Christelle Adolphe1,2, Angli Xue1, Atefeh Taherian Fard3, Laura A Genovesi1,2, Jian Yang4,5,6, Brandon J Wainwright7,8. 1. Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia. 2. The University of Queensland Diamantina Institute, Translational Research Institute, Woolloongabba, QLD, 4102, Australia. 3. Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD, 4072, Australia. 4. Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia. jian.yang@westlake.edu.cn. 5. School of Life Sciences, Westlake University, Hangzhou, 310024, Zhejiang, China. jian.yang@westlake.edu.cn. 6. Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, 310024, Zhejiang, China. jian.yang@westlake.edu.cn. 7. Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia. b.wainwright@imb.uq.edu.au. 8. The University of Queensland Diamantina Institute, Translational Research Institute, Woolloongabba, QLD, 4102, Australia. b.wainwright@imb.uq.edu.au.
Abstract
BACKGROUND: Basal cell carcinoma (BCC) of the skin is the most common form of human cancer, with more than 90% of tumours presenting with clear genetic activation of the Hedgehog pathway. However, polygenic risk factors affecting mechanisms such as DNA repair and cell cycle checkpoints or which modulate the tumour microenvironment or host immune system play significant roles in determining whether genetic mutations culminate in BCC development. We set out to define background genetic factors that play a role in influencing BCC susceptibility via promoting or suppressing the effects of oncogenic drivers of BCC. METHODS: We performed genome-wide association studies (GWAS) on 17,416 cases and 375,455 controls. We subsequently performed statistical analysis by integrating data from population-based genetic studies of multi-omics data, including blood- and skin-specific expression quantitative trait loci and methylation quantitative trait loci, thereby defining a list of functionally relevant candidate BCC susceptibility genes from our GWAS loci. We also constructed a local GWAS functional interaction network (consisting of GWAS nearest genes) and another functional interaction network, consisting specifically of candidate BCC susceptibility genes. RESULTS: A total of 71 GWAS loci and 46 functional candidate BCC susceptibility genes were identified. Increased risk of BCC was associated with the decreased expression of 26 susceptibility genes and increased expression of 20 susceptibility genes. Pathway analysis of the functional candidate gene regulatory network revealed strong enrichment for cell cycle, cell death, and immune regulation processes, with a global enrichment of genes and proteins linked to TReg cell biology. CONCLUSIONS: Our genome-wide association analyses and functional interaction network analysis reveal an enrichment of risk variants that function in an immunosuppressive regulatory network, likely hindering cancer immune surveillance and effective antitumour immunity.
BACKGROUND: Basal cell carcinoma (BCC) of the skin is the most common form of human cancer, with more than 90% of tumours presenting with clear genetic activation of the Hedgehog pathway. However, polygenic risk factors affecting mechanisms such as DNA repair and cell cycle checkpoints or which modulate the tumour microenvironment or host immune system play significant roles in determining whether genetic mutations culminate in BCC development. We set out to define background genetic factors that play a role in influencing BCC susceptibility via promoting or suppressing the effects of oncogenic drivers of BCC. METHODS: We performed genome-wide association studies (GWAS) on 17,416 cases and 375,455 controls. We subsequently performed statistical analysis by integrating data from population-based genetic studies of multi-omics data, including blood- and skin-specific expression quantitative trait loci and methylation quantitative trait loci, thereby defining a list of functionally relevant candidate BCC susceptibility genes from our GWAS loci. We also constructed a local GWAS functional interaction network (consisting of GWAS nearest genes) and another functional interaction network, consisting specifically of candidate BCC susceptibility genes. RESULTS: A total of 71 GWAS loci and 46 functional candidate BCC susceptibility genes were identified. Increased risk of BCC was associated with the decreased expression of 26 susceptibility genes and increased expression of 20 susceptibility genes. Pathway analysis of the functional candidate gene regulatory network revealed strong enrichment for cell cycle, cell death, and immune regulation processes, with a global enrichment of genes and proteins linked to TReg cell biology. CONCLUSIONS: Our genome-wide association analyses and functional interaction network analysis reveal an enrichment of risk variants that function in an immunosuppressive regulatory network, likely hindering cancer immune surveillance and effective antitumour immunity.
Entities:
Keywords:
BCC; Cancer susceptibility; GWAS; Immune surveillance; Protein interaction networks
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