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Genomic analysis and clinical implications of immune cell infiltration in gastric cancer.

ABSTRACT: The immune infiltration of patients with gastric cancer (GC) is closely associated with clinical prognosis. However, previous studies failed to explain the different subsets of immune cells involved in immune responses and diverse functions. The present study aimed to uncover the differences in immunophenotypes in a tumor microenvironment (TME) between adjacent and tumor tissues and to explore their therapeutic targets. In our study, the relative proportion of immune cells in 229 GC tumor samples and 22 paired matched tissues was evaluated with a Cell type Identification By Estimating Relative Subsets Of known RNA Transcripts (CIBERSORT) algorithm. The correlation between immune cell infiltration and clinical information was analyzed. The proportion of 22 immune cell subsets was assessed to determine the correlation between each immune cell type and clinical features. Three molecular subtypes were identified with 'CancerSubtypes' R-package. Functional enrichment was analyzed in each subtype. The profiles of immune infiltration in the GC cohort from The Cancer Genome Atlas (TCGA) varied significantly between the 22 paired tissues. TNM stage was associated with M1 macrophages and eosinophils. Follicular helper T cells were activated at the late stage. Monocytes were associated with radiation therapy. Three clustering processes were obtained via the 'CancerSubtypes' R-package. Each cancer subtype had a specific molecular classification and subtype-specific characterization. These findings showed that the CIBERSOFT algorithm could be used to detect differences in the composition of immune-infiltrating cells in GC samples, and these differences might be an important driver of GC progression and treatment response.

SUBMITTER: Wu M

PROVIDER: S-EPMC7240200 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Genomic analysis and clinical implications of immune cell infiltration in gastric cancer.

Wu Ming M Wang Yadong Y Liu Hang H Song Jukun J Ding Jie J

Bioscience reports 20200501 5

The immune infiltration of patients with gastric cancer (GC) is closely associated with clinical prognosis. However, previous studies failed to explain the different subsets of immune cells involved in immune responses and diverse functions. The present study aimed to uncover the differences in immunophenotypes in a tumor microenvironment (TME) between adjacent and tumor tissues and to explore their therapeutic targets. In our study, the relative proportion of immune cells in 229 GC tumor sample ...[more]

PMID: 32338286

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Project description:BackgroundGastric cancer (GC) is the fifth most common cancer and the second leading cause of cancer-related deaths worldwide. Due to the lack of specific markers, the early diagnosis of gastric cancer is very low, and most patients with gastric cancer are diagnosed at advanced stages. The aim of this study was to identify key biomarkers of GC and to elucidate GC-associated immune cell infiltration and related pathways.MethodsGene microarray data associated with GC were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were analyzed using Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia, Gene Set Enrichment Analysis (GSEA) and Protein-Protein Interaction (PPI) networks. Weighted gene coexpression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) algorithm were used to identify pivotal genes for GC and to assess the diagnostic accuracy of GC hub markers using the subjects' working characteristic curves. In addition, the infiltration levels of 28 immune cells in GC and their interrelationship with hub markers were analyzed using ssGSEA. And further validated by RT-qPCR.ResultsA total of 133 DEGs were identified. The biological functions and signaling pathways closely associated with GC were inflammatory and immune processes. Nine expression modules were obtained by WGCNA, with the pink module having the highest correlation with GC; 13 crossover genes were obtained by combining DEGs. Subsequently, the LASSO algorithm and validation set verification analysis were used to finally identify three hub genes as potential biomarkers of GC. In the immune cell infiltration analysis, infiltration of activated CD4 T cell, macrophages, regulatory T cells and plasmacytoid dendritic cells was more significant in GC. The validation part demonstrated that three hub genes were expressed at lower levels in the gastric cancer cells.ConclusionThe use of WGCNA combined with the LASSO algorithm to identify hub biomarkers closely related to GC can help to elucidate the molecular mechanism of GC development and is important for finding new immunotherapeutic targets and disease prevention.

Project description:The prognosis of patients with gastric cancer (GC) is still unsatisfying. Numerous markers of gastric cancer stem cells (GCSCs) have been identified and were thought to be related to cancer aggressiveness. However, the roles of GCSC markers in GC patients' prognosis and immune infiltration remain unknown. Expression of GCSC markers was analyzed using Oncomine and Gene Expression Profiling Interactive Analysis (GEPIA). Their associations with clinicopathological parameters were analyzed using UALCAN and LinkedOmics. Alternations and protein expression of GCSC markers were analyzed by cBioPortal and the Human Protein Atlas databases, respectively. The prognostic significance of GCSC markers was evaluated using Kaplan-Meier plotter. Correlations between the expression of GCSC markers and immune infiltration along with biomarkers of tumor-infiltrating immune cells (TIICs) were assessed combined Tumor Immune Estimation Resource and GEPIA. GeneMANIA was used to discover the interactive genes of GCSC markers, and enrichment analysis was performed using Database for Annotation, Visualization, and Integrated Discovery server. We identified six GCSC markers significantly up-expressed in GC, compared with normal stomach tissues. Among them, the overexpression of ICAM1, THY1, and CXCR4 significantly indicated adverse, while EPCAM indicated beneficial clinicopathological features of GC patients. The up-regulation of CXCR4 showed unfavorable prognostic significance, whereas EPCAM and TFRC showed the opposite. The six GCSC markers were all correlated with the infiltration and activation of distinct TIICs. Especially, ICAM1, THY1, and CXCR4 showed strongly positive correlations with tumor-associated macrophages. Besides, chemokine, Toll-like receptor, NF-kappa B, and HIF-1 signaling pathways might be involved in the regulation of GCSC markers on cancer development. This study proposed that GCSC markers might be promising targets of GC treatment to weaken cancer stem-like properties and strengthen anticancer immunity.

Project description:BackgroundGastric cancer (GC) is the fourth most common cause of cancer-related death and the fifth most frequent malignant cancer, especially advanced GC. Carboxypeptidase X member 1 (CPXM1) is an epigenetic factor involved in many physiological processes, including osteoclast differentiation and adipogenesis. Several studies have shown the association of CPXM1 with multiple tumors; however, the mechanism of CPXM1 involvement in the progression of GC is yet to be characterized.MethodCPXM1 expression data were obtained from the Tumor Immune Estimation Resource. The Cancer Genome Atlas and the Gene Expression Omnibus databases were used to obtain patient-matched clinicopathological information, and the Kaplan-Meier plot database was utilized for the prognosis analysis of GC patients. The Catalog of Somatic Mutations in Cancer and cBioportal databases were adopted to study CPXM1 mutations in tumors. Next, we utilized the Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis for mechanism research. Furthermore, we performed tumor microenvironment and immune infiltration analysis based on CPXM1. Finally, we predicted sensitivity to several targeted drugs in GC patients based on CPXM1.CPXM1 is upregulated in GC and is correlated with poor prognosis, gender, and tumor stage in GC patients. Gene enrichment analysis suggested that CPXM1 may regulate the occurrence and progression of GC via the PI3K-AKT and TGF-β pathway. Moreover, CPXM1 expression results in an increase in the proportion of immune and stromal cells. Additionally, the proportion of plasma cells was inversely related to the expression of CPXM1, whereas macrophage M2 expression was proportionate to CPXM1 expression. Finally, six small-molecule drugs that showed notable variations in IC50 between two groups were screened.ConclusionThese results suggested that CPXM1 regulates the progression of GC and may represent a novel target for the detection and treatment of GC.

Project description:Background: Gastric cancer (GC) was usually associated with poor prognosis and invalid therapeutical response to immunotherapy due to biological heterogeneity. It is urgent to screen reliable indices especially immunotherapy-associated parameters that can predict the therapeutic responses to immunotherapy of GC patients. Methods: Gene expression profile of 854 GC patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets (GSE84433) with their corresponding clinical and somatic mutation data. Based on immune cell infiltration (ICI) levels, molecular clustering classification was performed to identify subtypes and ICI scores in GC patients. After functional enrichment analysis of subtypes, we further explored the correlation between ICI scores and Tumor Mutation Burden (TMB) and the significance in clinical immunotherapy response. Results: Three subtypes were identified based on ICI scores with distinct immunological and prognostic characteristics. The ICI-cluster C, associated with better outcomes, was characterized by significantly higher stromal and immune scores, T lymphocytes infiltration and up-regulation of PD-L1. ICI scores were identified through using principal component analysis (PCA) and the low ICI scores were consistent with the increased TMB and the immune-activating signaling pathways. Contrarily, the high-ICI score cluster was involved in the immunosuppressive pathways, such as TGF-beta, MAPK and WNT signaling pathways, which might be responsible for poor prognosis of GC. External immunotherapy and chemotherapy cohorts validated the patients with lower ICI scores exhibited significant therapeutic responses and clinical benefits. Conclusion: This study elucidated that ICI score could sever as an effective prognostic and predictive indicator for immunotherapy in GC. These findings indicated that the systematic assessment of tumor ICI landscapes and identification of ICI scores have crucial clinical implications and facilitate tailoring optimal immunotherapeutic strategies.

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Genomic analysis and clinical implications of immune cell infiltration in gastric cancer.

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Genomic analysis and clinical implications of immune cell infiltration in gastric cancer.

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