Identification of Kynurenic Acid-Induced Apoptotic Biomarkers in Gastric Cancer-Derived AGS Cells through Next-Generation Transcriptome Sequencing Analysis.
Hun Hwan KimSang Eun HaMin Yeong ParkSe Hyo JeongPritam Bhangwan BhosaleAbuyaseer AbusaliyaChung Kil WonJeong Doo HeoMeejung AhnJe Kyung SeongHyun Wook KimGon Sup KimPublished in: Nutrients (2022)
Understanding the triggers and therapeutic targets for gastric cancer, one of the most common cancers worldwide, can provide helpful information for the development of therapeutics. RNA sequencing technology can be utilized to identify complex disease targets and therapeutic applications. In the present study, we aimed to establish the pharmacological target of Kynurenic acid (KYNA) for gastric cancer AGS cells and to identify the biological network. RNA sequencing identified differentially expressed genes (DEGs) between KYNA-treated and untreated cells. A total of 278 genes were differentially expressed, of which 120 genes were up-regulated, and 158 genes were down-regulated. Gene ontology results confirmed that KYNA had effects such as a reduction in genes related to DNA replication and nucleosome organization on AGS cells. Protein-protein interaction was confirmed through STRING analysis, and it was confirmed that cancer cell growth and proliferation were inhibited through KEGG, Reactome, and Wiki pathway analysis, and various signaling pathways related to cancer cell death were induced. It was confirmed that KYNA treatment reduced the gene expression of cancer-causing AP-1 factors (Fos, Jun, ATF, and JDP) in AGS cell lines derived from gastric cancer. Overall, using next-generation transcriptome sequencing data and bioinformatics tools, we confirmed that KYNA had an apoptosis effect by inducing changes in various genes, including factor AP-1, in gastric cancer AGS cells. This study can identify pharmacological targets for gastric cancer treatment and provide a valuable resource for drug development.
Keyphrases
- cell cycle arrest
- cell death
- induced apoptosis
- genome wide
- gene expression
- single cell
- endoplasmic reticulum stress
- transcription factor
- signaling pathway
- genome wide identification
- bioinformatics analysis
- pi k akt
- protein protein
- dna methylation
- papillary thyroid
- small molecule
- copy number
- genome wide analysis
- lymph node metastasis
- newly diagnosed
- big data
- childhood cancer