One of the major challenges in cancer research is identifying biomarkers involved in molecular aspects of cancer, including initiation, progression, and therapy outcomes of different cancers. Survival analysis is used to predict the impacts of alteration in gene expression of specific genes on cancer progression. Although studying the impacts of all genes would be infeasible, understanding the survival impacts of transcription factors might be useful. TCGA datasets have been widely used to do such analysis. Here, we have studied the impacts of transcription factors with a proven role in cancer (Oncofactors) on patients’ survival in 13 major TCGA datasets. We have first identified the differentially expressed genes among patients and healthy people. Next, we selected the differentially expressed oncofactors among these genes. In the next step, using clinical data, the survival analysis of each cancer type was conducted using a p-value of 0.01 as the significance level. Interestingly, different sets of TFs were significantly associated with survival for each type of cancer. Unexpectedly, our results indicate that only a limited number of oncofactors might impact on overall survival of cancer patients.