Guo Li, Kang Yihao, Xiong Yiqi, Jia Lin, Yan Xiaoqiang, Xia Daoliang, Yu Jiafeng, Wang Jun, Liang Tingming
Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Jiangsu Key Laboratory for Molecular and Medical Biotechnology, School of Life Science, Nanjing Normal University, Nanjing 210023, China.
Comput Struct Biotechnol J. 2022 Jul 14;20:3839-3850. doi: 10.1016/j.csbj.2022.07.020. eCollection 2022.
As one of common malignancies, prostate adenocarcinoma (PRAD) has been a growing health problem and a leading cause of cancer-related death. To obtain expression and functional relevant RNAs, we firstly screened candidate hub mRNAs and characterized their associations with cancer. Eight deregulated genes were identified and used to build a risk model (AUC was 0.972 at 10 years) that may be a specific biomarker for cancer prognosis. Then, relevant miRNAs and lncRNAs were screened, and the constructed primarily interaction networks showed the potential cross-talks among diverse RNAs. IsomiR landscapes were surveyed to understand the detailed isomiRs in relevant homologous miRNA loci, which largely enriched RNA interaction network due to diversities of sequence and expression. We finally characterized TK1, miR-222-3p and SNHG3 as crucial RNAs, and the abnormal expression patterns of them were correlated with poor survival outcomes. TK1 was found synthetic lethal interactions with other genes, implicating potential therapeutic target in precision medicine. LncRNA SNHG3 can sponge miR-222-3p to perturb RNA regulatory network and TK1 expression. These results demonstrate that TK1:miR-222-3p:SNHG3 axis may be a potential prognostic biomarker, which will contribute to further understanding cancer pathophysiology and providing potential therapeutic targets in precision medicine.
作为常见的恶性肿瘤之一，前列腺腺癌（PRAD）已成为一个日益严重的健康问题，是癌症相关死亡的主要原因。为了获得与表达和功能相关的RNA，我们首先筛选了候选枢纽mRNA，并对它们与癌症的关联进行了表征。鉴定出8个失调基因并用于构建一个风险模型（10年时的AUC为0.972），该模型可能是癌症预后的特异性生物标志物。然后，筛选了相关的miRNA和lncRNA，构建的初步相互作用网络显示了不同RNA之间潜在的相互作用。对异源miRNA景观进行了研究，以了解相关同源miRNA位点中的详细异源miRNA，由于序列和表达的多样性，这在很大程度上丰富了RNA相互作用网络。我们最终将TK1、miR-222-3p和SNHG3表征为关键RNA，它们的异常表达模式与不良生存结果相关。发现TK1与其他基因存在合成致死相互作用，这暗示了其在精准医学中的潜在治疗靶点。lncRNA SNHG3可以吸附miR-222-3p，从而扰乱RNA调控网络和TK1的表达。这些结果表明，TK1:miR-222-3p:SNHG3轴可能是一种潜在的预后生物标志物，这将有助于进一步了解癌症病理生理学，并为精准医学提供潜在的治疗靶点。
