Search Results (2)

Survival analysis of the Cancer Genome Atlas (TCGA) dataset is a well-known method for discovering gene expression-based prognostic biomarkers of head and neck squamous cell carcinoma (HNSCC). A cutoff point is usually used in survival analysis for patient dichotomization when using continuous gene expression values. There is some optimization software for cutoff determination. However, the software’s predetermined cutoffs are usually set at the medians or quantiles of gene expression values. There are also few clinicopathological features available in pre-processed datasets. We applied an in-house workflow, including data retrieving and pre-processing, feature selection, sliding-window cutoff selection, Kaplan–Meier survival analysis, and Cox proportional hazard modeling for biomarker discovery. In our approach for the TCGA HNSCC cohort, we scanned human protein-coding genes to find optimal cutoff values. After adjustments with confounders, clinical tumor stage and surgical margin involvement were found to be independent risk factors for prognosis. According to the results tables that show hazard ratios with Bonferroni-adjusted p values under the optimal cutoff, three biomarker candidates, CAMK2N1, CALML5, and FCGBP, are significantly associated with overall survival. We validated this discovery by using the another independent HNSCC dataset (GSE65858). Thus, we suggest that transcriptomic analysis could help with biomarker discovery. Moreover, the robustness of the biomarkers we identified should be ensured through several additional tests with independent datasets. Full article

The Pathology Atlas is an open-access database that reports the prognostic value of protein-coding transcripts in 17 cancers, including head and neck cancer. However, cancers of the various head and neck anatomical sites are specific biological entities. Thus, the aim of the present study was to validate promising prognostic markers for head and neck cancer reported in the Pathology Atlas in oral tongue squamous cell carcinoma (OTSCC). We selected three promising markers from the Pathology Atlas (CALML5, CD59, LIMA1), and analyzed their prognostic value in a Norwegian OTSCC cohort comprising 121 patients. We correlated target protein and mRNA expression in formalin-fixed, paraffin-embedded cancer tissue to five-year disease-specific survival (DSS) in univariate and multivariate analyses. Protein expression of CALML5 and LIMA1 were significantly associated with five-year DSS in the OTSCC cohort in univariate analyses (p = 0.016 and p = 0.043, respectively). In multivariate analyses, lymph node metastases, tumor differentiation, and CALML5 were independent prognosticators. The prognostic role of the other selected markers for head and neck cancer patients identified through unbiased approaches could not be validated in our OTSCC cohort. This underlines the need for subsite-specific analyses for head and neck cancer. Full article