Liggins Institute, The University of Auckland, New Zealand.
The Maurice Wilkins Centre, The University of Auckland, New Zealand.
Mol Oncol. 2024 Apr;18(4):1031-1048. doi: 10.1002/1878-0261.13599. Epub 2024 Feb 3.
Genome-wide association studies (GWAS) have associated 76 loci with the risk of developing melanoma. However, understanding the molecular basis of such associations has remained a challenge because most of these loci are in non-coding regions of the genome. Here, we integrated data on epigenomic markers, three-dimensional (3D) genome organization, and expression quantitative trait loci (eQTL) from melanoma-relevant tissues and cell types to gain novel insights into the mechanisms underlying melanoma risk. This integrative approach revealed a total of 151 target genes, both near and far away from the risk loci in linear sequence, with known and novel roles in the etiology of melanoma. Using protein-protein interaction networks, we identified proteins that interact-directly or indirectly-with the products of the target genes. The interacting proteins were enriched for known melanoma driver genes. Further integration of these target genes into tissue-specific gene regulatory networks revealed patterns of gene regulation that connect melanoma to its comorbidities. Our study provides novel insights into the biological implications of genetic variants associated with melanoma risk.
全基因组关联研究(GWAS)已经将 76 个位点与黑色素瘤发病风险相关联。然而,由于大多数这些位点都位于基因组的非编码区域,因此理解这些关联的分子基础仍然是一个挑战。在这里,我们整合了来自黑色素瘤相关组织和细胞类型的关于表观遗传标记物、三维(3D)基因组组织和表达数量性状基因座(eQTL)的数据,以深入了解黑色素瘤风险的潜在机制。这种综合方法总共揭示了 151 个靶基因,这些基因位于风险位点附近或远离线性序列,它们在黑色素瘤的发病机制中具有已知和新的作用。利用蛋白质-蛋白质相互作用网络,我们鉴定出与靶基因产物直接或间接相互作用的蛋白质。这些相互作用的蛋白质富含已知的黑色素瘤驱动基因。将这些靶基因进一步整合到组织特异性基因调控网络中,揭示了将黑色素瘤与其合并症联系起来的基因调控模式。我们的研究为与黑色素瘤风险相关的遗传变异的生物学意义提供了新的见解。