Identification of clinical prognostic features of esophageal cancer based on m6A regulators

Huimei Wang; Yiping Zhang; Lin Chen; Yufeng Liu; Chen Xu; Dongxian Jiang; Qi Song; Haixing Wang; Liyan Wang; Yu Lin; Yuanmei Chen; Junqiang Chen; Yuanji Xu; Yingyong Hou

doi:10.3389/fimmu.2022.950365

Identification of clinical prognostic features of esophageal cancer based on m6A regulators

Front Immunol. 2022 Sep 8:13:950365. doi: 10.3389/fimmu.2022.950365. eCollection 2022.

Authors

Huimei Wang¹, Yiping Zhang², Lin Chen², Yufeng Liu¹, Chen Xu¹, Dongxian Jiang¹, Qi Song¹, Haixing Wang¹, Liyan Wang², Yu Lin³, Yuanmei Chen⁴, Junqiang Chen³, Yuanji Xu³, Yingyong Hou¹

Affiliations

¹ Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China.
² Clinical Oncology School of Fujian Medical University, Fuzhou, China.
³ Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
⁴ Department of Thoracic Surgery, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.

Abstract

Background: Esophageal cancer (ESCA) is a common malignancy with high morbidity and mortality. n6-methyladenosine (m6A) regulators have been widely recognized as one of the major causes of cancer development and progression. However, for ESCA, the role of regulators is unclear. The aim of this study was to investigate the role of m6A RNA methylation regulators in the immune regulation and prognosis of ESCA.

Methods: RNA-seq data were downloaded using the Cancer Genome Atlas (TCGA) database, and the expression differences of m6A RNA methylation regulators in ESCA were analyzed. Further m6A methylation regulator markers were constructed, and prognostic and predictive values were assessed using survival analysis and nomograms. Patients were divided into low-risk and high-risk groups. The signature was evaluated in terms of survival, single nucleotide polymorphism (SNP), copy number variation (CNV), tumor mutation burden (TMB), and functional enrichment analysis (TMB). The m6A expression of key genes in clinical specimens was validated using quantitative reverse transcription polymerase chain reaction (qRT-PCR).

Results: In ESCA tissues, most of the 23 regulators were significantly differentially expressed. LASSO regression analysis included 7 m6A-related factors (FMR1, RBMX, IGFBP1, IGFBP2, ALKBH5, RBM15B, METTL14). In addition, this study also identified that the risk model is associated with biological functions, including base metabolism, DNA repair, and mismatch repair. In this study, a nomogram was created to predict the prognosis of ESCA patients. Bioinformatics analysis of human ESCA and normal tissues was performed using qRT-PCR. Finally. Seven genetic features were found to be associated with m6A in ESCA patients. The results of this study suggest that three different clusters of m6A modifications are involved in the immune microenvironment of ESCA, providing important clues for clinical diagnosis and treatment.

Keywords: esophageal cancer; m6A RNA methylation regulators; nomogram; prognosis; signature; the cancer genome atlas.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Biomarkers, Tumor / genetics
Biomarkers, Tumor / metabolism
DNA Copy Number Variations*
Esophageal Neoplasms* / genetics
Fragile X Mental Retardation Protein / genetics
Fragile X Mental Retardation Protein / metabolism
Humans
Methylation
Prognosis
RNA / metabolism
Tumor Microenvironment

Substances

Biomarkers, Tumor
FMR1 protein, human
Fragile X Mental Retardation Protein
RNA