Background: In recent years, high-throughput omics technologies have been widely used globally to identify potential biomarkers and therapeutic targets in various cancers. However, apart from large consortiums such as The Cancer Genome Atlas, limited attempts have been made to mine existing datasets pertaining to cancers. Methods and Results: In the current study, we used an omics data analysis approach wherein publicly available protein expression data were integrated to identify functionally important proteins that revealed consistent dysregulated expression in head and neck squamous cell carcinomas. Our analysis revealed members of the integrin family of proteins to be consistently altered in expression across disparate datasets. Additionally, through association evidence and network analysis, we also identified members of the laminin family to be significantly altered in head and neck cancers. Members of both integrin and laminin families are known to be involved in cell-extracellular matrix adhesion and have been implicated in tumor metastatic processes in several cancers. To this end, we carried out immunohistochemical analyses to validate the findings in a cohort (n = 50) of oral cancer cases. Laminin-111 expression (composed of LAMA1, LAMB1, and LAMC1) was found to correlate with cell differentiation in oral cancer, showing a gradual decrease from well differentiated to poorly differentiated cases. Conclusion: This study serves as a proof-of-principle for the mining of multiple omics datasets coupled with selection of functionally important group of molecules to provide novel insights into tumorigenesis and cancer progression.
All Science Journal Classification (ASJC) codes
- Pathology and Forensic Medicine
- Microbiology (medical)