LBPO.PS01 · 人群科学 · Late-Breaking

H3K27ac-HiChIP variant-to-gene mapping confirms the importance of cancer drivers and oncogenic signaling pathways in melanoma risk

编号 LB384 展板 14 时间 4/21 02:00–05:00 区域 Section 55 主讲 Rohit Thakur, BS;PhD

分会场 Late-Breaking Research: Population Sciences

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作者与单位

Rohit Thakur¹, G J M Shanika R Jayasinghe², Mai Xu¹, Linh Bui-Raborn¹, Jianxin Shi¹, Diptavo Dutta¹, Phuc H. Hoang¹, Mathias Seviiri², Christopher I. Amos³, Andrew Bakshi⁴, Anne E. Cust⁵, Florence Demenais⁶, David L. Duffy⁷, Lars G. Fritsche⁸, Jiali Han⁹, Nicholas K. Hayward¹⁰, Kiarash Khosrotehrani¹¹, Rajiv Kumar¹², John F. Thompson¹³, Stuart MacGregor¹⁴, Miguel Renteria¹⁵, Diane T. Smelser¹⁶, Sarah V. Ward¹⁷, Maria Concetta Fargnoli¹⁸, Paola Ghiorzo¹⁹, Alisa M. Goldstein¹, Chiara Menin²⁰, David Millan-Esteban²¹, Eduardo Nagore²², Cristina Pellegrini²³, Susana Puig²⁴, Alex Stratigos²⁵, David C. Whiteman², Melanoma Meta-Analysis Consortium, Mark M. Iles²⁶, Lee E. Whelees²⁷, Rebecca I. Hartman²⁸, Maria Teresa Landi¹, Matthew H. Law², Kevin M. Brown¹

¹National Cancer Institute, Bethesda, MD,²Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Australia,³Epidemiology & Population Science, Baylor College of Medicine, Houston, TX,⁴Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia,⁵The Daffodil Centre, Sydney School of Public Health, The University of Sydney, Sydney, Australia,⁶INSERM, Université Paris Diderot, Paris, France,⁷Genetic Epidemiology Laboratory, QIMR Berghofer Medical Research Institutee, Brisbane, Australia,⁸Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI,⁹IU Simon Cancer Center, Indiana University Indianapolis, Indianapolis, IN,¹⁰Oncogenomics, QIMR Berghofer Medical Research Institutenstitute, Brisbane, Australia,¹¹Frazer institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia,¹²German Cancer Research Center, Heidelberg, Germany,¹³Melanoma Institute Australia, The University of Sydney, Sydney, Australia,¹⁴Statistical Genetics, Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Australia,¹⁵QIMR Berghofer Medical Research Institute, Brisbane, Australia,¹⁶Department of Genomic Health, Geisinger Clinic, Geisinger Health System, Danville, PA,¹⁷School of Population and Global Health, The University of Western Australia, Perth, Australia,¹⁸Istituto Dermatologico San Gallicano - IRCCS, Rome, Italy,¹⁹IRCCS Ospedale Policlinico San Martino,University of Genoa, Genoa, Italy,²⁰Immunology and Molecular Oncology Unit, Veneto Institute of Oncology - IOV IRCCS, Padua, Italy,²¹Department of Dermatology, Universidad Catolica de Valencia San Vicente Mártir; Fundación Instituto Valenciano de Oncología, Valencia, Spain,²²Department of Dermatology, Fundación Instituto Valenciano de Oncología; Universidad Católica de Valencia San Vicente Mártir, Valencia, Spain,²³Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Abruzzo, Italy,²⁴Dermatology Department, Universitat de Barcelona, Barcelona, Spain,²⁵Department of Dermatology-Venereology, National and Kapodistrian University of Athens, Athens, Greece,²⁶Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom,²⁷Tennessee Valley Healthcare System VA Medical Center, Nashville, TN,²⁸Dermatology Section, VA Boston Healthcare System, Boston, MA

摘要 Abstract

We performed a new melanoma GWAS meta-analysis, roughly doubling the sample size to ~70,000 cases compared to the most recent study by Landi and colleagues. In the new meta-analysis, we identify 116 independent risk loci, replicating 52/54 loci previously reported. Post-GWAS variant-to-gene mapping remains critical to functionally interpret new loci discovered by this analysis. Most loci contain many candidate causal variants in linkage disequilibrium, with very few altering protein-coding sequence, suggesting cis -regulatory function underlying the majority of loci. Quantitative trait locus (QTL) colocalization methods can effectively prioritize target genes at susceptibility loci but many loci remain without assigned targets, perhaps reflecting context-specific variant effects not well-reflected in QTL datasets. To complement QTLs and more comprehensively identify potential causal genes, including those beyond 1 Mb, we applied H3K27ac-HiChIP in human primary melanocytes, the cell type of origin for melanoma. H3K27ac-HiChIP combines a Hi-C approach with a H3K27ac ChIP step to detect enhancer-promoter interactions at the risk loci. Statistically significant chromatin interactions were identified using the FitHiChIP pipeline. We subsequently performed variant-to-gene (V2G) mapping at all genome-wide significant melanoma loci, nominating target genes where fine-mapped variants overlapped or physically interacted with their respective promoters. HiChIP-based V2G mapping approach identified target genes at 94% loci (779 genes nominated at 109/116 loci), outperforming other gene nomination approaches (QTL colocalization, protein-coding variants), which nominated 102 candidate genes at 57% of risk loci (67/116 loci). Among genes identified by melanocyte or melanoma eQTL colocalization, a majority (19 of 32) were also nominated by V2G mapping. Likewise, 3 of 5 splice QTL genes and 21 of 34 meQTL genes overlapped with the V2G gene set. Next, we compared gene sets including the V2G mapping-identified candidates to those identified solely by QTLs and protein-coding variants. The gene set incorporating V2G candidates showed significant enrichment for oncogenic signaling pathways, including WNT/beta-catenin signaling (FDR: P with V2G gene set =  6.3 × 10 -05 vs P without V2G gene set = 0.2), aryl hydrocarbon receptor signaling (P= 1.6 × 10 -4 vs 0.2), and signaling by NOTCH1 (P=0.002 vs0.5). Notably, V2G mapping linked risk-associated variants to known cancer drivers (e.g. PIK3CA , NOTCH2 , MDM4 etc.) at 46% of loci (53/116; nominated 76 cancer drivers), with several located >1Mb away. Strikingly, we detected a highly significant long-range interaction (~2 Mb) connecting fine-mapped variants near the locus 8q24.21 to cancer driver MYC. Overall, H3K27ac-HiChIP-based V2G mapping greatly improves the interpretation of melanoma susceptibility loci by identifying distant susceptibility genes, highlighting known cancer drivers as potential targets, and revealing that these loci converge on key oncogenic signaling pathways.

利益披露 Disclosure

R. Thakur, None.. G. Jayasinghe, None.. M. Xu, None.. L. Bui-Raborn, None.. J. Shi, None.. D. Dutta, None.. P. H. Hoang, None.. M. Seviiri, None.. C. I. Amos, None.. A. Bakshi, None.. A. E. Cust, None.. F. Demenais, None.. D. L. Duffy, None.. L. G. Fritsche, None.. J. Han, None.. N. K. Hayward, None.. K. Khosrotehrani, None.. R. Kumar, None. J. F. Thompson, BMS Australia Received honoraria for advisory board participation.. MSD Australia Received honoraria for advisory board participation.. GSK Travel, Received honoraria for advisory board participation.. Provectus Biopharmaceuticals Travel, Received honoraria for advisory board participation.. Novartis Travel. S. MacGregor, None.. M. Renteria, None.. D. T. Smelser, None.. S. V. Ward, None.. M. C. Fargnoli, None.. P. Ghiorzo, None.. A. M. Goldstein, None.. C. Menin, None.. D. Millan-Esteban, None.. E. Nagore, None.. C. Pellegrini, None.. S. Puig, None.. A. Stratigos, None.. D. C. Whiteman, None.. M. M. Iles, None.. L. E. Whelees, None.. R. I. Hartman, None.. M. T. Landi, None.. M. H. Law, None.. K. M. Brown, None.

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