英国威康桑格研究所Mathew J. Garnett等研究人员合作绘制出一个以临床为依据的癌症细胞依赖关系综合图谱。该项研究成果于2024年1月11日在线发表在《癌细胞》杂志上。

研究人员用多组学数据注释了930个癌症细胞系，构建了第二代癌症依赖性图谱，并分析了CRISPR-Cas9筛选得出的分子标记与癌症依赖性之间的关系。研究人员确定了驱动基因之外的依赖性相关基因表达标记，并观察到许多由功能增益而非合成致死效应驱动的基因成瘾关系。

通过将临床意义上的依赖性标记物关联与蛋白质-蛋白质相互作用网络相结合，研究人员为27种癌症类型确定了370个抗癌优先靶点，其中许多靶点都有基于网络的证据表明与某一癌症类型中的标记物存在功能关联。将这些靶点与已测序的肿瘤队列进行映射，可确定不同癌症类型中的可治疗靶点。该靶点优先级图谱可加深对基因依赖性的理解，并为药物开发确定候选抗癌靶点。

研究人员表示，癌症细胞系的基因筛选可为基因功能和药物发现提供信息。人们需要更全面的多组学数据筛选数据集，来增加绘制基因脆弱性功能图谱的机会。

附：英文原文

Title: A comprehensive clinically informed map of dependencies in cancer cells and framework for target prioritization

Author: Clare Pacini, Emma Duncan, Emanuel Gonalves, James Gilbert, Shriram Bhosle, Stuart Horswell, Emre Karakoc, Howard Lightfoot, Ed Curry, Francesc Muyas, Monsif Bouaboula, Chandra Sekhar Pedamallu, Isidro Cortes-Ciriano, Fiona M. Behan, Lykourgos-Panagiotis Zalmas, Andrew Barthorpe, Hayley Francies, Steve Rowley, Jack Pollard, Pedro Beltrao, Leopold Parts, Francesco Iorio, Mathew J. Garnett

Issue&Volume: 2024-01-11

Abstract: Genetic screens in cancer cell lines inform gene function and drug discovery. More comprehensive screen datasets with multi-omics data are needed to enhance opportunities to functionally map genetic vulnerabilities. Here, we construct a second-generation map of cancer dependencies by annotating 930 cancer cell lines with multi-omic data and analyze relationships between molecular markers and cancer dependencies derived from CRISPR-Cas9 screens. We identify dependency-associated gene expression markers beyond driver genes, and observe many gene addiction relationships driven by gain of function rather than synthetic lethal effects. By combining clinically informed dependency-marker associations with protein-protein interaction networks, we identify 370 anti-cancer priority targets for 27 cancer types, many of which have network-based evidence of a functional link with a marker in a cancer type. Mapping these targets to sequenced tumor cohorts identifies tractable targets in different cancer types. This target prioritization map enhances understanding of gene dependencies and identifies candidate anti-cancer targets for drug development.

DOI: 10.1016/j.ccell.2023.12.016

Source: https://www.cell.com/cancer-cell/fulltext/S1535-6108(23)00444-0