Blocking of EGFR Signaling is a Latent Strategy for the Improvement of Prognosis of HPV Induced Cancer

Human papillomavirus (HPV) is a dsDNA virus and its high-risk subtypes increase cancer risks. Yet, the mechanism of HPV infection and pathogenesis still remain unclear. Therefore, understanding the molecular mechanisms, and the pathogenesis of HPV are crucial in the prevention of HPV related cancers. In this study, we analyzed cervix squamous cell carcinoma (CESC) and head and neck carcinoma (HNSC) combined data to investigate various HPV induced cancer common feature. We showed that epidermal growth factor receptor (EGFR) was downregulated in HPV positive (HPV+) cancer, and that HPV+ cancer patients exhibited better prognosis than HPV negative (HPV-) cancer patients. Our study also showed that TP53 mutation rate is lower in HPV+ cancer than in HPV- cancer and that TP53 can be modulated by HPV E7 protein. However, there was no significant difference in the expression of wildtype TP53 in both groups. Subsequently, we constructed HPV-human interaction network and found that EGFR is a critical factor. From the network, we also noticed that EGFR is regulated by HPV E7 protein and hsa-miR-944. Moreover, while phosphorylated EGFR is associated with a worse prognosis, EGFR total express level is not significantly correlated with prognosis. This indicates that EGFR activation will induce a worse outcome in HPV+ cancer patients. Further enrichment analysis showed that EGFR downstream pathway and cancer relative pathway are diversely activated in HPV+ cancer and HPV- cancer. In summary, HPV E7 protein downregulates EGFR that downregulates phosphorylated EGFR and inhibit EGFR related pathways which in turn and consequently induce better prognosis. ImportanceAlthough HPV infection has been studied in various cancer types, there are only limited studies that have focused on the common effect of HPV related cancer. Consequently, this study focused on CESC and HNSC, two cancer types with high HPV infection proportion in cohort, thereby, intending to dig out the common effects and mechanisms of HPV+ cancers. Unlike some virus-human interaction prediction studies, the P-HIPSter database provides virus-human protein interaction based on protein structure prediction. Through this data, our interaction network was able to uncover previously unnoticed protein interactions. Our finding revealed that HPV infection caused various gene expression differences, and a great amount of which interact with EGFR, a cancer related gene. Therefore, since EGFR is associated with HPV+ cancer patients survival, some FDA proved EGFR inhibitors would be potential anti-HPV drugs.