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Weng C, Zhao Y, Song M, Shao Z, Pang Y, Yu C, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Chen J, Chen Z, Genovese G, Terao C, Lv J, Li L, Sun D. Mosaic loss of chromosome Y, tobacco smoking and risk of age-related lung diseases: insights from two prospective cohorts. Eur Respir J 2024; 64:2400968. [PMID: 39401857 DOI: 10.1183/13993003.00968-2024] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Accepted: 09/11/2024] [Indexed: 12/31/2024]
Abstract
BACKGROUND Little is known about the underlying relationship between mosaic loss of chromosome Y (mLOY), the most common chromosomal alterations in older men, and the risk of age-related lung diseases. METHODS We included 217 780 participants from the UK Biobank (UKB) and 42 859 participants from the China Kadoorie Biobank. The mLOY events were detected using the Mosaic Chromosomal Alterations (MoChA) pipeline. Outcomes included all lung diseases, COPD, lung cancer and idiopathic pulmonary fibrosis (IPF). Cox proportional hazard models were fitted to estimate the hazard ratios and 95% confidence intervals of mLOY with lung diseases in both cohorts. The combined hazard ratios were derived from meta-analysis. RESULTS Results from the two cohorts showed that expanded mLOY was associated with increased risks of all lung diseases (HR 1.19 (95% CI 1.04-1.36)), COPD (HR 1.20 (95% CI 1.13-1.28)), lung cancer (HR 1.34 (95% CI 1.21-1.48)) and IPF (HR 1.34 (95% CI 1.16-1.56) in the UKB). There was evidence of positive interactions between mLOY and smoking behaviour (relative excess risk due to interaction (97.5% CI) >0). Additionally, we observed that current smokers with expanded mLOY had the highest risk of incident lung diseases in both cohorts. CONCLUSIONS mLOY may be a novel predictor for age-related lung diseases. For current smokers carrying mLOY, adopting quitting smoking behaviour may contribute to substantially reducing their risk of incident lung diseases.
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Affiliation(s)
- Chenghao Weng
- School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China
- These authors contributed equally to this work
| | - Yuxuan Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- These authors contributed equally to this work
| | - Mingyu Song
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Zilun Shao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Ling Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Giulio Genovese
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
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Mervic A, Goricar K, Blagus T, Franko A, Trebusak-Podkrajsek K, Fikfak MD, Dolzan V, Kovac V. Telomere length and TERT polymorphisms as biomarkers in asbestos-related diseases. Radiol Oncol 2024; 58:87-98. [PMID: 38378028 PMCID: PMC10878767 DOI: 10.2478/raon-2024-0009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 09/13/2023] [Indexed: 02/22/2024] Open
Abstract
BACKGROUND Asbestos exposure has been proposed as a risk factor for shorter telomere length. The aim of our study was to investigate whether telomere length in leukocytes and hTERT genetic polymorphisms may serve as potential biomarkers for the risk of developing asbestos-related diseases and as biomarkers of progression and chemotherapy response rate in malignant mesothelioma (MM). SUBJECTS AND METHODS We conducted two retrospective studies. In the first study, a case-control study, telomere length and hTERT polymorphisms were determined in patients with MM, subjects with pleural plaques and controls without the asbestos related disease, who were occupationally exposed to asbestos. In the second study, a longitudinal observational study, telomere length was also determined in samples from MM patients before and after chemotherapy. Telomere length was determined by monochromatic multiplex quantitative polymerase chain reaction (PCR), while competitive allele-specific PCR was used to genotype hTERT rs10069690, rs2736100 and rs2736098. Logistic regression and survival analysis were used in statistical analysis. RESULTS Patients with MM had shorter telomere length than subjects with pleural plaques (p < 0.001). After adjustment for age, rs2736098 CT, and rs10069690 TT and CT+TT genotypes were significantly associated with a higher risk of MM (padj = 0.023; padj = 0.026 and padj = 0.017), while rs2736100 AA and CA+AA genotypes conferred to a lower risk for MM compared to all other subjects (padj = 0.017, and padj = 0.026). Telomere length was not associated with a response to chemotherapy (p > 0.05) or time to disease progression (p > 0.05). Carriers of one or two polymorphic rs10069690 T alleles had a good response to chemotherapy (p = 0.039, and p = 0.048), these associations remained statistically significant after adjustment for age (padj = 0.019; padj = 0.017). Carriers of two polymorphic rs2736100 A alleles had a longer time to disease progression (p = 0.038). CONCLUSIONS Shorter telomere length and hTERT polymorphisms may serve as a biomarker for the risk of developing MM. Additionally, rs10069690 and rs2736100 polymorphisms, but not telomere length, were associated with a chemotherapy response or MM progression.
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Affiliation(s)
- Ana Mervic
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Katja Goricar
- Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Tanja Blagus
- Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Alenka Franko
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
- Clinical Institute of Occupational Medicine, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Katarina Trebusak-Podkrajsek
- Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
- Clinical Institute for Special Laboratory Diagnostics, University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Metoda Dodic Fikfak
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
- Clinical Institute of Occupational Medicine, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Vita Dolzan
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
- Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Viljem Kovac
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
- Institute of Oncology Ljubljana, Ljubljana, Slovenia
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Fan Y, Zheng C, Ma R, Wang J, Yang S, Ye Q. MMP19 Variants in Familial and Sporadic Idiopathic Pulmonary Fibrosis. Lung 2023; 201:571-580. [PMID: 37971547 DOI: 10.1007/s00408-023-00652-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 10/16/2023] [Indexed: 11/19/2023]
Abstract
BACKGROUND Gene variants have been identified in patients with familial or sporadic idiopathic pulmonary fibrosis (IPF). These variants may partially account for the genetic risk of IPF. The aim of this study was to identify potential genes involved in both familial and sporadic IPF. METHODS A Han family in northern China with four members diagnosed with IPF was investigated in this observational study. Whole-exome sequencing (WES) was used to identify germline variants underlying disease phenotypes in five members of this family. Candidate rare variants were validated by Sanger sequencing in samples from 16 family members and 119 patients with sporadic IPF. The plasma levels of proteins encoded by the above candidate genes were also examined in 16 family members, 119 other patients with sporadic IPF and 120 age- and sex-matched healthy controls. RESULTS In a Chinese Han family, MMP19 c.1222 C > T was identified in all familial IPF patients and six offspring from generations III and IV. This variant introduces a premature stop codon, which may damage protein function. Sanger sequencing revealed that 7.6% (9/119) of sporadic IPF patients harbored three MMP19 variants. The genetic risk analysis for pulmonary fibrosis showed that MMP19 c.1499 C > T and c.1316G > A were significantly associated with an increased risk of IPF (OR 3.66, p = 0.028 and OR 8.64, p < 0.001, respectively). The plasma levels of MMP19 were significantly higher in patients with sporadic or familial IPF than in healthy controls (all p < 0.001). CONCLUSIONS MMP19 variants were identified in familial or sporadic IPF, thus providing a potential new clue into IPF pathogenesis.
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Affiliation(s)
- Yali Fan
- Clinical Center for Interstitial Lung Diseases, Beijing Institute of Respiratory Medicine, Beijing Chaoyang Hospital, Capital Medical University, No.8 Worker's Stadium, Chaoyang District, Beijing, 100020, China
- Department of Respiratory Medicine and Critical Care, Beijing Jishuitan Hospital, Beijing, 100035, China
| | - Chunming Zheng
- Clinical Center for Interstitial Lung Diseases, Beijing Institute of Respiratory Medicine, Beijing Chaoyang Hospital, Capital Medical University, No.8 Worker's Stadium, Chaoyang District, Beijing, 100020, China
- Department of Medical Research Center, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, China
| | - Ruimin Ma
- Clinical Center for Interstitial Lung Diseases, Beijing Institute of Respiratory Medicine, Beijing Chaoyang Hospital, Capital Medical University, No.8 Worker's Stadium, Chaoyang District, Beijing, 100020, China
| | - Jingwei Wang
- Clinical Center for Interstitial Lung Diseases, Beijing Institute of Respiratory Medicine, Beijing Chaoyang Hospital, Capital Medical University, No.8 Worker's Stadium, Chaoyang District, Beijing, 100020, China
| | - Shuqiao Yang
- Clinical Center for Interstitial Lung Diseases, Beijing Institute of Respiratory Medicine, Beijing Chaoyang Hospital, Capital Medical University, No.8 Worker's Stadium, Chaoyang District, Beijing, 100020, China
- Department of Respiratory and Critical Care Medicine, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, China
| | - Qiao Ye
- Clinical Center for Interstitial Lung Diseases, Beijing Institute of Respiratory Medicine, Beijing Chaoyang Hospital, Capital Medical University, No.8 Worker's Stadium, Chaoyang District, Beijing, 100020, China.
- Department of Occupational Medicine and Toxicology, Beijing Chaoyang Hospital, Capital Medical University, No.8 Worker's Stadium, Chaoyang District, Beijing, 100020, China.
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Zalay O, Bontempi D, Bitterman DS, Birkbak N, Shyr D, Haugg F, Qian JM, Roberts H, Perni S, Prudente V, Pai S, Dekker A, Haibe-Kains B, Guthier C, Balboni T, Warren L, Krishan M, Kann BH, Swanton C, Ruysscher DD, Mak RH, Aerts HJWL. Decoding biological age from face photographs using deep learning. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.12.23295132. [PMID: 37745558 PMCID: PMC10516042 DOI: 10.1101/2023.09.12.23295132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Because humans age at different rates, a person's physical appearance may yield insights into their biological age and physiological health more reliably than their chronological age. In medicine, however, appearance is incorporated into medical judgments in a subjective and non-standardized fashion. In this study, we developed and validated FaceAge, a deep learning system to estimate biological age from easily obtainable and low-cost face photographs. FaceAge was trained on data from 58,851 healthy individuals, and clinical utility was evaluated on data from 6,196 patients with cancer diagnoses from two institutions in the United States and The Netherlands. To assess the prognostic relevance of FaceAge estimation, we performed Kaplan Meier survival analysis. To test a relevant clinical application of FaceAge, we assessed the performance of FaceAge in end-of-life patients with metastatic cancer who received palliative treatment by incorporating FaceAge into clinical prediction models. We found that, on average, cancer patients look older than their chronological age, and looking older is correlated with worse overall survival. FaceAge demonstrated significant independent prognostic performance in a range of cancer types and stages. We found that FaceAge can improve physicians' survival predictions in incurable patients receiving palliative treatments, highlighting the clinical utility of the algorithm to support end-of-life decision-making. FaceAge was also significantly associated with molecular mechanisms of senescence through gene analysis, while age was not. These findings may extend to diseases beyond cancer, motivating using deep learning algorithms to translate a patient's visual appearance into objective, quantitative, and clinically useful measures.
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Affiliation(s)
- Osbert Zalay
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
- Division of Radiation Oncology, Queen’s University, Kingston, Canada
| | - Dennis Bontempi
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
- Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, The Netherlands
- Department of Radiation Oncology (MAASTRO), Maastricht University, Maastricht, The Netherlands
| | - Danielle S Bitterman
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
| | - Nicolai Birkbak
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Bioinformatics Research Center, Aarhus University, Aarhus, Denmark
| | - Derek Shyr
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston
| | - Fridolin Haugg
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
| | - Jack M Qian
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
| | - Hannah Roberts
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
| | - Subha Perni
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
| | - Vasco Prudente
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
- Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, The Netherlands
| | - Suraj Pai
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
- Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, The Netherlands
| | - Andre Dekker
- Department of Radiation Oncology (MAASTRO), Maastricht University, Maastricht, The Netherlands
| | - Benjamin Haibe-Kains
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Christian Guthier
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
| | - Tracy Balboni
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
| | - Laura Warren
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
| | - Monica Krishan
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
| | - Benjamin H Kann
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
| | - Charles Swanton
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK
| | - Dirk De Ruysscher
- Department of Radiation Oncology (MAASTRO), Maastricht University, Maastricht, The Netherlands
| | - Raymond H Mak
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
| | - Hugo JWL Aerts
- Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America
- Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America
- Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, The Netherlands
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, United States of America
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5
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Chen H, Liang W, Zheng W, Li F, Pan X, Lu Y. A novel telomere-related gene prognostic signature for survival and drug treatment efficiency prediction in lung adenocarcinoma. Aging (Albany NY) 2023; 15:7956-7973. [PMID: 37589509 PMCID: PMC10497012 DOI: 10.18632/aging.204877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 06/19/2023] [Indexed: 08/18/2023]
Abstract
OBJECTIVE Telomere-related genes (TRGs) play a critical role in various types of tumors. However, there is a lack of comprehensive exploration of their relevance in lung cancer. This research aimed to verify the relationship between TRGs gene expression and the prognosis of patients with lung adenocarcinoma (LUAD), as well as the prediction of drug treatment efficiency. METHODS A total of 2093 TRGs were acquired from TelNet. The clinical information including age, tumor stage, follow up and outcome (death/survival) and TRGs expression profile of LUAD were obtained from the patients in The Cancer Genome Atlas (TCGA) database and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. The two databases were used to construct and verify a prognostic model based on the expression of hubTRGs. The tumor mutation burden, immune infiltration and subtypes, as well as IC50 prediction of multiple targeted drugs were also evaluated in TRGs-divided risk groups. RESULTS A total of 335 TRGs were significantly differentially expressed in LUAD as compared with normal control. Among them, 9 TRGs (ABCC2, ABCC8, ALDH2, FOXP3, GNMT, JSRP1, MACF1, PLCD3, SULT4A1) were finally identified as hubGenes and used to construct a TRG risk score. The TRG risk score showed favorable performance in constructing a prognostic nomogram in predicting survival of LUAD, and the ROC curves at 1, 3 and 5 years were plotted and the AUROC values were 0.743, 0.754 and 0.735, respectively. Higher TRGs risk score correlated with worse immune subtypes and higher tumor mutation burden in LUAD tissues. In addition, the patients in TRG high risk group harbored a lower TIDE score which indicated potentially better response to immunotherapy. CONCLUSION This study proposed a broad molecular signature of telomere-related genes that can be used in further functional and therapeutic investigations, and also represents an integrated modality for characterizing critical molecules when exploring novel targets for lung cancer immunotherapy.
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Affiliation(s)
- Haiming Chen
- Department of Oncology, The Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, Guangdong Province 528200, China
| | - Weiquan Liang
- Department of Respiration, Foshan Second People's Hospital, Foshan, Guangdong Province 528000, China
| | - Weiqiang Zheng
- Department of Respiration, Foshan Second People's Hospital, Foshan, Guangdong Province 528000, China
| | - Feilong Li
- Department of Oncology, The Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, Guangdong Province 528200, China
| | - Xingxi Pan
- Department of Oncology, The Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, Guangdong Province 528200, China
| | - Yiyu Lu
- Department of Oncology, The Sixth Affiliated Hospital, School of Medicine, South China University of Technology, Foshan, Guangdong Province 528200, China
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6
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Forder A, Zhuang R, Souza VGP, Brockley LJ, Pewarchuk ME, Telkar N, Stewart GL, Benard K, Marshall EA, Reis PP, Lam WL. Mechanisms Contributing to the Comorbidity of COPD and Lung Cancer. Int J Mol Sci 2023; 24:ijms24032859. [PMID: 36769181 PMCID: PMC9918127 DOI: 10.3390/ijms24032859] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 01/18/2023] [Accepted: 01/22/2023] [Indexed: 02/05/2023] Open
Abstract
Lung cancer and chronic obstructive pulmonary disease (COPD) often co-occur, and individuals with COPD are at a higher risk of developing lung cancer. While the underlying mechanism for this risk is not well understood, its major contributing factors have been proposed to include genomic, immune, and microenvironment dysregulation. Here, we review the evidence and significant studies that explore the mechanisms underlying the heightened lung cancer risk in people with COPD. Genetic and epigenetic changes, as well as the aberrant expression of non-coding RNAs, predispose the lung epithelium to carcinogenesis by altering the expression of cancer- and immune-related genes. Oxidative stress generated by tobacco smoking plays a role in reducing genomic integrity, promoting epithelial-mesenchymal-transition, and generating a chronic inflammatory environment. This leads to abnormal immune responses that promote cancer development, though not all smokers develop lung cancer. Sex differences in the metabolism of tobacco smoke predispose females to developing COPD and accumulating damage from oxidative stress that poses a risk for the development of lung cancer. Dysregulation of the lung microenvironment and microbiome contributes to chronic inflammation, which is observed in COPD and known to facilitate cancer initiation in various tumor types. Further, there is a need to better characterize and identify the proportion of individuals with COPD who are at a high risk for developing lung cancer. We evaluate possible novel and individualized screening strategies, including biomarkers identified in genetic studies and exhaled breath condensate analysis. We also discuss the use of corticosteroids and statins as chemopreventive agents to prevent lung cancer. It is crucial that we optimize the current methods for the early detection and management of lung cancer and COPD in order to improve the health outcomes for a large affected population.
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Affiliation(s)
- Aisling Forder
- British Columbia Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
- Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Rebecca Zhuang
- British Columbia Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
- Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Vanessa G P Souza
- British Columbia Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
- Molecular Oncology Laboratory, Experimental Research Unit, School of Medicine, São Paulo State University (UNESP), Botucatu 18618-687, SP, Brazil
| | - Liam J Brockley
- British Columbia Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
- Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Michelle E Pewarchuk
- British Columbia Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
- Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Nikita Telkar
- British Columbia Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
- Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC V6H 3N1, Canada
- British Columbia Children's Hospital Research Institute, Vancouver, BC V5Z 4H4, Canada
| | - Greg L Stewart
- British Columbia Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
- Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Katya Benard
- British Columbia Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
| | - Erin A Marshall
- British Columbia Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
- Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Patricia P Reis
- Molecular Oncology Laboratory, Experimental Research Unit, School of Medicine, São Paulo State University (UNESP), Botucatu 18618-687, SP, Brazil
| | - Wan L Lam
- British Columbia Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada
- Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
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7
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Ruiz A, Flores-Gonzalez J, Buendia-Roldan I, Chavez-Galan L. Telomere Shortening and Its Association with Cell Dysfunction in Lung Diseases. Int J Mol Sci 2021; 23:425. [PMID: 35008850 PMCID: PMC8745057 DOI: 10.3390/ijms23010425] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 12/22/2021] [Accepted: 12/29/2021] [Indexed: 01/10/2023] Open
Abstract
Telomeres are localized at the end of chromosomes to provide genome stability; however, the telomere length tends to be shortened with each cell division inducing a progressive telomere shortening (TS). In addition to age, other factors, such as exposure to pollutants, diet, stress, and disruptions in the shelterin protein complex or genes associated with telomerase induce TS. This phenomenon favors cellular senescence and genotoxic stress, which increases the risk of the development and progression of lung diseases such as idiopathic pulmonary fibrosis, chronic obstructive pulmonary disease, SARS-CoV-2 infection, and lung cancer. In an infectious environment, immune cells that exhibit TS are associated with severe lymphopenia and death, whereas in a noninfectious context, naïve T cells that exhibit TS are related to cancer progression and enhanced inflammatory processes. In this review, we discuss how TS modifies the function of the immune system cells, making them inefficient in maintaining homeostasis in the lung. Finally, we discuss the advances in drug and gene therapy for lung diseases where TS could be used as a target for future treatments.
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Affiliation(s)
| | | | | | - Leslie Chavez-Galan
- Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City 14080, Mexico; (A.R.); (J.F.-G.); (I.B.-R.)
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Furuie H, Arimura-Omori M, Hamada N, Yanagihara T, Kiyohara C. The Association of Aging-Related Polymorphisms with Susceptibility to Lung Cancer: A Case-Control Study in a Japanese Population. Asian Pac J Cancer Prev 2021; 22:1279-1285. [PMID: 33906323 PMCID: PMC8325147 DOI: 10.31557/apjcp.2021.22.4.1279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Telomere length is associated with cancer as well as aging. Telomerase reverse transcriptase (TERT), telomere RNA component (TERC) and oligonucleotide/oligosaccharide-binding fold containing 1 (OBFC1) are known to be involved in telomere length regulation. The tumor suppressor p53 (TP53), which has been shown to interact with tumor protein p53-binding protein 1 (TP53BP1), is implicated in the response to telomere shortening and aging. Polymorphisms in the TP53 and TP53BP1 genes are associated with various types of cancer. The aim of this study is to evaluate the impact of aging-related polymorphisms on lung cancer risk. MATERIALS AND METHODS This case-control study consists of 462 lung cancer cases and 379 controls from Japan. We examined the effect of TERT rs2736100, TERC rs1881984, OBFC1 rs11191865, TP53 rs1042522 and TP53BP1 rs560191 on the risk of lung cancer using a Taq-Man real-time PCR assay. Unconditional logistic regression was used to assess the adjusted odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS None of the main effects of any of the telomere-related polymorphisms were related to the risk of lung cancer. Similarly, none of the interactive effects of any of the telomere-related polymorphisms with smoking were associated with lung cancer risk. The significant multiplicative interaction between TERT rs2736100 and TP53BP1 rs560191 was statistically significant (OR for interaction = 0.34, 95% CI = 0.14-0.84). The multiplicative interaction between OBFC1 rs11191865 and TP53BP1 rs560191 was also statistically significant (OR for interaction = 2.44, 95% CI = 1.02-5.87) but the OR for interaction was in the opposite direction. CONCLUSIONS Our findings indicate that TP53BP1 rs560191 may predispose to lung cancer risk depending on the genotypes of telomere-related polymorphisms. Additional studies are warranted to confirm the findings suggested in the present study.<br />.
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Affiliation(s)
- Hironobu Furuie
- Department of Preventive Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Masako Arimura-Omori
- Research Institute for Diseases of the Chest, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Naoki Hamada
- Research Institute for Diseases of the Chest, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Toyoshi Yanagihara
- Research Institute for Diseases of the Chest, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Chikako Kiyohara
- Department of Preventive Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
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Mild catalytic defects of tert rs61748181 polymorphism affect the clinical presentation of chronic obstructive pulmonary disease. Sci Rep 2021; 11:4333. [PMID: 33619289 PMCID: PMC7900122 DOI: 10.1038/s41598-021-83686-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Accepted: 02/03/2021] [Indexed: 11/29/2022] Open
Abstract
Chronic obstructive pulmonary disease (COPD) is a disorder of accelerated lung aging. Multiple pieces of evidence support that the aging biomarker short telomeres, which can be caused by mutations in telomerase reverse transcriptase (TERT), contribute to COPD pathogenesis. We hypothesized that short telomere risk-associated single nucleotide polymorphisms (SNPs) in TERT, while not able to drive COPD development, nonetheless modify the disease presentation. We set out to test the SNP carrying status in a longitudinal study of smokers with COPD and found that rapid decline of FEV1 in lung function was associated with the minor allele of rs61748181 (adjusted odds ratio 2.49, p = 0.038). Biochemical evaluation of ex vivo engineered human cell models revealed that primary cells expressing the minor allele of rs61748181 had suboptimal telomere length maintenance due to reduced telomerase catalytic activity, despite having comparable cell growth kinetics as WT-TERT expressing cells. This ex vivo observation translated clinically in that shorter telomeres were found in minor allele carriers in a sub-population of COPD patients with non-declining lung function, over the 5-year period of the longitudinal study. Collectively, our data suggest that functional TERT SNPs with mild catalytic defects are nonetheless implicated in the clinical presentation of COPD.
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