Pan-Cancer Prognostic, Immunity, Stemness, and Anticancer Drug Sensitivity Characterization of N6-Methyladenosine RNA Modification Regulators in Human Cancers.

Rui Li,Yun-Hong Yin,Jian-Ping Li,Xiao Liu,Yi-Qing Qu,Xiu-Li Ji

doi:10.3389/fmolb.2021.644620

Abstract

N6-methyladenosine RNA modification plays a significant role in the progression of multiple tumorigenesis. Our study identified the imperative role of m6A regulators in the tumor immune microenvironment, survival, stemness score, and anticancer drug sensitivity of pan-cancer. The Wilcox test was to identify the differential expression between 17 m6A regulators across 33 TCGA cancer types and their normal tissues from UCSC Xena GDC pan-cancer. Survival analysis of m6A-related regulators in 33 TCGA cancer types was identified using the “survival” and “survminer” package. The Spearman correlation test and Pearson correlation test were used to identify the correlation relationship between m6A regulators expression and tumor microenvironment, tumor stem cell score, and drug sensitivity of anticancer drugs. ConsensusPathDB was used for exploring m6A regulators functional enrichment. The 17 (METTL3, WTAP, METTL14, RBM15, RBM15B, VIRMA, HNRNPC, HNRNPA2B1, YTHDC1, ZC3H13, YTHDF1, YTHDC2, YTHDF2, IGF2BP3, IGF2BP1, FTO, and ALKBH5) m6A regulators were differentially expressed in 18 TCGA cancer types and adjacent normal tissues. Correlation analysis indicated that the relationship between the expression of 17 m6A regulators and tumor microenvironment indicated that the higher expression of m6A regulators, the higher the degree of tumor stem cells. The anticancer drug sensitivity analysis indicated that ZC3H13 expression had a positive relationship with anticancer drugs such as selumetinib, dabrafenib, cobimetinib, trametinib, and hypothemycin (p < 0.001). YTHDF2 expression was significantly negatively correlated with the anticancer drug dasatinib (p < 0.001). The pan-cancer immune subtype analysis showed that the 17 m6A regulators were significantly different in immune subtype C1 (wound healing), C3 (inflammatory), C2 (IFN-gamma dominant), C5 (immunological quiet), C4 (lymphocyte depleted), and C6 (TGF-beta dominant) (p < 0.001). Our study provides a comprehensive insight for revealing the significant role of m6A regulators in the tumor immune microenvironment, stemness score, and anticancer drug sensitivity of human cancers.

Highlights

MATERIALS AND METHODSN6 adenosine methylation (m6A), as the most common type of RNA modification, is regulated by three types of regulators, including m6A-binding proteins (“readers”), methyltransferases (“writers”), and demethylases (“erasers”), which play a significant role in the progression and development of cancer (Choe et al, 2018; Yang et al, 2018).The methyltransferases complex includes METTL3, METTL14, WTAP, RBM15, RBM15B, VIRMA, and ZC3H13 (Wang et al., 2017)
We obtained m6A regulators expression in TCGA database from 18 (BLCA, LUAD, COAD, BRCA, CHOL, HNSC, ESCA, GBM, KIRC, UCEC, READ, KICH, LIHC, KIRP, LUSC, THCA, PRAD, and STAD) cancers
The expression levels of YTHDF1, YTHDF2, HNRNPC, and HNRNPA2B1 were higher in 18 TCGA pan-cancers, while the expression of IGF2BP1 and IGF2BP3 was lower in 18 TCGA pancancers

Summary

MATERIALS AND METHODS

N6 adenosine methylation (m6A), as the most common type of RNA modification, is regulated by three types of regulators, including m6A-binding proteins (“readers”), methyltransferases (“writers”), and demethylases (“erasers”), which play a significant role in the progression and development of cancer (Choe et al, 2018; Yang et al, 2018). Differential expression, tumor microenvironment, drug sensitivity, Cox, and immune subtype analysis of m6A regulators among 33 TCGA cancer types were still lacking. We deleted the normal data and kept the transcription data of 33 TCGA cancers to show a box plot of the expression levels of 17 m6A regulators (METTL3, WTAP, METTL14, RBM15, RBM15B, VIRMA, HNRNPC, HNRNPA2B1, YTHDC1, ZC3H13, YTHDC2, YTHDF2, IGF2BP3, IGF2BP1, FTO, YTHDF1, and ALKBH5) in 33 tumors. We intersected transcription gene expression data with estimate score of 33 TCGA cancer samples to perform the Spearman correlation test. We used the Spearman correlation test to conduct the correlation analysis between m6A-related gene expression and LUAD and LUSC immune score, estimate score, DNAss, RNAss, and stromal score

RESULTS

DISCUSSION

ETHICS STATEMENT