Identification of potential genes and pathways for response prediction of neoadjuvant chemoradiotherapy in patients with rectal cancer by systemic biological analysis

Identification of Key Gene Targets for Sensitizing Colorectal Cancer to Chemoradiation: an Integrative Network Analysis on Multiple Transcriptomics Data

PURPOSE

Colorectal cancer (CRC) is a main cause of morbidity and mortality in the world. Chemoradioresistance is a major problem in CRC treatment. Identification of novel therapeutic targets in order to overcome treatment resistance in CRC is necessary.

METHODS

In this study, gene expression omnibus (GEO) database was searched to find microarray datasets. Data normalization/analyzing was performed using ExAtlas. The gene ontology (GO) and pathway enrichment analysis was performed using g:Profiler. Protein-protein interaction network (PPIN) was constructed by Search Tool for the Retrieval of Interacting Genes (STRING) and analyzed using Cytoscape. Survival analysis was done using Kaplan-Meier curve method.

RESULTS

Forty-one eligible datasets were included in study. A total of 12,244 differentially expressed genes (DEGs) and 7337 unique DEGs were identified. Among them, 1187 DEGs were overlapped in ≥ 3 datasets. Fifty-five overlapped genes were considered as hub genes. Common hub genes in chemo/radiation/chemoradiation datasets were chosen as the essential candidate genes (n = 13). Forty-one hub gene and 7 essential candidate genes were contributed in the significant modules. The modules were mainly enriched in the signaling pathways of senescence, autophagy, NF-κB, HIF-1, stem cell pluripotency, notch, neovascularization, cell cycle, p53, chemokine, and PI3K-Akt. NGFR, FGF2, and PROM1 genes were significantly predictors of CRC patient's survival.

CONCLUSION

Our study revealed three-gene signatures as potential therapeutic targets and also candidate molecular markers in CRC chemoradioresistance.