Dataset Information

Dissecting the Role of Immune Checkpoint Regulation Patterns in Tumor Microenvironment and Prognosis of Gastric Cancer.

ABSTRACT: Many studies suggest that immune checkpoint molecules play a vital role in tumor progression and immune responses. However, the impact of the comprehensive regulation pattern of immune checkpoint molecules on immune responses, tumor microenvironment (TME) formation, and patient prognosis is poorly understood. In this study, we evaluated immune checkpoint regulation patterns in 1,174 gastric cancer (GC) samples based on 31 immune checkpoint genes (ICGs). Three distinct immune checkpoint regulation patterns with significant prognostic differences were ultimately identified. Moreover, GC patients were divided into two subgroups according to immune checkpoint score (ICscore). Patients with lower ICscore were characterized by a favorable prognosis and enhanced immune infiltration as well as an increased tumor mutation burden, non-recurrence, and microsatellite instability-high. Collectively, this study indicated that immune checkpoint regulation patterns were essential to forming the diversity of TME and a better understanding of that will contribute to assessing the characteristics of TME in GC, which intends to improve the development of immunotherapy.

SUBMITTER: Zhen Z

PROVIDER: S-EPMC9061997 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Dissecting the Role of Immune Checkpoint Regulation Patterns in Tumor Microenvironment and Prognosis of Gastric Cancer.

Zhen Zili Z Shen Zhemin Z Sun Peilong P

Frontiers in genetics 20220419

Many studies suggest that immune checkpoint molecules play a vital role in tumor progression and immune responses. However, the impact of the comprehensive regulation pattern of immune checkpoint molecules on immune responses, tumor microenvironment (TME) formation, and patient prognosis is poorly understood. In this study, we evaluated immune checkpoint regulation patterns in 1,174 gastric cancer (GC) samples based on 31 immune checkpoint genes (ICGs). Three distinct immune checkpoint regulatio ...[more]

PMID: 35518357

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Project description:BackgroundGlioma is the most common intracranial malignancy with a poor prognosis. Although remarkable advances have been made in the study of diagnostic and prognostic biomarkers, the efficacy of current treatment strategies is still unsatisfactory. Therefore, developing novel and reliable targets is desperately needed for glioma patients. Pyroptosis reshapes tumor immune microenvironment (TME) and promotes the destruction of the tumor by the immune system. Moreover, pyroptosis levels correlate with prognosis and immunotherapy response in many cancer patients. This study performed a comprehensive analysis of pyroptosis in the glioma, unveiling its potential value in glioma prognosis prediction and therapy efficacy.MethodsFirstly, the pyroptosis regulation patterns were comprehensively evaluated on 33 pyroptosis-related genes in 1716 glioma samples. The correlations were analyzed between pyroptosis regulation patterns and TME immune cell infiltration properties. Next, pyroptosis regulation patterns were measured by the PSscore model based on principal component analysis algorithms. The correlations were analyzed between PSscore and tumor mutational burden (TMB), immune checkpoint blockade (ICB) therapeutic advantages. Last, the findings were validated in an independently collected external clinical cohort.ResultsWe determined two distinct pyroptosis regulation patterns. The cluster-A was high immune cell infiltration with a poor prognosis (p < 0.001), whereas the cluster-B was low immune cell infiltration with a better prognosis (p < 0.001). We developed the PSscore as a measure for pyroptosis regulation patterns. The high PSscore with an inflamed TME phenotype, a high TMB (p < 0.0001), increased innate immune response, and a poor prognosis (p < 0.001). It was in stark contrast to the low PSscore (p < 0.001). Analysis of PSscore with checkpoint therapy indicated high PSscore were correlated with enhanced response to anti-PD-1 immunotherapy (p = 0.0046). For validation, we utilized in vitro experiments on an external clinical cohort. The results demonstrated that GSDMD expression level in the high PSscore group was significantly upregulated compared to the low PSscore group (p < 0.001); the CD3+ T cells and the CD3+PD-1+ cells significantly increased in the high PSscore group compared to the low PSscore group (p < 0.01).ConclusionsThe PSscore of pyroptosis regulation pattern is a reliable biomarker, and it is valuable to predict prognosis, TME, and ICB therapeutic efficiency in glioma patients.

Project description:BackgroundN6-methyladenosine (m6A) modification and long non-coding RNAs (lncRNAs) play pivotal roles in gastric cancer (GC) progression. The emergence of immunotherapy in GC has created a paradigm shift in the approaches of treatment, whereas there is significant heterogeneity with regard to degree of treatment responses, which results from the variability of tumor immune microenvironment (TIME). How the interplay between m6A and lncRNAs enrolling in the shaping of TIME remains unclear.MethodsThe RNA sequencing and clinical data of GC patients were collected from TCGA database. Pearson correlation test and univariate Cox analysis were used to screen out m6A-related lncRNAs. Consensus clustering method was implemented to classify GC patients into two clusters. Survival analysis, the infiltration level of immune cells, Gene set enrichment analysis (GSEA) and the mutation profiles were analyzed and compared between two clusters. A competing endogenous RNA (ceRNA) network and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied for the identification of pathways in which m6A-related lncRNAs enriched. Then least absolute shrinkage and selection operator (LASSO) COX regression was implemented to select pivotal lncRNAs, and risk model was constructed accordingly. The prognosis value of the risk model was explored. In addition, the response to immune checkpoint inhibitors (ICIs) therapy were compared between different risk groups. Finally, we performed qRT-PCR to detect expression patterns of the selected lncRNAs in the 35 tumor tissues and their paired adjacent normal tissues, and validated the prognostic value of risk model in our cohort (N = 35).ResultsThe expression profiles of 15 lncRNAs were included to cluster patients into 2 subtypes. Cluster1 with worse prognosis harbored higher immune score, stromal score, ESTIMATE score and lower mutation rates of the genes. Different immune cell infiltration patterns were also displayed between the two clusters. GSEA showed that cluster1 preferentially enriched in tumor hallmarks and tumor-related biological pathways. KEGG pathway analysis found that the target mRNAs which m6A-related lncRNAs regulated by sponging miRNAs mainly enriched in vascular smooth muscle contraction, cAMP signaling pathway and cGMP-PKG signaling pathway. Next, eight lncRNAs were selected by LASSO regression algorithm to construct risk model. Patients in the high-risk group had poor prognoses, which were consistent in our cohort. As for predicting responses to ICIs therapy, patients from high-risk group were found to have lower tumor mutation burden (TMB) scores and account for large proportion in the Microsatellite Instability-Low (MSI-L) subtype. Moreover, patients had distinct immunophenoscores in different risk groups.ConclusionOur study revealed that the interplay between m6A modification and lncRNAs might have critical role in predicting GC prognosis, sculpting TIME landscape and predicting the responses to ICIs therapy.

Dataset Information

Dissecting the Role of Immune Checkpoint Regulation Patterns in Tumor Microenvironment and Prognosis of Gastric Cancer.

Publications

Dissecting the Role of Immune Checkpoint Regulation Patterns in Tumor Microenvironment and Prognosis of Gastric Cancer.

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