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Differential gene expression analysis reveals new genetic variants implicated in oral cancer

A study published in Scientific Reports, has identified six significant oral cancer associated genes through differential analysis.

Oral cancer

Oral cancer is the eleventh most malignant cancer worldwide, constituting ~90% of all head and neck cancer subtypes. Surprisingly, the incidence of oral cancer is increasing within younger individuals. Evidence has shown that many biological systems are involved in the development and progression of oral cancer. However, the complications in system-interactions are unclear which hinders the development of effective treatments. Gene expression analysis can help investigate the differential expression of genes in different biological states, cell cycle stages, subjects or tissues. This is important in pinpointing biological processes for further investigation.

cDNA differential analysis

In this study, researchers performed a systems-level approach to explore the genetic complexity of oral cancer and to identify novel genes using cDNA differential analysis. Specifically, they analysed 21 oral cancer-related cDNA datasets. From the 30 differentially expressed genes, six were significant. This included CYP1A1, CYP1B1, ADCY2, C7, SERPINB5 and ANAPC13. These genes were aberrantly expressed in oral cancer. Furthermore, to determine their functional role, the team performed a genomic and interactive analysis. They found significant enrichment of these genes within xenobiotics metabolism, p53 signalling pathway and microRNA pathways – key pathways in cancer.

The expression profiling of these genes showed clear differences between cases and controls. Mutational analysis revealed the sequence predicted disordered region of 14%, 12.5%, 10.5% for ADCY2, CYP1B1, and C7 respectively. The team also found that these differentially associated with important gene signatures. Furthermore, they identified drug-interactions of these seed genes with seven FDA approved drugs. This has important implications for the design and identification of new drug targets.

To conclude, this study shows that system-level approaches are comprehensive and effective in sorting out disease-specific genetic variants from cDNA datasets. It has also provided further insight into oral cancer, with six new genes that researchers could use as potential diagnostic or drug targets. These seed genes interact with other essential genes that affect cell cycle and apoptosis resulting in carcinogenesis. The team believe that these findings provide a valuable framework for developing new therapeutic strategies against oral cancer. 

Image credit: By Image Team –

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Cancer / Cancer Research / Gene Expression