为了开发靶向治疗，至关重要的是确定黑色素瘤的全谱遗传驱动因素，包括非编码区域的遗传驱动因素。然而，最近探索非编码区的努力主要集中在基因邻近元件，例如启动子和非编码RNA，而基因间远端调控元件很大程度上未被探索。我们使用来自黑色素瘤细胞的Hi-C染色质接触数据来绘制远端、黑色素瘤中全基因组非编码、启动子相互作用的调控元件。利用这种“启动子相互作用网络”，以及来自全基因组泛癌分析的全基因组序列和基因表达数据，我们开发了多元线性回归模型来识别影响启动子活性的远端体细胞突变热点。我们识别了八个经常突变的热点新颖的、黑色素瘤特异性的、位于与启动子相互作用的远端调控元件中、改变转录因子结合基序、并影响先前在各种癌症中作为肿瘤抑制基因/癌基因的基因（例如 HSPB7、CLDN1、ADCY9 和 FDXR）的表达我们的研究表明，除了黑色素瘤中已明确表征的 TERT 启动子之外，还存在其他非编码驱动因素，这为了解可能有助于黑色素瘤发展的非编码突变对复杂调控网络的破坏提供了新的见解。此外，我们的研究提供了一个框架，用于整合多个级别的生物数据，以发现癌症特异性的非编码驱动因素。© 2024。作者。

To develop targeted treatments, it is crucial to identify the full spectrum of genetic drivers in melanoma, including those in non-coding regions. However, recent efforts to explore non-coding regions have primarily focused on gene-adjacent elements such as promoters and non-coding RNAs, leaving intergenic distal regulatory elements largely unexplored.We used Hi-C chromatin contact data from melanoma cells to map distal, non-coding, promoter-interacting regulatory elements genome-wide in melanoma. Using this "promoter-interaction network", alongside whole-genome sequence and gene expression data from the Pan Cancer Analysis of Whole Genomes, we developed multivariate linear regression models to identify distal somatic mutation hotspots that affect promoter activity.We identified eight recurrently mutated hotspots that are novel, melanoma-specific, located in promoter-interacting distal regulatory elements, alter transcription factor binding motifs, and affect the expression of genes (e.g., HSPB7, CLDN1, ADCY9 and FDXR) previously implicated as tumour suppressors/oncogenes in various cancers.Our study suggests additional non-coding drivers beyond the well-characterised TERT promoter in melanoma, offering new insights into the disruption of complex regulatory networks by non-coding mutations that may contribute to melanoma development. Furthermore, our study provides a framework for integrating multiple levels of biological data to uncover cancer-specific non-coding drivers.© 2024. The Author(s).