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An immune-related prognostic signature associated with immune landscape and therapeutic responses in gastric cancer.

ABSTRACT: Immune-related genes (IRGs) have attracted attention in recent years as therapeutic targets in various tumors. However, the role of IRGs in gastric cancer (GC) has not been clearly elucidated. This study presents a comprehensive analysis exploring the clinical, molecular, immune, and drug response features characterizing the IRGs in GC. Data were acquired from the TCGA and GEO databases. The Cox regression analyses were performed to develop a prognostic risk signature. The genetic variants, immune infiltration, and drug responses associated with the risk signature were explored using bioinformatics methods. Lastly, the expression of the IRS was verified by qRT-PCR in cell lines. In this manner, an immune-related signature (IRS) was established based on 8 IRGs. According to the IRS, patients were divided into the low-risk group (LRG) and high-risk group (HRG). Compared with the HRG, the LRG was characterized by a better prognosis, high genomic instability, more CD8+ T cell infiltration, greater sensitivity to chemotherapeutic drugs, and greater likelihood of benefiting from the immunotherapy. Moreover, the expression result showed good consistency between the qRT-PCR and TCGA cohort. Our findings provide insights into the specific clinical and immune features underlying the IRS, which may be important for patient treatment.

SUBMITTER: Sun JR

PROVIDER: S-EPMC10008502 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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An immune-related prognostic signature associated with immune landscape and therapeutic responses in gastric cancer.

Sun Jian-Rong JR Kong Chen-Fan CF Qu Xiang-Ke XK Sun An-Tao AT Zhao Kun-Peng KP Sun Jin-Hui JH

Aging 20230222 4

Immune-related genes (IRGs) have attracted attention in recent years as therapeutic targets in various tumors. However, the role of IRGs in gastric cancer (GC) has not been clearly elucidated. This study presents a comprehensive analysis exploring the clinical, molecular, immune, and drug response features characterizing the IRGs in GC. Data were acquired from the TCGA and GEO databases. The Cox regression analyses were performed to develop a prognostic risk signature. The genetic variants, immu ...[more]

PMID: 36812479

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Project description:BackgroundLong non-coding RNAs (lncRNAs) have been demonstrated to be useful in assessing the prognosis of cancer patients. However, few studies have focused on 5-methylcytosine-related lncRNAs (m5C-lncRNAs) in gastric cancer (GC). In this study, we aimed to establish a m5C-lncRNAs prognostic signature (m5C-LPS) and explore its potential impact on guiding clinical practice for GC.MethodsRNA-sequence and clinicopathological data were retrieved from The Cancer Genome Atlas (TCGA) database, while the coexpression of long non-coding RNAs (lncRNAs) was determined using Pearson's correlation analysis. A m5C-LPS model was constructed using univariate and Lasso Cox regression, and its prognostic value and accuracy were subsequently validated. Subsequently, the expression of 11 m5C-lncRNAs was verified via quantitative real-time PCR (qRT-PCR) in gastric cancer (GC) cell lines. The potential biological mechanism of this signature was elucidated using Gene Set Enrichment Analysis (GSEA). Based on the GSEA findings, CIBERSORT and ESTIMATE algorithms were utilized to conduct a comprehensive investigation of the tumor immune microenvironment (TIME) in GC. Additionally, pRRophetic and TIDE algorithms were employed to predict drug sensitivity and the efficacy of immunotherapy for GC patients.Results280 lncRNAs were identified as m5C-lncRNAs, including RHPN1-AS1, AC093752.3, TSC22D1-AS1, AL391152.1, MAGI2-AS3, AC048382.2, AL033527.3, AC007405.2, AC036103.1, CCDC183-AS1, and ADORA2A-AS1. Their prognostic value was validated, and the expression of these 11 lncRNAs was confirmed in four gastric cancer cell lines using quantitative reverse transcription PCR (qRT-PCR). A nomogram incorporating a risk score was developed to provide more precise clinical decision-making. Gene Set Enrichment Analysis (GSEA) showed that many classical signaling pathways related to tumor progression were enriched in this signature. Analyses related to immunity and drug sensitivity demonstrated distinct differences in features between high-risk and low-risk subgroups.ConclusionThe m5C-LPS can predict the survival of gastric cancer (GC) patients, provide novel therapeutic targets, and thus offer more thoughtful perspectives for future clinical decisions regarding GC.

Project description:Background: The construction of ferroptosis-related lncRNA prognostic models in malignancies has been an intense area of research recently. However, most of the studies focused on the exact expression of lncRNAs and had limited application values. Herein, we aim to establish a novel prognostic model for gastric cancer (GC) patients and discuss its correlation with immune landscapes and treatment responses. Methods: The present study retrieved transcriptional data of GC patients from the Cancer Genome Atlas (TCGA) database. We identified differentially expressed ferroptosis-related lncRNAs between tumor and normal controls of GC samples. Based on a new method of cyclically single pairing, we constructed a 0 or 1 matrix of ferroptosis-related lncRNA pairs (FRLPs). A risk score signature consisting of 10 FRLPs was established using multi-step Cox regression analysis. Next, we performed a series of systematic analyses to investigate the association of the FRLP model and tumor microenvironment, biological function, and treatment responses. An alternative model to the FRLP risk score signature, the gene set score (GS) model was also constructed, which could represent the former when lncRNA expression was not available. Results: We established a novel prognostic signature of 10 ferroptosis-related lncRNA pairs. High-risk patients in our risk score model were characterized by high infiltration of immune cells, upregulated carcinogenic and stromal activities, and heightened sensitivity to a wide range of anti-tumor drugs, whereas low-risk patients were associated with better responses to methotrexate treatment and elevated immunotherapeutic sensitivity. The practicability of the FRLP risk score model was also validated in two independent microarray datasets downloaded from Gene Expression Omnibus (GEO) using the GS model. Finally, two online dynamic nomograms were built to enhance the clinical utility of the study. Conclusion: In this study, we developed a ferroptosis-related lncRNA pair-based risk score model that did not rely on the exact lncRNA expression level. This novel model might provide insights for the accurate prediction and comprehensive management for GC patients.

Project description:BackgroundAn increasing number of reports have found that immune-related genes (IRGs) have a significant impact on the prognosis of a variety of cancers, but the prognostic value of IRGs in gastric cancer (GC) has not been fully elucidated.MethodsUnivariate Cox regression analysis was adopted for the identification of prognostic IRGs in three independent cohorts (GSE62254, n = 300; GSE15459, n = 191; and GSE26901, n = 109). After obtaining the intersecting prognostic genes, the three independent cohorts were merged into a training cohort (n = 600) to establish a prognostic model. The risk score was determined using multivariate Cox and LASSO regression analyses. Patients were classified into low-risk and high-risk groups according to the median risk score. The risk score performance was validated externally in the three independent cohorts (GSE26253, n = 432; GSE84437, n = 431; and TCGA, n = 336). Immune cell infiltration (ICI) was quantified by the CIBERSORT method.ResultsA risk score comprising nine genes showed high accuracy for the prediction of the overall survival (OS) of patients with GC in the training cohort (AUC > 0.7). The risk of death was found to have a positive correlation with the risk score. The univariate and multivariate Cox regression analyses revealed that the risk score was an independent indicator of the prognosis of patients with GC (p < 0.001). External validation confirmed the universal applicability of the risk score. The low-risk group presented a lower infiltration level of M2 macrophages than the high-risk group (p < 0.001), and the prognosis of patients with GC with a higher infiltration level of M2 macrophages was poor (p = 0.011). According to clinical correlation analysis, compared with patients with the diffuse and mixed type of GC, those with the Lauren classification intestinal GC type had a significantly lower risk score (p = 0.00085). The patients' risk score increased with the progression of the clinicopathological stage.ConclusionIn this study, we constructed and validated a robust prognostic signature for GC, which may help improve the prognostic assessment system and treatment strategy for GC.

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An immune-related prognostic signature associated with immune landscape and therapeutic responses in gastric cancer.

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An immune-related prognostic signature associated with immune landscape and therapeutic responses in gastric cancer.

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