular mechanisms of the reproduction-life-span antagonistic pleiotropy.
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Affiliation(s)
- Erping Long
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jianzhi Zhang
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA
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15
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Astore C, Sharma S, Nagpal S, Cutler DJ, Rioux JD, Cho JH, McGovern DPB, Brant SR, Kugathasan S, Jordan IK, Gibson G. The role of admixture in the rare variant contribution to inflammatory bowel disease. Genome Med 2023; 15:97. [PMID: 37968638 PMCID: PMC10647102 DOI: 10.1186/s13073-023-01244-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 10/10/2023] [Indexed: 11/17/2023] Open
Abstract
BACKGROUND Identification of rare variants involved in complex, polygenic diseases like Crohn's disease (CD) has accelerated with the introduction of whole exome/genome sequencing association studies. Rare variants can be used in both diagnostic and therapeutic assessments; however, since they are likely to be restricted to specific ancestry groups, their contributions to risk assessment need to be evaluated outside the discovery population. Prior studies implied that the three known rare variants in NOD2 are absent in West African and Asian populations and only contribute in African Americans via admixture. METHODS Whole genome sequencing (WGS) data from 3418 African American individuals, 1774 inflammatory bowel disease (IBD) cases, and 1644 controls were used to assess odds ratios and allele frequencies (AF), as well as haplotype-specific ancestral origins of European-derived CD variants discovered in a large exome-wide association study. Local and global ancestry was performed to assess the contribution of admixture to IBD contrasting European and African American cohorts. RESULTS Twenty-five rare variants associated with CD in European discovery cohorts are typically five-fold lower frequency in African Americans. Correspondingly, where comparisons could be made, the rare variants were found to have a predicted four-fold reduced burden for IBD in African Americans, when compared to European individuals. Almost all of the rare CD European variants were found on European haplotypes in the African American cohort, implying that they contribute to disease risk in African Americans primarily due to recent admixture. In addition, proportion of European ancestry correlates the number of rare CD European variants each African American individual carry, as well as their polygenic risk of disease. Similar findings were observed for 23 mutations affecting 10 other common complex diseases for which the rare variants were discovered in European cohorts. CONCLUSIONS European-derived Crohn's disease rare variants are even more rare in African Americans and contribute to disease risk mainly due to admixture, which needs to be accounted for when performing cross-ancestry genetic assessments.
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Affiliation(s)
- Courtney Astore
- Center for Integrative Genomics and School of Biological Sciences, Georgia Institute of Technology, Krone EBB1 Building, 950 Atlantic Drive, Atlanta, GA, 30332, USA
| | - Shivam Sharma
- Center for Integrative Genomics and School of Biological Sciences, Georgia Institute of Technology, Krone EBB1 Building, 950 Atlantic Drive, Atlanta, GA, 30332, USA
| | - Sini Nagpal
- Center for Integrative Genomics and School of Biological Sciences, Georgia Institute of Technology, Krone EBB1 Building, 950 Atlantic Drive, Atlanta, GA, 30332, USA
| | - David J Cutler
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - John D Rioux
- Department of Medicine, Université de Montréal and the Montreal Heart Institute Research Center, Montreal, QC, H1Y3N1, Canada
| | - Judy H Cho
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Dermot P B McGovern
- Department of Medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, 08901, USA
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ, 08554, USA
- Meyerhoff Inflammatory Bowel Disease Center, Johns Hopkins University School of Medicine, Baltimore, 21287, USA
| | - Steven R Brant
- Immunology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA
| | - Subra Kugathasan
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA
- Department of Pediatrics, Emory University School of Medicine, and Children's Healthcare of Atlanta, Atlanta, GA, 30322, USA
| | - I King Jordan
- Center for Integrative Genomics and School of Biological Sciences, Georgia Institute of Technology, Krone EBB1 Building, 950 Atlantic Drive, Atlanta, GA, 30332, USA
| | - Greg Gibson
- Center for Integrative Genomics and School of Biological Sciences, Georgia Institute of Technology, Krone EBB1 Building, 950 Atlantic Drive, Atlanta, GA, 30332, USA.
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16
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Guo X, Ping J, Yang Y, Su X, Shu XO, Wen W, Chen Z, Zhang Y, Tao R, Jia G, He J, Cai Q, Zhang Q, Giles GG, Pearlman R, Rennert G, Vodicka P, Phipps A, Gruber SB, Casey G, Peters U, Long J, Lin W, Zheng W. Large-scale alternative polyadenylation (APA)-wide association studies to identify putative susceptibility genes in human common cancers. medRxiv 2023:2023.11.05.23298125. [PMID: 37986797 PMCID: PMC10659493 DOI: 10.1101/2023.11.05.23298125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Alternative polyadenylation (APA) modulates mRNA processing in the 3' untranslated regions (3'UTR), which affect mRNA stability and translation efficiency. Here, we build genetic models to predict APA levels in multiple tissues using sequencing data of 1,337 samples from the Genotype-Tissue Expression, and apply these models to assess associations between genetically predicted APA levels and cancer risk with data from large genome-wide association studies of six common cancers, including breast, ovary, prostate, colorectum, lung, and pancreas among European-ancestry populations. At a Bonferroni-corrected P □<□0.05, we identify 58 risk genes, including seven in newly identified loci. Using luciferase reporter assays, we demonstrate that risk alleles of 3'UTR variants, rs324015 ( STAT6 ), rs2280503 ( DIP2B ), rs1128450 ( FBXO38 ) and rs145220637 ( LDAH ), could significantly increase post-transcriptional activities of their target genes compared to reference alleles. Further gene knockdown experiments confirm their oncogenic roles. Our study provides additional insight into the genetic susceptibility of these common cancers.
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Leon C, Manley E, Neely AM, Castillo J, Ramos Correa M, Velarde DA, Yang M, Puente PE, Romero DI, Ren B, Chai W, Gladstone M, Lamango NS, Huang Y, Offringa IA. Lack of racial and ethnic diversity in lung cancer cell lines contributes to lung cancer health disparities. Front Oncol 2023; 13:1187585. [PMID: 38023251 PMCID: PMC10651223 DOI: 10.3389/fonc.2023.1187585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 10/10/2023] [Indexed: 12/01/2023] Open
Abstract
Lung cancer is the leading cause of cancer death in the United States and worldwide, and a major source of cancer health disparities. Lung cancer cell lines provide key in vitro models for molecular studies of lung cancer development and progression, and for pre-clinical drug testing. To ensure health equity, it is imperative that cell lines representing different lung cancer histological types, carrying different cancer driver genes, and representing different genders, races, and ethnicities should be available. This is particularly relevant for cell lines from Black men, who experience the highest lung cancer mortality in the United States. Here, we undertook a review of the available lung cancer cell lines and their racial and ethnic origin. We noted a marked imbalance in the availability of cell lines from different races and ethnicities. Cell lines from Black patients were strongly underrepresented, and we identified no cell lines from Hispanic/Latin(x) (H/L), American Indian/American Native (AI/AN), or Native Hawaiian or other Pacific Islander (NHOPI) patients. The majority of cell lines were derived from White and Asian patients. Also missing are cell lines representing the cells-of-origin of the major lung cancer histological types, which can be used to model lung cancer development and to study the effects of environmental exposures on lung tissues. To our knowledge, the few available immortalized alveolar epithelial cell lines are all derived from White subjects, and the race and ethnicity of a handful of cell lines derived from bronchial epithelial cells are unknown. The lack of an appropriately diverse collection of lung cancer cell lines and lung cancer cell-of-origin lines severely limits racially and ethnically inclusive lung cancer research. It impedes the ability to develop inclusive models, screen comprehensively for effective compounds, pre-clinically test new drugs, and optimize precision medicine. It thereby hinders the development of therapies that can increase the survival of minority and underserved patients. The noted lack of cell lines from underrepresented groups should constitute a call to action to establish additional cell lines and ensure adequate representation of all population groups in this critical pre-clinical research resource.
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Affiliation(s)
- Christopher Leon
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Department of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | | | - Aaron M. Neely
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Hastings Center for Pulmonary Research, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Jonathan Castillo
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Michele Ramos Correa
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Diego A. Velarde
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Department of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Minxiao Yang
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Pablo E. Puente
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Department of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Diana I. Romero
- Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, United States
| | - Bing Ren
- Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, United States
| | - Wenxuan Chai
- Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, United States
| | - Matthew Gladstone
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Department of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Nazarius S. Lamango
- College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Florida A&M University, Tallahassee, FL, United States
| | - Yong Huang
- Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, United States
| | - Ite A. Offringa
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Department of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Department of Biochemistry and Molecular Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
- Hastings Center for Pulmonary Research, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
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Li Z, Lu L, Deng Y, Zhuo A, Hu F, Sun W, Huang G, Liu L, Rao B, Lu J, Yang L. Genetic susceptibility loci of lung cancer are associated with malignant risk of pulmonary nodules and improve malignancy diagnosis based on CEA levels. Chin J Cancer Res 2023; 35:501-510. [PMID: 37969964 PMCID: PMC10643346 DOI: 10.21147/j.issn.1000-9604.2023.05.07] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 10/20/2023] [Indexed: 11/17/2023] Open
Abstract
Objective The heightened prevalence of pulmonary nodules (PN) has escalated its significance as a public health concern. While the precise identification of high-risk PN carriers for malignancy remains an ongoing challenge, genetic variants hold potentials as determinants of disease susceptibility that can aid in diagnosis. Yet, current understanding of the genetic loci associated with malignant PN (MPN) risk is limited. Methods A frequency-matched case-control study was performed, comprising 247 MPN cases and 412 benign NP (BNP) controls. We genotyped 11 established susceptibility loci for lung cancer in a Chinese cohort. Loci associated with MPN risk were utilized to compute a polygenic risk score (PRS). This PRS was subsequently incorporated into the diagnostic evaluation of MPNs, with emphasis on serum tumor biomarkers. Results Loci rs10429489G>A, rs17038564A>G, and rs12265047A>G were identified as being associated with an increased risk of MPNs. The PRS, formulated from the cumulative risk effects of these loci, correlated with the malignant risk of PNs in a dose-dependent fashion. A high PRS was found to amplify the MPN risk by 156% in comparison to a low PRS [odds ratio (OR)=2.56, 95% confidence interval (95% CI), 1.40-4.67]. Notably, the PRS was observed to enhance the diagnostic accuracy of serum carcinoembryonic antigen (CEA) in distinguishing MPNs from BPNs, with diagnostic values rising from 0.716 to 0.861 across low- to high-PRS categories. Further bioinformatics investigations pinpointed rs10429489G>A as an expression quantitative trait locus. Conclusions Loci rs10429489G>A, rs17038564A>G, and rs12265047A>G contribute to MPN risk and augment the diagnostic precision for MPNs based on serum CEA concentrations.
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Affiliation(s)
- Zhi Li
- The State Key Lab of Respiratory Disease, Institute of Public Health, Guangzhou Medical University, Guangzhou 511436, China
| | - Liming Lu
- The State Key Lab of Respiratory Disease, Institute of Public Health, Guangzhou Medical University, Guangzhou 511436, China
| | - Yibin Deng
- Center for Medical Laboratory Science, the Affiliated Hospital of Youjiang Medical University for Nationalities, Baise 533000, China
| | - Amei Zhuo
- The State Key Lab of Respiratory Disease, Institute of Public Health, Guangzhou Medical University, Guangzhou 511436, China
| | - Fengling Hu
- The State Key Lab of Respiratory Disease, Institute of Public Health, Guangzhou Medical University, Guangzhou 511436, China
| | - Wanwen Sun
- The State Key Lab of Respiratory Disease, Institute of Public Health, Guangzhou Medical University, Guangzhou 511436, China
| | - Guitian Huang
- Physical examination center, Guangzhou First People’s Hospital, Guangzhou 511468, China
| | - Linyuan Liu
- The State Key Lab of Respiratory Disease, Institute of Public Health, Guangzhou Medical University, Guangzhou 511436, China
| | - Boqi Rao
- The State Key Lab of Respiratory Disease, Institute of Public Health, Guangzhou Medical University, Guangzhou 511436, China
| | - Jiachun Lu
- The State Key Lab of Respiratory Disease, Institute of Public Health, Guangzhou Medical University, Guangzhou 511436, China
| | - Lei Yang
- The State Key Lab of Respiratory Disease, Institute of Public Health, Guangzhou Medical University, Guangzhou 511436, China
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19
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Yang Y, Xu S, Jia G, Yuan F, Ping J, Guo X, Tao R, Shu XO, Zheng W, Long J, Cai Q. Integrating genomics and proteomics data to identify candidate plasma biomarkers for lung cancer risk among European descendants. Br J Cancer 2023; 129:1510-1515. [PMID: 37679517 PMCID: PMC10628278 DOI: 10.1038/s41416-023-02419-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 08/22/2023] [Accepted: 08/29/2023] [Indexed: 09/09/2023] Open
Abstract
BACKGROUND Plasma proteins are potential biomarkers for complex diseases. We aimed to identify plasma protein biomarkers for lung cancer. METHODS We investigated genetically predicted plasma levels of 1130 proteins in association with lung cancer risk among 29,266 cases and 56,450 controls of European descent. For proteins significantly associated with lung cancer risk, we evaluated associations of genetically predicted expression of their coding genes with the risk of lung cancer. RESULTS Nine proteins were identified with genetically predicted plasma levels significantly associated with overall lung cancer risk at a false discovery rate (FDR) of <0.05. Proteins C2, MICA, AIF1, and CTSH were associated with increased lung cancer risk, while proteins SFTPB, HLA-DQA2, MICB, NRP1, and GMFG were associated with decreased lung cancer risk. Stratified analyses by histological types revealed the cross-subtype consistency of these nine associations and identified an additional protein, ICAM5, significantly associated with lung adenocarcinoma risk (FDR < 0.05). Coding genes of NRP1 and ICAM5 proteins are located at two loci that have never been reported by previous GWAS. Genetically predicted blood levels of genes C2, AIF1, and CTSH were associated with lung cancer risk, in directions consistent with those shown in protein-level analyses. CONCLUSION Identification of novel plasma protein biomarkers provided new insights into the biology of lung cancer.
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Affiliation(s)
- Yaohua Yang
- Center for Public Health Genomics, Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, Charlottesville, VA, USA.
| | - Shuai Xu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Guochong Jia
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Fangcheng Yuan
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jie Ping
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA.
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Long E, Yin J, Shin JH, Li Y, Kane A, Patel H, Luong T, Xia J, Han Y, Byun J, Zhang T, Zhao W, Landi MT, Rothman N, Lan Q, Chang YS, Yu F, Amos C, Shi J, Lee JG, Kim EY, Choi J. Context-aware single-cell multiome approach identified cell-type specific lung cancer susceptibility genes. bioRxiv 2023:2023.09.25.559336. [PMID: 37808664 PMCID: PMC10557605 DOI: 10.1101/2023.09.25.559336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, the genetic mechanisms and target genes underlying these loci are largely unknown, as most risk-associated-variants might regulate gene expression in a context-specific manner. Here, we generated a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Accessible chromatin peak detection identified cell-type-specific candidate cis-regulatory elements (cCREs) from each lung cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs prioritized the variants for 68% of the GWAS loci, a subset of which was also supported by transcription factor abundance and footprinting. cCRE colocalization and single-cell based trait relevance score nominated epithelial and immune cells as the main cell groups contributing to lung cancer susceptibility. Notably, cCREs of rare proliferating epithelial cell types, such as AT2-proliferating (0.13%) and basal cells (1.8%), overlapped with CCVs, including those in TERT. A multi-level cCRE-gene linking system identified candidate susceptibility genes from 57% of lung cancer loci, including those not detected in tissue- or cell-line-based approaches. cCRE-gene linkage uncovered that adjacent genes expressed in different cell types are correlated with distinct subsets of coinherited CCVs, including JAML and MPZL3 at the 11q23.3 locus. Our data revealed the cell types and contexts where the lung cancer susceptibility genes are functional.
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Affiliation(s)
- Erping Long
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Current affiliation: Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jinhu Yin
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ju Hye Shin
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yuyan Li
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Alexander Kane
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Harsh Patel
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Thong Luong
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jun Xia
- Department of Biomedical Sciences, Creighton University, Omaha, NE, USA
| | - Younghun Han
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Jinyoung Byun
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Tongwu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Wei Zhao
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Yoon Soo Chang
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Fulong Yu
- Guangzhou National Laboratory, Guangzhou International Bio Island, Guangzhou, China
| | - Christopher Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jin Gu Lee
- Department of Thoracic and Cardiovascular Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Eun Young Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jiyeon Choi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
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21
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Im C, Sharafeldin N, Yuan Y, Wang Z, Sapkota Y, Lu Z, Spector LG, Howell RM, Arnold MA, Hudson MM, Ness KK, Robison LL, Bhatia S, Armstrong GT, Neglia JP, Yasui Y, Turcotte LM. Polygenic Risk and Chemotherapy-Related Subsequent Malignancies in Childhood Cancer Survivors: A Childhood Cancer Survivor Study and St Jude Lifetime Cohort Study Report. J Clin Oncol 2023; 41:4381-4393. [PMID: 37459583 PMCID: PMC10522108 DOI: 10.1200/jco.23.00428] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 04/26/2023] [Accepted: 05/18/2023] [Indexed: 08/07/2023] Open
Abstract
PURPOSE Chemotherapeutic exposures are associated with subsequent malignant neoplasm (SMN) risk. The role of genetic susceptibility in chemotherapy-related SMNs should be defined as use of radiation therapy (RT) decreases. PATIENTS AND METHODS SMNs among long-term childhood cancer survivors of European (EUR; N = 9,895) and African (AFR; N = 718) genetic ancestry from the Childhood Cancer Survivor Study and St Jude Lifetime Cohort Study were evaluated. An externally validated 179-variant polygenic risk score (PRS) associated with pleiotropic adult cancer risk from the UK Biobank Study (N > 400,000) was computed for each survivor. SMN cumulative incidence comparing top and bottom PRS quintiles was estimated, along with hazard ratios (HRs) from proportional hazards models. RESULTS A total of 1,594 survivors developed SMNs, with basal cell carcinomas (n = 822), breast cancers (n = 235), and thyroid cancers (n = 221) being the most frequent. Although SMN risk associations with the PRS were extremely modest in RT-exposed EUR survivors (HR, 1.22; P = .048; n = 4,630), the increase in 30-year SMN cumulative incidence and HRs comparing top and bottom PRS quintiles was statistically significant among nonirradiated EUR survivors (n = 4,322) treated with alkylating agents (17% v 6%; HR, 2.46; P < .01), anthracyclines (20% v 8%; HR, 2.86; P < .001), epipodophyllotoxins (23% v 1%; HR, 12.20; P < .001), or platinums (46% v 7%; HR, 8.58; P < .01). This PRS also significantly modified epipodophyllotoxin-related SMN risk among nonirradiated AFR survivors (n = 414; P < .01). Improvements in prediction attributable to the PRS were greatest for epipodophyllotoxin-exposed (AUC, 0.71 v 0.63) and platinum-exposed (AUC,0.68 v 0.58) survivors. CONCLUSION A pleiotropic cancer PRS has strong potential for improving SMN clinical risk stratification among nonirradiated survivors treated with specific chemotherapies. A polygenic risk screening approach may be a valuable complement to an early screening strategy on the basis of treatments and rare cancer-susceptibility mutations.
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Affiliation(s)
- Cindy Im
- Department of Pediatrics, University of Minnesota, Minneapolis, MN
| | - Noha Sharafeldin
- Hematology Oncology Division, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL
- Institute for Cancer Outcomes and Survivorship, University of Alabama at Birmingham, Birmingham, AL
| | - Yan Yuan
- School of Public Health, University of Alberta, Edmonton, Alberta, Canada
| | - Zhaoming Wang
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN
- Department of Computational Biology, St Jude Children's Research Hospital, Memphis, TN
| | - Yadav Sapkota
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN
| | - Zhanni Lu
- Department of Pediatrics, University of Minnesota, Minneapolis, MN
| | - Logan G. Spector
- Department of Pediatrics, University of Minnesota, Minneapolis, MN
| | - Rebecca M. Howell
- Department of Radiation Physics, University of Texas at MD Anderson Cancer Center, Houston, TX
| | - Michael A. Arnold
- Department of Pathology and Laboratory Medicine, University of Colorado and Children's Hospital Colorado, Anschutz Medical Campus, Aurora, CO
| | - Melissa M. Hudson
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN
- Department of Oncology, St Jude Children's Research Hospital, Memphis, TN
| | - Kirsten K. Ness
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN
| | - Leslie L. Robison
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN
| | - Smita Bhatia
- Institute for Cancer Outcomes and Survivorship, University of Alabama at Birmingham, Birmingham, AL
| | - Gregory T. Armstrong
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN
- Department of Oncology, St Jude Children's Research Hospital, Memphis, TN
| | - Joseph P. Neglia
- Department of Pediatrics, University of Minnesota, Minneapolis, MN
| | - Yutaka Yasui
- School of Public Health, University of Alberta, Edmonton, Alberta, Canada
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN
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22
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Wang Y, Ding Y, Liu S, Wang C, Zhang E, Chen C, Zhu M, Zhang J, Zhu C, Ji M, Dai J, Jin G, Hu Z, Shen H, Ma H. Integrative splicing-quantitative-trait-locus analysis reveals risk loci for non-small-cell lung cancer. Am J Hum Genet 2023; 110:1574-1589. [PMID: 37562399 PMCID: PMC10502736 DOI: 10.1016/j.ajhg.2023.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 07/13/2023] [Accepted: 07/14/2023] [Indexed: 08/12/2023] Open
Abstract
Splicing quantitative trait loci (sQTLs) have been demonstrated to contribute to disease etiology by affecting alternative splicing. However, the role of sQTLs in the development of non-small-cell lung cancer (NSCLC) remains unknown. Thus, we performed a genome-wide sQTL study to identify genetic variants that affect alternative splicing in lung tissues from 116 individuals of Chinese ancestry, which resulted in the identification of 1,385 sQTL-harboring genes (sGenes) containing 378,210 significant variant-intron pairs. A comprehensive characterization of these sQTLs showed that they were enriched in actively transcribed regions, genetic regulatory elements, and splicing-factor-binding sites. Moreover, sQTLs were largely distinct from expression quantitative trait loci (eQTLs) and showed significant enrichment in potential risk loci of NSCLC. We also integrated sQTLs into NSCLC GWAS datasets (13,327 affected individuals and 13,328 control individuals) by using splice-transcriptome-wide association study (spTWAS) and identified alternative splicing events in 19 genes that were significantly associated with NSCLC risk. By using functional annotation and experiments, we confirmed an sQTL variant, rs35861926, that reduced the risk of lung adenocarcinoma (rs35861926-T, OR = 0.88, 95% confidence interval [CI]: 0.82-0.93, p = 1.87 × 10-5) by promoting FARP1 exon 20 skipping to downregulate the expression level of the long transcript FARP1-011. Transcript FARP1-011 promoted the migration and proliferation of lung adenocarcinoma cells. Overall, our study provided informative lung sQTL resources and insights into the molecular mechanisms linking sQTL variants to NSCLC risk.
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Affiliation(s)
- Yuzhuo Wang
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Yue Ding
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Su Liu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Cheng Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Erbao Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Congcong Chen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Jing Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Chen Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Department of Cancer Prevention, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, Zhejiang 310022, China
| | - Mengmeng Ji
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Guangfu Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Zhibin Hu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing 100730, China.
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China.
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23
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Luyapan J, Bossé Y, Li Z, Xiao X, Rosenberger A, Hung RJ, Lam S, Zienolddiny S, Liu G, Kiemeney LA, Chen C, McKay J, Johansson M, Johansson M, Tardon A, Fernandez-Tardon G, Brennan P, Field JK, Davies MP, Woll PJ, Cox A, Taylor F, Arnold SM, Lazarus P, Grankvist K, Landi MT, Christiani DC, MacKenzie TA, Amos CI. Candidate pathway analysis of surfactant proteins identifies CTSH and SFTA2 that influences lung cancer risk. Hum Mol Genet 2023; 32:2842-2855. [PMID: 37471639 PMCID: PMC10481107 DOI: 10.1093/hmg/ddad095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 05/22/2023] [Accepted: 05/24/2023] [Indexed: 07/22/2023] Open
Abstract
Pulmonary surfactant is a lipoprotein synthesized and secreted by alveolar type II cells in lung. We evaluated the associations between 200,139 single nucleotide polymorphisms (SNPs) of 40 surfactant-related genes and lung cancer risk using genotyped data from two independent lung cancer genome-wide association studies. Discovery data included 18,082 cases and 13,780 controls of European ancestry. Replication data included 1,914 cases and 3,065 controls of European descent. Using multivariate logistic regression, we found novel SNPs in surfactant-related genes CTSH [rs34577742 C > T, odds ratio (OR) = 0.90, 95% confidence interval (CI) = 0.89-0.93, P = 7.64 × 10-9] and SFTA2 (rs3095153 G > A, OR = 1.16, 95% CI = 1.10-1.21, P = 1.27 × 10-9) associated with overall lung cancer in the discovery data and validated in an independent replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.80-0.96, P = 5.76 × 10-3) and SFTA2 (rs3095153 G > A, OR = 1.14, 95% CI = 1.01-1.28, P = 3.25 × 10-2). Among ever smokers, we found SNPs in CTSH (rs34577742 C > T, OR = 0.89, 95% CI = 0.85-0.92, P = 1.94 × 10-7) and SFTA2 (rs3095152 G > A, OR = 1.20, 95% CI = 1.14-1.27, P = 4.25 × 10-11) associated with overall lung cancer in the discovery data and validated in the replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.79-0.97, P = 1.64 × 10-2) and SFTA2 (rs3095152 G > A, OR = 1.15, 95% CI = 1.01-1.30, P = 3.81 × 10-2). Subsequent transcriptome-wide association study using expression weights from a lung expression quantitative trait loci study revealed genes most strongly associated with lung cancer are CTSH (PTWAS = 2.44 × 10-4) and SFTA2 (PTWAS = 2.32 × 10-6).
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Affiliation(s)
- Jennifer Luyapan
- Quantitative Biomedical Science Program, Geisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA
- Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
| | - Yohan Bossé
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Université Laval, Quebec City, G1V 0A6, Canada
- Department of Molecular Medicine, Laval University, Quebec City, G1V 0A6, Canada
| | - Zhonglin Li
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Université Laval, Quebec City, G1V 0A6, Canada
| | - Xiangjun Xiao
- Department of Medicine, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Albert Rosenberger
- Institut für Genetische Epidemiologie, Georg-August-Universität Göttingen, Gottingen, Niedersachsen, Germany
| | - Rayjean J Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbuaum Research Institute, Sinai Health System, Toronto, ON, M5G 1X5, Canada
| | - Stephen Lam
- Department of Integrative Oncology, British Columbia Cancer Agency, Vancouver, BC, V5Z 4E6, Canada
| | - Shanbeh Zienolddiny
- Department of Toxicology, National Institute of Occupational Health, Oslo 0033, Norway
| | - Geoffrey Liu
- Princess Margaret Cancer Centre, Princess Margaret Research Institute, Epidemiology Division,Toronto, ON, M5G 1L7, Canada
| | - Lambertus A Kiemeney
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, 6525 GA, the Netherlands
| | - Chu Chen
- Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - James McKay
- International Agency for Research on Cancer (IARC/WHO), Genomic Epidemiology Branch Lyon 69008, France
| | - Mattias Johansson
- International Agency for Research on Cancer (IARC/WHO), Genomic Epidemiology Branch Lyon 69008, France
| | - Mikael Johansson
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, 901 87, Sweden
| | - Adonina Tardon
- Health Research Institute of the Principality of Asturias, University of Oviedo and CIBERSP, Oviedo, Asturias, 33071, Spain
| | - Guillermo Fernandez-Tardon
- Health Research Institute of the Principality of Asturias, University of Oviedo and CIBERSP, Oviedo, Asturias, 33071, Spain
| | - Paul Brennan
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Epidemiology, Ludwig Maximillians University, Munich, Bavaria, 80539, Germany
| | - John K Field
- Molecular and Clinical Cancer Medicine, Roy Castle Lung Cancer Research Programme, The University of Liverpool Institute of Translational Medicine, Liverpool, L69 7ZX, UK
| | - Michael P Davies
- Molecular and Clinical Cancer Medicine, Roy Castle Lung Cancer Research Programme, The University of Liverpool Institute of Translational Medicine, Liverpool, L69 7ZX, UK
| | - Penella J Woll
- Academic Unit of Clinical Oncology, University of Sheffield, Sheffield, S10 2AH, UK
| | - Angela Cox
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, S10 2AH, UK
| | - Fiona Taylor
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, S10 2AH, UK
| | - Susanne M Arnold
- Division of Medical Oncology, Cancer Center, University of Kentucky, Lexington, KY 40508, USA
| | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, WA, 99163, USA
| | - Kjell Grankvist
- Department of Medical Biosciences, Clinical Chemistry, Umeå University, Umeå, 901 87, Sweden
| | - Maria T Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, 20892, USA
| | - David C Christiani
- Department of Environmental Health, Harvard School of Public Health, Boston, MA 02115, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA 02115, USA
| | - Todd A MacKenzie
- Quantitative Biomedical Science Program, Geisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA
- Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
| | - Christopher I Amos
- Quantitative Biomedical Science Program, Geisel School of Medicine, Dartmouth College, Hanover, NH 03755, USA
- Department of Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
- Department of Medicine, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
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24
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Cheng C, Hong W, Li Y, Xiao X, McKay J, Han Y, Byun J, Peng B, Albanes D, Lam S, Tardon A, Chen C, Bojesen SE, Landi MT, Johansson M, Risch A, Bickeböller H, Wichmann HE, Christiani DC, Rennert G, Arnold S, Goodman G, Field JK, Davies MPA, Shete SS, Le Marchand L, Liu G, Hung RJ, Andrew AS, Kiemeney LA, Zhu M, Shen H, Zienolddiny S, Grankvist K, Johansson M, Cox A, Hong YC, Yuan JM, Lazarus P, Schabath MB, Aldrich MC, Brennan P, Li Y, Gorlova O, Gorlov I, Amos CI. Mosaic Chromosomal Alterations Are Associated With Increased Lung Cancer Risk: Insight From the INTEGRAL-ILCCO Cohort Analysis. J Thorac Oncol 2023; 18:1003-1016. [PMID: 37150255 PMCID: PMC10435278 DOI: 10.1016/j.jtho.2023.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 04/21/2023] [Accepted: 05/01/2023] [Indexed: 05/09/2023]
Abstract
INTRODUCTION Mosaic chromosomal alterations (mCAs) detected in white blood cells represent a type of clonal hematopoiesis (CH) that is understudied compared with CH-related somatic mutations. A few recent studies indicated their potential link with nonhematological cancers, especially lung cancer. METHODS In this study, we investigated the association between mCAs and lung cancer using the high-density genotyping data from the OncoArray study of INTEGRAL-ILCCO, the largest single genetic study of lung cancer with 18,221 lung cancer cases and 14,825 cancer-free controls. RESULTS We identified a comprehensive list of autosomal mCAs, ChrX mCAs, and mosaic ChrY (mChrY) losses from these samples. Autosomal mCAs were detected in 4.3% of subjects, in addition to ChrX mCAs in 3.6% of females and mChrY losses in 9.6% of males. Multivariable logistic regression analysis indicated that the presence of autosomal mCAs in white blood cells was associated with an increased lung cancer risk after adjusting for key confounding factors, including age, sex, smoking status, and race. This association was mainly driven by a specific type of mCAs: copy-neutral loss of heterozygosity on autosomal chromosomes. The association between autosome copy-neutral loss of heterozygosity and increased risk of lung cancer was further confirmed in two major histologic subtypes, lung adenocarcinoma and squamous cell carcinoma. In addition, we observed a significant increase of ChrX mCAs and mChrY losses in smokers compared with nonsmokers and racial differences in certain types of mCA events. CONCLUSIONS Our study established a link between mCAs in white blood cells and increased risk of lung cancer.
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Affiliation(s)
- Chao Cheng
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas; Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas; Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Wei Hong
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas
| | - Yafang Li
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas; Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas; Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Xiangjun Xiao
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas
| | - James McKay
- Section of Genetics, International Agency for Research on Cancer, WHO, Lyon, France
| | - Younghun Han
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas; Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Jinyoung Byun
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas; Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Bo Peng
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas; Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Demetrios Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Stephen Lam
- Department of Integrative Oncology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Adonina Tardon
- Public Health Department, University of Oviedo, ISPA and CIBERESP, Asturias, Spain
| | - Chu Chen
- Program in Epidemiology, Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Stig E Bojesen
- Department of Clinical Biochemistry, Copenhagen University Hospital, Copenhagen, Denmark; Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Maria T Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Mattias Johansson
- Section of Genetics, International Agency for Research on Cancer, WHO, Lyon, France
| | - Angela Risch
- Thoraxklinik at University Hospital Heidelberg, Heidelberg, Germany; Translational Lung Research Center Heidelberg (TLRC-H), Heidelberg, Germany; University of Salzburg and Cancer Cluster Salzburg, Salzburg, Austria
| | - Heike Bickeböller
- Department of Genetic Epidemiology, University Medical Center, Georg-August-University Göttingen, Göttingen, Germany
| | - H-Erich Wichmann
- Institute of Medical Statistics and Epidemiology, Technical University Munich, Munich, Germany
| | - David C Christiani
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Gad Rennert
- Clalit National Cancer Control Center at Carmel Medical Center and Technion Faculty of Medicine, Haifa, Israel
| | - Susanne Arnold
- University of Kentucky, Markey Cancer Center, Lexington, Kentucky
| | | | - John K Field
- Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, United Kingdom
| | - Michael P A Davies
- Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, United Kingdom
| | - Sanjay S Shete
- Department of Biostatistics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas; Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Geoffrey Liu
- University Health Network- The Princess Margaret Cancer Centre, Toronto, California
| | - Rayjean J Hung
- Luenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Canada; Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Angeline S Andrew
- Department of Epidemiology, Dartmouth College, Hanover, New Hampshire; Department of Community and Family Medicine, Dartmouth College, Hanover, New Hampshire
| | | | - Meng Zhu
- Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Hongbing Shen
- Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | | | - Kjell Grankvist
- Department of Medical Biosciences, Umeå University, Umeå, Sweden
| | | | - Angela Cox
- Academic Unit of Clinical Oncology University of Sheffield, Weston Park Hospital, Whitham Road, Sheffield, United Kingdom
| | - Yun-Chul Hong
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jian-Min Yuan
- University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center, Pittsburgh, Pennsylvania
| | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington
| | - Matthew B Schabath
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Melinda C Aldrich
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Paul Brennan
- Section of Genetics, International Agency for Research on Cancer, WHO, Lyon, France
| | - Yong Li
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas; Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas; Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Olga Gorlova
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas; Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas; Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Ivan Gorlov
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas; Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas; Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Christopher I Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas; Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas; Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas.
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25
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Gao M, Li Y, Huang H, Fan Y, Shi R, Su L, Chen C, Li X, Zhu G, Wu D, Cao P, Liu H, Chen J, Kang S. Exploring the Association Between PRC2 Genes Variants and Lung Cancer Risk in Chinese Han Population. Onco Targets Ther 2023; 16:499-513. [PMID: 37425980 PMCID: PMC10328106 DOI: 10.2147/ott.s417190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 06/27/2023] [Indexed: 07/11/2023] Open
Abstract
Background Genetic susceptibilities play a large role in the pathogenesis of lung cancer (LC). The polycomb repressive complex 2 (PRC2) is a conserved chromatin-associated complex that represses gene expression and is crucial for proper organismal development and gene expression patterns. Despite PRC2 dysregulation has been observed in various human cancers, the relationship between PRC2 genes variants and lung cancer risk remains largely unexplored. Methods To investigate the association between single nucleotide polymorphisms (SNPs) in PRC2 genes and the risk of developing LC, we genotyped blood genomic DNA from 270 LC patients and 452 healthy individuals of Chinese Han ethnicity using the TaqMan™ genotyping technique. Results We found that rs17171119T>G(adjusted odds ratio (OR) = 0.662, 95% CI: 0.467-0.938, P < 0.05), rs10898459 T>C(adjusted OR = 0.615, 95% CI: 0.4-0.947, P < 0.05), and rs1136258 C>T(adjusted OR = 0.273, 95% CI: 0.186-0.401, P < 0.001) were significantly associated with a reduced risk of LC. Stratified analysis revealed a protective effect of rs17171119 in both male and female patients, specifically those with lung adenocarcinoma (LUAD). Additionally, rs1391221 showed a protective effect in both the LUAD and lung squamous cell carcinoma (LUSC) groups, while rs1136258 exhibited a protective effect in both females and males, as well as in both LUAD and LUSC groups. Furthermore, analysis of The Cancer Genome Atlas (TCGA) dataset revealed expression levels of EED and RBBP4 in both LUAD and LUSC. Conclusion This study provides evidence that allelic variants in EZH2, EED, and RBBP4 may act as protective factors against LC development and could serve as genetic markers associated with susceptibility to LC.
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Affiliation(s)
- Min Gao
- Department of Thoracic Surgery, the Affiliated Hospital of Inner Mongolia Medical University, Hohhot, 010010, People’s Republic of China
- Inner Mongolia Medical University, Hohhot, 010010, People’s Republic of China
| | - Yongwen Li
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, People’s Republic of China
| | - Hua Huang
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, People’s Republic of China
| | - Yaguang Fan
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, People’s Republic of China
| | - Ruifeng Shi
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, People’s Republic of China
| | - Lianchun Su
- Department of Thoracic Surgery, First Affiliated Hospital of Shihezi University School of Medicine, Shihezi, People’s Republic of China
| | - Chen Chen
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, People’s Republic of China
| | - Xuanguang Li
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, People’s Republic of China
| | - Guangsheng Zhu
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, People’s Republic of China
| | - Di Wu
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, People’s Republic of China
| | - Peijun Cao
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, People’s Republic of China
| | - Hongyu Liu
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, People’s Republic of China
| | - Jun Chen
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, People’s Republic of China
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, People’s Republic of China
- Department of Thoracic Surgery, First Affiliated Hospital of Shihezi University School of Medicine, Shihezi, People’s Republic of China
| | - Shirong Kang
- Department of Thoracic Surgery, the Affiliated Hospital of Inner Mongolia Medical University, Hohhot, 010010, People’s Republic of China
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26
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Langlois AWR, El-Boraie A, Pouget JG, Cox LS, Ahluwalia JS, Fukunaga K, Mushiroda T, Knight J, Chenoweth MJ, Tyndale RF. Genotyping, characterization, and imputation of known and novel CYP2A6 structural variants using SNP array data. J Hum Genet 2023:10.1038/s10038-023-01148-y. [PMID: 37059825 DOI: 10.1038/s10038-023-01148-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 03/23/2023] [Accepted: 03/30/2023] [Indexed: 04/16/2023]
Abstract
CYP2A6 metabolically inactivates nicotine. Faster CYP2A6 activity is associated with heavier smoking and higher lung cancer risk. The CYP2A6 gene is polymorphic, including functional structural variants (SV) such as gene deletions (CYP2A6*4), duplications (CYP2A6*1 × 2), and hybrids with the CYP2A7 pseudogene (CYP2A6*12, CYP2A6*34). SVs are challenging to genotype due to their complex genetic architecture. Our aims were to develop a reliable protocol for SV genotyping, functionally phenotype known and novel SVs, and investigate the feasibility of CYP2A6 SV imputation from SNP array data in two ancestry populations. European- (EUR; n = 935) and African- (AFR; n = 964) ancestry individuals from smoking cessation trials were genotyped for SNPs using an Illumina array and for CYP2A6 SVs using Taqman copy number (CN) assays. SV-specific PCR amplification and Sanger sequencing was used to characterize a novel SV. Individuals with SVs were phenotyped using the nicotine metabolite ratio, a biomarker of CYP2A6 activity. SV diplotype and SNP array data were integrated and phased to generate ancestry-specific SV reference panels. Leave-one-out cross-validation was used to investigate the feasibility of CYP2A6 SV imputation. A minimal protocol requiring three Taqman CN assays for CYP2A6 SV genotyping was developed and known SV associations with activity were replicated. The first domain swap CYP2A6-CYP2A7 hybrid SV, CYP2A6*53, was identified, sequenced, and associated with lower CYP2A6 activity. In both EURs and AFRs, most SV alleles were identified using imputation (>70% and >60%, respectively); importantly, false positive rates were <1%. These results confirm that CYP2A6 SV imputation can identify most SV alleles, including a novel SV.
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Affiliation(s)
- Alec W R Langlois
- Department of Pharmacology and Toxicology, University of Toronto, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 100 Stokes Street, Toronto, ON, M6J 1H4, Canada
| | - Ahmed El-Boraie
- Department of Pharmacology and Toxicology, University of Toronto, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 100 Stokes Street, Toronto, ON, M6J 1H4, Canada
| | - Jennie G Pouget
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 100 Stokes Street, Toronto, ON, M6J 1H4, Canada
- Department of Psychiatry, University of Toronto, 250 College Street, Toronto, ON, M5T 1R8, Canada
| | - Lisa Sanderson Cox
- Department of Population Health, University of Kansas School of Medicine, Kansas City, KS, 66160, USA
| | - Jasjit S Ahluwalia
- Departments of Behavioral and Social Sciences and Medicine, Brown University School of Public Health, Providence, RI, 02912, USA
| | - Koya Fukunaga
- Center for Integrative Medical Sciences, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
| | - Taisei Mushiroda
- Center for Integrative Medical Sciences, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
| | - Jo Knight
- Data Science Institute and Medical School, Lancaster University, Lancaster, UK
| | - Meghan J Chenoweth
- Department of Pharmacology and Toxicology, University of Toronto, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 100 Stokes Street, Toronto, ON, M6J 1H4, Canada
- Department of Psychiatry, University of Toronto, 250 College Street, Toronto, ON, M5T 1R8, Canada
| | - Rachel F Tyndale
- Department of Pharmacology and Toxicology, University of Toronto, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada.
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 100 Stokes Street, Toronto, ON, M6J 1H4, Canada.
- Department of Psychiatry, University of Toronto, 250 College Street, Toronto, ON, M5T 1R8, Canada.
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27
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Zhang R, Li Y, Chen F, Christiani DC. Reply to Scott et al: "Gene-Gene interaction in ever-smokers with lung cancer: Is there confounding by COPD in GWAS?". J Thorac Oncol 2023; 18:e24-e26. [PMID: 36842814 DOI: 10.1016/j.jtho.2022.12.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 12/08/2022] [Indexed: 02/26/2023]
Affiliation(s)
- Ruyang Zhang
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts; China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Yi Li
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Feng Chen
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention, and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China.
| | - David C Christiani
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts; Pulmonary and Critical Care Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
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28
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Ma Z, Zhu C, Wang H, Ji M, Huang Y, Wei X, Zhang J, Wang Y, Yin R, Dai J, Xu L, Ma H, Hu Z, Jin G, Zhu M, Shen H. Association between biological aging and lung cancer risk: Cohort study and Mendelian randomization analysis. iScience 2023; 26:106018. [PMID: 36852276 PMCID: PMC9958377 DOI: 10.1016/j.isci.2023.106018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 12/14/2022] [Accepted: 01/16/2023] [Indexed: 01/20/2023] Open
Abstract
Chronological age only represents the passage of time, whereas biological age reflects the physiology states and the susceptibility to morbidity and mortality. The association between biological age and lung cancer risk remains controversial. Hence, we conducted a prospective analysis in the UK Biobank study and two-sample Mendelian randomization analysis to investigate this association. Biological aging was evaluated by PhenoAgeAccel, derived from routine clinical biomarkers. Independent of chronological age, PhenoAgeAccel was positively associated with the risk of overall and histological subtypes of lung cancer. There was a joint effect of PhenoAgeAccel and genetics in lung cancer incidence. In Mendelian randomization analysis, the genetically predicted PhenoAgeAccel was associated with the increased risk of overall lung cancer, small cell, and squamous cell carcinoma. Our findings suggest PhenoAgeAccel is an independent risk factor for lung cancer, which could be incorporated with polygenic risk score to identify high-risk individuals for lung cancer.
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Affiliation(s)
- Zhimin Ma
- Department of Epidemiology, School of Public Health, Southeast University, Nanjing 210009, China,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Chen Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China,Department of Cancer Prevention, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China,Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China
| | - Hui Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Mengmeng Ji
- Department of Epidemiology, School of Public Health, Southeast University, Nanjing 210009, China,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yanqian Huang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Xiaoxia Wei
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Jing Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yuzhuo Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China,Department of Thoracic Surgery, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing 210009, China
| | - Rong Yin
- Department of Thoracic Surgery, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing 210009, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Lin Xu
- Department of Thoracic Surgery, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing 210009, China
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China,Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing 100000, China
| | - Zhibin Hu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China
| | - Guangfu Jin
- Department of Epidemiology, School of Public Health, Southeast University, Nanjing 210009, China,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China,Corresponding author
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China,Corresponding author
| | - Hongbing Shen
- Department of Epidemiology, School of Public Health, Southeast University, Nanjing 210009, China,Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China,Department of Cancer Prevention, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou 310022, China,Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing 100000, China,Corresponding author
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29
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Jiang L, Sun Y, Brumpton BM, Langhammer A, Chen Y, Mai X. Body mass index and incidence of lung cancer in the HUNT study: using observational and Mendelian randomization approaches. BMC Cancer 2022; 22:1152. [DOI: 10.1186/s12885-022-10215-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Accepted: 10/23/2022] [Indexed: 11/11/2022] Open
Abstract
Abstract
Background
Traditional observational studies have shown an inverse association between body mass index (BMI) and lung cancer risk. Mendelian randomization (MR) analysis using genetic variants as instruments for BMI may clarify the nature of the association.
Aims
We studied the causal association between BMI and lung cancer incidence using observational and MR approaches.
Methods
We followed up 62,453 cancer-free Norwegian adults from 1995–97 (HUNT2) until 2017. BMI at baseline in HUNT2 was classified as < 25.0, 25.0–29.9 and ≥ 30.0 kg/m2. BMI change over ten years between HUNT1 (1984–86) and HUNT2 was calculated and classified into quartiles. Seventy-five genetic variants were included as instruments for BMI (among which 14 also associated with smoking behavior). Incident lung cancer cases were ascertained from the Cancer Registry of Norway. Cox regression models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). Multivariable MR was used to examine the effect of BMI after genetically controlling for smoking.
Results
During a median follow-up of 21.1 years, 1009 participants developed lung cancer including 327 with lung adenocarcinoma. The HRs and 95% CIs for incidence of adenocarcinoma were 0.73 (0.58–0.92) for BMI 25.0–29.9 kg/m2 and 0.53 (0.37–0.76) for BMI ≥ 30 kg/m2 compared with BMI < 25.0 kg/m2 in HUNT2 (P for trend < 0.001). However, there was little evidence of a dose–response relationship between the BMI change from HUNT1 to HUNT2 in quartiles and the incidence of adenocarcinoma (P for trend = 0.08). Furthermore, multivariable MR approach suggested a positive association between genetically determined 1 kg/m2 increase in BMI and the incidence of adenocarcinoma (HR 1.25, 95% CI 1.02–1.53). No associations were found with other lung cancer histologic types.
Conclusions
Our study suggests that the inverse association between baseline BMI and lung adenocarcinoma in observational analysis may not be causal. More MR studies are needed to confirm our finding of a positive association between BMI and lung adenocarcinoma.
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30
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Mukherjee S, Carrot-Zhang J. Whole-genome sequencing of East Asian lung cancers reveals new germline pathogenic variants. Cancer Cell 2022; 40:1081-1083. [PMID: 36179687 DOI: 10.1016/j.ccell.2022.09.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
In this issue of Cancer Cell, Wang et al. use whole-genome sequencing of lung cancer cases and controls with East Asian ancestry to comprehensively characterize both common and rare variants that predispose to lung cancer. Their findings suggest that rare promoter variants in BRCA2 are associated with increased lung cancer risk.
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Affiliation(s)
- Semanti Mukherjee
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Jian Carrot-Zhang
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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31
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Li Y, Xiao X, Li J, Byun J, Cheng C, Bossé Y, McKay J, Albanes D, Lam S, Tardon A, Chen C, Bojesen SE, Landi MT, Johansson M, Risch A, Bickeböller H, Wichmann HE, Christiani DC, Rennert G, Arnold S, Goodman G, Field JK, Davies MPA, Shete SS, Le Marchand L, Melander O, Brunnström H, Liu G, Hung RJ, Andrew AS, Kiemeney LA, Shen H, Sun R, Zienolddiny S, Grankvist K, Johansson M, Caporaso N, Teare DM, Hong YC, Lazarus P, Schabath MB, Aldrich MC, Schwartz AG, Gorlov I, Purrington K, Yang P, Liu Y, Han Y, Bailey-Wilson JE, Pinney SM, Mandal D, Willey JC, Gaba C, Brennan P, Amos CI. Genome-wide interaction analysis identified low-frequency variants with sex disparity in lung cancer risk. Hum Mol Genet 2022; 31:2831-2843. [PMID: 35138370 PMCID: PMC9402242 DOI: 10.1093/hmg/ddac030] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 01/14/2022] [Accepted: 01/31/2022] [Indexed: 01/12/2023] Open
Abstract
Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene-sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10-8); rs79942605 (OR = 2.17, P = 2.81×10-8) and rs208908 (OR = 0.70, P = 4.54×10-8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.
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Affiliation(s)
- Yafang Li
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX 77030, USA
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Xiangjun Xiao
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jianrong Li
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jinyoung Byun
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX 77030, USA
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
| | - Chao Cheng
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX 77030, USA
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Yohan Bossé
- Institut universitaire de cardiologie et de pneumologie de Québec, Department of Molecular Medicine, Laval University, Quebec City G1V 4G5, Canada
| | - James McKay
- Section of Genetics, International Agency for Research on Cancer, World Health Organization, Lyon 69372, France
| | - Demetrios Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Stephen Lam
- Department of Integrative Oncology, University of British Columbia, Vancouver, BC V5Z 1L3, Canada
| | - Adonina Tardon
- Public Health Department, University of Oviedo, ISPA and CIBERESP, Asturias 33003, Spain
| | - Chu Chen
- Program in Epidemiology, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Stig E Bojesen
- Department of Clinical Biochemistry, Copenhagen University Hospital, Copenhagen 2600, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2177, Denmark
| | - Maria T Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Mattias Johansson
- Section of Genetics, International Agency for Research on Cancer, World Health Organization, Lyon 69372, France
| | - Angela Risch
- Thoraxklinik at University Hospital Heidelberg, Heidelberg 69126, Germany
- Translational Lung Research Center Heidelberg (TLRC-H), Heidelberg 69120, Germany
- University of Salzburg and Cancer Cluster Salzburg, 5020, Austria
| | - Heike Bickeböller
- Department of Genetic Epidemiology, University Medical Center, Georg-August-University Göttingen, 37099, Germany
| | - H-Erich Wichmann
- Institute of Medical Statistics and Epidemiology, Technical University Munich, 80333, Germany
| | - David C Christiani
- Departments of Environmental Health and Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02115, USA
| | - Gad Rennert
- Clalit National Cancer Control Center at Carmel Medical Center and Technion Faculty of Medicine, Haifa 3436212, Israel
| | - Susanne Arnold
- University of Kentucky, Markey Cancer Center, Lexington, Kentucky 40536, USA
| | - Gary Goodman
- Swedish Cancer Institute, Seattle, WA 98104, USA
| | - John K Field
- Institute of Translational Medicine, University of Liverpool, Liverpool L69 7BE, United Kingdom
| | - Michael P A Davies
- Institute of Translational Medicine, University of Liverpool, Liverpool L69 7BE, United Kingdom
| | - Sanjay S Shete
- Department of Biostatistics, The University of Texas, M.D. Anderson Cancer Center, Houston, TX 77030, USA
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI 96813, USA
| | - Olle Melander
- Faculty of Medicine, Lund University, Lund 22184, Sweden
| | | | - Geoffrey Liu
- University Health Network- The Princess Margaret Cancer Centre, Toronto, CA ON, M5G 2C1, Canada
| | - Rayjean J Hung
- Luenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto ON, M5G 1X5, Canada
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto ON, M5T 3M7, Canada
| | - Angeline S Andrew
- Departments of Epidemiology and Community and Family Medicine, Dartmouth College, Hanover, NH 03755, USA
| | | | - Hongbing Shen
- Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing 211166, P.R. China
| | - Ryan Sun
- Department of Biostatistics, The University of Texas, M.D. Anderson Cancer Center, Houston, TX 77030, USA
| | | | - Kjell Grankvist
- Department of Medical Biosciences, Umeå University, Umeå 901 87, Sweden
| | - Mikael Johansson
- Department of Radiation Sciences, Umeå University, Umeå 901 87, Sweden
| | - Neil Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Dawn M Teare
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, NE2 4AX, UK
| | - Yun-Chul Hong
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy, Washington State University, Spokane, Washington 99202, USA
| | - Matthew B Schabath
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA
| | - Melinda C Aldrich
- Department of Thoracic Surgery, Division of Epidemiology, Vanderbilt University Medical Center Nashville, TN 37232, USA
| | - Ann G Schwartz
- Department of Oncology, Wayne State University School of Medicine, Detroit, MI 48201, USA
- Karmanos Cancer Institute, Detroit, MI 48201, USA
| | - Ivan Gorlov
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX 77030, USA
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | | | - Ping Yang
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinics Rochester, MN, 55905, USA
| | - Yanhong Liu
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Younghun Han
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX 77030, USA
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
| | | | - Susan M Pinney
- University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Diptasri Mandal
- Louisiana State University Health Sciences Center, New Orleans, LA 70112, USA
| | - James C Willey
- College of Medicine and Life Sciences, University of Toledo, Toledo, OH 43614, USA
| | - Colette Gaba
- The University of Toledo College of Medicine, Toledo, OH 43614, USA
| | - Paul Brennan
- Section of Genetics, International Agency for Research on Cancer, World Health Organization, Lyon 69372, France
| | - Christopher I Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX 77030, USA
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
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