Abstract
Fanconi anemia (FA) pathway is a typical and multienzyme-regulated DNA damage repairer that influences the occurrence and development of disease including cancers. Few comprehensive analyses were reported about the role of FA-related genes (FARGs) and their prognostic values in cancers. In this study, a comprehensive pan-cancer analysis on 79 FARGs was performed. According to the correlation analyses between HPV integration sites and FARGs, we found that FARGs played specific and critical roles in HPV-related cancers, especially in cervical cancer (CC). Based on this, a FARGs-associated prognostic risk score (FPS) model was constructed, and subsequently a nomogram model containing the FPS was developed with a good accuracy for CC overall survival (OS) and recurrence-free survival (RFS) outcome prediction. We also used the similar expression pattern of FARGs by consensus clustering analysis to separate the patients into three subgroups that exhibited significant differential OS but not RFS. Moreover, differential expressed genes (DEGs) between the two risk groups or three clusters were identified and immune pathways as well as cell adhesion processes were determined by functional enrichment analysis. Results indicated that FARGs might promote occurrence and development of CC by regulating the immune cells' infiltration and cell adhesion. In addition, through the machine learning models containing decision tree, random forest, naïve bayes, and support vector machine models, screening of important variables on CC prognosis, we finally determined that ZBTB32 and CENPS were the main elements affecting CC OS, while PALB2 and BRCA2 were for RFS. Kaplan-Meier analysis revealed that bivariate prediction of CC outcome was reliable. Our study systematically analyzed the prognostic prediction values of FARGs and demonstrated their potential mechanism in CC aggressiveness. Results provided perspective in FA pathway-associated modification and theoretical basis for CC clinical treatments.