Prognosis-related gene signature is enriched in cancer-associated fibroblasts in the stem-like subtype of gastric cancer.
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ABSTRACT:
SUBMITTER: Sung JY
PROVIDER: S-EPMC9234682 | biostudies-literature | 2022 Jun
REPOSITORIES: biostudies-literature
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Prognosis-related gene signature is enriched in cancer-associated fibroblasts in the stem-like subtype of gastric cancer.
Sung Ji-Yong JY Cheong Jae-Ho JH
Clinical and translational medicine 20220601 6
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Project description: Not available
| S-EPMC10387327 | biostudies-literature
Project description:Gastric cancer (GC) is a prevalent form of malignancy characterized by significant heterogeneity. The development of a specific prediction model is of utmost importance to improve therapy alternatives. The presence of H. pylori can elicit pyroptosis, a notable carcinogenic process. Furthermore, the administration of chemotherapeutic drugs is often employed as a therapeutic approach to addressing this condition. In the present investigation, it was observed that there were variations in the production of 17 pyroptosis-regulating proteins between stomach tissue with tumor development and GC cells. The predictive relevance of each gene associated with pyroptosis was assessed using the cohort from the cancer genome atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) was utilized to enhance the outcomes of the regression approach. Patients with gastric cancer GC in the cohort from the TCGA were categorized into low-risk or high-risk groups based on their gene expression profiles. Patients with a low risk of gastric cancer had a higher likelihood of survival compared to persons classified as high risk (P<0.0001). A subset of patients diagnosed with GC from a Genes Expression Omnibus (GEO) cohort was stratified according to their overall survival (OS) duration. The statistical analysis revealed a higher significance level (P=0.0063) regarding OS time among low-risk individuals. The study revealed that the GC risk score emerged as a significant independent prognostic factor for OS in patients diagnosed with GC. The results of Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) research revealed that genes associated with a high-risk group had significantly elevated levels of immune system-related activity. Furthermore, it was found that the state of immunity was diminished within this particular group. The relationship between the immune response to cancer and pyroptosis genes is highly interconnected, suggesting that these genes have the potential to serve as prognostic indicators for GC.
| S-EPMC10990040 | biostudies-literature
Project description:BackgroundAlthough the outcome of patients with gastric cancer (GC) has improved significantly with the recent implementation of annual screening programs. Reliable prognostic biomarkers are still needed due to the disease heterogeneity. Increasing pieces of evidence revealed an association between immune signature and GC prognosis. Thus, we aim to build an immune-related signature that can estimate prognosis for GC.MethodsFor identification of a prognostic immune-related gene signature (IRGS), gene expression profiles and clinical information of patients with GC were collected from 3 public cohorts, divided into training cohort (n = 300) and 2 independent validation cohorts (n = 277 and 433 respectively).ResultsWithin 1811 immune genes, a prognostic IRGS consisting of 16 unique genes was constructed which was significantly associated with survival (hazard ratio [HR], 3.9 [2.78-5.47]; P < 1.0 × 10). In the validation cohorts, the IRGS significantly stratified patients into high- vs low-risk groups in terms of prognosis across (HR, 1.84 [1.47-2.30]; P = 6.59 × 10) and within subpopulations with stage I&II disease (HR, 1.96 [1.34-2.89]; P = 4.73 × 10) and was prognostic in univariate and multivariate analyses. Several biological processes, including TGF-β and EMT signaling pathways, were enriched in the high-risk group. T cells CD4 memory resting and Macrophage M2 were significantly higher in the high-risk risk group compared with the low-risk group.ConclusionIn short, we developed a prognostic IRGS for estimating prognosis in GC, including stage I&II disease, providing new insights into the identification of patients with GC with a high risk of mortality.
| S-EPMC6635287 | biostudies-literature
Project description:As a cold tumor, malignant glioma has strong immunosuppression and immune escape characteristics. The tumor microenvironment (TME) provides the "soil" for the survival of malignant tumors, and cancer-associated fibroblasts (CAFs) are the architects of matrix remodeling in TME. Therefore, CAFs have potent regulatory effects on the recruitment and functional differentiation of immune cells, whereby they synthesize and secrete numerous collagens, cytokines, chemokines, and other soluble factors whose interaction with tumor cells creates an immunosuppressive TME. This consequently facilitates the immune escape of tumor cells. Targeting CAFs would improve the TME and enhance the efficacy of immunotherapy. Thus, regulation of CAFs and CAFs-related genes holds promise as effective immunotherapies for gliomas. Here, by analyzing the Chinese Glioma Genome Atlas and the Cancer Genome Atlas database, the proportion of CAFs in the tumor was revealed to be associated with clinical and immune characteristics of gliomas. Moreover, a risk model based on the expression of CAFs-related six-gene for the assessment of glioma patients was constructed using the least absolute shrinkage and selection operator and the results showed that a high-risk group had a higher expression of the CAFs-related six-genes and lower overall survival rates compared with those in the low-risk group. Additionally, patients in the high-risk group exhibited older age, high tumor grade, isocitrate dehydrogenase wildtype, 1p/19q non-codeletion, O-6-methylguanine-DNA methyltransferase promoter unmethylation and poor prognosis. The high-risk subtype had a high proportion CAFs in the TME of glioma, and a high expression of immune checkpoint genes. Analysis of the Submap algorithm indicated that the high-risk patients could show potent response to anti-PD-1 therapy. The established risk prediction model based on the expression of six CAFs-related genes has application prospects as an independent prognostic indicator and a predictor of the response of patients to immunotherapy.
| S-EPMC8586504 | biostudies-literature
Project description:BackgroundGastric Cancer (GC) presents poor outcome, which is consequence of the high incidence of recurrence and metastasis at early stages. GC patients presenting recurrent or metastatic disease display a median life expectancy of only 8 months. The mechanisms underlying GC progression remain poorly understood.MethodsWe took advantage of public available GC datasets from TCGA using GEPIA, and identified the matched genes among the 100 genes most significantly associated with overall survival (OS) and disease free survival (DFS). Results were confirmed in ACRG cohort and in over 2000 GC cases obtained from several cohorts integrated using our own analysis pipeline. The Kaplan-Meier method and multivariate Cox regression analyses were used for prognostic significance and linear modelling and correlation analyses for association with clinic-pathological parameters and biological hallmarks. In vitro and in vivo functional studies were performed in GC cells with candidate genes and the related molecular pathways were studied by RNA sequencing.ResultsHigh expression of ANKRD6, ITIH3, SORCS3, NPY1R and CCDC178 individually and as a signature was associated with poor prognosis and recurrent disease in GC. Moreover, the expression of ANKRD6 and ITIH3 was significantly higher in metastasis and their levels associated to Epithelial to Mesenchymal Transition (EMT) and stemness markers. In line with this, RNAseq analysis revealed genes involved in EMT differentially expressed in ANKRD6 silencing cells. Finally, ANKRD6 silencing in GC metastatic cells showed impairment in GC tumorigenic and metastatic traits in vitro and in vivo.ConclusionsOur study identified a novel signature involved in GC malignancy and prognosis, and revealed a novel pro-metastatic role of ANKRD6 in GC.
| S-EPMC11322236 | biostudies-literature
Project description:BackgroundMetabolic reprograming have been associated with cancer occurrence and progression within the tumor immune microenvironment. However, the prognostic potential of metabolism-related genes in colorectal cancer (CRC) has not been comprehensively studied. Here, we investigated metabolic transcript-related CRC subtypes and relevant immune landscapes, and developed a metabolic risk score (MRS) for survival prediction.MethodsMetabolism-related genes were collected from the Molecular Signatures Database and metabolic subtypes were identified using an unsupervised clustering algorithm based on the expression profiles of survival-related metabolic genes in GSE39582. The ssGSEA and ESTIMATE methods were applied to estimate the immune infiltration among subtypes. The MRS model was developed using LASSO Cox regression in the GSE39582 dataset and independently validated in the TCGA CRC and GSE17537 datasets.ResultsWe identified two metabolism-related subtypes (cluster-A and cluster-B) of CRC based on the expression profiles of 539 survival-related metabolic genes with distinct immune profiles and notably different prognoses. The cluster-B subtype had a shorter OS and RFS than the cluster-A subtype. Eighteen metabolism-related genes that were mostly involved in lipid metabolism pathways were used to build the MRS in GSE39582. Patients with higher MRS had worse prognosis than those with lower MRS (HR 3.45, P < 0.001). The prognostic role of MRS was validated in the TCGA CRC (HR 2.12, P = 0.00017) and GSE17537 datasets (HR 2.67, P = 0.039). Time-dependent receiver operating characteristic curve and stratified analyses revealed the robust predictive ability of the MRS in each dataset. Multivariate Cox regression analysis indicted that the MRS could predict OS independent of TNM stage and age.ConclusionsOur study provides novel insight into metabolic heterogeneity and its relationship with immune landscape in CRC. The MRS was identified as a robust prognostic marker and may facilitate individualized therapy for CRC patients.
| S-EPMC8244251 | biostudies-literature
Project description:The majority of gastric cancer (GC) patients are in a progressive stage at the initial stage of treatment, and the overall response rate to immunotherapy remains unsatisfactory largely due to the lack of effective prognostic biomarkers. Immunogenic cell death (ICD) was identified as a new form of regulated cell death that can activate adaptive immune responses and further promote immunotherapy efficacy. Therefore, we attempted to characterize the ICD-associated signature to stratify patients who could benefit from immunotherapy. In our study, two subgroups of patients were identified based on the data of 34 ICD-related genes extracted from The Cancer Genome Atlas database via consensus clustering. The estimated scores, stromal scores, immune scores, tumor purity, and survival rate showed significant differences between the low and high ICD groups. Then, we constructed an ICD-related risk signature, including IFNB1, IL6, LY96, and NT5E, using least absolute shrinkage and selection operator Cox regression analysis; then, high- and low-risk groups could be clearly distinguished. Notably, the risk score is a reliable predictor of the prognosis and immunotherapy outcome in GC, which was further validated in an immunohistochemistry assay. These results suggest that ICD is closely associated with the prognosis and tumor immune microenvironment in GC. Taken together, this study first constructed and validated a prognostic ICD-related signature to predict the survival and effect of immunotherapy in GC, which provided new insight for potent individualized immunotherapy strategies.
| S-EPMC10196197 | biostudies-literature
Project description:Previously, in the Asian Cancer Research Group (ACRG) project, we defined four distinct molecular subtypes in gastric cancer (GC). Mesenchymal (microsatellite stable with epithelial-to-mesenchymal transition phenotype, MSS/EMT) tumors showed the worst prognosis among all the subtypes. To develop a gene signature for predicting mesenchymal subtype GC, we conducted gene expression profiling using a NanoString assay in 70 ACRG specimens. The gene signature was validated in an independent set obtained from the prospective Adjuvant chemoRadioTherapy In Stomach Tumor (ARTIST) trial. The association between the mesenchymal subtype and survival was investigated. After cross-platform concordance test performed in 70 ACRG specimens, a 71-gene MSS/EMT signature was obtained. In the validation set, the gene signature predicted that 20 of 73 (27%) patients had mesenchymal tumors. Patients with mesenchymal subtype had diffuse GC, poorly-differentiated or signet ring cell carcinoma, and were microsatellite stable. The estimated hazard ratio for survival in patients with mesenchymal GC compared to those with non-mesenchymal tumors was 2.262 (95% confidence interval, 1.410 to 3.636; P=0.001). The survival difference remained significant when the subtypes were analyzed according to clinical prognostic parameters. This study suggested that the NanoString-based 71-gene signature for mesenchymal subtype is a strong predictor of the outcome in patients with GC.
| S-EPMC5630413 | biostudies-literature
Project description:Gastric cancer peritoneal metastases (GCPM) is a leading cause of GC-related death. Early detection of GCPM is critical for improving the prognosis of advanced GC. Differentially expressed genes (DEGs) were identified in the GSE62254 database to distinguish between GCPM and non-GCPM. The gastric cancer peritoneal metastases signature (GCPMs) was developed using DEGs. We analysed the effectiveness of GCPMs as indicators for prognosis, chemotherapy, and immune therapy response in GC patients. Subsequently, we analysed the correlation between GCPMs and immune microenvironment as well as immune escape in GC patients. Random forest model and immunohistochemistry was utilized to identify the crucial genes that can aid in the diagnosis of GCPM. We identified five DEGs and utilized their expression to construct GCPMs. Patients with high GCPMs had a higher likelihood of a poor prognosis, while those with low GCPMs appeared to potentially benefit more from chemotherapy. GCPMs were a dependable marker for predicting the response to immunotherapy. Additionally, GCPMs was found to be significantly linked to stromal score and cancer-associated fibroblasts. SYNPO2 has been identified as the gene with the highest significance in the diagnosis of GCPM. Immunohistochemistry suggests that SYNPO2-positive expression in tumour cells, fibroblasts, inflammatory cell may be associated with promoting peritoneal metastasis in GC. GCPMs have shown to be a promising biomarker for predicting the prognosis and response of GC patients to chemotherapy and immunotherapy. The use of GCPMs for individual tumour evaluation may pave the way for personalized treatment for GC patients in the future.
| S-EPMC10660625 | biostudies-literature
Project description:BackgroundGastric cancer (GC) is one of the most common malignancies. Cuproptosis is a newly discovered type of cell death caused by protein toxicity stress, with copper having considerable importance in GC development.MethodsFirst, differentially expressed (DE) cuproptosis-related genes (CRGs) were screened in GC. The tumor mutation burden (TMB) of CRGs was analyzed. We then performed enrichment analyses of DE-CRGs. Next, we constructed a GC cuproptosis-related (CR) signature (CRs) using Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. The predictive efficacy was assessed using receiver operating characteristic (ROC) curves. Furthermore, we performed gene set enrichment analysis (GSEA). Different methods were used to assess tumor immunity of the CRs, and the Wilcoxon test was used to examine the expressions of m6A-, m7G-, and ferroptosis-related genes. The "pRRophetic" R package (The R Foundation for Statistical Computing) was used to predict the half maximal inhibitory concentration IC50 of common chemotherapeutic agents. Finally, the expression of CRGs in different clusters was analyzed using single-cell RNA sequencing (scRNA-seq).ResultsWe identified 8 DE-CRGs in GC. There were 9 CRGs with TMB values >1%. We constructed gene expression networks and CRs for GC. The DE-CRGs were involved in important mitochondrial metabolic pathways, and the CRs was a valuable independent prognosis factor. The GSEA revealed that angiogenesis and metabolic-related pathways were enriched in the high-risk group, whereas the low-risk group showed enrichment in DNA replication mismatch and repair pathways. The expressions of immunological checkpoints, ferroptosis-, m6A-, and m7G-related genes, type II interferon (INF) response, major histocompatibility complex (MHC class-I), and the IC50 of the copper-based carrier drug elesclomol were significantly different between the 2 groups of the CRs. Furthermore, the scRNA-seq analysis showed that most CRGs were mainly upregulated in endothelial cells.ConclusionsThe novel CRs could predict the prognosis of GC.
| S-EPMC10007928 | biostudies-literature