Institute of Bioinformatics and Applied Biotechnology, Electronic City Phase 1, Bangalore, Karnataka, India.
Manipal Academy of Higher Education, Manipal, India.
J Cancer Res Clin Oncol. 2023 Jun;149(6):2451-2462. doi: 10.1007/s00432-022-04111-0. Epub 2022 Jun 23.
Prostate cancer is the second most common cancer diagnosed worldwide and the third most common cancer among men in India. This study's objective was to characterise the mutational landscape of Indian prostate cancer using whole-exome sequencing to identify population-specific polymorphisms.
Whole-exome sequencing was performed of 58 treatment-naive primary prostate tumors of Indian origin. Multiple computational and statistical analyses were used to profile the known common mutations, other deleterious mutations, driver genes, prognostic biomarkers, and gene signatures unique to each clinical parameter. Cox analysis was performed to validate survival-associated genes. McNemar test identified genes significant to recurrence and receiver-operating characteristic (ROC) analysis was conducted to determine its accuracy. OncodriveCLUSTL algorithm was used to deduce driver genes. The druggable target identified was modeled with its known inhibitor using Autodock.
TP53 was the most commonly mutated gene in our cohort. Three novel deleterious variants unique to the Indian prostate cancer subtype were identified: POLQ, FTHL17, and OR8G1. COX regression analysis identified ACSM5, a mitochondrial gene responsible for survival. CYLC1 gene, which encodes for sperm head cytoskeletal protein, was identified as an unfavorable prognostic biomarker indicative of recurrence. The novel POLQ mutant, also identified as a driver gene, was evaluated as the druggable target in this study. POLQ, a DNA repair enzyme implicated in various cancer types, is overexpressed and is associated with a poor prognosis. The mutant POLQ was subjected to structural analysis and modeled with its known inhibitor novobiocin resulting in decreased binding efficiency necessitating the development of a better drug.
In this pilot study, the molecular profiling using multiple computational and statistical analyses revealed distinct polymorphisms in the Indian prostate cancer cohort. The mutational signatures identified provide a valuable resource for prognostic stratification and targeted treatment strategies for Indian prostate cancer patients. The DNA repair enzyme, POLQ, was identified as the druggable target in this study.
前列腺癌是全球第二大常见癌症，也是印度男性中第三大常见癌症。本研究的目的是通过全外显子组测序来描述印度前列腺癌的突变特征，以鉴定具有种群特异性的多态性。
对 58 例未经治疗的印度原发性前列腺癌肿瘤进行全外显子组测序。使用多种计算和统计分析方法来描述已知的常见突变、其他有害突变、驱动基因、预后生物标志物和每个临床参数特有的基因特征。进行 Cox 分析以验证与生存相关的基因。McNemar 检验确定与复发相关的基因，ROC 分析确定其准确性。使用 OncodriveCLUSTL 算法推断驱动基因。用其已知抑制剂对鉴定出的可用药靶进行分子对接模拟。
TP53 是我们队列中突变最常见的基因。鉴定出 3 种独特的印度前列腺癌亚型的新型有害变异：POLQ、FTHL17 和 OR8G1。COX 回归分析确定 ACSM5 为与生存相关的线粒体基因。编码精子头细胞骨架蛋白的 CYLC1 基因被鉴定为不良预后的生物标志物，提示复发。还鉴定出作为驱动基因的新型 POLQ 突变体作为本研究的可用药靶。POLQ 是一种参与多种癌症类型的 DNA 修复酶，过表达与不良预后相关。对 POLQ 突变体进行结构分析，并与已知抑制剂诺维本进行对接模拟，结果表明结合效率降低，因此需要开发更好的药物。
在这项初步研究中，通过多种计算和统计分析的分子谱分析揭示了印度前列腺癌队列中的独特多态性。鉴定出的突变特征为印度前列腺癌患者的预后分层和靶向治疗策略提供了有价值的资源。在本研究中，DNA 修复酶 POLQ 被鉴定为可用药靶。
