N7-methylguanosine-related lncRNAs: Distinction between hot and cold tumors and construction of predictive models in colon adenocarcinoma

Zhichao Cheng; Jiaqi Wang; Yixin Xu; Tao Jiang; Zhenyu Xue; Shuai Li; Ying Zhao; Hu Song; Jun Song

doi:10.3389/fonc.2022.951452

N7-methylguanosine-related lncRNAs: Distinction between hot and cold tumors and construction of predictive models in colon adenocarcinoma

Front Oncol. 2022 Sep 15:12:951452. doi: 10.3389/fonc.2022.951452. eCollection 2022.

Authors

Zhichao Cheng^{1

2

3}, Jiaqi Wang⁴, Yixin Xu², Tao Jiang², Zhenyu Xue³, Shuai Li³, Ying Zhao³, Hu Song², Jun Song^{2

3}

Affiliations

¹ The Graduate School, Xuzhou Medical University, Xuzhou, Jiangsu, China.
² Department of General Surgery, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, China.
³ Institute of Digestive Diseases, Xuzhou Medical University, Xuzhou, Jiangsu, China.
⁴ Department of General Surgery, Southwest Hospital, Third Military Medical University, Chongqing, China.

Abstract

Colon adenocarcinoma (COAD) is a prevalent malignant tumor that severely threatens human health across the globe. Immunotherapy is an essential need for patients with COAD. N7-methylguanosine (m7G) has been associated with human diseases, and non-coding RNAs (lncRNAs) regulate various tumor-related biological processes. Nonetheless, the m7G-related lncRNAs involved in COAD regulation are limited. This study aims to construct the clustering features and prognostic model of m7G-related lncRNAs in COAD. First, The Cancer Genome Atlas (TCGA) database was used to identify m7G-related differentially expressed lncRNAs (DELs), based on which COAD cases could be classified into two subtypes. Subsequently, univariate Cox analysis was used to identify 9 prognostic m7G-related lncRNAs. Further, Five candidates were screened by LASSO-Cox regression to develop new models. The patients were divided into high-risk and low-risk groups based on the median risk score. Consequently, the Kaplan-Meier survival curve demonstrated a statistically significant overall survival (OS) between the high- and low-risk groups (P<0.001). Multivariate Cox regression analysis revealed that risk score is an independent prognostic factor in COAD patients (P<0.001). This confirms the clinical applicability of the model. Additionally, we performed Gene Set Enrichment Analysis (GSEA), which uncovered the biological and functional differences between risk subgroups, i.e., enrichment of immune-related diseases in the high-risk group and enrichment of metabolic-related pathways in the low-risk group. In a drug sensitivity analysis, high-risk group were more sensitive to some chemotherapeutics and targeted drugs than low-risk group. Eventually, the stability of the model was confirmed by qRT-PCR. Our study unraveled the features of different immune states of COAD and established a prognostic model, including five m7G-related lncRNAs for COAD patients. These results will bolster clinical treatment and survival prediction of COAD.

Keywords: cold tumor; colon adenocarcinoma; hot tumor; lncRNA; m7G; model.