Identification of N1 methyladenosine‐related biomarker predicting overall survival outcomes and experimental verification in ovarian cancer

Abstract

AbstractAimThis study aimed to construct a N1‐methyladenosine (m1A)‐related biomarker model for predicting the prognosis of ovarian cancer (OVCA).MethodsOVCA samples were clustered into two subtypes using the Non‐Negative Matrix Factorization (NMF) algorithm, including TCGA (n = 374) as the training set and GSE26712 (n = 185) as the external validation set. Hub genes, which were screened to construct a risk model, and nomogram to predict the overall survival of OVCA were explored and validated through various bioinformatic analysis and quantitative real‐time PCR.ResultsFollowing bootstrap correction, the C‐index of nomogram was 0.62515, showing reliable performance. The functions of DEGs in the high‐ and low‐risk groups were mainly enriched in immune response, immune regulation, and immune‐related diseases. The immune cells relevant to the expression of hub genes were explored, for example, Natural Killer (NK) cells, T cells, activated dendritic cells (aDC).ConclusionsAADAC, CD38, CACNA1C, and ATP1A3 might be used as m1A‐related biomarkers for OVCA, and the nomogram labeled with m1A for the first time had excellent performance for predicting overall survival in OVCA.