m7G regulator-mediated molecular subtypes and tumor microenvironment in kidney renal clear cell carcinoma.

RNA methylation modification plays an important role in immune regulation. m7G RNA methylation is an emerging research hotspot in the RNA methylation field. However, its role in the tumor immune microenvironment of kidney renal clear cell carcinoma (KIRC) is still unclear. We analyzed the expression profiles of 29 m7G regulators in KIRC, integrated multiple datasets to identify a novel m7G regulator-mediated molecular subtype, and developed the m7G score. We evaluated the immune tumor microenvironments in m7G clusters and analyzed the correlation of the m7G score with immune cells and drug sensitivity. We tested the predictive power of the m7G score for prognosis of patients with KIRC and verified the predictive accuracy of the m7G score by using the GSE40912 and E-MTAB-1980 datasets. The genes used to develop the m7G score were verified by qRT-PCR. Finally, we experimentally analyzed the effects of WDR4 knockdown on KIRC proliferation, migration, invasion, and drug sensitivity. We identified three m7G clusters. The expression of m7G regulators was higher in cluster C than in other clusters. m7G cluster C was related to immune activation, low tumor purity, good prognosis, and low m7G score. Cluster B was related to drug metabolism, high tumor purity, poor survival, and high m7G score. Cluster A was related to purine metabolism. The m7G score can well-predict the prognosis of patients with KIRC, and its prediction accuracy based on the m7G score nomogram was very high. Patients with high m7G scores were more sensitive to rapamycin, gefitinib, sunitinib, and vinblastine than other patients. Knocking down WDR4 can inhibit the proliferation, migration, and invasion of 786-0 and Caki-1 cells and increase sensitivity to sorafenib and sunitinib. We proposed a novel molecular subtype related to m7G modification and revealed the immune cell infiltration characteristics of different subtypes. The developed m7G score can well-predict the prognosis of patients with KIRC, and our research provides a basis for personalized treatment of patients with KIRC.