Prognostic and Predictive Value of Transcription Factors Panel for Digestive System Carcinoma - Fang, Guoxu; Fan, Jianhui; Ding, Zongren; Li, Rong; Lin, Kongying; Fu, Jun; Huang, Qizhen; Zeng, Yongyi; Liu, Jingfeng (Frontiers in Oncology, 2021)
Purpose: Digestive system carcinoma is one of the most devastating diseases worldwide. Lack of valid clinicopathological parameters as prognostic factors needs more accurate and effective biomarkers for high-confidence prognosis that guide decision making for optimal treatment of digestive system carcinoma. The aim of the present study was to establish a novel model to improve prognosis prediction of digestive system carcinoma, with a particular interest in transcription factors (TFs). Materials and Methods: A TF-related prognosis model of digestive system carcinoma with data from TCGA database successively were processed by univariate and multivariate Cox regression analysis. Then, for evaluating the prognostic prediction value of the model, ROC curve and survival analysis were performed by external data from GEO database. Furthermore, we verified the expression of TFs expression by qPCR in digestive system carcinoma tissue. Finally, we constructed a TF clinical characteristics nomogram to furtherly predict digestive system carcinoma patient survival probability with TCGA database. Results: By Cox regression analysis, a panel of 17 TFs (NFIC, YBX2, ZBTB47, ZNF367, CREB3L3, HEYL, FOXD1, TIGD1, SNAI1, HSF4, CENPA, ETS2, FOXM1, ETV4, MYBL2, FOXQ1, ZNF589) was identified to present with powerful predictive performance for overall survival of digestive system carcinoma patients based on TCGA database. A nomogram that integrates TFs was established, allowing efficient prediction of survival probabilities and displaying higher clinical utility. Conclusion: The 17-TF panel is an independent prognostic factor for digestive system carcinoma, and 17 TFs based nomogram might provide implication an effective approach for digestive system carcinoma patient management and treatment.