1
|
Zhao X, Yang M, Fan J, Wang M, Wang Y, Qin N, Zhu M, Jiang Y, Gorlova OY, Gorlov IP, Albanes D, Lam S, Tardón A, Chen C, Goodman GE, Bojesen SE, Landi MT, Johansson M, Risch A, Wichmann HE, Bickeböller H, Christiani DC, Rennert G, Arnold SM, Brennan P, Field JK, Shete S, Le Marchand L, Liu G, Hung RJ, Andrew AS, Kiemeney LA, Zienolddiny S, Grankvist K, Johansson M, Caporaso NE, Woll PJ, Lazarus P, Schabath MB, Aldrich MC, Patel AV, Davies MPA, Ma H, Jin G, Hu Z, Amos CI, Shen H, Dai J. Identification of genetically predicted DNA methylation markers associated with non-small cell lung cancer risk among 34,964 cases and 448,579 controls. Cancer 2024; 130:913-926. [PMID: 38055287 PMCID: PMC11327897 DOI: 10.1002/cncr.35130] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 05/05/2023] [Accepted: 05/22/2023] [Indexed: 12/07/2023]
Abstract
BACKGROUND Although the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non-small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated. METHODS The genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established. The prediction models were applied to a fixed-effect meta-analysis of screening data sets with 27,120 NSCLC cases and 27,355 controls to identify the methylation markers, which were then replicated in independent data sets with 7844 lung cancer cases and 421,224 controls. Also performed was a multi-omics functional annotation for the identified CpGs by integrating genomics, epigenomics, and transcriptomics and investigation of the potential regulation pathways. RESULTS Of the 29,894 CpG sites passing the quality control, 39 CpGs associated with NSCLC risk (Bonferroni-corrected p ≤ 1.67 × 10-6 ) were originally identified. Of these, 16 CpGs remained significant in the validation stage (Bonferroni-corrected p ≤ 1.28 × 10-3 ), including four novel CpGs. Multi-omics functional annotation showed nine of 16 CpGs were potentially functional biomarkers for NSCLC risk. Thirty-five genes within a 1-Mb window of 12 CpGs that might be involved in regulatory pathways of NSCLC risk were identified. CONCLUSIONS Sixteen promising DNA methylation markers associated with NSCLC were identified. Changes of the methylation level at these CpGs might influence the development of NSCLC by regulating the expression of genes nearby. PLAIN LANGUAGE SUMMARY The epigenetic consequences of DNA methylation in lung cancer development are still largely unknown. This study used summary data of large-scale genome-wide association studies to investigate the associations between genetically predicted levels of methylation biomarkers and non-small cell lung cancer risk at the first time. This study looked at how well larotrectinib worked in adult patients with sarcomas caused by TRK fusion proteins. These findings will provide a unique insight into the epigenetic susceptibility mechanisms of lung cancer.
Collapse
Affiliation(s)
- Xiaoyu Zhao
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Statistics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Meiqi Yang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jingyi Fan
- 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 and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
- Health Management Center, Gusu School, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Mei Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yifan Wang
- 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 and China International Cooperation Center for Environment and Human Health, Gusu School, 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 and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, 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, China
| | - Yue Jiang
- 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 and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| | - Olga Y Gorlova
- Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, USA
- Department of Medicine, Epidemiology Section, Institute for Clinical and Translational Research, Baylor Medical College, Houston, Texas, USA
| | - Ivan P Gorlov
- Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, USA
- Department of Medicine, Epidemiology Section, Institute for Clinical and Translational Research, Baylor Medical College, Houston, Texas, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Stephen Lam
- Department of Integrative Oncology, British Columbia Cancer Agency, Vancouver, British Columbia, Canada
| | - Adonina Tardón
- Department of Public Health IUOPA, University of Oviedo, ISPA and CIBERESP, Oviedo, Spain
| | - Chu Chen
- Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Gary E Goodman
- Public Health Sciences Division, Swedish Cancer Institute, Seattle, Washington, USA
| | - Stig E Bojesen
- Department of Clinical Biochemistry, Copenhagen University Hospital, Copenhagen, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Mattias Johansson
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Angela Risch
- Department of Biosciences, Allergy-Cancer-BioNano Research Centre, University of Salzburg, Salzburg, Austria
- Division of Epigenomics and Cancer Risk Factors, DKFZ-German Cancer Research Center, Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC-H), German Center for Lung Research (DZL), Heidelberg, Germany
| | - H-Erich Wichmann
- Institute of Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
| | - Heike Bickeböller
- Department of Genetic Epidemiology, University Medical Center Goettingen, Goettingen, Germany
| | - David C Christiani
- Departments of Environmental Health and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Gad Rennert
- Technion Faculty of Medicine, Carmel Medical Center, Haifa, Israel
| | - Susanne M Arnold
- Markey Cancer Center, University of Kentucky, Lexington, Kentucky, USA
| | - Paul Brennan
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - John K Field
- Molecular and Clinical Cancer Medicine, Roy Castle Lung Cancer Research Programme, The University of Liverpool Institute of Translational Medicine, Liverpool, UK
| | - Sanjay Shete
- Department of Epidemiology, The University of Texas, MD Anderson Cancer Center, Houston, Texas, USA
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawai'i Cancer Center, Honolulu, Hawaii, USA
| | - Geoffrey Liu
- Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Rayjean J Hung
- Prosseman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada
| | - Angeline S Andrew
- Department of Neurology, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire, USA
| | - Lambertus A Kiemeney
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Kjell Grankvist
- Department of Medical Biosciences, Umeå University, Umea, Sweden
| | | | - Neil E Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| | - Penella J Woll
- Academic Unit of Clinical Oncology, University of Sheffield, Sheffield, UK
| | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, Washington, 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 (Division of Genetic Medicine), Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Alpa V Patel
- Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, Georgia, USA
| | - Michael P A Davies
- Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - 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 and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| | - Guangfu Jin
- 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 and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| | - Zhibin Hu
- 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 and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| | - Christopher I Amos
- Baylor College of Medicine, Institute for Clinical and Translational Research, Houston, Texas, USA
| | - Hongbing Shen
- 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 and China International Cooperation Center for Environment and Human Health, Gusu School, 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 and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing, China
| |
Collapse
|
2
|
Liu Z, Yan W, Liu S, Liu Z, Xu P, Fang W. Regulatory network and targeted interventions for CCDC family in tumor pathogenesis. Cancer Lett 2023; 565:216225. [PMID: 37182638 DOI: 10.1016/j.canlet.2023.216225] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 05/03/2023] [Accepted: 05/10/2023] [Indexed: 05/16/2023]
Abstract
CCDC (coiled-coil domain-containing) is a coiled helix domain that exists in natural proteins. There are about 180 CCDC family genes, encoding proteins that are involved in intercellular transmembrane signal transduction and genetic signal transcription, among other functions. Alterations in expression, mutation, and DNA promoter methylation of CCDC family genes have been shown to be associated with the pathogenesis of many diseases, including primary ciliary dyskinesia, infertility, and tumors. In recent studies, CCDC family genes have been found to be involved in regulation of growth, invasion, metastasis, chemosensitivity, and other biological behaviors of malignant tumor cells in various cancer types, including nasopharyngeal carcinoma, lung cancer, colorectal cancer, and thyroid cancer. In this review, we summarize the involvement of CCDC family genes in tumor pathogenesis and the relevant upstream and downstream molecular mechanisms. In addition, we summarize the potential of CCDC family genes as tumor therapy targets. The findings discussed here help us to further understand the role and the therapeutic applications of CCDC family genes in tumors.
Collapse
Affiliation(s)
- Zhen Liu
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, 510315, Guangzhou, China.
| | - Weiwei Yan
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, 510315, Guangzhou, China
| | - Shaohua Liu
- Department of General Surgery, Pingxiang People's Hospital, Pingxiang, Jiangxi, 337000, China
| | - Zhan Liu
- Department of Gastroenterology and Clinical Nutrition, The First Affiliated Hospital (People's Hospital of Hunan Province), Hunan Normal University, Changsha, 410002, China
| | - Ping Xu
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, 510315, Guangzhou, China; Respiratory Department, Peking University Shenzhen Hospital, Shenzhen, 518034, China.
| | - Weiyi Fang
- Cancer Center, Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, 510315, Guangzhou, China.
| |
Collapse
|
3
|
Quintana I, Mur P, Terradas M, García-Mulero S, Aiza G, Navarro M, Piñol V, Brunet J, Moreno V, Sanz-Pamplona R, Capellá G, Valle L. Potential Involvement of NSD1, KRT24 and ACACA in the Genetic Predisposition to Colorectal Cancer. Cancers (Basel) 2022; 14:cancers14030699. [PMID: 35158968 PMCID: PMC8833793 DOI: 10.3390/cancers14030699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 01/26/2022] [Indexed: 01/27/2023] Open
Abstract
Simple Summary Methods used for the identification of hereditary cancer genes have evolved in parallel to technological progress; however, much of the genetic predisposition to cancer remains unexplained. A new in silico method based on Knudson’s two-hit hypothesis recently identified ~50 putative cancer predisposing genes, but their actual association with cancer has not yet been validated. In our study, we aimed to assess the involvement of these genes in familial/early-onset colorectal cancer (CRC) using different lines of evidence. Our results indicated that most of those genes were not associated with a genetic predisposition to CRC, but suggested a possible association for NSD1, KRT24 and ACACA. Abstract The ALFRED (Allelic Loss Featuring Rare Damaging) in silico method was developed to identify cancer predisposition genes through the identification of somatic second hits. By applying ALFRED to ~10,000 tumor exomes, 49 candidate genes were identified. We aimed to assess the causal association of the identified genes with colorectal cancer (CRC) predisposition. Of the 49 genes, NSD1, HDAC10, KRT24, ACACA and TP63 were selected based on specific criteria relevant for hereditary CRC genes. Gene sequencing was performed in 736 patients with familial/early onset CRC or polyposis without germline pathogenic variants in known genes. Twelve (predicted) damaging variants in 18 patients were identified. A gene-based burden test in 1596 familial/early-onset CRC patients, 271 polyposis patients, 543 TCGA CRC patients and >134,000 controls (gnomAD, non-cancer), revealed no clear association with CRC for any of the studied genes. Nevertheless, (non-significant) over-representation of disruptive variants in NSD1, KRT24 and ACACA in CRC patients compared to controls was observed. A somatic second hit was identified in one of 20 tumors tested, corresponding to an NSD1 carrier. In conclusion, most genes identified through the ALFRED in silico method were not relevant for CRC predisposition, although a possible association was detected for NSD1, KRT24 and ACACA.
Collapse
Affiliation(s)
- Isabel Quintana
- Hereditary Cancer Program, Catalan Institute of Oncology, Oncobell Program, IDIBELL, Hospitalet de Llobregat, 08908 Barcelona, Spain; (I.Q.); (P.M.); (M.T.); (G.A.); (M.N.); (J.B.); (G.C.)
| | - Pilar Mur
- Hereditary Cancer Program, Catalan Institute of Oncology, Oncobell Program, IDIBELL, Hospitalet de Llobregat, 08908 Barcelona, Spain; (I.Q.); (P.M.); (M.T.); (G.A.); (M.N.); (J.B.); (G.C.)
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain
| | - Mariona Terradas
- Hereditary Cancer Program, Catalan Institute of Oncology, Oncobell Program, IDIBELL, Hospitalet de Llobregat, 08908 Barcelona, Spain; (I.Q.); (P.M.); (M.T.); (G.A.); (M.N.); (J.B.); (G.C.)
| | - Sandra García-Mulero
- Unit of Biomarkers and Susceptibility, Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology, Hospitalet de Llobregat, 08908 Barcelona, Spain; (S.G.-M.); (V.M.); (R.S.-P.)
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain
| | - Gemma Aiza
- Hereditary Cancer Program, Catalan Institute of Oncology, Oncobell Program, IDIBELL, Hospitalet de Llobregat, 08908 Barcelona, Spain; (I.Q.); (P.M.); (M.T.); (G.A.); (M.N.); (J.B.); (G.C.)
| | - Matilde Navarro
- Hereditary Cancer Program, Catalan Institute of Oncology, Oncobell Program, IDIBELL, Hospitalet de Llobregat, 08908 Barcelona, Spain; (I.Q.); (P.M.); (M.T.); (G.A.); (M.N.); (J.B.); (G.C.)
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain
| | - Virginia Piñol
- Gastroenterology Unit, Hospital Universitario de Girona Dr. Josep Trueta, 17007 Girona, Spain;
| | - Joan Brunet
- Hereditary Cancer Program, Catalan Institute of Oncology, Oncobell Program, IDIBELL, Hospitalet de Llobregat, 08908 Barcelona, Spain; (I.Q.); (P.M.); (M.T.); (G.A.); (M.N.); (J.B.); (G.C.)
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain
- Catalan Institute of Oncology, IDIBGi, 17007 Girona, Spain
| | - Victor Moreno
- Unit of Biomarkers and Susceptibility, Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology, Hospitalet de Llobregat, 08908 Barcelona, Spain; (S.G.-M.); (V.M.); (R.S.-P.)
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain
- Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, 08907 Barcelona, Spain
| | - Rebeca Sanz-Pamplona
- Unit of Biomarkers and Susceptibility, Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology, Hospitalet de Llobregat, 08908 Barcelona, Spain; (S.G.-M.); (V.M.); (R.S.-P.)
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain
| | - Gabriel Capellá
- Hereditary Cancer Program, Catalan Institute of Oncology, Oncobell Program, IDIBELL, Hospitalet de Llobregat, 08908 Barcelona, Spain; (I.Q.); (P.M.); (M.T.); (G.A.); (M.N.); (J.B.); (G.C.)
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain
| | - Laura Valle
- Hereditary Cancer Program, Catalan Institute of Oncology, Oncobell Program, IDIBELL, Hospitalet de Llobregat, 08908 Barcelona, Spain; (I.Q.); (P.M.); (M.T.); (G.A.); (M.N.); (J.B.); (G.C.)
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain
- Correspondence:
| |
Collapse
|
4
|
Li L, Cao Y, Fan Y, Li R. Gene signature to predict prognostic survival of hepatocellular carcinoma. Open Med (Wars) 2022; 17:135-150. [PMID: 35071775 PMCID: PMC8742913 DOI: 10.1515/med-2021-0405] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 10/18/2021] [Accepted: 11/09/2021] [Indexed: 12/11/2022] Open
Abstract
Hepatocellular carcinoma (HCC) has a high incidence and poor prognosis and is the second most fatal cancer, and certain HCC patients also show high heterogeneity. This study developed a prognostic model for predicting clinical outcomes of HCC. RNA and microRNA (miRNA) sequencing data of HCC were obtained from the cancer genome atlas. RNA dysregulation between HCC tumors and adjacent normal liver tissues was examined by DESeq algorithms. Survival analysis was conducted to determine the basic prognostic indicators. We identified competing endogenous RNA (ceRNA) containing 15,364 pairs of mRNA–long noncoding RNA (lncRNA). An imbalanced ceRNA network comprising 8 miRNAs, 434 mRNAs, and 81 lncRNAs was developed using hypergeometric test. Functional analysis showed that these RNAs were closely associated with biosynthesis. Notably, 53 mRNAs showed a significant prognostic correlation. The least absolute shrinkage and selection operator’s feature selection detected four characteristic genes (SAPCD2, DKC1, CHRNA5, and UROD), based on which a four-gene independent prognostic signature for HCC was constructed using Cox regression analysis. The four-gene signature could stratify samples in the training, test, and external validation sets (p <0.01). Five-year survival area under ROC curve (AUC) in the training and validation sets was greater than 0.74. The current prognostic gene model exhibited a high stability and accuracy in predicting the overall survival (OS) of HCC patients.
Collapse
Affiliation(s)
- Li Li
- Department of Oncology, The Comprehensive Cancer Centre of Drum Tower Hospital, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University , Nanjing , Jiangsu, 210000 , China
| | - Yundi Cao
- Department of Medical Oncology, Affiliated Taikang Xianlin Drum Tower Hospital, Medical School of Nanjing University , Nanjing , Jiangsu , China
| | - YingRui Fan
- Department of Medical Oncology, Affiliated Taikang Xianlin Drum Tower Hospital, Medical School of Nanjing University , Nanjing , Jiangsu , China
| | - Rong Li
- Department of Medical Oncology, Affiliated Taikang Xianlin Drum Tower Hospital, Medical School of Nanjing University , Nanjing , Jiangsu , China
| |
Collapse
|
5
|
Wikramanayake TC, Nicu C, Chéret J, Czyzyk TA, Paus R. Mitochondrially localized MPZL3 emerges as a signaling hub of mammalian physiology. Bioessays 2021; 43:e2100126. [PMID: 34486148 DOI: 10.1002/bies.202100126] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Revised: 08/15/2021] [Accepted: 08/16/2021] [Indexed: 12/23/2022]
Abstract
MPZL3 is a nuclear-encoded, mitochondrially localized, immunoglobulin-like V-type protein that functions as a key regulator of epithelial cell differentiation, lipid metabolism, ROS production, glycemic control, and energy expenditure. Recently, MPZL3 has surfaced as an important modulator of sebaceous gland function and of hair follicle cycling, an organ transformation process that is also governed by peripheral clock gene activity and PPARγ. Given the phenotype similarities and differences between Mpzl3 and Pparγ knockout mice, we propose that MPZL3 serves as a signaling hub that is regulated by core clock gene products and/or PPARγ to translate signals from these nuclear transcription factors to the mitochondria to modulate circadian and metabolic regulation. Conservation between murine and human MPZL3 suggests that human MPZL3 may have similarly complex functions in health and disease. We summarize current knowledge and discuss future directions to elucidate the full spectrum of MPZL3 functions in mammalian physiology.
Collapse
Affiliation(s)
- Tongyu C Wikramanayake
- Dr Phillip Frost Department of Dermatology & Cutaneous Surgery, University of Miami Miller School of Medicine, Miami, Florida, USA.,Molecular Cell and Developmental Biology Program, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Carina Nicu
- Dr Phillip Frost Department of Dermatology & Cutaneous Surgery, University of Miami Miller School of Medicine, Miami, Florida, USA.,Wellcome MRC Cambridge Stem Cell Institute, University of Cambridge, Jeffrey Cheah Biomedical Centre, Cambridge, UK
| | - Jérémy Chéret
- Dr Phillip Frost Department of Dermatology & Cutaneous Surgery, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Traci A Czyzyk
- Department of Anesthesiology & Perioperative Medicine, Penn State University College of Medicine, Hershey, Pennsylvania, USA.,Metabolic Health Program, Mayo Clinic in Arizona, Scottsdale, Arizona, USA.,Discovery Biology-CMD, Merck & Co., Inc., South San Francisco, California, USA
| | - Ralf Paus
- Dr Phillip Frost Department of Dermatology & Cutaneous Surgery, University of Miami Miller School of Medicine, Miami, Florida, USA.,Monasterium Laboratory, Münster, Germany.,Centre for Dermatology Research, University of Manchester and NIHR Manchester Biomedical Research Centre, Manchester, UK
| |
Collapse
|
6
|
Zhu M, Fan J, Zhang C, Xu J, Yin R, Zhang E, Wang Y, Ji M, Sun Q, Dai J, Jin G, Chen L, Xu L, Hu Z, Ma H, Shen H. A cross-tissue transcriptome-wide association study identifies novel susceptibility genes for lung cancer in Chinese populations. Hum Mol Genet 2021; 30:1666-1676. [PMID: 33909040 DOI: 10.1093/hmg/ddab119] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 04/18/2021] [Accepted: 04/20/2021] [Indexed: 01/04/2023] Open
Abstract
Although dozens of susceptibility loci have been identified for lung cancer in genome-wide association studies (GWASs), the susceptibility genes and underlying mechanisms remain unclear. In this study, we conducted a cross-tissue transcriptome-wide association study (TWAS) with UTMOST based on summary statistics from 13 327 lung cancer cases and 13 328 controls and the genetic-expression matrix over 44 human tissues in the Genotype-Tissue Expression (GTEx) project. After further evaluating the associations in each tissue, we revealed 6 susceptibility genes in known loci and identified 12 novel ones. Among those, five novel genes, including DCAF16 (Pcross-tissue = 2.57 × 10-5, PLung = 2.89 × 10-5), CBL (Pcross-tissue = 5.08 × 10-7, PLung = 1.82 × 10-4), ATR (Pcross-tissue = 1.45 × 10-5, PLung = 9.68 × 10-5), GYPE (Pcross-tissue = 1.45 × 10-5, PLung = 2.17 × 10-3) and PARD3 (Pcross-tissue = 5.79 × 10-6, PLung = 4.05 × 10-3), were significantly associated with the risk of lung cancer in both cross-tissue and lung tissue models. Further colocalization analysis indicated that rs7667864 (C > A) and rs2298650 (G > T) drove the GWAS association signals at 4p15.31-32 (OR = 1.09, 95%CI: 1.04-1.12, PGWAS = 5.54 × 10-5) and 11q23.3 (OR = 1.08, 95%CI: 1.04-1.13, PGWAS = 5.55 × 10-5), as well as the expression of DCAF16 (βGTEx = 0.24, PGTEx = 9.81 × 10-15; βNJLCC = 0.29, PNJLCC = 3.84 × 10-8) and CBL (βGTEx = -0.17, PGTEx = 2.82 × 10-8; βNJLCC = -0.32, PNJLCC = 2.61 × 10-7) in lung tissue. Functional annotations and phenotype assays supported the carcinogenic effect of these novel susceptibility genes in lung carcinogenesis.
Collapse
Affiliation(s)
- 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.,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
| | - Jingyi Fan
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Chang Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.,Department of Epidemiology, School of Public Health, Southeast University, Nanjing 210009, China
| | - Jing Xu
- Department of Thoracic Surgery, the First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, 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
| | - Erbao 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
| | - Mengmeng Ji
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.,Department of Epidemiology, School of Public Health, Southeast University, Nanjing 210009, China
| | - Qi Sun
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, 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
| | - Guangfu Jin
- 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
| | - Liang Chen
- Department of Thoracic Surgery, the First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, 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
| | - 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
| | - 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
| | - Hongbing Shen
- 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
| |
Collapse
|
7
|
Benchmark of site- and structure-specific quantitative tissue N-glycoproteomics for discovery of potential N-glycoprotein markers: a case study of pancreatic cancer. Glycoconj J 2021; 38:213-231. [PMID: 33835347 DOI: 10.1007/s10719-021-09994-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Revised: 03/16/2021] [Accepted: 03/19/2021] [Indexed: 02/07/2023]
Abstract
Pancreatic cancer is a highly malignant tumor of the digestive tract that is difficult to diagnose and treat. It is more common in developed countries and has become one of the main causes of death in some countries and regions. Currently, pancreatic cancer generally has a poor prognosis, partly due to the lack of symptoms in the early stages of pancreatic cancer. Therefore, most cases are diagnosed at advanced stage. With the continuous in-depth research of glycoproteomics in precision medical diagnosis, there have been some reports on quantitative analysis of cancer-related cells, plasma or tissues to find specific biomarkers for targeted therapy. This research is based on the developed complete N-linked glycopeptide database search engine GPSeeker, combined with liquid-mass spectrometry and stable diethyl isotope labeling, providing a benchmark of site- and structure-specific quantitative tissue N-glycoproteomics for discovery of potential N-glycoprotein markers. With spectrum-level FDR ≤1%, 20,038 intact N-Glycopeptides corresponding to 4518 peptide backbones, 228 N-glycan monosaccharide compositions 1026 N-glycan putative structures, 4460 N-glycosites and 3437 intact N-glycoproteins were identified. With the criteria of ≥1.5-fold change and p value<0.05, 52 differentially expressed intact N-glycopeptides (DEGPs) were found in pancreatic cancer tussues relative to control, where 38 up-regulated and 14 down-regulated, respectively.
Collapse
|
8
|
Ni J, Deng B, Zhu M, Wang Y, Yan C, Wang T, Liu Y, Li G, Ding Y, Jin G. Integration of GWAS and eQTL Analysis to Identify Risk Loci and Susceptibility Genes for Gastric Cancer. Front Genet 2020; 11:679. [PMID: 32754194 PMCID: PMC7366424 DOI: 10.3389/fgene.2020.00679] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Accepted: 06/03/2020] [Indexed: 02/05/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified several susceptibility loci for gastric cancer (GC), but the majority of identified single-nucleotide polymorphisms (SNPs) fall within the non-coding region and are likely to exert their biological function by modulating gene expression. To systematically estimate expression-associated SNPs (eSNPs) that confer genetic predisposition to GC, we evaluated the associations of 314,203 stomach tissue-specific eSNPs with GC risk in three GWAS datasets (2,631 cases and 4,373 controls). Subsequently, we conducted a gene-based analysis to calculate the cumulative effect of eSNPs through sequence kernel association combined test and Sherlock integrative analysis. At the SNP-level, we identified two novel variants (rs836545 at 7p22.1 and rs1892252 at 6p22.2) associated with GC risk. The risk allele carriers of rs836545-T and rs1892252-G exhibited higher expression levels of DAGLB (P = 3.70 × 10–18) and BTN3A2 (P = 3.20 × 10–5), respectively. Gene-based analyses identified DAGLB and FBXO43 as novel susceptibility genes for GC. DAGLB and FBXO43 were significantly overexpressed in GC tissues than in their adjacent tissues (P = 5.59 × 10–7 and P = 3.90 × 10–6, respectively), and high expression level of these two genes was associated with an unfavorable prognosis of GC patients (P = 1.30 × 10–7 and P = 7.60 × 10–3, respectively). Co-expression genes with these two novel genes in normal stomach tissues were significantly enriched in several cancer-related pathways, including P53, MAPK and TGF-beta pathways. In summary, our findings confirm the importance of eSNPs in dissecting the genetic basis of GC, and the identified eSNPs and relevant genes will provide new insight into the genetic and biological basis for the mechanism of GC development.
Collapse
Affiliation(s)
- Jing Ni
- 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 Medicine, Nanjing Medical University, Nanjing, China
| | - Bin Deng
- Department of Gastroenterology, Affiliated Hospital of Yangzhou University, Yangzhou, 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 Medicine, Nanjing Medical University, Nanjing, China
| | - Yuzhuo Wang
- 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 Medicine, Nanjing Medical University, Nanjing, China
| | - Caiwang Yan
- 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 Medicine, Nanjing Medical University, Nanjing, China
| | - Tianpei Wang
- 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 Medicine, Nanjing Medical University, Nanjing, China
| | - Yaqian Liu
- 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 Medicine, Nanjing Medical University, Nanjing, China
| | - Gang Li
- Department of General Surgery, Jiangsu Institute of Cancer Research, Jiangsu Cancer Hospital, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Yanbing Ding
- Department of Gastroenterology, Affiliated Hospital of Yangzhou University, Yangzhou, China
| | - Guangfu Jin
- 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 Medicine, Nanjing Medical University, Nanjing, China
| |
Collapse
|
9
|
Wang Y, Gorlova OY, Gorlov IP, Zhu M, Dai J, Albanes D, Lam S, Tardon A, Chen C, Goodman GE, Bojesen SE, Landi MT, Johansson M, Risch A, Wichmann HE, Bickeboller H, Christiani DC, Rennert G, Arnold SM, Brennan P, Field JK, Shete S, Le Marchand L, Melander O, Brunnstrom H, Liu G, Hung RJ, Andrew AS, Kiemeney LA, Zienolddiny S, Grankvist K, Johansson M, Caporaso NE, Woll PJ, Lazarus P, Schabath MB, Aldrich MC, Stevens VL, Ma H, Jin G, Hu Z, Amos CI, Shen H. Association Analysis of Driver Gene-Related Genetic Variants Identified Novel Lung Cancer Susceptibility Loci with 20,871 Lung Cancer Cases and 15,971 Controls. Cancer Epidemiol Biomarkers Prev 2020; 29:1423-1429. [PMID: 32277007 PMCID: PMC8120681 DOI: 10.1158/1055-9965.epi-19-1085] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Revised: 11/10/2019] [Accepted: 04/07/2020] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND A substantial proportion of cancer driver genes (CDG) are also cancer predisposition genes. However, the associations between genetic variants in lung CDGs and the susceptibility to lung cancer have rarely been investigated. METHODS We selected expression-related single-nucleotide polymorphisms (eSNP) and nonsynonymous variants of lung CDGs, and tested their associations with lung cancer risk in two large-scale genome-wide association studies (20,871 cases and 15,971 controls of European descent). Conditional and joint association analysis was performed to identify independent risk variants. The associations of independent risk variants with somatic alterations in lung CDGs or recurrently altered pathways were investigated using data from The Cancer Genome Atlas (TCGA) project. RESULTS We identified seven independent SNPs in five lung CDGs that were consistently associated with lung cancer risk in discovery (P < 0.001) and validation (P < 0.05) stages. Among these loci, rs78062588 in TPM3 (1q21.3) was a new lung cancer susceptibility locus (OR = 0.86, P = 1.65 × 10-6). Subgroup analysis by histologic types further identified nine lung CDGs. Analysis of somatic alterations found that in lung adenocarcinomas, rs78062588[C] allele (TPM3 in 1q21.3) was associated with elevated somatic copy number of TPM3 (OR = 1.16, P = 0.02). In lung adenocarcinomas, rs1611182 (HLA-A in 6p22.1) was associated with truncation mutations of the transcriptional misregulation in cancer pathway (OR = 0.66, P = 1.76 × 10-3). CONCLUSIONS Genetic variants can regulate functions of lung CDGs and influence lung cancer susceptibility. IMPACT Our findings might help unravel biological mechanisms underlying lung cancer susceptibility.
Collapse
Affiliation(s)
- Yuzhuo Wang
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Thoracic Surgery, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China
| | - Olga Y Gorlova
- Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire
- Department of Medicine, Epidemiology Section, Institute for Clinical and Translational Research, Baylor Medical College, Houston, Texas
| | - Ivan P Gorlov
- Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire
- Department of Medicine, Epidemiology Section, Institute for Clinical and Translational Research, Baylor Medical College, Houston, Texas
| | - Meng Zhu
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Thoracic Surgery, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Juncheng Dai
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, 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 Medicine, Nanjing Medical University, Nanjing, China
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - Stephen Lam
- Department of Integrative Oncology, British Columbia Cancer Agency, Vancouver, British Columbia, Canada
| | - Adonina Tardon
- Department of Public Health IUOPA, University of Oviedo, ISPA and CIBERESP, Oviedo, Spain
| | - Chu Chen
- Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Gary E Goodman
- Public Health Sciences Division, Swedish Cancer Institute, 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
| | | | - Mattias Johansson
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Angela Risch
- University of Salzburg, Department of Biosciences, Allergy-Cancer-BioNano Research Centre, Salzburg, Austria
- Division of Epigenomics and Cancer Risk Factors, DKFZ-German Cancer Research Center, Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC-H), German Center for Lung Research (DZL), Heidelberg, Germany
| | - Heunz-Erich Wichmann
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Epidemiology, Ludwig Maximilians University, Munich, Bavaria, Germany
- Helmholtz Zentrum Munchen, German Research Center for Environmental Health (GmbH), Institute of Epidemiology, Neuherberg, Germany
- Institute of Medical Statistics and Epidemiology, Technical University Munich, Munich, Germany
| | - Heike Bickeboller
- Department of Genetic Epidemiology, University Medical Center Goettingen, Goettingen, Germany
| | - David C Christiani
- Departments of Environmental Health and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Gad Rennert
- Technion Faculty of Medicine, Carmel Medical Center, Haifa, Israel
| | - Susanne M Arnold
- Markey Cancer Center, University of Kentucky, Lexington, Kentucky
| | - Paul Brennan
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - John K Field
- Molecular and Clinical Cancer Medicine, Roy Castle Lung Cancer Research Programme, The University of Liverpool Institute of Translational Medicine, Liverpool, United Kingdom
| | - Sanjay Shete
- Department of Epidemiology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawai'i Cancer Center, Honolulu, Hawai'i
| | - Olle Melander
- Clinical Sciences, Lund University, Lund, Sweden
- Department of Internal Medicine, Skåne University Hospital, Malmö, Sweden
| | | | - Geoffrey Liu
- Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Rayjean J Hung
- Prosseman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada
| | - Angeline S Andrew
- Department of Neurology, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire
| | - Lambertus A Kiemeney
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Kjell Grankvist
- Department of Medical Biosciences, Umeå University, Umea, Sweden
| | | | - Neil E Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland
| | - Penella J Woll
- Academic Unit of Clinical Oncology, University of Sheffield, Sheffield, United Kingdom
| | - 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 (Division of Genetic Medicine), Vanderbilt University Medical Center, Nashville, Tennessee
| | - Victoria L Stevens
- Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, Georgia
| | - Hongxia Ma
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, 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 Medicine, Nanjing Medical University, Nanjing, China
| | - Guangfu Jin
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, 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 Medicine, Nanjing Medical University, Nanjing, China
| | - Zhibin Hu
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, 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 Medicine, Nanjing Medical University, Nanjing, China
| | - Christopher I Amos
- Department of Medicine, Epidemiology Section, Institute for Clinical and Translational Research, Baylor Medical College, Houston, Texas.
| | - Hongbing Shen
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, 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 Medicine, Nanjing Medical University, Nanjing, China
| |
Collapse
|
10
|
Zhao Q, Zhuang K, Han K, Tang H, Wang Y, Si W, Yang Z. Silencing DVL3 defeats MTX resistance and attenuates stemness via Notch Signaling Pathway in colorectal cancer. Pathol Res Pract 2020; 216:152964. [PMID: 32414668 DOI: 10.1016/j.prp.2020.152964] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 03/20/2020] [Accepted: 04/11/2020] [Indexed: 01/17/2023]
Abstract
Chemoresistance and recurrence of colorectal cancer are mainly caused by the existence of cancer stem-like cells. Dishevelled-3 (DVL3) is a common member of both Wnt/β-catenin pathway and the Notch signaling pathway, which were involved in cancer progression, chemoresistance and even maintenance of stem cell-like properties. However, the underlying biological function of DVL3 still remains unclear. In this study, we proposed DVL3 was simultaneously involved in Methotrexate (MTX) resistance and Colorectal cancer (CRC) stemness by bioinformatic analysis. We also demonstrated DVL3 knockdown sensitized CRC cells to MTX and inhibited their stem cell-like properties by functional experiments. As for the mechanism, DVL3 silencing attenuated the activated Notch signaling by down-regulating Notch intracellular domain (NICD) as well as its downstream targets. Additionally, we demonstrated that CRC cancer tissues had greater DVL3 expression than adjacent non-cancer tissues and patients' overall survival was closely associated with DVL3 according to the data in our clinical center. Accordingly, our data suggest that DVL3 is a key regulator in CRC stemness and chemoresistance and targeting DVL3 could be a potential strategy for CRC therapy.
Collapse
Affiliation(s)
- Qian Zhao
- Department of Gastroenterology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, PR China
| | - Kun Zhuang
- Department of Gastroenterology, Xi'an Central Hospital, Xi'an, Shaanxi 710061, PR China
| | - Kun Han
- Department of Gastroenterology, Xi'an Central Hospital, Xi'an, Shaanxi 710061, PR China
| | - Hailing Tang
- Department of Gastroenterology, Xi'an Central Hospital, Xi'an, Shaanxi 710061, PR China
| | - Yu Wang
- Department of Gastroenterology, Xi'an Central Hospital, Xi'an, Shaanxi 710061, PR China
| | - Wangli Si
- Department of Gastroenterology, Xi'an Central Hospital, Xi'an, Shaanxi 710061, PR China
| | - Zhenwei Yang
- Department of Gastroenterology, Xi'an Central Hospital, Xi'an, Shaanxi 710061, PR China.
| |
Collapse
|
11
|
Dai J, Li Z, Amos CI, Hung RJ, Tardon A, Andrew AS, Chen C, Christiani DC, Albanes D, van der Heijden EHFM, Duell EJ, Rennert G, Mckay JD, Yuan JM, Field JK, Manjer J, Grankvist K, Le Marchand L, Teare MD, Schabath MB, Aldrich MC, Tsao MS, Lazarus P, Lam S, Bojesen SE, Arnold S, Wu X, Haugen A, Janout V, Johansson M, Brhane Y, Fernandez-Somoano A, Kiemeney LA, Davies MPA, Zienolddiny S, Hu Z, Shen H. Systematic analyses of regulatory variants in DNase I hypersensitive sites identified two novel lung cancer susceptibility loci. Carcinogenesis 2020; 40:432-440. [PMID: 30590402 DOI: 10.1093/carcin/bgy187] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 11/26/2018] [Accepted: 12/22/2018] [Indexed: 02/03/2023] Open
Abstract
DNase I hypersensitive sites (DHS) are abundant in regulatory elements, such as promoter, enhancer and transcription factor binding sites. Many studies have revealed that disease-associated variants were concentrated in DHS-related regions. However, limited studies are available on the roles of DHS-related variants in lung cancer. In this study, we performed a large-scale case-control study with 20 871 lung cancer cases and 15 971 controls to evaluate the associations between regulatory genetic variants in DHS and lung cancer susceptibility. The expression quantitative trait loci (eQTL) analysis and pathway-enrichment analysis were performed to identify the possible target genes and pathways. In addition, we performed motif-based analysis to explore the lung-cancer-related motifs using sequence kernel association test. Two novel variants, rs186332 in 20q13.3 (C>T, odds ratio [OR] = 1.17, 95% confidence interval [95% CI]: 1.10-1.24, P = 8.45 × 10-7) and rs4839323 in 1p13.2 (T>C, OR = 0.92, 95% CI: 0.89-0.95, P = 1.02 × 10-6) showed significant association with lung cancer risk. The eQTL analysis suggested that these two SNPs might regulate the expression of MRGBP and SLC16A1, respectively. What's more, the expression of both MRGBP and SLC16A1 was aberrantly elevated in lung tumor tissues. The motif-based analysis identified 10 motifs related to the risk of lung cancer (P < 1.71 × 10-4). Our findings suggested that variants in DHS might modify lung cancer susceptibility through regulating the expression of surrounding genes. This study provided us a deeper insight into the roles of DHS-related genetic variants for lung cancer.
Collapse
Affiliation(s)
- Juncheng Dai
- Department of Epidemiology, Center for Global Health, International Joint Research Center, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center of Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Zhihua Li
- Department of Epidemiology, Center for Global Health, International Joint Research Center, School of Public Health, Nanjing Medical University, Nanjing, China.,Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Christopher I Amos
- Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA
| | - Rayjean J Hung
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada.,Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Adonina Tardon
- Faculty of Medicine, IUOPA, University of Oviedo and CIBERESP, Oviedo, Spain
| | - Angeline S Andrew
- Norris Cotton Cancer Center, Geisel School of Medicine, Hanover, NH, USA
| | - Chu Chen
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - David C Christiani
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Demetrios Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | | | - Eric J Duell
- Unit of Nutrition and Cancer, Catalan Institute of Oncology (ICO), Barcelona, Spain
| | - Gad Rennert
- Clalit National Cancer Control Center, Carmel Medical Center, Haifa, Israel
| | - James D Mckay
- International Agency for Research on Cancer (IARC), World Health Organization, Lyon, France
| | - Jian-Min Yuan
- University of Pittsburgh Cancer Institute, Pittsburgh, PA, USA
| | - John K Field
- Roy Castle Lung Cancer Research Programme, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, The William Duncan Building, Liverpool, UK
| | - Jonas Manjer
- Unit for Breast Surgery, Department of Surgery, Lund University, Malmö, Sweden.,Department of Surgery, Skåne University Hospital, Malmö, Sweden
| | - Kjell Grankvist
- Department of Medical Biosciences, Umeå University, Umeå, Sweden
| | - Loic Le Marchand
- Epidemiology Program, University of Hawai'i Cancer Center, Honolulu, HI, USA
| | - M Dawn Teare
- School of Health and Related Research, University of Sheffield, Sheffield, South Yorkshire, UK
| | - Matthew B Schabath
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Melinda C Aldrich
- Department of Thoracic Surgery, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy, Washington State University, Spokane, WA, USA
| | - Stephen Lam
- British Columbia Cancer Agency, Vancouver, British Columbia, Canada
| | - Stig E Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Denmark.,Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Denmark.,Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Susanne Arnold
- Division of Medical Oncology Markey Cancer Center, Lexington, KY, USA
| | - Xifeng Wu
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Aage Haugen
- Department of Chemical and Biological Work Environment, National Institute of Occupational Health (STAMI), Oslo, Norway
| | - Vladimir Janout
- Department of Epidemiology and Public Health, Faculty of Health Sciences, Palacky University, Olomouc, Czech Republic
| | | | - Yonathan Brhane
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada.,Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | | | - Lambertus A Kiemeney
- Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - Michael P A Davies
- Roy Castle Lung Cancer Research Programme, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, The William Duncan Building, Liverpool, UK
| | - Shanbeh Zienolddiny
- Department of Chemical and Biological Work Environment, National Institute of Occupational Health (STAMI), Oslo, Norway
| | - Zhibin Hu
- Department of Epidemiology, Center for Global Health, International Joint Research Center, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center of Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, International Joint Research Center, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center of Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| |
Collapse
|
12
|
Fan Z, Xue W, Li L, Zhang C, Lu J, Zhai Y, Suo Z, Zhao J. Identification of an early diagnostic biomarker of lung adenocarcinoma based on co-expression similarity and construction of a diagnostic model. J Transl Med 2018; 16:205. [PMID: 30029648 PMCID: PMC6053739 DOI: 10.1186/s12967-018-1577-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Accepted: 07/13/2018] [Indexed: 12/13/2022] Open
Abstract
Background The purpose of this study was to achieve early and accurate diagnosis of lung cancer and long-term monitoring of the therapeutic response. Methods We downloaded GSE20189 from GEO database as analysis data. We also downloaded human lung adenocarcinoma RNA-seq transcriptome expression data from the TCGA database as validation data. Finally, the expression of all of the genes underwent z test normalization. We used ANOVA to identify differentially expressed genes specific to each stage, as well as the intersection between them. Two methods, correlation analysis and co-expression network analysis, were used to compare the expression patterns and topological properties of each stage. Using the functional quantification algorithm, we evaluated the functional level of each significantly enriched biological function under different stages. A machine-learning algorithm was used to screen out significant functions as features and to establish an early diagnosis model. Finally, survival analysis was used to verify the correlation between the outcome and the biomarkers that we found. Results We screened 12 significant biomarkers that could distinguish lung cancer patients with diverse risks. Patients carrying variations in these 12 genes also presented a poor outcome in terms of survival status compared with patients without variations. Conclusions We propose a new molecular-based noninvasive detection method. According to the expression of the stage-specific gene set in the peripheral blood of patients with lung cancer, the difference in the functional level is quantified to realize the early diagnosis and prediction of lung cancer.
Collapse
Affiliation(s)
- Zhirui Fan
- Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Wenhua Xue
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Lifeng Li
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.,Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Chaoqi Zhang
- Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Jingli Lu
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Yunkai Zhai
- Center of Telemedicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.,Engineering Laboratory for Digital Telemedicine Service, Zhengzhou, 450052, Henan, China
| | - Zhenhe Suo
- Cancer Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Jie Zhao
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China. .,Center of Telemedicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China. .,Engineering Laboratory for Digital Telemedicine Service, Zhengzhou, 450052, Henan, China.
| |
Collapse
|