Differential expression analysis of genes and long non-coding RNAs associated with KRAS mutation in colorectal cancer cells.
Mahsa SalianiRazieh JalalAli JavadmaneshPublished in: Scientific reports (2022)
KRAS mutation is responsible for 40-50% of colorectal cancers (CRCs). RNA-seq data and bioinformatics methods were used to analyze the transcriptional profiles of KRAS mutant (mtKRAS) in comparison with the wild-type (wtKRAS) cell lines, followed by in-silico and quantitative real-time PCR (qPCR) validations. Gene set enrichment analysis showed overrepresentation of KRAS signaling as an oncogenic signature in mtKRAS. Gene ontology and pathway analyses on 600 differentially-expressed genes (DEGs) indicated their major involvement in the cancer-associated signal transduction pathways. Significant hub genes were identified through analyzing PPI network, with the highest node degree for PTPRC. The evaluation of the interaction between co-expressed DEGs and lncRNAs revealed 12 differentially-expressed lncRNAs which potentially regulate the genes majorly enriched in Rap1 and RAS signaling pathways. The results of the qPCR showed the overexpression of PPARG and PTGS2, and downregulation of PTPRC in mtKRAS cells compared to the wtKRAS one, which confirming the outputs of RNA-seq analysis. Further, significant upregualtion of miR-23b was observed in wtKRAS cells. The comparison between the expression level of hub genes and TFs with expression data of CRC tissue samples deposited in TCGA databank confirmed them as distinct biomarkers for the discrimination of normal and tumor patient samples. Survival analysis revealed the significant prognostic value for some of the hub genes, TFs, and lncRNAs. The results of the present study can extend the vision on the molecular mechanisms involved in KRAS-driven CRC pathogenesis.
Keyphrases
- wild type
- genome wide identification
- rna seq
- bioinformatics analysis
- genome wide
- genome wide analysis
- single cell
- transcription factor
- poor prognosis
- long non coding rna
- network analysis
- induced apoptosis
- signaling pathway
- cell proliferation
- dna methylation
- cell cycle arrest
- gene expression
- oxidative stress
- copy number
- big data
- electronic health record
- lymph node
- high resolution
- endoplasmic reticulum stress
- cell death
- young adults
- artificial intelligence
- binding protein
- heat stress
- epithelial mesenchymal transition