A Novel Six-Gene-Based Prognostic Model Predicts Survival and Clinical Risk Score for Gastric Cancer

Abstract

Background: Autophagy plays a vital role in cancer initiation, malignant progression, and resistance to treatment. However, autophagy-related genes (ARGs) have rarely been analyzed in gastric cancer (GC). The purpose of this study was to analyze ARGs in GC using bioinformatic analysis and to identify new biomarkers for predicting the overall survival (OS) of patients with GC.Methods: The gene expression profiles and clinical data of patients with GC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, and ARGs were obtained from two other datasets (the Human Autophagy Database and Molecular Signatures Database). Lasso, univariate, and multivariate Cox regression analyses were performed to identify the OS-related ARGs. Finally, a six-ARG model was identified as a prognostic indicator using the risk-score model, and survival and prognostic performance were analyzed based on the Kaplan-Meier test and ROC curve. Estimate calculations were used to assess the immune status of this model, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed for investigating the functions and terms associated with the model-related genes in GC.Results: The six ARGs, DYNLL1, PGK2, HPR, PLOD2, PHYHIP, and CXCR4, were identified using Lasso and Cox regression analyses. Survival analysis revealed that the OS of GC patients in the high-risk group was significantly lower than that of the low-risk group (p < 0.05). The ROC curves revealed that the risk score model exhibited better prognostic performance with respect to OS. Multivariate Cox regression analysis indicated that the model was an independent predictor of OS and was not affected by most of the clinical traits (p < 0.05). The model-related genes were associated with immune suppression and several biological process terms, such as extracellular structure organization and matrix organization. Moreover, the genes were associated with the P13K-Akt signaling pathway, focal adhesion, and MAPK signaling pathway.Conclusions: This study presents potential prognostic biomarkers for GC patients that would aid in determining the best patient-specific course of treatment.

Extracellular Matrix-Associated Pathways Promote the Progression of Gastric Cancer by Impacting the Dendritic Cell Axis

“…Izumi et al 29 constructed a gene expression-based 15-gene signature to distinguish lymph node status and obtained an AUC value of only 0.829 in the GSE62254 cohort. Li et al 30 constructed a six gene-based prognostic model in the TCGA-STAD cohort; however, the AUC value they validated in GSE62254 was only 0.60-0.63. In addition, the prognostic model we established was an independent prognostic factor after adjusting for the clinical features of age, sex, stage, grade, and EBV status.…”

Pan-Cancer Analyses Reveal Oncogenic and Immunological Role of PLOD2

“…In order to investigate the research status of PLOD2 and gastric cancer, we conducted a search on the PubMed using the following search strategy: [“stomach neoplasms” (Title/Abstract) OR “stomach neoplasms” (MeSH Terms) OR “gastric adenocarcinoma” (Title/Abstract)] AND [“PLOD2” (Title/Abstract)]. Finally, seven studies were found ( Kiyozumi et al, 2018 ; Li S. S et al, 2020 ; Luo et al, 2020 ; Wang et al, 2020 ; Dai et al, 2021 ; Li et al, 2021 ; Song et al, 2021 ). Dai et al constructed a prognostic model for five genes including PLOD2 , which was subsequently validated by RT-PCR in normal tissue and gastric cancer cell lines ( Dai et al, 2021 ).…”

“…However, their study did not perform analyses related to tumor immunity (including infiltrating immune cells, TMB, etc.). Similarly, Li J et al( Li et al, 2021 ), Li SS et al ( Li S. S et al, 2020 ), Luo et al ( Luo et al, 2020 ), and Song et al( Song et al, 2021 ) were also constructed multiple genes (including PLOD2 ) prognostic model, but all lacked tumor immune-related analysis or only had comparisons of different immune cell classifications. Kiyozumi et al study showed that PLOD2 promotes cell invasion and migration in gastric cancer under hypoxic conditions and leads to dissemination to the peritoneum, in vitro ( Kiyozumi et al, 2018 ).…”

Inhibitory Mechanism of Combined Hydroxychavicol With Epigallocatechin-3-Gallate Against Glioma Cancer Cell Lines: A Transcriptomic Analysis

“…Our findings are far from exhaustive and may be further explored in terms of the long noncoding genes and alternative splicing expression patterns. For instance, DYNLL1 alternative splicing expression, which is significantly decreased in EGCG+HC treated glioma cells, is reported to be upregulated in gastric cancer high-risk group patients and hepatocellular cancer ( Berkel and Cacan, 2020 ) ( Li et al, 2021 ). How DYNLL1 promotes aberrant transcription in cancers are still unknown.…”