Abstract

Numerous studies have shown that long uncoded RNA (lncRNA) MSC-AS1 may play an important role in the occurrence and development of some types of cancer. However, its role in gastric cancer has rarely been discussed. This study aimed to clarify the association between lncRNA MSC-AS1 and gastric cancer using The Cancer Genome Atlas (TCGA) database. We determined the expression of MSC-AS1 using the Wilcoxon rank sum test; in addition, logistic regression was applied to evaluate the association between MSC-AS1 and clinicopathological characteristics. Also, Kaplan-Meier and Cox regression were used to evaluate the relationship between MSC-AS1 and survival. A nomogram was conducted to predict the impact of MSC-AS1 on prognosis. Moreover, Gene Set enrichment analysis (GSEA) was performed to annotate the biological function of MSC-AS1. Quantitative analysis of immune infiltration was carried out by single-set GSEA (ssGSEA). The MSC-AS1 level was elevated in gastric cancer tissues. An increased MSC-AS1 level was significantly correlated with T stage (odds ratio [OR] = 2.55 for T3 and T4 vs. T1 and T2), histological type (OR = 5.28 for diffuse type vs. tubular type), histological grade (OR = 3.09 for grade 3 vs. grades 1 and 2), TP53 status (OR = 0.55 for mutated vs. wild type), and PIK3CA status (OR = 0.55 for mutated vs. wild type) (all p < 0.05) by univariate logistic regression. Kaplan-Meier survival analysis showed high MSC-AS1 expression had a poor overall survival [hazard ratio (HR) = 1.75; 95% confidence interval (CI): 1.25–2.45; p = 0.001] and progression-free interval (HR = 1.47; 95% CI: 1.03–2.10; p = 0.034). Multivariate survival analysis revealed that MSC-AS1 expression (HR = 1.681; 95% CI: 1.057–2.673; p = 0.028) was independently correlated with overall survival. GSEA demonstrated that the P38/MAPK pathway, the VEGF pathway, the cell adhesion molecules cams, the NOD-like receptor signaling pathway were differentially enriched in the high MSC-AS1 expression phenotype. SsGSEA and Spearman correlation revealed the relationships between MSC-AS1 and macrophages, NK cells, and Tems were the strongest. Coregulatory proteins were included in the PPI network. Upregulated lncRNA MSC-AS1 might be a potential biomarker for the diagnosis and prognosis of gastric cancer.

Highlights

  • Gastric cancer is one of the top five cancers and a leading cause of cancer-related deaths around the world, regardless of country development [1]

  • According to the mean expression of lncRNA MSC-AS1, patients were assigned to the high-expression group, and patients were assigned to the low-expression group

  • MSC-AS1 was significantly expressed in adrenal cortical carcinoma (ACC), bladder urothelial carcinoma (BLCA), breast-infiltrating carcinoma (BRCA), cervical squamous carcinoma and adenocarcinoma (CESC), bile duct carcinoma (CHOL), colon cancer (COAD), diffuse large B-cell lymphoma (DLBC), esophageal cancer (ESCA), lung adenocarcinoma (LUAS), lung squamous carcinoma (LUSC), ovarian serous cystadenocarcinoma (OV), pancreatic cancer (PAAD), prostate cancer (PRAD), rectal adenocarcinoma (READ), skin melanoma (SKCM), gastric cancer (STAD), and other cancers, and the results were statistically significant

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Summary

Introduction

Gastric cancer is one of the top five cancers and a leading cause of cancer-related deaths around the world, regardless of country development [1]. The prognosis of patients with early gastric cancer is good, but the prognosis of patients with advanced gastric cancer is poor because of the lack of effective targeted drugs and the susceptibility to drug resistance. Serum or plasma tumor markers are substances synthesized directly by tumor cells or released into the blood by non-tumor cells—for example, cancer and tumor suppressor gene products, enzymes, isozymes, carcinoembryonic antigens, and tumor-related antigens. These substances are commonly used to detect gastric cancer and to predict the prognosis of patients with gastric cancer. No single marker with high sensitivity and specificity exists, and most available markers must be combined for detection and analysis to reduce the misdiagnosis rate

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