Rambabu Majji, Konageni Nagaraj, Vasudevan Karthick, Dasegowda K R, Gokul Anand, Jayanthi Sivaraman, Rohini Karunakaran
Department of Biotechnology, REVA University, Bengaluru, Karnataka, India.
Department of Computer Science, University of Southern California, Los Angeles, CA, USA.
Saudi J Biol Sci. 2023 Nov;30(11):103819. doi: 10.1016/j.sjbs.2023.103819. Epub 2023 Sep 26.
Pancreatic cancer shows malignancy around the world standing in 4th position for causing death globally. This cancer is majorly divided into exocrine and neuroendocrine where exocrine pancreatic ductal adenocarcinoma is observed to be nearly 85% of cases. The lack of diagnosis of pancreatic cancer is considered to be one of the major drawbacks to the prognosis and treatment of pancreatic cancer patients. The survival rate after diagnosis is very low, due to the higher incidence of drug resistance to cancer which leads to an increase in the mortality rate. The transcriptome analysis for pancreatic cancer involves dataset collection from the ENA database, incorporating them into quality control analysis to the quantification process to get the summarized read counts present in collected samples and used for further differential gene expression analysis using the DESeq2 package. Additionally, explore the enriched pathways using GSEA software and represented them by utilizing the enrichment map finally, the gene network has been constructed by Cytoscape software. Furthermore, explored the hub genes that are present in the particular pathways and how they are interconnected from one pathway to another has been analyzed. Finally, we identified the , and genes and their associated pathways can be better biomarker for the clinical processes to increase the survival rate of of pancreatic cancer.
胰腺癌在全球范围内显示出恶性程度，在导致全球死亡的原因中排名第四。这种癌症主要分为外分泌型和神经内分泌型，其中外分泌型胰腺导管腺癌约占病例的85%。胰腺癌缺乏诊断被认为是胰腺癌患者预后和治疗的主要缺点之一。诊断后的生存率非常低，这是由于癌症耐药性的高发生率导致死亡率增加。胰腺癌的转录组分析包括从ENA数据库收集数据集，将它们纳入质量控制分析到定量过程，以获得收集样本中存在的汇总读数计数，并用于使用DESeq2软件包进行进一步的差异基因表达分析。此外，使用GSEA软件探索富集途径，并最终通过利用富集图来表示它们，基因网络已由Cytoscape软件构建。此外，还探索了特定途径中存在的枢纽基因，以及它们如何从一个途径相互连接到另一个途径。最后，我们确定了 、 和 基因，它们相关的途径可能成为提高胰腺癌生存率的临床过程中更好的生物标志物。
