Tang Yulai, Fahira Aamir, Lin Siying, Shao Yiming, Huang Zunnan
Key Laboratory of Computer-Aided Drug Design of Dongguan City, The First Dongguan Affiliated Hospital, School of Pharmacy, Guangdong Medical University, Dongguan 523710, China.
Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Guangdong Medical University, Dongguan 523808, China.
Comput Struct Biotechnol J. 2024 Nov 5;23:4271-4287. doi: 10.1016/j.csbj.2024.11.005. eCollection 2024 Dec.
Digestive system malignancies, including esophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), liver hepatocellular carcinoma (LIHC), and colon adenocarcinoma (COAD), pose significant global health challenges. Identifying shared and distinct regulatory mechanisms across these cancers can lead to improved therapies. This study aims to construct and compare competing endogenous RNA (ceRNA) networks across ESCA, STAD, LIHC, and COAD to identify RNA biomarkers that could serve as precision therapeutic targets to enhance clinical outcomes and advance personalized cancer care.
Clinical and transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed to predict differentially expressed RNAs using the edgeR package. The ceRNA networks were constructed using the miRcode and ENCORI databases. Functional enrichment analysis and prognostic RNA screening were performed with ConsensusPathDB and univariate Cox regression analysis.
we identified 6, 88, 55, and 41 RNA biomarkers in ESCA, STAD, LIHC, and COAD, respectively. Network analysis revealed shared and specific elements, with shared nodes enriched in cell cycle and mitotic processes. Several biomarkers, including HMGB3 and RGS16 (ESCA), COL4A1 and COL6A3 (STAD), CDCA5 and CDCA8 (LIHC), and LIMK1 and OSBPL3 (COAD), were consistent with prior studies, while novel biomarkers, such as C3P1 (ESCA), P2RY6 (STAD), and N4BP2L1 and PPP1R3B (LIHC), were discovered. Based on RNA correlation analysis, 1, 23, and 2 potential ceRNA regulatory axes were identified in STAD (PVT1/miR-490-3p/HMGA2), LIHC (DLX6-AS1/miR-139-5p/TOP2A, etc.), and COAD (STRCP1 & LINC00488/miR-142-3p/GAB1), respectively.
This study advances the understanding of ceRNA networks in digestive cancers, highlighting RNA biomarkers with potential as therapeutic targets for personalized treatment strategies.
消化系统恶性肿瘤,包括食管癌(ESCA)、胃腺癌(STAD)、肝细胞癌(LIHC)和结肠腺癌(COAD),给全球健康带来了重大挑战。识别这些癌症中共同的和独特的调控机制可以带来更好的治疗方法。本研究旨在构建并比较ESCA、STAD、LIHC和COAD中的竞争性内源RNA(ceRNA)网络,以识别可作为精准治疗靶点的RNA生物标志物,从而改善临床结果并推进个性化癌症治疗。
分析来自癌症基因组图谱(TCGA)的临床和转录组数据,使用edgeR软件包预测差异表达的RNA。利用miRcode和ENCORI数据库构建ceRNA网络。使用ConsensusPathDB和单变量Cox回归分析进行功能富集分析和预后RNA筛选。
我们分别在ESCA、STAD、LIHC和COAD中鉴定出6、88、55和41个RNA生物标志物。网络分析揭示了共同的和特定的元素,共同节点在细胞周期和有丝分裂过程中富集。包括HMGB3和RGS16(ESCA)、COL4A1和COL6A3(STAD)、CDCA5和CDCA8(LIHC)以及LIMK1和OSBPL3(COAD)在内的几种生物标志物与先前的研究一致,同时还发现了新的生物标志物,如C3P1(ESCA)、P2RY6(STAD)以及N4BP2L1和PPP1R3B(LIHC)。基于RNA相关性分析,分别在STAD(PVT1/miR-490-3p/HMGA2)、LIHC(DLX6-AS1/miR-139-5p/TOP2A等)和COAD(STRCP1 & LINC00488/miR-142-3p/GAB1)中鉴定出1、23和2个潜在的ceRNA调控轴。
本研究推进了对消化系统癌症中ceRNA网络的理解,突出了具有作为个性化治疗策略治疗靶点潜力的RNA生物标志物。