Up-regulation of extracellular-matrix and inflammation related genes in oral squamous cell carcinoma.

OBJECTIVE: Oral squamous cell carcinoma (OSCC) is the most prevalent malignancy with late-presentation, site-specific heterogeneity, and high-propensity for recurrence/metastasis that has shown rise in mortality. Lately, research emphasize on dynamic interactions between tumor-cells and extracellular-matrix components within tumor-microenvironment that promote tissue integrity loss and carcinogenesis. Therefore, OSCC clinical-management is still challenging. DESIGN: Present study validated clinical utility of a 13 gene-panel in two chief sub-sites of OSCC: Buccal mucosa squamous cell carcinoma (BMSCC) (N = 50) and Tongue squamous cell carcinoma (TSCC) (N = 52) using qRT-PCR. Principal component analysis and binary logistic regression analysis were applied to acquire definite multi gene models. Protein expression analysis was employed using the Human Protein Atlas, UALCAN and TIMER 2.0 databases to explore potential correlation between immune cells and gene-panels. RESULTS: Significant up-regulation of CXCL8, CXCL10, FN1, GBP1, IFIT3, ISG15, MMP1, MMP3, MMP10, PLAU, SERPINE1 and SPP1 except OASL was observed in OSCC tissue in comparison of absolute normal controls. Although, this gene-panel could potentially discriminate OSCC tissues from absolute normal controls as solitarily diagnostic and/or predictive biomarkers, models generated also showed substantial discriminating efficacy. Eight-genes were found to be significantly associated with poor-prognosis on clinico-pathological association. Protein-expression confirmed overexpression of gene-panel and added advantage of being secretory-protein. Importantly, up-regulated genes in our study showed significant relation with immune-cells infiltration suggesting their contribution in immune-escape. CONCLUSION: Thus, we propose that the 13 gene-panel could pave the way to effective and personalized clinical-management of OSCC in terms of diagnostic and prognostic measures and thereby as therapeutic targets.

An integrative analysis to enumerate candidate genes for clinical use in oral cancer.

Background: Oral cancer (OC) is the most pernicious sub-site of head and neck tumours with poor prognostic value that is largely ascribed to the lack of ideal biomarkers and therapeutic targets. This fact highlights an urgent need to identify biomarkers that can further aid in OC management. Aim: The aim of this study was to identify a gene panel with a maximum clinical utility for OC. Materials and Methods: Eight eligible datasets were downloaded from the Gene Expression Omnibus Database, containing 320OC samples and 173 normal samples. The data were processed by GeneSpring software to reveal differentially expressed genes between OC tissues and normal tissues in eight individual experiments. Functional enrichment and network analysis were performed using PANTHER and STRING databases for concordant genes (fold change >10; P ≤ 0.05). The selected genes were cross-validated in the cancer genome atlas (TCGA), Oncomine, and KaplanMeier (KM) plotter databases. Results: Totally, 65 concordant genes were identified, including 37 up-regulated genes and 28 down-regulated genes. A 13-gene panel CXCL8, CXCL10, FN1, GBP1, IFIT3, ISG15, MMP1, MMP3, MMP10, OASL, SERPINE1, SPP1, and PLAU was elected from the lists of functionally enriched genes, hub genes, and genes that showed high alterations for mutation, copy number variation, and mRNA expression status in 'Head and Neck Squamous Cell Carcinoma patients (n = 279; TCGA, Nature 2015)'. Further, validation in Oncomine database demonstrated significant over-expression of all elected genes in OC patients across multiple datasets. In addition, out of 13, six genes (CXCL8, CXCL10, FN1, PLAU, SERPINE1, and SPP1) showed significant association with the prognosis of Head and Neck cancer patients (n = 500) in the KM plotter database. Conclusions: Using an integrative analysis, our study investigated and validated a 13-gene panel for OC which can be used to improve current diagnostic, prognostic, and treatment approaches.