PO.BCS01.01 · 生物信息与计算

癌症基因组中的突变特征改变参与细胞信号网络的短线性蛋白基序

Mutational signatures in cancer genomes alter short linear protein motifs involved in cellular signaling networks

海报缩略图:癌症基因组中的突变特征改变参与细胞信号网络的短线性蛋白基序
编号 59 展板 21 时间 4/19 02:00–05:00 区域 Section 3 主讲 Jigyansa Mishra, BS;MS
分会场 Application of Bioinformatics to Cancer Biology 1
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作者与单位 Authors & Affiliations

Jigyansa Mishra1, Masroor Bayati1, Nina Adler2, Zoe P. Klein1, Kevin C. L. Cheng1, Juri Reimand1

1Ontario Institute for Cancer Research, Toronto, ON, Canada,2University of Toronto, Toronto, ON, Canada

摘要 Abstract

中文摘要
癌症基因组因多种突变过程而累积体细胞突变,这些过程由外源性致癌物暴露和内源性DNA修复缺陷驱动,留下称为突变特征的独特基因组印记。突变特征是通过计算方法从大规模癌症基因组学数据集中推断出来,并经实验验证的,然而它们对蛋白编码序列和蛋白功能的功能性影响在很大程度上仍未被探索。借助机器学习和统计学,我们旨在辨别单碱基替换(SBS)突变特征在重塑保守的短线性蛋白基序(SLiMs)方面的影响。这些是介导关键蛋白-蛋白相互作用和翻译后修饰的肽序列。我们对19种癌症类型、12,000个基因组中的110万个错义单核苷酸变异(msSNVs)进行了蛋白基因组学分析。我们评估了msSNVs对由激酶及参与细胞信号网络的其他酶所识别的150类SLiMs的影响。不同的突变特征与破坏、创建或在特定SLiMs之间切换的msSNVs显著相关。例如,与紫外线相关的特征SBS7b破坏了脯氨酸导向的激酶基序,而由异常APOBEC胞苷脱氨酶活性产生的特征SBS2和SBS13破坏了对细胞凋亡至关重要的caspase切割基序,以及参与DNA损伤应答的基序。这些突变特征的差异性影响源于其三核苷酸背景偏好,后者引导特定的密码子变化,在不同的SLiMs中诱导氨基酸替换。在基因水平上,重现性的SLiM重塑变异聚集于22个经典癌症驱动基因(如BRAF、CTNNB1和U2AF1)和35个候选基因中,揭示了突变过程与致癌信号通路之间的机制性联系。BRAF中紫外线诱导的V600E替换创建了一个新的polo样激酶(PLK1)结合基序,可能有助于黑色素瘤患者对vemurafenib的耐药。剪接因子U2AF1中重现性的S34F替换由APOBEC活性驱动,破坏了一个对剪接位点保真度至关重要的调节性磷酸化位点,提示APOBEC驱动的诱变与肺癌中RNA剪接失调之间存在联系。最后,细胞信号网络中的基序重塑改变与患者属性(如吸烟状态)以及功能特征(如APOBEC基因表达)强烈相关,揭示了生活方式变量和内源性诱变程序如何可能重新配置细胞信号传导和蛋白-蛋白相互作用。总之,我们的结果揭示了突变过程特异性的蛋白组学后果,为癌症病因学提供了机制性见解,并暴露了潜在的治疗脆弱性。
查看英文原文 English abstract
Cancer genomes accumulate somatic mutations from diverse mutational processes, driven by extrinsic carcinogen exposures and intrinsic DNA repair deficiencies, leaving distinct genomic imprints referred to as mutational signatures. Mutational signatures are inferred computationally from large cancer genomics datasets and validated in experiments, however their functional impacts on protein-coding sequences and protein function remain largely unexplored. Leveraging machine learning and statistics, we aimed to discern the impact of single base substitution (SBS) mutational signatures in rewiring conserved short linear protein motifs (SLiMs). These are peptide sequences that mediate key protein-protein interactions and post-translational modifications. We performed a proteogenomic analysis of 1.1 million missense single-nucleotide variants (msSNVs) in 12,000 genomes across 19 cancer types. We assessed the impact of msSNVs on 150 classes of SLiMs recognized by kinases and other enzymes involved in cellular signaling networks. Distinct signatures were significantly associated with msSNVs that disrupted, created or switched between specific SLiMs. For example, UV light-associated signature SBS7b disrupted proline-directed kinase motifs, while signatures arising from aberrant APOBEC cytidine deaminase activity, SBS2 and SBS13, disrupted caspase-cleavage motifs, vital for apoptosis, as well as motifs involved in the DNA damage response. These differential signature impacts stem from their trinucleotide-context biases, which steer specific codon changes, inducing amino acid substitutions in distinct SLiMs. At the gene level, recurrent SLiM-rewiring variants clustered in 22 canonical cancer drivers such as BRAF , CTNNB1 and U2AF1 , and 35 candidate genes revealing mechanistic connections between mutational processes and oncogenic signaling pathways. UV light-induced V600E substitutions in BRAF create a novel polo-like kinase (PLK1)-binding motif, putatively contributing to vemurafenib resistance in melanoma patients. Recurrent S34F substitutions in the splicing factor U2AF1 are driven by APOBEC activity and disrupt a regulatory phosphorylation site critical in splice-site fidelity, suggesting a link between APOBEC-driven mutagenesis and RNA splicing dysregulation in lung cancer. Lastly, motif-rewiring alterations in cellular signaling networks strongly correlated with patient attributes such as smoking status and functional characteristics such as APOBEC gene expression, revealing how lifestyle variables and intrinsic mutagenic programs can potentially reconfigure cellular signaling and protein-protein interactions. Together, our results uncover process-specific proteomic consequences of mutational processes, offering mechanistic insights into cancer etiology and exposing potential therapeutic vulnerabilities.
利益披露 Disclosure
J. Mishra, None.. M. Bayati, None.. Z. P. Klein, None.. K. C. L. Cheng, None.

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