Heller Erik Marcel, Barthel Karen, Räschle Markus, Schukken Klaske M, Sheltzer Jason M, Storchová Zuzana
Department of Molecular Genetics, Faculty of Biology, Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau, Kaiserslautern, Germany.
Department of Surgery, Yale School of Medicine, Yale University, New Haven, USA.
bioRxiv. 2025 May 13:2025.05.12.653427. doi: 10.1101/2025.05.12.653427.
Aneuploidy, a hallmark of cancer, leads to widespread changes in chromosome copy number, altering the abundance of hundreds or thousands of proteins. However, evidence suggests that levels of proteins encoded on affected chromosomes are often buffered toward their abundances observed in diploid cells. Despite its prevalence, the molecular mechanisms driving this protein dosage compensation remain largely unknown. It is unclear whether all proteins are buffered to a similar degree, what factors determine buffering, and whether dosage compensation varies across different cell lines or tumor types. Moreover, its potential adaptive advantage and therapeutic relevance remain unexplored. Here, we established a novel approach to quantify protein dosage buffering in a gene copy number-dependent manner, showing that dosage compensation is widespread but variable in cancer cell lines and tumor samples. By developing multifactorial machine learning models, we identify mean gene dependency, protein complex participation, haploinsufficiency, and mRNA decay as key predictors of buffering. We also show that dosage compensation can affect oncogenic potential and that higher buffering correlates with reduced proteotoxic stress and increased drug resistance. These findings highlight protein dosage compensation as a crucial regulatory mechanism and a potential therapeutic target in aneuploid cancers.
非整倍体是癌症的一个标志，会导致染色体拷贝数广泛变化，改变数百或数千种蛋白质的丰度。然而，有证据表明，受影响染色体上编码的蛋白质水平通常会朝着二倍体细胞中观察到的丰度进行缓冲。尽管其普遍存在，但驱动这种蛋白质剂量补偿的分子机制在很大程度上仍不清楚。目前尚不清楚所有蛋白质是否都以相似的程度进行缓冲，哪些因素决定缓冲作用，以及剂量补偿在不同细胞系或肿瘤类型中是否存在差异。此外，其潜在的适应性优势和治疗相关性仍未得到探索。在这里，我们建立了一种新方法，以基因拷贝数依赖的方式量化蛋白质剂量缓冲，结果表明剂量补偿在癌细胞系和肿瘤样本中普遍存在但存在差异。通过开发多因素机器学习模型，我们确定平均基因依赖性、蛋白质复合物参与、单倍体不足和mRNA衰变是缓冲作用的关键预测因子。我们还表明，剂量补偿会影响致癌潜力，更高的缓冲作用与降低的蛋白毒性应激和增加的耐药性相关。这些发现突出了蛋白质剂量补偿作为非整倍体癌症中的一种关键调节机制和潜在治疗靶点。
