Prognostic significance of microsatellite instability‑associated pathways and genes in gastric cancer

Abstract

The aim of the present study was to reveal the potential molecular mechanisms of microsatellite instability (MSI) on the prognosis of gastric cancer (GC). The investigation was performed based on an RNAseq expression profiling dataset downloaded from The Cancer Genome Atlas, including 64 high-level MSI (MSI-H) GC samples, 44 low-level MSI (MSI-L) GC samples and 187 stable microsatellite (MSI-S) GC samples. Differentially expressed genes (DEGs) were identified between the MSI-H, MSI-L and MSI-S samples. Pathway enrichment analysis was performed for the identified DEGs and the pathway deviation scores of the significant enrichment pathways were calculated. A Multi-Layer Perceptron (MLP) classifier, based on the different pathways associated with the MSI statuses was constructed for predicting the outcome of patients with GC, which was validated in another independent dataset. A total of 190 DEGs were selected between the MSI-H, MSI-L and MSI-S samples. The MLP classifier was established based on the deviation scores of 10 significant pathways, among which antigen processing and presentation, and inflammatory bowel disease pathways were significantly enriched with HLA-DRB5, HLA-DMA, HLA-DQA1 and HLA-DRA; the measles, toxoplasmosis and herpes simplex infection pathways were significantly enriched with Janus kinase 2 (JAK2), caspase-8 (CASP8) and Fas. The classifier performed well on an independent validation set with 100 GC samples. Taken together, the results indicated that MSI status may affect GC prognosis, partly through the antigen processing and presentation, inflammatory bowel disease, measles, toxoplasmosis and herpes simplex infection pathways. HLA-DRB5, HLA-DMA, HLA-DQA1, HLA-DRA, JAK2, CASP8 and Fas may be predictive factors for prognosis in GC.

Correlations between microsatellite instability and the biological behaviour of tumours

“…In addition, the detailed molecular mechanism that MSI patterns affect the prognosis of GC patients was systematically researched among 295 patients by Hang et al (2018). The results indicated that the effect of MSI on the prognosis of GC patients may be mediated by ten important pathways, including measles, antigen processing and presentation, rheumatoid arthritis, phagosome, systemic lupus erythaematosus, herpes simplex infection, inflammatory bowel disease, tuberculosis, type I diabetes mellitus, and toxoplasmosis pathways.…”

The Pattern of Signatures in Gastric Cancer Prognosis

“…Microsatellite instability (MSI) is an important indication of the DNA mismatch repair deficiency, and therefore it is perceived as a factor in the expeditive collection of genetic changes in the gastric carcinogenesis process [ 32 ]. Hang et al, 2018 [ 33 ] presented the molecular mechanisms of of microsatellite instability (MSI) and its importance in GC prognosis. Next generation sequencing data of the whole transcriptome were investigated from The Cancer Genome Atlas (TCGA), covering 64 high-level MSI (MSI-H) gastric cancer samples, 44 low-level MSI (MSI-L) and 187 stable microsatellite (MSI-S) gastric cancer samples [ 33 ].…”

“…Hang et al, 2018 [ 33 ] presented the molecular mechanisms of of microsatellite instability (MSI) and its importance in GC prognosis. Next generation sequencing data of the whole transcriptome were investigated from The Cancer Genome Atlas (TCGA), covering 64 high-level MSI (MSI-H) gastric cancer samples, 44 low-level MSI (MSI-L) and 187 stable microsatellite (MSI-S) gastric cancer samples [ 33 ]. The results showed that MSI status might have impact on the prognosis of GC patients, partially through the inflammatory bowel disease, antigen processing and presentation, measles, toxoplasmosis, and herpes simplex infection pathways.…”

A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine

“…It is a potential biomarker which can be reflected in gastric cancer (GC) patients with microsatellite instability-high (MSI-H) achieve superior responses to PD-1 antibody [4]. Significant difference in prognosis can be seen with different MSI state [5]. LncRNAs data analysis done by TANRIC showed there might be a correlation existed in lncRNAs and MSI [6].…”