Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.
Special Infectious Agents Unit-BSL3, King Fahad Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia.
Sci Rep. 2022 May 4;12(1):7240. doi: 10.1038/s41598-022-11143-6.
Cancer is among the highly complex disease and renal cell carcinoma is the sixth-leading cause of cancer death. In order to understand complex diseases such as cancer, diabetes and kidney diseases, high-throughput data are generated at large scale and it has helped in the research and diagnostic advancement. However, to unravel the meaningful information from such large datasets for comprehensive and minute understanding of cell phenotypes and disease pathophysiology remains a trivial challenge and also the molecular events leading to disease onset and progression are not well understood. With this goal, we have collected gene expression datasets from publicly available dataset which are for two different stages (I and II) for renal cell carcinoma and furthermore, the TCGA and cBioPortal database have been utilized for clinical relevance understanding. In this work, we have applied computational approach to unravel the differentially expressed genes, their networks for the enriched pathways. Based on our results, we conclude that among the most dominantly altered pathways for renal cell carcinoma, are PI3K-Akt, Foxo, endocytosis, MAPK, Tight junction, cytokine-cytokine receptor interaction pathways and the major source of alteration for these pathways are MAP3K13, CHAF1A, FDX1, ARHGAP26, ITGBL1, C10orf118, MTO1, LAMP2, STAMBP, DLC1, NSMAF, YY1, TPGS2, SCARB2, PRSS23, SYNJ1, CNPPD1, PPP2R5E. In terms of clinical significance, there are large number of differentially expressed genes which appears to be playing critical roles in survival.
癌症是一种高度复杂的疾病，肾细胞癌是第六大癌症死亡原因。为了了解癌症、糖尿病和肾脏疾病等复杂疾病，需要大规模生成高通量数据，这有助于推动研究和诊断进展。然而，要从这些大型数据集解译出有意义的信息，全面深入地了解细胞表型和疾病病理生理学，仍然是一个艰巨的挑战，而且导致疾病发生和进展的分子事件也尚未被充分理解。为了实现这一目标，我们从公共数据库中收集了两个不同阶段（I 期和 II 期）的肾细胞癌基因表达数据集，此外，还利用了 TCGA 和 cBioPortal 数据库来了解临床相关性。在这项工作中，我们应用计算方法来解译差异表达基因及其网络，以确定富集途径。基于我们的研究结果，我们得出结论，在肾细胞癌中，最显著改变的途径包括 PI3K-Akt、Foxo、内吞作用、MAPK、紧密连接、细胞因子-细胞因子受体相互作用途径，这些途径改变的主要来源是 MAP3K13、CHAF1A、FDX1、ARHGAP26、ITGBL1、C10orf118、MTO1、LAMP2、STAMBP、DLC1、NSMAF、YY1、TPGS2、SCARB2、PRSS23、SYNJ1、CNPPD1、PPP2R5E。从临床意义上讲，有大量差异表达的基因似乎在生存中发挥着关键作用。
