Comprehensive analysis of tumor mutation burden and immune microenvironment in gastric cancer

Yu, Jie; Zhang, QianYun; Wang, Mengchuan; Liang, Shi-Dong; Huang, Hongyun; Xie, Lang; Cui, Chunhui

doi:10.1042/bsr20203336

Cited by 21 publications

(14 citation statements)

References 47 publications

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“…MUC16, which encodes the cancer antigen CA-125, was shown to be strongly associated with higher TMB and favorable survival outcomes in GC patients (30). Our result illustrated that GC patients with high TMB had a higher survival rate than those with low TMB, which was consistent with the result of Zhao et al (31), Yu et al (32) and Wang et al (33). Besides, higher TMB was associated with late T and N stages.…”

Section: Discussionsupporting

confidence: 91%

Identification of a Gene Prognostic Model of Gastric Cancer Based on Analysis of Tumor Mutation Burden

Ma¹,

Li²,

Liu³

et al. 2021

Pathol. Oncol. Res.

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Introduction: Gastric cancer is one of the most common cancers. Although some progress has been made in the treatment of gastric cancer with the improvement of surgical methods and the application of immunotherapy, the prognosis of gastric cancer patients is still unsatisfactory. In recent years, there has been increasing evidence that tumor mutational load (TMB) is strongly associated with survival outcomes and response to immunotherapy. Given the variable response of patients to immunotherapy, it is important to investigate clinical significance of TMB and explore appropriate biomarkers of prognosis in patients with gastric cancer (GC).Material and Methods: All data of patients with gastric cancer were obtained from the database of The Cancer Genome Atlas (TCGA). Samples were divided into two groups based on median TMB. Differently expressed genes (DEGs) between the high- and low-TMB groups were identified and further analyzed. We identified TMB-related genes using Lasso, univariate and multivariate Cox regression analysis and validated the survival result of 11 hub genes using Kaplan-Meier Plotter. In addition, “CIBERSORT” package was utilized to estimate the immune infiltration.Results: Single nucleotide polymorphism (SNP), C > T transition were the most common variant type and single nucleotide variant (SNV), respectively. Patients in the high-TMB group had better survival outcomes than those in the low-TMB group. Besides, eleven TMB-related DEGs were utilized to construct a prognostic model that could be an independent risk factor to predict the prognosis of patients with GC. What’s more, the infiltration levels of CD4+ memory-activated T cells, M0 and M1 macrophages were significantly increased in the high-TMB group compared with the low-TMB group.Conclusions: Herein, we found that patients with high TMB had better survival outcomes in GC. In addition, higher TMB might promote immune infiltration, which could provide new ideas for immunotherapy.

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Section: Discussionsupporting

confidence: 91%

Identification of a Gene Prognostic Model of Gastric Cancer Based on Analysis of Tumor Mutation Burden

Ma¹,

Li²,

Liu³

et al. 2021

Pathol. Oncol. Res.

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“…Maurer’s study found that compared with normal tissues adjacent to cancer, the expression of ICAM-1 (intercellular adhesion molecular-1) in CRC tissues was significantly increased and positively correlated with the infiltration of inflammatory cells in the tumor microenvironment. The results of in vitro culture experiments show that the high expression of ICAM-1 depends on the increased dose of IFN-γ and IL-1β( Maurer et al, 1998 ; Xiang et al, 2001 ), For the high-risk cohort: KEGG analysis shows that the neuroactive ligand receptor interaction is mainly signaling pathway, that consistent with recent research ( Yu et al, 2021 ) ( Supplementary Figure 8 ). Moreover, CG Score was identified as an independent prognosis predictor for patients with CRC.…”

Section: Discussionsupporting

confidence: 87%

Identification of a Novel Immune-Related CpG Methylation Signature to Predict Prognosis in Stage II/III Colorectal Cancer

Chen

Pei

Liu³

et al. 2021

Front. Genet.

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With the increasing incidence of colorectal cancer (CRC) and continued difficulty in treating it using immunotherapy, there is an urgent need to identify an effective immune-related biomarker associated with the survival and prognosis of patients with this disease. DNA methylation plays an essential role in maintaining cellular function, and changes in methylation patterns may contribute to the development of autoimmunity, aging, and cancer. In this study, we aimed to identify a novel immune-related methylated signature to aid in predicting the prognosis of patients with CRC. We investigated DNA methylation patterns in patients with stage II/III CRC using datasets from The cancer genome atlas (TCGA). Overall, 182 patients were randomly divided into training (n = 127) and test groups (n = 55). In the training group, five immune-related methylated CG sites (cg11621464, cg13565656, cg18976437, cg20505223, and cg20528583) were identified, and CG site-based risk scores were calculated using univariate Cox proportional hazards regression in patients with stage II/III CRC. Multivariate Cox regression analysis indicated that methylated signature was independent of other clinical parameters. The Kaplan–Meier analysis results showed that CG site-based risk scores could significantly help distinguish between high- and low-risk patients in both the training (P = 0.000296) and test groups (P = 0.022). The area under the receiver operating characteristic curve in the training and test groups were estimated to be 0.771 and 0.724, respectively, for prognosis prediction. Finally, stratified analysis results suggested the remarkable prognostic value of CG site-based risk scores in CRC subtypes. We identified five methylated CG sites that could be used as an efficient overall survival (OS)-related biomarker for stage II/III CRC patients.

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“…Moreover, the activation of protein anabolism is important to high-grade cancers because proteins are required for cell division during proliferation and against cancer-associated cachexia and malnutrition [36]. Studies have reported that neuroactive ligand receptor interactions are involved in tumor immune infiltration and metastasis [37][38][39]. Therefore, these pathway analysis results may contribute to the comprehensive illumination of the hidden pathogenesis of IMPA.…”

Section: Discussionmentioning

confidence: 97%

Integrated weighted gene coexpression network analysis identifies Frizzled 2 (FZD2) as a key gene in invasive malignant pleomorphic adenoma

et al. 2022

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Background Invasive malignant pleomorphic adenoma (IMPA) is a highly malignant neoplasm of the oral salivary glands with a poor prognosis and a considerable risk of recurrence. Many disease-causing genes of IMPA have been identified in recent decades (e.g., P53, PCNA and HMGA2), but many of these genes remain to be explored. Weighted gene coexpression network analysis (WGCNA) is a newly emerged algorithm that can cluster genes and form modules based on similar gene expression patterns. This study constructed a gene coexpression network of IMPA via WGCNA and then carried out multifaceted analysis to identify novel disease-causing genes. Methods RNA sequencing (RNA-seq) was performed for 10 pairs of IMPA and normal tissues to acquire the gene expression profiles. Differentially expressed genes (DEGs) were screened out with the cutoff criteria of |log2 Fold change (FC)|> 1 and adjusted p value < 0.05. Then, WGCNA was applied to systematically identify the hidden diagnostic hub genes of IMPA. Results In this research, a total of 1970 DEGs were screened out in IMPA tissues, including 1056 upregulated DEGs and 914 downregulated DEGs. Functional enrichment analysis was performed for identified DEGs and revealed an enrichment of tumor-associated GO terms and KEGG pathways. We used WGCNA to identify gene module most relevant with the histological grade of IMPA. The gene FZD2 was then recognized as the hub gene of the selected module with the highest module membership (MM) value and intramodule connectivity in protein–protein interaction (PPI) network. According to immunohistochemistry (IHC) staining, the expression level of FZD2 was higher in low-grade IMPA than in high-grade IMPA. Conclusion FZD2 shows an expression dynamic that is negatively correlated with the clinical malignancy of IMPA and it plays a central role in the transcription network of IMPA. Thus, FZD2 serves as a promising histological indicator for the precise prediction of IMPA histological stages.

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Comprehensive analysis of tumor mutation burden and immune microenvironment in gastric cancer

Cited by 21 publications

References 47 publications

Identification of a Gene Prognostic Model of Gastric Cancer Based on Analysis of Tumor Mutation Burden

Identification of a Gene Prognostic Model of Gastric Cancer Based on Analysis of Tumor Mutation Burden

Identification of a Novel Immune-Related CpG Methylation Signature to Predict Prognosis in Stage II/III Colorectal Cancer

Integrated weighted gene coexpression network analysis identifies Frizzled 2 (FZD2) as a key gene in invasive malignant pleomorphic adenoma

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