Search

Stomach adenocarcinoma (STAD) is a type of cancer which often at itsadvanced stage apon diagnosis and mortality in clinical practice. Several factors influencethe prognosis of STAD, including the expression and regulation of immune cells in the tumor microenvironment. We here investigated the biomarkers related to the diagnosis and prognosis of gastric cancer, hoping to provide insights for the diagnosis and treatment of gastric cancer in the future. STAD and normal patient RNA sequencing data sets were accessed from the cancer genome atlas (TCGA database). Differential genes were determined and obtained by using the R package DESeq2. The stromal, immune, and ESTIMATE scores are calculated by the ESTIMATE algorithm, followed by the modular genes screening using the R package WGCNA. Subsequently, the intersection between the modular gene and the differential gene was taken and the STRING database was used for PPI network module analysis. The R packages clusterProfiler, enrichplot, and ggplot2 were used for GO and KEGG enrichment analysis. Cox regression analysis was used to screen survival-related genes, and finally, the R package Venn Diagram was used to take the intersection and obtain 7 hub genes. The time-dependent ROC curve and Kaplan–Meier survival curve were used to find the SERPINE1 gene, which plays a critical role in prognosis. Finally, the expression pattern, clinical characteristics, and regulatory mechanism of SERPINE1 were analyzed in STAD. We revealed that the expression of SERPINE1 was significantly increased in the samples from STAD compared with normal samples. Cox regression, time-dependent ROC, and Kaplan–Meier survival analyses demonstrated that SERPINE1 was significantly related to the adverse prognosis of STAD patients. The expression of SERPINE1 increased with the progression of T, N, and M classification of the tumor. In addition, the results of immune infiltration analysis indicated that the immune cells' expression were higher in high SERPINE1 expression group than that in low SERPINE1 expression group, including CD4+ T cells, B cells, CD8+ T cells, macrophages, neutrophils and other immune cells. SERPINE1 was closely related to immune cells in the STAD immune microenvironment and had a synergistic effect with the immune checkpoints PD1 and PD-L1. In conclusion, we proved that SERPINE1 is a promising prognostic and diagnostic biomarker for STAD and a potential target for immunotherapy. [ABSTRACT FROM AUTHOR]

Gastric carcinoma (GC) heterogeneity represents a major barrier to accurate diagnosis and treatment. Here, we established a comprehensive single-cell transcriptional atlas to identify the cellular heterogeneity in malignant epithelial cells of GC using single-cell RNA sequencing (scRNA-seq). A total of 49,994 cells from nine patients with paired primary tumor and normal tissues were analyzed by multiple strategies. This study focused on the malignant epithelial cells, which were divided into three subtypes, including pit mucous cells, chief cells, and gastric and intestinal cells. The trajectory analysis results suggest that the differentiation of the three subtypes could be from the pit mucous cells to the chief cells and then to the gastric and intestinal cells. Lauren's histopathology of GC might originate from various subtypes of malignant epithelial cells. The functional enrichment analysis results show that the three subtypes focused on different biological processes (BP) and pathways related to tumor development. In addition, we generated and validated the prognostic signatures for predicting the OS in GC patients by combining the scRNA-seq and bulk RNA sequencing (bulk RNA-seq) datasets. Overall, our study provides a resource for understanding the heterogeneity of GC that will contribute to accurate diagnosis and prognosis. [ABSTRACT FROM AUTHOR]

Stomach adenocarcinoma (STAD) is one of the most malignant cancers that endanger human health. There is growing evidence that competitive endogenous RNA (ceRNA) regulatory networks play an important role in various human tumors. However, the complexity and behavioral characteristics of the ceRNA network in STAD are still unclear. In this study, we constructed a ceRNA regulatory network to identify the potential prognostic biomarkers associated with STAD. The expression profile of lncRNA, miRNA, and mRNA was downloaded from The Cancer Genome Atlas (TCGA). After performing bioinformatics analysis, the CCDC144NL-AS1/hsa-miR-145-5p/SERPINE1 ceRNA network associated to STAD prognosis of STAD was obtained. The CCDC144NL-AS1/SERPINE1 axis in the ceRNA network was identified by correlation analysis and considered as a clinical prognosis model by Cox regression analysis. In addition, methylation analysis indicated that the abnormal upregulation of CCDC144NL-AS1/SERPINE1 axis might be related to the aberrant methylation of some sites, and immune infiltration analysis suggested that CCDC144NL-AS1/SERPINE1 axis probably influences the alteration of tumor immune microenvironment and the occurrence and development of STAD. In particular, the CCDC144NL-AS1/SERPINE1 axis based on the ceRNA network constructed in the present study might be an important novel factor correlating with the diagnosis and prognosis of STAD. [ABSTRACT FROM AUTHOR]