Computational measurement of tumor immune microenvironment in gastric adenocarcinomas.
Ontology highlight
ABSTRACT:
SUBMITTER: Chang YH
PROVIDER: S-EPMC6141531 | biostudies-literature | 2018 Sep
REPOSITORIES: biostudies-literature
Publications
Computational measurement of tumor immune microenvironment in gastric adenocarcinomas.
Chang Young Hwan YH Heo You Jeong YJ Cho Junhun J Song Sang Yong SY Lee Jeeyun J Kim Kyoung-Mee KM
Scientific reports 20180917 1
The use of four groups of tumor immune microenvironments (TME) based on PD-L1 and tumor-infiltrating T lymphocytes (TIL) is a reliable biomarker for anti-PD-1/PD-L1 inhibitor therapy. We classified the TME in 241 gastric cancers which were subdivided according to 40 EBV+, 76 microsatellite instability-high (MSI-H), and 125 EBV-/microsatellite-stable (MSS) subtypes by quantitative image analysis (QIA) and correlated the results with mRNA expression levels. The mean PD-L1 ratio and CD8 ratio in EB ...[more]
Similar Datasets
Project description:BackgroundGastroesophageal adenocarcinomas (GEAs) are heterogeneous cancers where immune checkpoint inhibitors have robust efficacy in heavily inflamed microsatellite instability (MSI) or Epstein-Barr virus (EBV)-positive subtypes. Immune checkpoint inhibitor responses are markedly lower in diffuse/genome stable (GS) and chromosomal instable (CIN) GEAs. In contrast to EBV and MSI subtypes, the tumor microenvironment of CIN and GS GEAs have not been fully characterized to date, which limits our ability to improve immunotherapeutic strategies.Patients and methodsHere we aimed to identify tumor-immune cell association across GEA subclasses using data from The Cancer Genome Atlas (N = 453 GEAs) and archival GEA resection specimen (N = 71). The Cancer Genome Atlas RNAseq data were used for computational inferences of immune cell subsets, which were correlated to tumor characteristics within and between subtypes. Archival tissues were used for more spatial immune characterization spanning immunohistochemistry and mRNA expression analyses.ResultsOur results confirmed substantial heterogeneity in the tumor microenvironment between distinct subtypes. While MSI-high and EBV+ GEAs harbored most intense T cell infiltrates, the GS group showed enrichment of CD4+ T cells, macrophages and B cells and, in ∼50% of cases, evidence for tertiary lymphoid structures. In contrast, CIN cancers possessed CD8+ T cells predominantly at the invasive margin while tumor-associated macrophages showed tumor infiltrating capacity. Relatively T cell-rich 'hot' CIN GEAs were often from Western patients, while immunological 'cold' CIN GEAs showed enrichment of MYC and cell cycle pathways, including amplification of CCNE1.ConclusionsThese results reveal the diversity of immune phenotypes of GEA. Half of GS gastric cancers have tertiary lymphoid structures and are therefore promising candidates for immunotherapy. The majority of CIN GEAs, however, exhibit T cell exclusion and infiltrating macrophages. Associations of immune-poor CIN GEAs with MYC activity and CCNE1 amplification may enable new studies to determine precise mechanisms of immune evasion, ultimately inspiring new therapeutic modalities.
| S-EPMC7690253 | biostudies-literature
Project description:BackgroundGastric cancer (GC) still represents the third leading cause of cancer-related death worldwide. Peritoneal relapse (PR) is the most frequent metastasis occurring among patients with advanced gastric cancer. Increasingly more evidence have clarified the tumor immune microenvironment (TIME) may predict survival and have clinical significance in GC. However, tumor-transcriptomics based immune signatures derived from immune profiling have not been established for predicting the peritoneal recurrence of the advanced GC.MethodsIn this study, we depict the immune landscape of GC by using transcriptome profiling and clinical characteristics retrieved from GSE62254 of Gene Expression Omnibus (GEO). Immune cell infiltration score was evaluated via single-sample gene set enrichment (ssGSEA) analysis algorithm. The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was used to select the valuable immune cells and construct the final model for the prediction of PR. The receiver operating characteristic (ROC) curve and the Kaplan-Meier curve were used to check the accuracy of PRIs. Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to explore the molecular pathways associated with PRIs.ResultsA peritoneal recurrence related immune score (PRIs) with 10 immune cells was constructed. Compared to the low-PRIs group, the high-PRIs group had a greater risk. The upregulation of the focal adhesion signaling was observed in the high-PRIs subtype by GSEA and KEGG. Multivariate analysis found that both in the internal training cohort and the internal validation cohort, PRIs was a stable and independent predictor for PR. A nomogram that integrated clinicopathological features and PRIs to predict peritoneal relapse was constructed. Subgroup analysis indicated that the PRIs could obviously distinguish peritoneal recurrence in different molecular subtypes, pathological stages and Lauren subtypes, in which PRIs of Epithelial-Mesenchymal Transitions (EMT) subtype, III-IV stage and diffuse subtype are higher respectively.ConclusionOverall, we performed a comprehensive evaluation of the immune landscape of GC and constructed a predictive PR model based on the immune cell infiltration. The PRIs represents novel promising feature of predicting peritoneal recurrence of GC and sheds light on the improvement of the personalized management of GC patients after surgery.
| S-EPMC8155484 | biostudies-literature
Project description:Tumor mutation burden (TMB) was a promising marker for immunotherapy. We aimed to investigate the prognostic role of TMB and its relationship with immune cells infiltration in gastric cancer (GC). We analyzed the mutation landscape of all GC cases and TMB of each GC patient was calculated and patients were divided into TMB-high and TMB-low group. Differentially expressed genes (DEGs) between the two groups were identified and pathway analysis was performed. The immune cells infiltration in each GC patient was evaluated and Kaplan-Meier analysis was performed to investigate the prognostic role of immune cells infiltration. At last, hub immune genes were identified and a TMB prognostic risk score (TMBPRS) was constructed to predict the survival outcome of GC patients. The relationships between mutants of hub immune genes and immune infiltration level in GC was investigated. We found higher TMB was correlated with better survival outcome and female patients, patients with T1-2 and N0 had higher TMB score. Altogether 816 DEGs were harvested and pathway analysis demonstrated that patients in TMB-high group were associated with neuroactive ligand-receptor interaction, cAMP signaling pathway, calcium signaling pathway. The infiltration of activated CD4+ memory T cells, follicular helper T cells, resting NK cells, M0 and M1 macrophages and neutrophils in TMB-high group were higher compared than that in TMB-low group and high macrophage infiltration was correlated with inferior survival outcome of GC patients. Lastly, the TMBPRS was constructed and GC patients with high TMBPRS had poor prognosis.
| S-EPMC7921293 | biostudies-literature
Project description:The tumor microenvironment is closely related to the progression and immune escape of tumor cells. Tumor-infiltrating immune cells (TIICs) and immune-related genes (IRGs) are indispensable components of the tumor microenvironment and have been demonstrated to be highly valuable in determining the prognosis of multiple cancers. To elucidate the prognostic value of TIICs and IRGs in gastric cancer, we conducted a comprehensive analysis focusing on the abundances of 22 types of TIICs and differentially expressed IRGs based on a dataset from The Cancer Genome Atlas (TCGA). The results showed that great composition differences in TIICs and immune cell subfractions were associated with survival outcomes in different stages. Additionally, 29 hub genes were characterized from 345 differentially expressed IRGs and found to be significantly associated with survival outcomes. Then, an independent prognostic indicator based on ten IRGs was successfully constructed after multivariate adjustment for some clinical parameters. Further validation revealed that these hub IRGs could reflect the infiltration levels of immune cells. Thus, our results confirmed the clinical significance of TIICs and IRGs in gastric cancer and may establish a foundation for further exploring immune cell and gene targets for personalized treatment.
| S-EPMC7585095 | biostudies-literature
Project description:Gastric cancer is one of the leading causes of cancer-related death due to late diagnosis with high metastatic frequency. In this study, the impact of tumor secreted exosomes on immune function in the tumor environment was investigated using exosomes isolated from gastric cancer cell lines MKN-28, MKN-45, and SGC-7901. Results show that exosomes derived from all of these cell lines changed the gene expression and cytokine secretion levels of CD8+ T cells. They also block cell cycle progression, induced apoptosis in CD8+ T cells. Image analysis of fluorescent labeled exosomes derived from three cell lines injected systemically into C57BL/6 mice revealed these exosomes primarily localize to the lungs. We further showed exosomes were mainly taken up by natural killer cells and macrophages in the lung. After long-term exposure to inject exosomes from MKN-45 cells, mice developed an immunosuppressive tumor microenvironment in the lung with increased frequency of effector memory CD4+ T and MDSC, decreased CD8+ T cell and NK frequency. This immune suppressive environment promotes gastric cancer lung metastasis. Lung metastasis sites developed after mice were exposed to exosomes isolated from all three gastric cancer cell lines when the mice were injected with MFC cells. Results suggest that exosomes derived from gastric cancer cells (especially MKN-45 and MKN-28) changed CD8+ T cell gene expression and cytokine secretion patterns to create an immunosuppressive condition for metastatic niche formation in the lung. Overall, this study provides new insights into how gastric cancer derived exosomes modulate the immune response to promote lung tumor metastasis.
| S-EPMC7479614 | biostudies-literature
Project description:In recent years, molecular and genetic research hotspots of gastric cancer have been investigated, including microRNAs, long noncoding RNAs (lncRNAs) and messenger RNA (mRNAs). The study on the role of lncRNAs may help to develop personalized treatment and identify potential prognostic biomarkers in gastric cancer. The RNA-seq and miRNA-seq data of gastric cancer were downloaded from the TCGA database. Differential analysis of RNA expression between gastric cancer samples and normal samples was performed using the edgeR package. The ceRNA regulatory network was visualized using Cytoscape. KEGG pathway analysis of mRNAs in the ceRNA network was performed using the clusterProfiler package. CIBERSORT was used to distinguish 22 immune cell types and the prognosis-related genes and immune cells were determined using Kaplan-Meier and Cox proportional hazard analyses. To estimate these nomograms, we used receiver operating characteristic and calibration curve studies. The ceRNA regulation network of gastric cancer was built in this study, and the genes in the network were analyzed for prognosis. A total of 980 lncRNAs were differentially expressed, of which 774 were upregulated and 206 were downregulated. A survival study identified 15 genes associated with gastric cancer prognosis, including VCAN-AS1, SERPINE1, AL139002.1, LINC00326, AC018781.1, C15orf54, hsa-miR-145. Monocytes and Neutrophils were associated with the survival rate of gastric cancer. Our research uncovers new ceRNA network for the detection, treatment, and monitoring of gastric cancer.
| S-EPMC10495442 | biostudies-literature
Project description:BackgroundAdvanced gastric cancer (AGC) is a disease with poor prognosis due to the current lack of effective therapeutic strategies. Immune checkpoint blockade treatments have shown effective responses in patient subgroups but biomarkers remain challenging. Traditional classification of gastric cancer (GC) is based on genomic profiling and molecular features. Therefore, it is critical to identify the immune-related subtypes and predictive markers by immuno-genomic profiling.MethodsSingle-sample gene-set enrichment analysis (ssGSEA) and ESTIMATE algorithm were used to identify the immue-related subtypes of AGC in two independent GEO datasets. Weighted gene co-expression network analysis (WGCNA) and Molecular Complex Detection (MCODE) algorithm were applied to identify hub-network of immune-related subtypes. Hub genes were confirmed by prognostic data of KMplotter and GEO datasets. The value of hub-gene in predicting immunotherapeutic response was analyzed by IMvigor210 datasets. MTT assay, Transwell migration assay and Western blotting were performed to confirm the cellular function of hub gene in vitro.ResultsThree immune-related subtypes (Immunity_H, Immunity_M and Immunity_L) of AGC were identified in two independent GEO datasets. Compared to Immunity_L, the Immuntiy_H subtype showed higher immune cell infiltration and immune activities with favorable prognosis. A weighted gene co-expression network was constructed based on GSE62254 dataset and identified one gene module which was significantly correlated with the Immunity_H subtype. A Hub-network which represented high immune activities was extracted based on topological features and Molecular Complex Detection (MCODE) algorithm. Furthermore, ADAM like decysin 1 (ADAMDEC1) was identified as a seed gene among hub-network genes which is highly associated with favorable prognosis in both GSE62254 and external validation datasets. In addition, high expression of ADAMDEC1 correlated with immunotherapeutic response in IMvigor210 datasets. In vitro, ADAMDEC1 was confirmed as a potential protein in regulating proliferation and migration of gastric cancer cell. Deficiency of ADAMDEC1 of gastric cancer cell also associated with high expression of PD-L1 and Jurkat T cell apoptosis.ConclusionsWe identified immune-related subtypes and key tumor microenvironment marker in AGC which might facilitate the development of novel immune therapeutic targets.
| S-EPMC8665569 | biostudies-literature
Project description:Recent evidence demonstrates that the reprogramming of energy metabolism can interact with the tumor immune microenvironment, thereby participating in the progression of cancer. In this study, multi-omics data of 2471 gastric cancer samples were used to identify tumor glycometabolism and its correlation with tumor immune microenvironment. A series of bioinformatic approaches were performed to establish a scoring system to predict the survival and response of chemotherapy and immunotherapy. Three glycometabolic subtypes and two immune clustering subgroups of gastric cancer were determined. We further established a Gluco-Immune Scoring system to quantify the cancer glycometabolic status and immune infiltration of individual patients. Patients with low Gluco-Immune Score were sensitive to adjuvant chemotherapy, while patients with high Gluco-Immune Score may benefit from immunotherapy. Our results indicate that in gastric cancer, the assessment of tumor glucose metabolism and immune microenvironment has application value for the prediction of curative effects and the formulation of combined treatment strategies.
| S-EPMC10006618 | biostudies-literature
Project description:Accumulated evidence has elucidated that the tumor microenvironment (TME) is great of clinical significance in predicting survival outcomes and therapeutic efficacy. Nonetheless, few studies have investigated the prognostic and immunotherapeutic signature correlated with TME phenotypes in gastrointestinal adenocarcinomas (GIAC). Here, by estimating the TME pattern of immune infiltration and expression in over 1,000 GIAC patients, we revealed three TME subgroups and identified six key differential genes. To predict the TME phenotypes, TMEscore was established and validated to be an independent prognostic factor, where the high TMEscore was characterized by immune activation and response to immunotherapy and accompanied with favorable prognosis in GIAC. Furthermore, TMEscore was confirmed to predict prognosis and immunotherapeutic response in six datasets. In summary, depicting TME landscape of GIAC patients may be beneficial for interpreting survival and immunotherapeutic response, and provide new strategies for clinical treatment of GIAC.
| S-EPMC9831739 | biostudies-literature
Project description:The tumor immune microenvironment (TIME) is associated with tumor prognosis and immunotherapy response. Here we develop and validate a CT-based radiomics score (RS) using 2272 gastric cancer (GC) patients to investigate the relationship between the radiomics imaging biomarker and the neutrophil-to-lymphocyte ratio (NLR) in the TIME, including its correlation with prognosis and immunotherapy response in advanced GC. The RS achieves an AUC of 0.795-0.861 in predicting the NLR in the TIME. Notably, the radiomics imaging biomarker is indistinguishable from the IHC-derived NLR status in predicting DFS and OS in each cohort (HR range: 1.694-3.394, P < 0.001). We find the objective responses of a cohort of anti-PD-1 immunotherapy patients is significantly higher in the low-RS group (60.9% and 42.9%) than in the high-RS group (8.1% and 14.3%). The radiomics imaging biomarker is a noninvasive method to evaluate TIME, and may correlate with prognosis and anti PD-1 immunotherapy response in GC patients.
| S-EPMC9427761 | biostudies-literature