Prognostic Value and Possible Mechanism of m6A Methyltransferase METTL3 in Prostate Cancer

Abstract

Background: The N6-methyladenosine (m6A) methyltransferase METTL3 has been reported to be closely related to prostate cancer (PCa). Thus, we aimed to explore its prognostic value and possible mechanism in PCa.Methods: The METTL3 gene and protein expression status in between the PCa and normal tissues as well as the correlation between METTL3 and Gleason score (GS) were evaluated using The Cancer Genome Atlas Project (TCGA) dataset and the tissue microarray (TMA) dataset. The prognostic value of METTL3 was evaluated using 490 PCa patients from TCGA cohort followed by the verification using 515 PCa patients from the dataset integrated by TCGA cohort and International Cancer Genome Consortium (ICGC) cohort. The machine learning methods were used for the possible mechanism of METTL3 which was closely related to the prognosis of PCa. A nomogram was constructed to provide a quantitative approach to predict the prognosis of PCa. Results: The gene and protein expression levels of METTL3 in the PCa tissues were significantly higher than those in the normal tissues, and the gene and protein expression levels of METTL3 in the high (GS>7) risk PCa tissues were significantly higher than those in the low-moderate risk PCa (GS≤7) tissues. The PCa patients with high expression level of METTL3 had higher risk for the progression-free survival (PFS) events and poorer short-term and long-term PFS than those with low expression level of METTL3. Through using machine learning, a METTL3 related risk model (M-RM) consisted of seven m6A methyltransferase METTL3 target genes was obtained. The high M-RM score was revealed to be significantly related to the poor PFS of PCa as well as the high activity of the KEGG pathways closely related to the process of cell cycle. Conclusion: METTL3 has the potential to be the prognostic predictor of PCa. Its coded protein may affect the prognosis of PCa mainly through regulating the expression of their target genes closely related to the process of cell cycle. These outcomes will be benefit to improve the prognosis of patients, as well as reduce the mortality of PCa.