摘要：Abstract This study aims to identify pathway involvement in the development of cisplatin (cis-diamminedichloroplatinum (II); CDDP) resistance in A549 lung cancer (LC) cells by utilizing advanced bioinformatics software. We developed CDDP-resistant A549 (A549/DDP) cells through prolonged incubation with the drug and performed RNA-seq on RNA extracts to determine differential mRNA and miRNA expression between A549/DDP and A549 cells. We analyzed the gene dysregulation with Ingenuity Pathway Analysis (IPA; QIAGEN) software. In contrast to prior research, which relied on the clustering of dysregulated genes to pathways as an indication of pathway activity, we utilized the IPA software for the dynamic evaluation of pathway activity depending on the gene dysregulation levels. We predicted 15 pathways significantly contributing to the chemoresistance, with several of them to have not been previously reported or analyzed in detail. Among them, the PKR signaling, cholesterol biosynthesis, and TEC signaling pathways are included, as well as genes, such as PIK3R3, miR-34c-5p, and MDM2, among others. We also provide a preliminary analysis of SNPs and indels, present exclusively in A549/DDP cells. This study's results provide novel potential mechanisms and molecular targets that can be explored in future studies and assist in improving the understanding of the chemoresistance phenotype.
其他摘要：Abstract This study aims to identify pathway involvement in the development of cisplatin (cis-diamminedichloroplatinum (II); CDDP) resistance in A549 lung cancer (LC) cells by utilizing advanced bioinformatics software. We developed CDDP-resistant A549 (A549/DDP) cells through prolonged incubation with the drug and performed RNA-seq on RNA extracts to determine differential mRNA and miRNA expression between A549/DDP and A549 cells. We analyzed the gene dysregulation with Ingenuity Pathway Analysis (IPA; QIAGEN) software. In contrast to prior research, which relied on the clustering of dysregulated genes to pathways as an indication of pathway activity, we utilized the IPA software for the dynamic evaluation of pathway activity depending on the gene dysregulation levels. We predicted 15 pathways significantly contributing to the chemoresistance, with several of them to have not been previously reported or analyzed in detail. Among them, the PKR signaling, cholesterol biosynthesis, and TEC signaling pathways are included, as well as genes, such as PIK3R3, miR-34c-5p, and MDM2, among others. We also provide a preliminary analysis of SNPs and indels, present exclusively in A549/DDP cells. This study's results provide novel potential mechanisms and molecular targets that can be explored in future studies and assist in improving the understanding of the chemoresistance phenotype.
