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Guo X, Ping J, Yang Y, Su X, Shu XO, Wen W, Chen Z, Zhang Y, Tao R, Jia G, He J, Cai Q, Zhang Q, Giles GG, Pearlman R, Rennert G, Vodicka P, Phipps A, Gruber SB, Casey G, Peters U, Long J, Lin W, Zheng W. Large-Scale Alternative Polyadenylation-Wide Association Studies to Identify Putative Cancer Susceptibility Genes. Cancer Res 2024; 84:2707-2719. [PMID: 38759092 PMCID: PMC11326986 DOI: 10.1158/0008-5472.can-24-0521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 03/26/2024] [Accepted: 05/15/2024] [Indexed: 05/19/2024]
Abstract
Alternative polyadenylation (APA) modulates mRNA processing in the 3'-untranslated regions (3' UTR), affecting mRNA stability and translation efficiency. Research into genetically regulated APA has the potential to provide insights into cancer risk. In this study, we conducted large APA-wide association studies to investigate associations between APA levels and cancer risk. Genetic models were built to predict APA levels in multiple tissues using genotype and RNA sequencing data from 1,337 samples from the Genotype-Tissue Expression project. Associations of genetically predicted APA levels with cancer risk were assessed by applying the prediction models to data from large genome-wide association studies of six common cancers among European ancestry populations: breast, ovarian, prostate, colorectal, lung, and pancreatic cancers. A total of 58 risk genes (corresponding to 76 APA sites) were associated with at least one type of cancer, including 25 genes previously not linked to cancer susceptibility. Of the identified risk APAs, 97.4% and 26.3% were supported by 3'-UTR APA quantitative trait loci and colocalization analyses, respectively. Luciferase reporter assays for four selected putative regulatory 3'-UTR variants demonstrated that the risk alleles of 3'-UTR variants, rs324015 (STAT6), rs2280503 (DIP2B), rs1128450 (FBXO38), and rs145220637 (LDHA), significantly increased the posttranscriptional activities of their target genes compared with reference alleles. Furthermore, knockdown of the target genes confirmed their ability to promote proliferation and migration. Overall, this study provides insights into the role of APA in the genetic susceptibility to common cancers. Significance: Systematic evaluation of associations of alternative polyadenylation with cancer risk reveals 58 putative susceptibility genes, highlighting the contribution of genetically regulated alternative polyadenylation of 3'UTRs to genetic susceptibility to cancer.
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Affiliation(s)
- Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Jie Ping
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Yaohua Yang
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
- Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, Charlottesville, Virginia
| | - Xinwan Su
- International Institutes of Medicine, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, Zhejiang University, Yiwu, China
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Zhishan Chen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Yunjing Zhang
- International Institutes of Medicine, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, Zhejiang University, Yiwu, China
| | - Ran Tao
- Department of Biostatistics, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Guochong Jia
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Jingni He
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, Canada
- Department of Medical Genetics, University of Calgary, Calgary, Canada
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Qingrun Zhang
- Department of Mathematics and Statistics, Alberta Children's Hospital Research Institute, Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Canada
| | - Graham G Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - Rachel Pearlman
- Division of Human Genetics, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio
| | - Gad Rennert
- Department of Community Medicine and Epidemiology, Lady Davis Carmel Medical Center, Haifa, Israel
| | - Pavel Vodicka
- Department of Molecular Biology of Cancer, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czech Republic
- Institute of Biology and Medical Genetics, First Faculty of Medicine, Charles University, Prague, Czech Republic
- Faculty of Medicine and Biomedical Center in Pilsen, Charles University, Pilsen, Czech Republic
| | - Amanda Phipps
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Department of Epidemiology, University of Washington School of Public Health, Seattle, Washington
| | - Stephen B Gruber
- Department of Preventive Medicine and USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Graham Casey
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Department of Epidemiology, University of Washington School of Public Health, Seattle, Washington
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Weiqiang Lin
- International Institutes of Medicine, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, Zhejiang University, Yiwu, China
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
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He J, Perera D, Wen W, Ping J, Li Q, Lyu L, Chen Z, Shu X, Long J, Cai Q, Shu XO, Zheng W, Long Q, Guo X. Enhancing Disease Risk Gene Discovery by Integrating Transcription Factor-Linked Trans-located Variants into Transcriptome-Wide Association Analyses. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.10.10.23295443. [PMID: 37873299 PMCID: PMC10593059 DOI: 10.1101/2023.10.10.23295443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Transcriptome-wide association studies (TWAS) have been successful in identifying disease susceptibility genes by integrating cis-variants predicted gene expression with genome-wide association studies (GWAS) data. However, trans-located variants for predicting gene expression remain largely unexplored. Here, we introduce transTF-TWAS, which incorporates transcription factor (TF)-linked trans-located variants to enhance model building. Using data from the Genotype-Tissue Expression project, we predict gene expression and alternative splicing and applied these models to large GWAS datasets for breast, prostate, and lung cancers. We demonstrate that transTF-TWAS outperforms other existing TWAS approaches in both constructing gene prediction models and identifying disease-associated genes, as evidenced by simulations and real data analysis. Our transTF-TWAS approach significantly contributes to the discovery of disease risk genes. Findings from this study have shed new light on several genetically driven key regulators and their associated regulatory networks underlying disease susceptibility.
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3
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Li JL, McClellan JC, Zhang H, Gao G, Huo D. Multi-tissue transcriptome-wide association studies identified 235 genes for intrinsic subtypes of breast cancer. J Natl Cancer Inst 2024; 116:1105-1115. [PMID: 38400758 PMCID: PMC11223833 DOI: 10.1093/jnci/djae041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 01/25/2024] [Accepted: 02/20/2024] [Indexed: 02/26/2024] Open
Abstract
BACKGROUND Although genome-wide association studies (GWAS) of breast cancer (BC) identified common variants which differ between intrinsic subtypes, genes through which these variants act to impact BC risk have not been fully established. Transcriptome-wide association studies (TWAS) have identified genes associated with overall BC risk, but subtype-specific differences are largely unknown. METHODS We performed two multi-tissue TWAS for each BC intrinsic subtype, including an expression-based approach that collated TWAS signals from expression quantitative trait loci (eQTLs) across multiple tissues and a novel splicing-based approach that collated signals from splicing QTLs (sQTLs) across intron clusters and subsequently across tissues. We used summary statistics for five intrinsic subtypes including Luminal A-like, Luminal B-like, Luminal B/HER2-negative-like, HER2-enriched-like, and triple-negative BC, generated from 106 278 BC cases and 91 477 controls in the Breast Cancer Association Consortium. RESULTS Overall, we identified 235 genes in 88 loci that were associated with at least one of the five intrinsic subtypes. Most genes were subtype-specific, and many have not been reported in previous TWAS. We discovered common variants that modulate expression of CHEK2 confer increased risk to Luminal A-like BC, in contrast to the viewpoint that CHEK2 primarily harbors rare, penetrant mutations. Additionally, our splicing-based TWAS provided population-level support for MDM4 splice variants that increased the risk of triple-negative BC. CONCLUSION Our comprehensive, multi-tissue TWAS corroborated previous GWAS loci for overall BC risk and intrinsic subtypes, while underscoring how common variation that impacts expression and splicing of genes in multiple tissue types can be used to further elucidate the etiology of BC.
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Affiliation(s)
- James L Li
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Julian C McClellan
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Haoyu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Guimin Gao
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Dezheng Huo
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
- Department of Medicine, Section of Hematology and Oncology, University of Chicago, IL, USA
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4
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Gao G, McClellan J, Barbeira AN, Fiorica PN, Li JL, Mu Z, Olopade OI, Huo D, Im HK. A multi-tissue, splicing-based joint transcriptome-wide association study identifies susceptibility genes for breast cancer. Am J Hum Genet 2024; 111:1100-1113. [PMID: 38733992 PMCID: PMC11179262 DOI: 10.1016/j.ajhg.2024.04.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 04/13/2024] [Accepted: 04/15/2024] [Indexed: 05/13/2024] Open
Abstract
Splicing-based transcriptome-wide association studies (splicing-TWASs) of breast cancer have the potential to identify susceptibility genes. However, existing splicing-TWASs test the association of individual excised introns in breast tissue only and thus have limited power to detect susceptibility genes. In this study, we performed a multi-tissue joint splicing-TWAS that integrated splicing-TWAS signals of multiple excised introns in each gene across 11 tissues that are potentially relevant to breast cancer risk. We utilized summary statistics from a meta-analysis that combined genome-wide association study (GWAS) results of 424,650 women of European ancestry. Splicing-level prediction models were trained in GTEx (v.8) data. We identified 240 genes by the multi-tissue joint splicing-TWAS at the Bonferroni-corrected significance level; in the tissue-specific splicing-TWAS that combined TWAS signals of excised introns in genes in breast tissue only, we identified nine additional significant genes. Of these 249 genes, 88 genes in 62 loci have not been reported by previous TWASs, and 17 genes in seven loci are at least 1 Mb away from published GWAS index variants. By comparing the results of our splicing-TWASs with previous gene-expression-based TWASs that used the same summary statistics and expression prediction models trained in the same reference panel, we found that 110 genes in 70 loci that are identified only by the splicing-TWASs. Our results showed that for many genes, expression quantitative trait loci (eQTL) did not show a significant impact on breast cancer risk, whereas splicing quantitative trait loci (sQTL) showed a strong impact through intron excision events.
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Affiliation(s)
- Guimin Gao
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Julian McClellan
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Alvaro N Barbeira
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Peter N Fiorica
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - James L Li
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Zepeng Mu
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Olufunmilayo I Olopade
- Section of Hematology and Oncology, Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Dezheng Huo
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA; Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA.
| | - Hae Kyung Im
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA.
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5
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Li Q, Song Q, Chen Z, Choi J, Moreno V, Ping J, Wen W, Li C, Shu X, Yan J, Shu XO, Cai Q, Long J, Huyghe JR, Pai R, Gruber SB, Casey G, Wang X, Toriola AT, Li L, Singh B, Lau KS, Zhou L, Wu C, Peters U, Zheng W, Long Q, Yin Z, Guo X. Large-scale integration of omics and electronic health records to identify potential risk protein biomarkers and therapeutic drugs for cancer prevention and intervention. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.29.24308170. [PMID: 38853880 PMCID: PMC11160851 DOI: 10.1101/2024.05.29.24308170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Identifying risk protein targets and their therapeutic drugs is crucial for effective cancer prevention. Here, we conduct integrative and fine-mapping analyses of large genome-wide association studies data for breast, colorectal, lung, ovarian, pancreatic, and prostate cancers, and characterize 710 lead variants independently associated with cancer risk. Through mapping protein quantitative trait loci (pQTL) for these variants using plasma proteomics data from over 75,000 participants, we identify 365 proteins associated with cancer risk. Subsequent colocalization analysis identifies 101 proteins, including 74 not reported in previous studies. We further characterize 36 potential druggable proteins for cancers or other disease indications. Analyzing >3.5 million electronic health records, we uncover five drugs (Haloperidol, Trazodone, Tranexamic Acid, Haloperidol, and Captopril) associated with increased cancer risk and two drugs (Caffeine and Acetazolamide) linked to reduced colorectal cancer risk. This study offers novel insights into therapeutic drugs targeting risk proteins for cancer prevention and intervention.
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6
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Chen Z, Song W, Shu XO, Wen W, Devall M, Dampier C, Moratalla-Navarro F, Cai Q, Long J, Van Kaer L, Wu L, Huyghe JR, Thomas M, Hsu L, Woods MO, Albanes D, Buchanan DD, Gsur A, Hoffmeister M, Vodicka P, Wolk A, Marchand LL, Wu AH, Phipps AI, Moreno V, Ulrike P, Zheng W, Casey G, Guo X. Novel insights into genetic susceptibility for colorectal cancer from transcriptome-wide association and functional investigation. J Natl Cancer Inst 2024; 116:127-137. [PMID: 37632791 PMCID: PMC10777674 DOI: 10.1093/jnci/djad178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 07/10/2023] [Accepted: 08/19/2023] [Indexed: 08/28/2023] Open
Abstract
BACKGROUND Transcriptome-wide association studies have been successful in identifying candidate susceptibility genes for colorectal cancer (CRC). To strengthen susceptibility gene discovery, we conducted a large transcriptome-wide association study and an alternative splicing transcriptome-wide association study in CRC using improved genetic prediction models and performed in-depth functional investigations. METHODS We analyzed RNA-sequencing data from normal colon tissues and genotype data from 423 European descendants to build genetic prediction models of gene expression and alternative splicing and evaluated model performance using independent RNA-sequencing data from normal colon tissues of the Genotype-Tissue Expression Project. We applied the verified models to genome-wide association studies (GWAS) summary statistics among 58 131 CRC cases and 67 347 controls of European ancestry to evaluate associations of genetically predicted gene expression and alternative splicing with CRC risk. We performed in vitro functional assays for 3 selected genes in multiple CRC cell lines. RESULTS We identified 57 putative CRC susceptibility genes, which included the 48 genes from transcriptome-wide association studies and 15 genes from splicing transcriptome-wide association studies, at a Bonferroni-corrected P value less than .05. Of these, 16 genes were not previously implicated in CRC susceptibility, including a gene PDE7B (6q23.3) at locus previously not reported by CRC GWAS. Gene knockdown experiments confirmed the oncogenic roles for 2 unreported genes, TRPS1 and METRNL, and a recently reported gene, C14orf166. CONCLUSION This study discovered new putative susceptibility genes of CRC and provided novel insights into the biological mechanisms underlying CRC development.
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Affiliation(s)
- Zhishan Chen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Wenqiang Song
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Matthew Devall
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Christopher Dampier
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Ferran Moratalla-Navarro
- Oncology Data Analytics Program, Catalan Institute of Oncology (ICO), L’Hospitalet de Llobregat, Barcelona, Spain
- Colorectal Cancer Group, ONCOBELL Program, Institut de Recerca Biomedica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Barcelona, Spain
- Department of Clinical Sciences, Faculty of Medicine and Health Sciences and Universitat de Barcelona Institute of Complex Systems (UBICS), University of Barcelona (UB), L’Hospitalet de Llobregat, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Luc Van Kaer
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lan Wu
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jeroen R Huyghe
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Minta Thomas
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Li Hsu
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Michael O Woods
- Memorial University of Newfoundland, Discipline of Genetics, St. John’s, ON, Canada
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Daniel D Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, VIC, Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, VIC, Australia
- Genetic Medicine and Family Cancer Clinic, The Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Andrea Gsur
- Center for Cancer Research, Medical University of Vienna, Vienna, Austria
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Pavel Vodicka
- Department of Molecular Biology of Cancer, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czech Republic
- Institute of Biology and Medical Genetics, First Faculty of Medicine, Charles University, Prague, Czech Republic
- Faculty of Medicine and Biomedical Center in Pilsen, Charles University, Pilsen, Czech Republic
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | | | - Anna H Wu
- Preventative Medicine, University of Southern California, Los Angeles, CA, USA
| | - Amanda I Phipps
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Victor Moreno
- Oncology Data Analytics Program, Catalan Institute of Oncology (ICO), L’Hospitalet de Llobregat, Barcelona, Spain
- Colorectal Cancer Group, ONCOBELL Program, Institut de Recerca Biomedica de Bellvitge (IDIBELL), L’Hospitalet de Llobregat, Barcelona, Spain
- Department of Clinical Sciences, Faculty of Medicine and Health Sciences and Universitat de Barcelona Institute of Complex Systems (UBICS), University of Barcelona (UB), L’Hospitalet de Llobregat, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Peters Ulrike
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Graham Casey
- Department of Public Health Sciences, Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, USA
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7
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Guo X, Ping J, Yang Y, Su X, Shu XO, Wen W, Chen Z, Zhang Y, Tao R, Jia G, He J, Cai Q, Zhang Q, Giles GG, Pearlman R, Rennert G, Vodicka P, Phipps A, Gruber SB, Casey G, Peters U, Long J, Lin W, Zheng W. Large-scale alternative polyadenylation (APA)-wide association studies to identify putative susceptibility genes in human common cancers. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.05.23298125. [PMID: 37986797 PMCID: PMC10659493 DOI: 10.1101/2023.11.05.23298125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Alternative polyadenylation (APA) modulates mRNA processing in the 3' untranslated regions (3'UTR), which affect mRNA stability and translation efficiency. Here, we build genetic models to predict APA levels in multiple tissues using sequencing data of 1,337 samples from the Genotype-Tissue Expression, and apply these models to assess associations between genetically predicted APA levels and cancer risk with data from large genome-wide association studies of six common cancers, including breast, ovary, prostate, colorectum, lung, and pancreas among European-ancestry populations. At a Bonferroni-corrected P □<□0.05, we identify 58 risk genes, including seven in newly identified loci. Using luciferase reporter assays, we demonstrate that risk alleles of 3'UTR variants, rs324015 ( STAT6 ), rs2280503 ( DIP2B ), rs1128450 ( FBXO38 ) and rs145220637 ( LDAH ), could significantly increase post-transcriptional activities of their target genes compared to reference alleles. Further gene knockdown experiments confirm their oncogenic roles. Our study provides additional insight into the genetic susceptibility of these common cancers.
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8
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Fazilaty H, Basler K. Reactivation of embryonic genetic programs in tissue regeneration and disease. Nat Genet 2023; 55:1792-1806. [PMID: 37904052 DOI: 10.1038/s41588-023-01526-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 09/11/2023] [Indexed: 11/01/2023]
Abstract
Embryonic genetic programs are reactivated in response to various types of tissue damage, providing cell plasticity for tissue regeneration or disease progression. In acute conditions, these programs remedy the damage and then halt to allow a return to homeostasis. In chronic situations, including inflammatory diseases, fibrosis and cancer, prolonged activation of embryonic programs leads to disease progression and tissue deterioration. Induction of progenitor identity and cell plasticity, for example, epithelial-mesenchymal plasticity, are critical outcomes of reactivated embryonic programs. In this Review, we describe molecular players governing reactivated embryonic genetic programs, their role during disease progression, their similarities and differences and lineage reversion in pathology and discuss associated therapeutics and drug-resistance mechanisms across many organs. We also discuss the diversity of reactivated programs in different disease contexts. A comprehensive overview of commonalities between development and disease will provide better understanding of the biology and therapeutic strategies.
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Affiliation(s)
- Hassan Fazilaty
- Department of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.
| | - Konrad Basler
- Department of Molecular Life Sciences, University of Zürich, Zürich, Switzerland
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9
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Qian L, Li N, Lu XC, Xu M, Liu Y, Li K, Zhang Y, Hu K, Qi YT, Yao J, Wu YL, Wen W, Huang S, Chen ZJ, Yin M, Lei QY. Enhanced BCAT1 activity and BCAA metabolism promotes RhoC activity in cancer progression. Nat Metab 2023; 5:1159-1173. [PMID: 37337119 DOI: 10.1038/s42255-023-00818-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 05/05/2023] [Indexed: 06/21/2023]
Abstract
Increased expression of branched-chain amino acid transaminase 1 or 2 (BCAT1 and BCAT2) has been associated with aggressive phenotypes of different cancers. Here we identify a gain of function of BCAT1 glutamic acid to alanine mutation at codon 61 (BCAT1E61A) enriched around 2.8% in clinical gastric cancer samples. We found that BCAT1E61A confers higher enzymatic activity to boost branched-chain amino acid (BCAA) catabolism, accelerate cell growth and motility and contribute to tumor development. BCAT1 directly interacts with RhoC, leading to elevation of RhoC activity. Notably, the BCAA-derived metabolite, branched-chain α-keto acid directly binds to the small GTPase protein RhoC and promotes its activity. BCAT1 knockout-suppressed cell motility could be rescued by expressing BCAT1E61A or adding branched-chain α-keto acid. We also identified that candesartan acts as an inhibitor of BCAT1E61A, thus repressing RhoC activity and cancer cell motility in vitro and preventing peritoneal metastasis in vivo. Our study reveals a link between BCAA metabolism and cell motility and proliferation through regulating RhoC activation, with potential therapeutic implications for cancers.
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Affiliation(s)
- Lin Qian
- Fudan University Shanghai Cancer Center & Institutes of Biomedical Sciences; School of Basic Medical Sciences; Cancer Institutes; Key Laboratory of Breast Cancer in Shanghai; Shanghai Key Laboratory of Radiation Oncology; The Shanghai Key Laboratory of Medical Epigenetics, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Na Li
- Fudan University Shanghai Cancer Center & Institutes of Biomedical Sciences; School of Basic Medical Sciences; Cancer Institutes; Key Laboratory of Breast Cancer in Shanghai; Shanghai Key Laboratory of Radiation Oncology; The Shanghai Key Laboratory of Medical Epigenetics, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Biochemistry and Molecular Cell Biology, Key Laboratory of Cell Differentiation and Apoptosis of National Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiao-Chen Lu
- Fudan University Shanghai Cancer Center & Institutes of Biomedical Sciences; School of Basic Medical Sciences; Cancer Institutes; Key Laboratory of Breast Cancer in Shanghai; Shanghai Key Laboratory of Radiation Oncology; The Shanghai Key Laboratory of Medical Epigenetics, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Midie Xu
- Fudan University Shanghai Cancer Center & Institutes of Biomedical Sciences; School of Basic Medical Sciences; Cancer Institutes; Key Laboratory of Breast Cancer in Shanghai; Shanghai Key Laboratory of Radiation Oncology; The Shanghai Key Laboratory of Medical Epigenetics, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Pathology, Fudan University Shanghai Cancer Center; Institute of Pathology, Fudan University, Shanghai, China
| | - Ying Liu
- Department of Pathology, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Kaiyue Li
- Fudan University Shanghai Cancer Center & Institutes of Biomedical Sciences; School of Basic Medical Sciences; Cancer Institutes; Key Laboratory of Breast Cancer in Shanghai; Shanghai Key Laboratory of Radiation Oncology; The Shanghai Key Laboratory of Medical Epigenetics, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yi Zhang
- Fudan University Shanghai Cancer Center & Institutes of Biomedical Sciences; School of Basic Medical Sciences; Cancer Institutes; Key Laboratory of Breast Cancer in Shanghai; Shanghai Key Laboratory of Radiation Oncology; The Shanghai Key Laboratory of Medical Epigenetics, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Kewen Hu
- Fudan University Shanghai Cancer Center & Institutes of Biomedical Sciences; School of Basic Medical Sciences; Cancer Institutes; Key Laboratory of Breast Cancer in Shanghai; Shanghai Key Laboratory of Radiation Oncology; The Shanghai Key Laboratory of Medical Epigenetics, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yu-Ting Qi
- Fudan University Shanghai Cancer Center & Institutes of Biomedical Sciences; School of Basic Medical Sciences; Cancer Institutes; Key Laboratory of Breast Cancer in Shanghai; Shanghai Key Laboratory of Radiation Oncology; The Shanghai Key Laboratory of Medical Epigenetics, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jun Yao
- Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Ying-Li Wu
- Hongqiao International Institute of Medicine, Shanghai Tongren Hospital/Faculty of Basic Medicine, Chemical Biology Division of Shanghai Universities E-Institutes, Key Laboratory of Cell Differentiation and Apoptosis of the Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenyu Wen
- Fudan University Shanghai Cancer Center & Institutes of Biomedical Sciences; School of Basic Medical Sciences; Cancer Institutes; Key Laboratory of Breast Cancer in Shanghai; Shanghai Key Laboratory of Radiation Oncology; The Shanghai Key Laboratory of Medical Epigenetics, Shanghai Medical College, Fudan University, Shanghai, China
- State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China
| | - Shenglin Huang
- Fudan University Shanghai Cancer Center & Institutes of Biomedical Sciences; School of Basic Medical Sciences; Cancer Institutes; Key Laboratory of Breast Cancer in Shanghai; Shanghai Key Laboratory of Radiation Oncology; The Shanghai Key Laboratory of Medical Epigenetics, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zheng-Jun Chen
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai, China
| | - Miao Yin
- Fudan University Shanghai Cancer Center & Institutes of Biomedical Sciences; School of Basic Medical Sciences; Cancer Institutes; Key Laboratory of Breast Cancer in Shanghai; Shanghai Key Laboratory of Radiation Oncology; The Shanghai Key Laboratory of Medical Epigenetics, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Qun-Ying Lei
- Fudan University Shanghai Cancer Center & Institutes of Biomedical Sciences; School of Basic Medical Sciences; Cancer Institutes; Key Laboratory of Breast Cancer in Shanghai; Shanghai Key Laboratory of Radiation Oncology; The Shanghai Key Laboratory of Medical Epigenetics, Shanghai Medical College, Fudan University, Shanghai, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
- State Key Laboratory of Medical Neurobiology, Fudan University, Shanghai, China.
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10
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Jia G, Yang Y, Ping J, Xu S, Liu L, Guo X, Tao R, Long J, Zheng W. Identification of target proteins for breast cancer genetic risk loci and blood risk biomarkers in a large study by integrating genomic and proteomic data. Int J Cancer 2023; 152:2314-2320. [PMID: 36779764 PMCID: PMC10079603 DOI: 10.1002/ijc.34472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 01/24/2023] [Accepted: 02/03/2023] [Indexed: 02/14/2023]
Abstract
Genome-wide association studies (GWAS) have identified around 200 loci associated with breast cancer risk. However, protein targets for these loci remain largely unknown. Identifying protein targets and biomarkers can improve the understanding of cancer biology and etiology and identify high-risk individuals for cancer prevention. In this study, we investigated genetically predicted levels of 1142 circulating proteins with breast cancer risk in 133 384 cases and 113 789 controls of European ancestry included in the Breast Cancer Association Consortium (BCAC). We identified 22 blood protein biomarkers associated with the risk of overall breast cancer at a false discovery rate (FDR) <0.05, including nine proteins encoded by genes located at least 500 kb away from previously reported risk variants for breast cancer. Analyses focusing on 124 encoding genes located at GWAS-identified breast cancer risk loci found 20 proteins associated with overall breast cancer risk and one protein associated with triple-negative breast cancer risk at FDR <0.05. Adjustment for the GWAS-identified risk variants significantly attenuated the association for 13 of these proteins, suggesting that these proteins may be the targets of these GWAS-identified risk loci. The identified proteins are involved in various biological processes, including glutathione conjugation, STAT5 signaling and NF-κB signaling pathways. Our study identified novel protein targets and risk biomarkers for breast cancer risk.
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Affiliation(s)
- Guochong Jia
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yaohua Yang
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Center for Public Health Genomics, Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Jie Ping
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Shuai Xu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lili Liu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
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11
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Gao G, Fiorica PN, McClellan J, Barbeira AN, Li JL, Olopade OI, Im HK, Huo D. A joint transcriptome-wide association study across multiple tissues identifies candidate breast cancer susceptibility genes. Am J Hum Genet 2023; 110:950-962. [PMID: 37164006 PMCID: PMC10257003 DOI: 10.1016/j.ajhg.2023.04.005] [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: 01/28/2023] [Accepted: 04/14/2023] [Indexed: 05/12/2023] Open
Abstract
Genome-wide association studies (GWASs) have identified more than 200 genomic loci for breast cancer risk, but specific causal genes in most of these loci have not been identified. In fact, transcriptome-wide association studies (TWASs) of breast cancer performed using gene expression prediction models trained in breast tissue have yet to clearly identify most target genes. To identify candidate genes, we performed a GWAS analysis in a breast cancer dataset from UK Biobank (UKB) and combined the results with the GWAS results of the Breast Cancer Association Consortium (BCAC) by a meta-analysis. Using the summary statistics from the meta-analysis, we performed a joint TWAS analysis that combined TWAS signals from multiple tissues. We used expression prediction models trained in 11 tissues that are potentially relevant to breast cancer from the Genotype-Tissue Expression (GTEx) data. In the GWAS analysis, we identified eight loci distinct from those reported previously. In the TWAS analysis, we identified 309 genes at 108 genomic loci to be significantly associated with breast cancer at the Bonferroni threshold. Of these, 17 genes were located in eight regions that were at least 1 Mb away from published GWAS hits. The remaining TWAS-significant genes were located in 100 known genomic loci from previous GWASs of breast cancer. We found that 21 genes located in known GWAS loci remained statistically significant after conditioning on previous GWAS index variants. Our study provides insights into breast cancer genetics through mapping candidate target genes in a large proportion of known GWAS loci and discovering multiple new loci.
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Affiliation(s)
- Guimin Gao
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Peter N Fiorica
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Julian McClellan
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Alvaro N Barbeira
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - James L Li
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Olufunmilayo I Olopade
- Section of Hematology & Oncology, Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Hae Kyung Im
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA.
| | - Dezheng Huo
- Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA; Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL 60637, USA.
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12
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Zhao Z, Meng M, Yao J, Zhou H, Chen Y, Liu J, Wang J, Liu Y, Qiao Y, Zhang M, Qi J, Zhang T, Zhou Z, Jiang T, Shang B, Zhou Q. The long non-coding RNA keratin-7 antisense acts as a new tumor suppressor to inhibit tumorigenesis and enhance apoptosis in lung and breast cancers. Cell Death Dis 2023; 14:293. [PMID: 37185462 PMCID: PMC10130017 DOI: 10.1038/s41419-023-05802-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 03/31/2023] [Accepted: 04/06/2023] [Indexed: 05/17/2023]
Abstract
Expression of the long non-coding RNA (lncRNA) keratin-7 antisense (KRT7-AS) is downregulated in various types of cancer; however, the impact of KRT7-AS deficiency on tumorigenesis and apoptosis is enigmatic. We aim to explore the influence of KRT7-AS in carcinogenesis and apoptosis. We found that KRT7-AS was deficient in breast and lung cancers, and low levels of KRT7-AS were a poor prognostic factor in breast cancer. Cellular studies showed that silencing of KRT7-AS in lung cancer cells increased oncogenic Keratin-7 levels and enhanced tumorigenesis, but diminished cancer apoptosis of the cancer cells; by contrast, overexpression of KRT7-AS inhibited lung cancer cell tumorigenesis. Additionally, KRT7-AS sensitized cancer cells to the anti-cancer drug cisplatin, consequently enhancing cancer cell apoptosis. In vivo, KRT7-AS overexpression significantly suppressed tumor growth in xenograft mice, while silencing of KRT7-AS promoted tumor growth. Mechanistically, KRT7-AS reduced the levels of oncogenic Keratin-7 and significantly elevated amounts of the key tumor suppressor PTEN in cancer cells through directly binding to PTEN protein via its core nucleic acid motif GGCAAUGGCGG. This inhibited the ubiquitination-proteasomal degradation of PTEN protein, therefore elevating PTEN levels in cancer cells. We also found that KRT7-AS gene transcription was driven by the transcription factor RXRα; intriguingly, the small molecule berberine enhanced KRT7-AS expression, reduced tumorigenesis, and promoted apoptosis of cancer cells. Collectively, KRT7-AS functions as a new tumor suppressor and an apoptosis enhancer in lung and breast cancers, and we unraveled that the RXRα-KRT7-AS-PTEN signaling axis controls carcinogenesis and apoptosis. Our findings highlight a tumor suppressive role of endogenous KRT7-AS in cancers and an important effect the RXRα-KRT7-AS-PTEN axis on control of cancer cell tumorigenesis and apoptosis, and offer a new platform for developing novel therapeutics against cancers.
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Affiliation(s)
- Zhe Zhao
- Cyrus Tang Hematology Center, Jiangsu Institute of Hematology, Soochow University, Suzhou, Jiangsu, 215123, PR China
- CAS Key Laboratory of Nano-Bio Interface, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, Jiangsu, 215123, PR China
| | - Mei Meng
- Cyrus Tang Hematology Center, Jiangsu Institute of Hematology, Soochow University, Suzhou, Jiangsu, 215123, PR China
| | - Jun Yao
- Department of General Surgery, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, Jiangsu, 215123, PR China
| | - Hao Zhou
- Department of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215006, PR China
| | - Yu Chen
- Cyrus Tang Hematology Center, Jiangsu Institute of Hematology, Soochow University, Suzhou, Jiangsu, 215123, PR China
| | - Juntao Liu
- Cyrus Tang Hematology Center, Jiangsu Institute of Hematology, Soochow University, Suzhou, Jiangsu, 215123, PR China
| | - Jie Wang
- Department of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215006, PR China
| | - Yuxi Liu
- Cyrus Tang Hematology Center, Jiangsu Institute of Hematology, Soochow University, Suzhou, Jiangsu, 215123, PR China
| | - Yingnan Qiao
- Cyrus Tang Hematology Center, Jiangsu Institute of Hematology, Soochow University, Suzhou, Jiangsu, 215123, PR China
| | - Mengli Zhang
- Cyrus Tang Hematology Center, Jiangsu Institute of Hematology, Soochow University, Suzhou, Jiangsu, 215123, PR China
| | - Jindan Qi
- School of Nursing, Soochow University, Suzhou, Jiangsu, 215006, PR China
| | - Tong Zhang
- Cyrus Tang Hematology Center, Jiangsu Institute of Hematology, Soochow University, Suzhou, Jiangsu, 215123, PR China
| | - Zhou Zhou
- Cyrus Tang Hematology Center, Jiangsu Institute of Hematology, Soochow University, Suzhou, Jiangsu, 215123, PR China
| | - Tao Jiang
- Department of Pathology, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, Jiangsu, 215123, PR China
| | - Bingxue Shang
- Institutes for Translational Medicine, State Key Laboratory of Radiation Medicine and Protection, Soochow University, 215123, Suzhou, PR China
- State Key Laboratory of Radiation Medicine and Protection, School of Radiation Medicine and Protection, Soochow University, Suzhou, Jiangsu, 215123, PR China
- The First Affiliated Hospital of Soochow University, Suzhou, PR China
| | - Quansheng Zhou
- Cyrus Tang Hematology Center, Jiangsu Institute of Hematology, Soochow University, Suzhou, Jiangsu, 215123, PR China.
- State Key Laboratory of Radiation Medicine and Protection, School of Radiation Medicine and Protection, Soochow University, Suzhou, Jiangsu, 215123, PR China.
- National Clinical Research Center for Hematologic Diseases, The Affiliated Hospital of Soochow University, Suzhou, PR China.
- Key Laboratory of Thrombosis and Hemostasis, Ministry of Health; Soochow University, Suzhou, Jiangsu, 215123, PR China.
- 2011 Collaborative Innovation Center of Hematology, Soochow University, Suzhou, Jiangsu, 215123, PR China.
- The Ninth Affiliated Hospital, Soochow University, Suzhou, Jiangsu, 215123, PR China.
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13
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Jia G, Ping J, Shu X, Yang Y, Cai Q, Kweon SS, Choi JY, Kubo M, Park SK, Bolla MK, Dennis J, Wang Q, Guo X, Li B, Tao R, Aronson KJ, Chan TL, Gao YT, Hartman M, Ho WK, Ito H, Iwasaki M, Iwata H, John EM, Kasuga Y, Kim MK, Kurian AW, Kwong A, Li J, Lophatananon A, Low SK, Mariapun S, Matsuda K, Matsuo K, Muir K, Noh DY, Park B, Park MH, Shen CY, Shin MH, Spinelli JJ, Takahashi A, Tseng C, Tsugane S, Wu AH, Yamaji T, Zheng Y, Dunning AM, Pharoah PDP, Teo SH, Kang D, Easton DF, Simard J, Shu XO, Long J, Zheng W. Genome- and transcriptome-wide association studies of 386,000 Asian and European-ancestry women provide new insights into breast cancer genetics. Am J Hum Genet 2022; 109:2185-2195. [PMID: 36356581 PMCID: PMC9748250 DOI: 10.1016/j.ajhg.2022.10.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 10/20/2022] [Indexed: 11/10/2022] Open
Abstract
By combining data from 160,500 individuals with breast cancer and 226,196 controls of Asian and European ancestry, we conducted genome- and transcriptome-wide association studies of breast cancer. We identified 222 genetic risk loci and 137 genes that were associated with breast cancer risk at a p < 5.0 × 10-8 and a Bonferroni-corrected p < 4.6 × 10-6, respectively. Of them, 32 loci and 15 genes showed a significantly different association between ER-positive and ER-negative breast cancer after Bonferroni correction. Significant ancestral differences in risk variant allele frequencies and their association strengths with breast cancer risk were identified. Of the significant associations identified in this study, 17 loci and 14 genes are located 1Mb away from any of the previously reported breast cancer risk variants. Pathways analyses including 221 putative risk genes identified multiple signaling pathways that may play a significant role in the development of breast cancer. Our study provides a comprehensive understanding of and new biological insights into the genetics of this common malignancy.
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Affiliation(s)
- Guochong Jia
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA
| | - Jie Ping
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA
| | - Xiang Shu
- Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yaohua Yang
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA
| | - Sun-Seog Kweon
- Department of Preventive Medicine, Chonnam National University Medical School, Hwasun, Korea; Jeonnam Regional Cancer Center, Chonnam National University Hwasun Hospital, Hwasun, Korea
| | - Ji-Yeob Choi
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea; Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea; Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Sue K Park
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea; Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea; Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA
| | - Bingshan Li
- Department of Molecular Physiology & Biophysics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kristan J Aronson
- Department of Public Health Sciences and Queen's Cancer Research Institute, Queen's University, Kingston, ON, Canada
| | - Tsun L Chan
- Hong Kong Hereditary Breast Cancer Family Registry, Hong Kong SAR, China; Department of Molecular Pathology, Hong Kong Sanatorium & Hospital, Hong Kong SAR, China
| | - Yu-Tang Gao
- State Key Laboratory of Oncogene and Related Genes & Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Mikael Hartman
- Department of Surgery, National University Hospital, Singapore, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore; Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Weang Kee Ho
- Department of Applied Mathematics, Faculty of Engineering, University of Nottingham Malaysia Campus, Semenyih, Selangor, Malaysia
| | - Hidemi Ito
- Division of Cancer Information and Control, Aichi Cancer Center Research Institute, Nagoya, Japan; Department of Descriptive Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Motoki Iwasaki
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Hiroji Iwata
- Department of Breast Oncology, Aichi Cancer Center, Nagoya, Aichi, Japan
| | - Esther M John
- Departments of Epidemiology, Cancer Prevention Institute of California, Fremont, CA, USA; Departments of Health Research and Policy, School of Medicine, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Yoshio Kasuga
- Department of Surgery, Nagano Matsushiro General Hospital, Nagano, Japan
| | - Mi-Kyung Kim
- Division of Cancer Epidemiology and Management, National Cancer Center, Goyang, Korea
| | - Allison W Kurian
- Departments of Health Research and Policy, School of Medicine, Stanford University, Stanford, CA, USA
| | - Ava Kwong
- Hong Kong Hereditary Breast Cancer Family Registry, Hong Kong SAR, China; Department of Surgery, University of Hong Kong, Hong Kong SAR, China; Department of Surgery, Hong Kong Sanatorium & Hospital, Hong Kong SAR, China
| | - Jingmei Li
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; Human Genetics, Genome Institute of Singapore, Singapore, Singapore; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Artitaya Lophatananon
- Division of Health Sciences, Warwick Medical School, Warwick University, Coventry, UK; Institute of Population Health, University of Manchester, Manchester, UK
| | - Siew-Kee Low
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | | | - Koichi Matsuda
- Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Keitaro Matsuo
- Division of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan; Division of Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kenneth Muir
- Division of Health Sciences, Warwick Medical School, Warwick University, Coventry, UK; Institute of Population Health, University of Manchester, Manchester, UK
| | - Dong-Young Noh
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea; Department of Surgery, Seoul National University Hospital, Seoul, South Korea
| | - Boyoung Park
- Department of Medicine, Hanyang University College of Medicine, Seoul, Korea
| | - Min-Ho Park
- Department of Surgery, Chonnam National University Medical School, Gwangju, Korea
| | - Chen-Yang Shen
- College of Public Health, China Medical University, Taichong, Taiwan; Taiwan Biobank, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Min-Ho Shin
- Department of Preventive Medicine, Chonnam National University Medical School, Hwasun, Korea
| | - John J Spinelli
- Department of Cancer Control Research, British Columbia Cancer Agency, Vancouver, BC, Canada; School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
| | - Atsushi Takahashi
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; Department of Genomic Medicine, Research Institute, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
| | - Chiuchen Tseng
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Shoichiro Tsugane
- National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan
| | - Anna H Wu
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Taiki Yamaji
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Ying Zheng
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Soo-Hwang Teo
- Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia; Department of Surgery, Faculty of Medicine, University Malaya, Kuala Lumpar, Malaysia
| | - Daehee Kang
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea; Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea; Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Korea; Institute of Environmental Medicine, Seoul National University Medical Research Center, Seoul, Korea
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Jacques Simard
- Genomics Center, Centre Hospitalier Universitaire de Québec - Université Laval, Research Center, Québec City, QC, Canada
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN, USA.
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14
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He J, Wen W, Beeghly A, Chen Z, Cao C, Shu XO, Zheng W, Long Q, Guo X. Integrating transcription factor occupancy with transcriptome-wide association analysis identifies susceptibility genes in human cancers. Nat Commun 2022; 13:7118. [PMID: 36402776 PMCID: PMC9675749 DOI: 10.1038/s41467-022-34888-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 11/10/2022] [Indexed: 11/21/2022] Open
Abstract
Transcriptome-wide association studies (TWAS) have successfully discovered many putative disease susceptibility genes. However, TWAS may suffer from inaccuracy of gene expression predictions due to inclusion of non-regulatory variants. By integrating prior knowledge of susceptible transcription factor occupied elements, we develop sTF-TWAS and demonstrate that it outperforms existing TWAS approaches in both simulation and real data analyses. Under the sTF-TWAS framework, we build genetic models to predict alternative splicing and gene expression in normal breast, prostate and lung tissues from the Genotype-Tissue Expression project and apply these models to data from large genome-wide association studies (GWAS) conducted among European-ancestry populations. At Bonferroni-corrected P < 0.05, we identify 354 putative susceptibility genes for these cancers, including 189 previously unreported in GWAS loci and 45 in loci unreported by GWAS. These findings provide additional insight into the genetic susceptibility of human cancers. Additionally, we show the generalizability of the sTF-TWAS on non-cancer diseases.
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Affiliation(s)
- Jingni He
- grid.22072.350000 0004 1936 7697Department of Biochemistry & Molecular Biology, University of Calgary, Calgary, Canada ,grid.452223.00000 0004 1757 7615Department of Oncology, Xiangya Hospital, Central South University, Changsha, Hunan China
| | - Wanqing Wen
- grid.152326.10000 0001 2264 7217Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN USA
| | - Alicia Beeghly
- grid.152326.10000 0001 2264 7217Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN USA
| | - Zhishan Chen
- grid.152326.10000 0001 2264 7217Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN USA
| | - Chen Cao
- grid.22072.350000 0004 1936 7697Department of Biochemistry & Molecular Biology, University of Calgary, Calgary, Canada
| | - Xiao-Ou Shu
- grid.152326.10000 0001 2264 7217Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN USA
| | - Wei Zheng
- grid.152326.10000 0001 2264 7217Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN USA
| | - Quan Long
- grid.22072.350000 0004 1936 7697Department of Biochemistry & Molecular Biology, University of Calgary, Calgary, Canada ,grid.22072.350000 0004 1936 7697Department of Medical Genetics, University of Calgary, Calgary, Canada ,grid.22072.350000 0004 1936 7697Department of Mathematics & Statistics, University of Calgary, Calgary, Canada ,grid.22072.350000 0004 1936 7697Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Canada ,grid.22072.350000 0004 1936 7697Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Xingyi Guo
- grid.152326.10000 0001 2264 7217Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN USA ,grid.152326.10000 0001 2264 7217Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN USA
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15
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Qiu A, Xu H, Mao L, Xu B, Fu X, Cheng J, Zhao R, Cheng Z, Liu X, Xu J, Zhou Y, Dong Y, Tian T, Tian G, Chu M. A Novel apaQTL-SNP for the Modification of Non-Small-Cell Lung Cancer Susceptibility across Histological Subtypes. Cancers (Basel) 2022; 14:cancers14215309. [PMID: 36358727 PMCID: PMC9658938 DOI: 10.3390/cancers14215309] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 10/24/2022] [Accepted: 10/26/2022] [Indexed: 11/23/2022] Open
Abstract
Background: Alternative polyadenylation (APA) events may be modulated by single nucleotide polymorphisms (SNPs). Therefore, this study aims to evaluate the association between APA quantitative trait loci (apaQTLs)-related SNPs (apaQTL-SNPs) and non-small-cell lung cancer (NSCLC) risk. Methods: APA-related genes associated with NSCLC (LUAD and LUSC) were first identified, and the respective apaQTL-SNPs of those genes were selected. Then, a two-phase case-control study was performed to evaluate the association between candidate apaQTL-SNPs and NSCLC risk. Results: A total of 7 LUAD- and 21 LUSC-associated apaQTL-SNPs were selected. In the first phase, the apaQTL-SNP rs10138506 was significantly associated with LUAD risk (p < 0.05), whereas the other two apaQTL-SNPs (rs1130698 and rs1130719) were significantly associated with LUSC risk (p < 0.05). In the second phase, the variant G allele of rs10138506 was still significantly associated with an increased risk of LUAD (OR = 1.42, 95%CI = 1.02−1.98, p = 0.038). Functional annotation indicated that the variant G allele of rs10138506 was significantly associated with a higher PDUI value of CHURC1. Meanwhile, 3′RACE experiments verified the presence of two poly(A) sites (proximal and distal) in CHURC1, while qRT-PCR results indicated that different genotypes of rs1127968 which, in perfect LD with rs10138506, can mediate changes in the lengths of the 3′UTR of CHURC1 isoforms. Conclusion: The variant G allele of rs10138506 in CHURC1 was correlated with a longer 3′UTR of CHURC1 mRNA and an increased LUAD risk. Further studies should evaluate the interaction between rs10138506 and different 3′UTR lengths of CHURC1 that regulate LUAD development.
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Affiliation(s)
- Anni Qiu
- Department of Epidemiology, School of Public Health, Nantong University, Nantong 226019, China
| | - Huiwen Xu
- Department of Epidemiology, School of Public Health, Nantong University, Nantong 226019, China
| | - Liping Mao
- Department of Oncology, Affiliated Nantong Hospital of Shanghai University (The Sixth People’s Hospital of Nantong), Nantong 226001, China
| | - Buyun Xu
- Department of Epidemiology, School of Public Health, Nantong University, Nantong 226019, China
| | - Xiaoyu Fu
- Department of Epidemiology, School of Public Health, Nantong University, Nantong 226019, China
| | - Jingwen Cheng
- Department of Epidemiology, School of Public Health, Nantong University, Nantong 226019, China
| | - Rongrong Zhao
- Department of Oncology, Jiangdu People’s Hospital of Yangzhou, Yangzhou 225202, China
| | - Zhounan Cheng
- Department of Epidemiology, School of Public Health, Nantong University, Nantong 226019, China
| | - Xiaoxuan Liu
- Department of Epidemiology, School of Public Health, Nantong University, Nantong 226019, China
| | - Jingsheng Xu
- Department of Epidemiology, School of Public Health, Nantong University, Nantong 226019, China
| | - Yan Zhou
- Department of Epidemiology, School of Public Health, Nantong University, Nantong 226019, China
| | - Yang Dong
- Department of Epidemiology, School of Public Health, Nantong University, Nantong 226019, China
| | - Tian Tian
- Department of Epidemiology, School of Public Health, Nantong University, Nantong 226019, China
| | - Guangyu Tian
- Department of Oncology, Jiangdu People’s Hospital of Yangzhou, Yangzhou 225202, China
- Correspondence: (M.C.); (G.T.)
| | - Minjie Chu
- Department of Epidemiology, School of Public Health, Nantong University, Nantong 226019, China
- Correspondence: (M.C.); (G.T.)
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16
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An Integrated Study on the Differential Expression of the FOX Gene Family in Cancer and Their Response to Chemotherapy Drugs. Genes (Basel) 2022; 13:genes13101754. [PMID: 36292640 PMCID: PMC9602029 DOI: 10.3390/genes13101754] [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: 08/08/2022] [Revised: 09/09/2022] [Accepted: 09/23/2022] [Indexed: 11/17/2022] Open
Abstract
The Forkhead-box (FOX) transcription factors, as one of the largest gene families in humans, play key roles in cancer. Although studies have suggested that several FOX transcription factors have a significant impact on cancer, the functions of most of the FOX genes in cancer remain elusive. In the study, the expression of 43 FOX genes in 63 kinds of cancer diseases (including many subtypes of same cancer) and in response to 60 chemical substances was obtained from the Gene Expression Atlas database of the European Bioinformatics Institute. Based on the high degree of overlap in FOXO family members differentially expressed in various cancers and their particular responses to chemotherapeutic drugs, our data disclosed the FOX genes that played an important role in the development and progression of cancer. More importantly, we predicted the role of one or several combinatorial FOX genes in the diagnosis and prognostic assessment of a specific cancer and evaluated the potential of a certain anticancer drug therapy for this type of cancer by integrating patterns of FOX genes expression with anticancer drugs sensitivity.
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17
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High Levels of Progesterone Receptor B in MCF-7 Cells Enable Radical Anti-Tumoral and Anti-Estrogenic Effect of Progestin. Biomedicines 2022; 10:biomedicines10081860. [PMID: 36009407 PMCID: PMC9405688 DOI: 10.3390/biomedicines10081860] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/18/2022] [Accepted: 07/25/2022] [Indexed: 11/16/2022] Open
Abstract
The widely reported conflicting effects of progestin on breast cancer suggest that the progesterone receptor (PR) has dual functions depending on the cellular context. Cell models that enable PR to fully express anti-tumoral properties are valuable for the understanding of molecular determinant(s) of the anti-tumoral property. This study evaluated whether the expression of high levels of PR in MCF-7 cells enabled a strong anti-tumoral response to progestin. MCF-7 cells were engineered to overexpress PRB by stable transfection. A single dose of Promegestone (R5020) induced an irreversible cell growth arrest and senescence-associated secretory phenotype in MCF-7 cells with PRB overexpression (MCF-7PRB cells) but had no effect on MCF-7 cells with PRA overexpression. The growth-arresting effect was associated with downregulations of cyclin A2 and B1, CDK2, and CDK4 despite an initial upregulation of cyclin A2 and B1. R5020 also induced an evident activation of Nuclear Factor κB (NF-κB) and upregulation of interleukins IL-1α, IL-1β, and IL-8. Although R5020 caused a significant increase of CD24+CD44+ cell population, R5020-treated MCF-7PRB cells were unable to form tumorspheres and underwent massive apoptosis, which is paradoxically associated with marked downregulations of the pro-apoptotic proteins BID, BAX, PARP, and Caspases 7 and 8, as well as diminution of anti-apoptotic protein BCL-2. Importantly, R5020-activated PRB abolished the effect of estrogen. This intense anti-estrogenic effect was mediated by marked downregulation of ERα and pioneer factor FOXA1, leading to diminished chromatin-associated ERα and FOXA1 and estrogen-induced target gene expression. In conclusion, high levels of agonist-activated PRB in breast cancer cells can be strongly anti-tumoral and anti-estrogenic despite the initial unproductive cell cycle acceleration. Repression of ERα and FOXA1 expression is a major mechanism for the strong anti-estrogenic effect.
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