Transcriptomic Profiling of OSCC Patients in an Indian Subset

Document Type : Research Articles

Authors

1 Department of Microbiology, School of Science, RK University, Rajkot, Gujarat, India.

2 Shashwat Haemato Onco Associates, Rajkot, Gujarat, India.

3 Department of Bioinformatics, Faculty of Technology, Marwadi University, Rajkot, Gujarat, India.

Abstract

Background: Tumor-specific biomarkers are needed for accomplishing antidote in early detection, as well as prognosis and designing therapeutic strategies. Comprehensive transcriptome profiling offers critical insights into the disease and reveal new avenue for drug discovery. Methods: Total 5 cancerous and histopathological normal tissue pairs of 5 OSCC patients included in the petite study. Transcriptome sequencing was performed using Roche’s 454 sequencing platform followed by CLC Genomics Workbench was used to examine gene expression in OC development. Results: A total 2082 genes were differentially expressed across all the five tumor-control pairs collected from the OC patients during the surgery. From these 1092 upregulated and 273 downregulated genes, whereas 717 genes were found to be non-significant. The genes with pvalue <0.05 and log2foldchange > 1 or log2foldchange < -1 were considered for further enrichment analysis. Topfunn was used for gene enrichment analysis to identify gene enrichment pathway analysis found some cancer related pathways such as TNF signaling, p53 signaling pathway, cGMP-PKG signaling pathway, Apelin signaling pathway and IL-17 signaling pathway were strikingly involved in proliferation and apoptosis of tumor cells. The PPI network construction was performed and identified 8 best protein interactions. Conclusion: The current study reports molecular biomarkers including INHBA, FJX1, OLR1, CDK2, IGHM, CXCL11, SH2D5 and FABP5 associated with cancer that can led to identify potential therapeutic targets for the better prognosis of the cancer patients. The signature candidate can be translated to clinical practice to increase early diagnostic accuracy.

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Volume 25, Issue 1
January 2024
Pages 233-239
  • Receive Date: 11 September 2023
  • Revise Date: 23 November 2023
  • Accept Date: 24 January 2024
  • First Publish Date: 24 January 2024