Comprehensive analysis of the functional and prognostic value of E2F transcription factors in human prostate cancer through data mining and experimental validation

BACKGROUND: A growing body of evidence shows that E2F transcription factors play a significant role in the tumorigenesis of prostate cancer. However, their functional and prognostic value has not been fully illustrated. Therefore, we used bioinformatics methods to further analyze the possible roles of E2F transcription factors in the development and progression of prostate cancer. METHODS: We explored the expression levels of E2F transcription factors using data from The Cancer Genome Atlas (TCGA) and Oncomine database in paired and unpaired samples. The clinical correlation and prognostic value of E2F transcription factors were assessed. Using the R package “pROC”, we judged the diagnostic value of E2F transcription factors. The online website tool cBioPortal was also employed to find possible gene alterations of E2F transcription factors in samples from TCGA. The R package “clusterprofiler” was used to conduct functional analysis. Moreover, we also used the Tumor Immune Estimation Resource to search for the associations between E2F transcription factors and the infiltration levels of 6 kinds of immune cells. Finally, quantitative real-time polymerase chain reaction (PCR) was conducted to validate the expression levels of E2F transcription factors in human paired prostate tissues. RESULTS: E2F1/2/3/5 messenger RNA (mRNA) expression levels were higher in prostate cancer tissues than in normal tissues, while E2F4 and E2F6 mRNA expression levels were lower (P<0.05). All E2F transcription factors were associated with clinical parameters. Kaplan-Meier analysis revealed that E2F1/4/6/8 were notably associated with the overall survival of patients with prostate cancer (P<0.05). Receiver operating characteristic (ROC) curve results showed that except for E2F7, the other E2F transcription factors had diagnostic value for prostate cancer (P<0.05). We further found close associations between E2F transcription factors and the infiltration levels of immune cells. The results of quantitative real-time PCR were consistent with those from public databases. CONCLUSIONS: E2F transcription factor family members are differentially expressed in prostate cancer and are significantly related to the prognosis of patients, suggesting that they may be adopted as biomarkers for prognosis prediction and the treatment of prostate cancer.