In silico identification of the specific pathways in each stage of colorectal cancer and the association of their top genes with drug resistance and sensitivity.
Reza HashemiMaryam PeymaniKamran GhaediHana SaffarPublished in: Medical oncology (Northwood, London, England) (2022)
Investigating the specific pathways and their relation with survival, mutation, sensitivity, and resistance to various drugs in different stages of colorectal cancer (CRC) could be effective in cancer treatment. In this study, identifying the specific pathways in each stage of CRC compared to other stages was considered via meta-analytic methodology. The Cancer Genome Atlas (TCGA) data with gene set enrichment analysis (GSEA) software, and CRC RNA-Seq data were used to enrich and determine specific pathways as well as to evaluate the expression level of TOP RANK genes. In addition, The Cancer Cell Line Encyclopedia (CCLE) data were used to correlate candidate genes with drug resistance. Finally, using Gene Expression Omnibus (GEO) data, drugs that could affect the expression level of these genes were identified. Three specific molecular pathways, including oxidative phosphorylation (OXPHOS), regulation of transporter activity (RTA), and negative regulation of transmembrane receptor protein serine threonine kinase (NRSTK) have been identified as hub pathways for stages II, III, and IV, respectively (P < 0.01). The expression level of TOP RANK genes in each stage increased on average twice compared to other stages (P < 0.01), and CCNB1, DKK1, NOG genes were associated with survival in stages II and IV, respectively (P < 0.01). The expression of some selected genes had a correlation with drug resistance and sensitivity (P < 0.05). GEO data revealed that gamma-tocotrienol (g-T3), NSC319726, and Casiopeina Cas-II-gly may reduce the expression of, NDUFAF1, CCNB1, DKK1 genes, respectively (P < 0.01). Specific pathways and TOP RANK genes could lead to cancer progression and malignancy, resistance to chemotherapy drugs, poor survival in patients, and metastasis. Therefore, identification and targeting these pathways at each stage could be crucial in inhibiting progression at different stages of CRC.
Keyphrases
- childhood cancer
- bioinformatics analysis
- genome wide
- poor prognosis
- genome wide identification
- gene expression
- rna seq
- single cell
- electronic health record
- dna methylation
- big data
- genome wide analysis
- end stage renal disease
- chronic kidney disease
- machine learning
- transcription factor
- signaling pathway
- artificial intelligence
- copy number
- radiation therapy
- tyrosine kinase
- newly diagnosed
- cancer therapy
- papillary thyroid
- free survival
- patient reported outcomes
- protein protein
- locally advanced