Identification of Hypoxia-Related Subtypes, Establishment of Prognostic Models, and Characteristics of Tumor Microenvironment Infiltration in Colon Cancer.
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ABSTRACT:
SUBMITTER: Wang C
PROVIDER: S-EPMC9247151 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The role of pyroptosis, which is also a kind of cell-intrinsic death mechanism, in tumorigenesis and cancer progression has been revolutionized. However, the expression of pyroptosis-related genes (PYGs) in colon cancer (CC) and their prognostic value remain unclear. In this study, we comprehensively identified two PYG-mediated molecular subtypes with a distinct tumor microenvironment (TME) in 1,415 CC samples, which were based on 10 PYGs. The six-gene signature (pyroptosis score, PY-score) was constructed to quantify the molecular patterns of individual tumors using a least absolute shrinkage and selection operator (LASSO)-Cox regression model through the differentially expressed genes between the two molecular subtypes. Significant infiltration of activated immune cells (such as M1 macrophages and cytotoxic T cells) was observed in the low PY-score group, while naive and suppressive immune cells (such as naive CD8+ T cells and M2 macrophages) dominated in the high PY-score group. CC patients in the low PY-score group showed not only significant survival advantage but also sensitivity to immune checkpoint inhibitor treatment, anti-epidermal growth factor receptor (EGFR) therapy, and chemotherapy. Overall, this work revealed that the PYGs played a vital role in the formation of heterogeneity in the TME. The analysis of the PYG-mediated molecular patterns helps in understanding the characterization of TME infiltration and provides insights into more effective therapeutic strategies.
| S-EPMC8631352 | biostudies-literature
Project description:BackgroundNumerous reports have highlighted that pyroptosis is closely linked to tumorigenesis and drug resistance of tumors. However, the potential role of pyroptosis in regulating immune cell infiltration in tumor microenvironment (TME) remains unclear.MethodsHere, we performed consensus clustering analysis based on the expression of 10 typical pyroptosis-related regulators (PRRs) to construct pyroptosis-mediated tumor pattern clusters and pyroptosis-related gene signature in breast cancer (BC). GSVA combined with ssGSEA methods were applied to evaluate the differences in biological pathway and immune cell infiltration level, respectively. The PCA method was employed to construct the pyro-score to quantify the pyroptosis pattern level of individual BC patient.ResultsWe determined three distinct pyro-clusters among 1852 BC samples, which exhibited different survival outcomes and enriched biological processes. The TME features demonstrated that these three clusters corresponded to three established immune profiles: immune-desert, immune-excluded and immune-inflamed phenotype, respectively. Based on pyroptosis-related signature genes, we constructed the pyro-score and stratified BC patients into high and low pyro-score group. Patients with high pyro-score exhibited favorable outcome and increased infiltration of immune cells. Further investigation revealed that high pyro-score was also related to high expression of immunosuppressive molecules, decreased tumor mutation burden (TMB) and high rate of mutation in significantly mutated genes (SMGs) (eg, PIK3CA and CDH1).ConclusionThis research emphasizes the indispensable role of pyroptosis in TME complexity and diversity. Assessing the pyroptosis pattern level of individual BC patient will assist us in better understanding TME features and directing more effective immunotherapeutic approaches.
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Project description:The current study aimed to construct a prognostic predictive model based on tumor microenvironment. CIBERSORT and ESTIMATE algorithms were used to reveal the immune cell infiltration (ICI) landscape of colon cancer. Patients were classified into three clusters by ConsensusClusterPlus algorithm. ICI scores of each patient were determined by principal component analysis. Patients were divided into high and low ICI score groups. Survival, gene expression, and somatic mutation of the two groups were compared. We found that patients with no lymph node invasion, no metastasis, T1-2 disease, and stage I-II had higher ICI scores. Calcium signaling pathway, leukocyte transendothelial migration pathway, MAPK signaling pathway, TGF β pathway, and Wnt signaling pathway were enriched in the high ICI score group. Immune-checkpoint and immune-activity associated genes were decreased in high ICI score patients. Patients in the high ICI score group had better survival. Prognostic value of ICI score was independent of tumor mutational burden (TMB). The ICI score model constructed in the current study may serve as an independent prognostic biomarker in colon cancer.
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Project description:Background Gastrointestinal malignant cancers affect many sites in the intestinal tract, including the colon. In this study, we purposed to improve prognostic predictions for colon cancer (CC) patients by establishing a novel biosignature of immune-related genes (IRGs) based on the tumor microenvironment (TME). Methods Using the estimation of stromal and immune cells in malignant tumor tissues using expression data (ESTIMATE) algorithm, we calculated the stromal and immune scores of every CC patient extracted from The Cancer Genome Atlas (TCGA). We then identified 4 immune-related messenger RNA (mRNA) biosignatures through a Cox and least absolute shrinkage and selection operator (LASSO) univariate analysis, and a Cox multivariate analysis. Relationships between tumor immune infiltration and the risk score were evaluated through the CIBERSORT algorithm and Tumor Immune Estimation Resource (TIMER) database. Results Our studies showed that individuals who had a high immune score (P=0.017) and low stromal score (P=0.041) had a favorable overall survival (OS) rate. By comparing high/low scores cohort, 220 differentially expressed genes (DEGs) were determined. Then an immune-related four-mRNA biosignature, including PDIA2, NAFTC1, VEGFC, and CD1B was identified. Kaplan-Meier, calibration, and receiver operating characteristic (ROC) curves verified the model’s performance. By using univariate and multivariate Cox analyses, we found each biosignature was an independent risk factor for assessing a CC patient’s survival. Three external GEO cohorts validated its good efficiency in estimating OS among individuals with CC. Moreover, the signature was also related to infiltration of several cells of the immune system in the tumor microenvironment. Conclusions The resultant model in our study included 4 IRGs associated with the TME. These IRGs can be utilized as an auxiliary variable to estimate and help improve the prognosis of individuals with CC.
| S-EPMC8576251 | biostudies-literature
Project description:The interaction between hypoxia and RNA N6-methyladenosine (m6A) is an emerging focus of investigation. However, alterations in m6A modifications at distinct hypoxia levels remain uncharacterized in gastric cancer (GC). Unsupervised hierarchical clustering was performed to stratify samples into different clusters. Differentially expressed gene analysis, univariate Cox proportional hazards regression analysis, and hazard ratio calculations were used to establish an m6A score to quantify m6A regulator modification patterns. After using an algorithm integrating Least absolute shrinkage and selection operator (LASSO) and bootstrapping, we identified the best candidate predictive genes. Thence, we established an m6A-related hypoxia pathway gene prognostic signature and built a nomogram to evaluate its predictive ability. The area under the curve (AUC) value of the nomogram was 0.811, which was higher than that of the risk score (AUC=0.695) and stage (AUC=0.779), suggesting a high credibility of the nomogram. Furthermore, the clinical response of anti-PD-1/CTLA-4 immunotherapy between high- and low-risk patients showed a significant difference. Our study successfully explored a brand-new GC pathological classification based on hypoxia pathway genes and the quantification of m6A modification patterns. Comprehensive immune analysis and validation demonstrated that hypoxia clusters were reliable, and our signature could provide a new approach for clinical decision-making and immunotherapeutic strategies for GC patients.
| S-EPMC9253390 | biostudies-literature
Project description:BackgroundGrowing evidence has shown that the prognosis for colon cancer depends on changes in microenvironment. The purpose of this study was to elucidate the prognostic value of long noncoding RNAs (lncRNAs) related to immune microenvironment (IM) in colon cancer.MethodsSingle sample gene set enrichment analysis (ssGSEA) was used to identify the subtypes of colon cancer based on the immune genomes of 29 immune signatures. Cox regression analysis identified a lncRNA signatures associated with immune infiltration. The Tumor Immune Estimation Resource database was used to analyze immune cell content.ResultsColon cancer samples were divided into three subtypes by unsupervised cluster analysis. Cox regression analysis identified an immune infiltration-related 5-lncRNA signature. This signature combined with clinical factors can effectively improve the predictive ability for the overall survival (OS) of colon cancer. At the same time, we found that the expression of H19 affects the content of B cells and macrophages in the microenvironment of colon cancer and affects the prognosis of colon cancer. Finally, we constructed the H19 regulatory network and further analyzed the possible mechanisms. We found that knocking down the expression of H19 can significantly inhibit the expression of CCND1 and VEGFA. At the same time, the immunohistochemical assay found that the expression of CCND1 and VEGFA protein was significantly positively correlated with the infiltration of M2 type macrophages.ConclusionThe findings may help to formulate clinical strategies and understand the underlying mechanisms of H19 regulation. H19 may be a biomarker for targeted treatment of colon cancer.
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Project description:In cancer immunotherapy, cytotoxic T or NK cells need to engage cancer cells to initiate the killing. However, in clinical studies and in mouse models, some solid tumors are found with no lymphocytes. It is likely that these tumors will be resistant to all sorts of immunotherapies. Thus, restoring lymphocytic infiltration will be vital to the success of immunotherapies on solid tumors. In order to understand the complex interaction between cancer cells and stromal cells, we propose to establish animal models for studying the tumor microenvironment and to develop and test therapies to restore lymphocytic infiltration of tumors Without lymphocytes infiltrating tumors, all immunotherapies on solid tumors become ineffective.
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Project description:Background:Prostate cancer (PCa) is one of the most common cancers and the fifth leading cause of cancer-related death in men. Immune responses in the tumor microenvironment are hypothesized to be related to the prognosis of PCa patients; however, no studies are available to confirm the same. In this study, we aimed to explore the potential link between these two factors and identify new biomarkers to estimate the survival rate of PCa patients. Methods:A total of 490 cases were obtained from The Cancer Genome Atlas (TCGA) database. The gene expression data were analyzed by the ESTIMATE algorithm to evaluate the immune and stromal scores. The survival rate was calculated according to the case-specific clinical data. Enrichment analysis was performed to discover the main biological processes and signaling pathways of immune responses. We further identified and analyzed hub genes in the protein-protein interaction (PPI) network and evaluated their prognostic values. Results:Immune score significantly correlated with immune cell infiltration and overall survival of PCa patients. The genes CXCR4 and GPR183, identified as hub genes in the PPI network, correlated with immune cell infiltration and prognosis of PCa patients. Conclusion:CXCR4 and GPR183 participate in immune cell infiltration and function in PCa patients. The immune score, as well as the expression of CXCR4 and GPR183 in prostate cancer tissues, could be potential indexes for the prognosis of prostate cancer.
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Project description:Colon cancer is one of the most common malignancies causing death worldwide. It is well known that the cells of the tumor microenvironment contribute to the progression and prognosis of colon cancer. However, the gene alterations and potential remodeling mechanisms in the tumor microenvironment of colon cancer remain largely unknown. In this study, immune scores from the ESTIMATE algorithm were used to discriminate between patients with high or low immune-cell infiltration. There were 42 immune differentially expressed genes (DEGs) of prognostic value identified in this study. Among them, KCNJ5 is a key factor in promoting M2 macrophage recruitment and tumor immune infiltration in colon cancer. These findings may provide novel insights for decoding the complicated interplay between cancer cells and the tumor microenvironment as well as for developing new avenues for therapeutic intervention in colon cancer.
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Project description:Simple Summary Understanding how endoplasmic reticulum stress influences colorectal cancer progression and the composition of the tumor microenvironment is important for developing novel strategies in the treatment of colorectal cancer. In this study, we identified two endoplasmic reticulum stress-related subtypes of colorectal cancer with distinct prognosis and infiltration patterns in the tumor microenvironment. Besides, we constructed a prognostic model for predicting patients’ survival, which involved an endoplasmic reticulum stress-related 14-gene signature. Furthermore, by utilizing spatial transcriptomics data from two untreated colorectal cancer patients, we explored endoplasmic reticulum stress-related gene signatures at a subcellular level and found that colorectal cancer cells and regulatory T cells showed an evidently increased expression of endoplasmic reticulum stress-related gene signature, and cancer-associated fibroblasts might be the leading characteristic that distinguishes the endoplasmic reticulum stress-related subtypes of colorectal cancer. We suggest that targeting endoplasmic reticulum stress in colorectal cancer might reshape the exhausted tumor microenvironment and mitigate tumor progression. Abstract Recently, endoplasmic reticulum (ER) stress has been shown to influence tumor progression and immune cell function in the tumor microenvironment (TME). However, the underlying role of ER stress-related gene patterns in colorectal cancer (CRC) development remains unclear. We analyzed the ER stress-related gene patterns in 884 patients with CRC from the Gene Expression Omnibus database and evaluated the cell-infiltrating patterns in the TME. Two ER stress-related patterns were identified in patients with CRC that had distinct cell-infiltrating patterns in the TME and clinical characteristics. A risk score and nomogram based on 14 screened prognosis-correlated genes was built and validated to predict patient survival. Patients with a higher risk score were shown to have an unfavorable prognosis, and the risk score was associated with cell infiltration and drug sensitivity. Furthermore, spatial transcriptomics data were utilized to explore ER stress-related gene patterns in CRC tissues, and it was shown that ER stress phenotype involves in the formation of the immunosuppressive TME. This study demonstrated that ER stress-related gene patterns play a role in influencing the TME and predicting prognosis. These analyses of ER stress in the TME of CRC might deepen our understanding of CRC progression and immune escape and provide novel insights into therapeutic strategies.
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