The purpose of the study has been the identification of mutated gene pairs, which results in poor survival in 3 types of squamous cell carcinomas: Head and Neck Squamous Cell Carcinoma (HNSCC), Cervical Squamous Cell Carcinoma (CSCC), and Skin Squamous Cell Carcinoma (SSCC). The genomic and clinical data used in the study were downloaded from the cBioPortal for Cancer Genomics platform, were preprocessed and were analyzed using the R language and the maftools library. In technical terms, the data sets obtained from the platform represent objects from the class DataFrame with tens of thousands of rows and hundreds of columns. Kaplan-Meier analysis was performed for each gene combination identified as a poor prognostic factor. Through genemania algorithm, we detected the genes that can spotlight the interconnection between each pair of genes and specific cancer. The bioinformatics analysis of the data allowed the identification of three gene sets that if mutate simultaneously, dramatically decrease the probability of survival. The sets are MUC4-EP300 in CSCC, TP53-RYR2 in HNSCC, and CSMD1PCDH15 in SSCC. In all cases p-value is less than 0.05. The three sets of genes associated with poor survival of patients with different types of squamous cell carcinoma have the potential to be used as prognostic and risk stratification biomarkers.