In Silico Analysis of Differentially Expressed Genes in Colorectal Carcinoma

Sobia Hassan, Talat Mirza, Ambrina Khatoon, Uzma Bukhari, Fouzia Shaikh


Background: Colorectal carcinoma (CRC) is a primary cause of morbidity and mortality worldwide. Resistance to therapy contributes to poor patient prognosis. The aim of our study is to identify the key proteins and interaction networks implicated in CRC which may serve as possible therapeutic targets and help in overcoming therapy resistance.

Methods: The microarray dataset of 58 cases and 62 controls was used to identify Differentially Expressed Genes (DEGs).After constructing protein-protein interaction networks , Cytoscape analysis was done to identify the hub proteins. Based on sub graph centrality, between-ness and degree (≥10), hub proteins were selected for further literature search and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.

Results: A total of 85 up-regulated genes and 95 down-regulated genes of CRC patients were selected based on criteria of P>0.05 and fold change>2.0. The PPI analysis revealed STAT3, HNRNPA2B1, RBM8A, RBM25, ATM, HIST1H2BK, SRSF5 and HNRNPDLas hub proteins. On the basis of criteria set for cytoscape analysis, STAT3 and HNRNPA2B1 were identified as key hub proteins. KEGG pathway analysis revealed vital role of STAT3 in carcinogenesis.

Conclusion: In addition of HNRNPA2B1 activation by STAT3, cross talk of STAT3 with other oncogenic signaling pathways signifies its role in colorectal carcinogenesis. Our study highlights thatSTAT3may be a possible therapeutic target which may help in overcoming the dilemma of resistance to drug treatment in advanced cases.

Keywords: STAT3, drug resistance, targeted therapy, bioinformatics    


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