Becchi Tommaso, Beltrame Luca, Mannarino Laura, Calura Enrica, Marchini Sergio, Romualdi Chiara
Department of Biology, University of Padova, 35131 Padova, Italy.
Laboratory of Cancer Pharmacology, IRCCS Humanitas Research Hospital, via Manzoni 56, 20089 Rozzano - Milan, Italy.
J Biomed Inform. 2023 Nov;147:104529. doi: 10.1016/j.jbi.2023.104529. Epub 2023 Oct 18.
Copy number variations (CNVs) play crucial roles in physiological and pathological processes, including cancer. However, the functional implications of somatic CNVs in tumor progression and evolution remain unclear. This study focuses on identifying CNV alterations with high pathogenic potential that drive and sustain tumorigenesis, distinguishing them from passenger alterations that accumulate during tumor growth. Our goal is to explore the variability of CNVs across different tumor types and infer their impact on tumor cell functions.
Starting from 7352 copy number profiles across 33 different cancer types, we infer the pathogenicity of each CNV and perform both intra- and inter-tumor analyses to predict the functional impact of different genomic patterns. We evaluate the actionability of genes belonging to altered regions and we correlate the presence of pathogenic regions with genome instability patterns and patients' survival.
Our analysis uncovered large heterogeneity among different tumors suggesting in many cases distinct genetic drivers of tumorigenesis. Recurrent genomic alterations frequently coincide with dysfunctional homologous recombination pathways and negative regulation of the immune system. In certain tumors, the number of pathogenic CNVs emerged as a prognostic biomarker, highlighting their significance in cancer progression.
This study contributes to elucidate the functional impact of pathogenic CNVs in tumor progression and sheds light on their potential as prognostic markers in specific cancer types.
拷贝数变异(CNV)在包括癌症在内的生理和病理过程中发挥着关键作用。然而,体细胞CNV在肿瘤进展和演变中的功能意义仍不清楚。本研究聚焦于识别具有高致病潜力的CNV改变,这些改变驱动并维持肿瘤发生,将它们与肿瘤生长过程中积累的乘客性改变区分开来。我们的目标是探索不同肿瘤类型中CNV的变异性,并推断它们对肿瘤细胞功能的影响。
从33种不同癌症类型的7352个拷贝数图谱出发,我们推断每个CNV的致病性,并进行肿瘤内和肿瘤间分析,以预测不同基因组模式的功能影响。我们评估属于改变区域的基因的可操作性,并将致病区域的存在与基因组不稳定模式和患者生存情况相关联。
我们的分析揭示了不同肿瘤之间存在很大的异质性,这表明在许多情况下肿瘤发生有不同的遗传驱动因素。反复出现的基因组改变常常与功能失调的同源重组途径和免疫系统的负调控同时出现。在某些肿瘤中,致病CNV的数量成为一种预后生物标志物,突出了它们在癌症进展中的重要性。
本研究有助于阐明致病CNV在肿瘤进展中的功能影响,并揭示它们作为特定癌症类型预后标志物的潜力。