Comprehensive Pan-Cancer Analyses of Pyroptosis-Related Genes to Predict Survival and Immunotherapeutic Outcome.
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ABSTRACT:
SUBMITTER: Wang Q
PROVIDER: S-EPMC8750048 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Despite mounting evidence linking pyroptotic cell death to tumor growth, the clinical significance and disease mechanism of pyroptosis in cancer remain uncertain. In this study, we established a unique gene signature (π signature) that can be used as a predictive and prognostic tool in pyroptosis-related cancer subtypes. We found that the 13 core pyroptosis genes exerted opposite prognostic effects in different cancer types, which were subgrouped as pyroptosis positively related cancer and pyroptosis negatively related cancer. Subsequently, π signature was identified separately from the hub genes in pyroptosis positively related cancer and pyroptosis negatively related cancer subtypes. It was shown that π signature was well correlated with patient survival, pathological stages, tumor lymphocyte infiltration, and immunotherapy response. π signature was also applied as a predictive tool for chemotherapy drug responses and used as an independent factor for patient overall survival prediction. In short, this elaborated genetic signature could help us understand the oncogenic mechanism and pave the way for further therapeutic strategies based on pyroptosis.
| S-EPMC9236821 | biostudies-literature
Project description:Pyroptosis is a recently-identified pathway of host cell death that is stimulated by a range of microbial infections. Emerging evidence indicates pyroptosis plays crucial roles in tumor growth, disease progression, and migration of different cancer cells. However, the clinical significance of pyroptosis in tumor behavior prognosis, as well as the underlying mechanism in different cancers remains elusive. Here, by evaluating the expression level of pyroptosis genes in colorectal cancer (CRC) patients from the TCGA cohort and GEO cohort (GSE39582), we identified pyroptosis-related DEGs and then built a 13-gene risk model by applying the LASSO Cox regression algorithm. Furthermore, functional analysis using GSEA and GSEV revealed that our prognostic model may function through regulating immune responses and tumor biogenesis pathways. Significant infiltration of activated immune cells (e.g. cytotoxic T cells) was observed in the low risk score group. The selected gene set was further validated in the GEO cohort. Time-dependent ROC curves confirmed that our risk score model is robust in predicting 1, 3 and 5-year overall survival in CRC patients. Overall, we have identified a pyroptosis-related gene signature that consists of 13 genes, which serves as a potent indicator of CRC prognosis. Thus, our model provides insights in how to make better clinical decision in the future.
| S-EPMC9077106 | biostudies-literature
Project description:BackgroundCurrently, the most predominant type of liver cancer is hepatocellular carcinoma (HCC), which is also the fourth leading cause of cancer-related death in the global population. Pyroptosis is an emerging form of cell death that affects the prognosis of cancer patients by modulating tumor cell migration, proliferation and invasion. However, the evaluation of pyroptosis in the prognosis of HCC is still insufficient.MethodsA total of 365 HCC patients from the TCGA-LIHC cohort were classified into two distinct subtypes using consensus clustering of pyroptosis-related genes (PRGs). Following univariate Cox analysis of differentially expressed genes between subtypes, we established a prognostic model (PRGs-score, PRGS) by LASSO Cox analysis. We further tested the predictive power of the prognostic model in the ICGC (LIRI-JP) and GEO (GSE14520) cohorts. The tumor microenvironment (TME) was studied using the CIBERSORT. The enrichment scores for immune cells and immune functions in low- and high-PRGS groups were assessed using ssGSEA. The IMvigor210 cohort was used to investigate the immunotherapy efficacy. Furthermore, we validated the expression of prognostic genes in PRGS by RT-qPCR in vitro.ResultsThe subtyping of HCC based on PRGs exhibited distinct clinical characteristics. We developed a prognostic model PRGS by differentially expressed genes between different subtypes. The results showed that PRGS could well forecast the survival of HCC patients in different cohorts and was associated with the immune microenvironment. Moreover, PRGS was considered to be an independent prognostic risk factor and superior to other pyroptosis-related signatures. Low-PRGS implied greater immune cell infiltration and better overall survival with immunotherapy. The results of RT-qPCR also showed that prognostic genes were significantly dysregulated in HCC.ConclusionsPRGS has promising application in forecasting the prognosis of HCC patients, and its relationship with the immune microenvironment provides a basis for the subsequent treatment and research of HCC.
| S-EPMC9840857 | biostudies-literature
Project description:Background Immunotherapy has emerged as a significant strategy to treat numerous tumors. The positive response to immunotherapy depends on the dynamic interaction between tumor cells and infiltrating lymphocytes in the tumor microenvironment (TME). Pyroptosis, inflammation-induced cell death, is intricately associated with several tumors. However, the relationship between pyroptosis and clinical prognosis, immune cell infiltration, and immunotherapy effect is unclear in breast cancer (BRCA). Methods We comprehensively evaluated 33 pyroptosis-related genes and systematically assessed the relationship between pyroptosis and tumor progression, prognosis, and immune cell infiltration. The PyroptosisScore was used to quantify the pyroptosis pattern of a single tumor patient. We then assessed their values for predicting prognoses and therapeutic responses in BRCA. Results Three different modes of PyroptosisClusters were determined. The characteristics of TME cell infiltration in these three PyroptosisClusters were highly consistent with three immunophenotypes of tumors, including immune-excluded, immune-inflamed, and immune-desert phenotypes. Comprehensive bioinformatics analysis revealed that patients with a low PyroptosisScore had higher immune checkpoint expression, higher immune checkpoint inhibitor (ICI) scores, increased immune microenvironment infiltration, and were more sensitive to immunotherapy than those with a high PyroptosisScore. Conclusions Our findings revealed the crucial role of pyroptosis in maintaining the diversity and complexity of TME. Pyroptosis is closely related to tumor progression, tumor prognosis, and immunotherapy response. Evaluating the PyroptosisScore of a single tumor can assist in understanding the characteristics of TME infiltration and lead to the development of more effective immunotherapy strategies.
| S-EPMC8515898 | biostudies-literature
Project description:Gastric cancer (GC) is a highly molecular heterogeneous tumor with unfavorable outcomes. The Notch signaling pathway is an important regulator of immune cell differentiation and has been associated with autoimmune disorders, the development of tumors, and immunomodulation caused by tumors. In this study, by developing a gene signature based on genes relevant to the Notch pathway, we could improve our ability to predict the outcome of patients with GC. From the TCGA database, RNA sequencing data of GC tumors and associated normal tissues were obtained. Microarray data were collected from GEO datasets. The Molecular Signature Database (MSigDB) was accessed in order to retrieve sets of human Notch pathway-related genes (NPRGs). The LASSO analysis performed on the TCGA cohort was used to generate a multigene signature based on prognostic NPRGs. In order to validate the gene signature, the GEO cohort was utilized. Using the CIBERSORT method, we were able to determine the amounts of immune cell infiltration in the GC. In this study, a total of 21 differentially expressed NPRGs were obtained between GC specimens and nontumor specimens. The construction of a prognostic prediction model for patients with GC involved the identification and selection of three different NPRGs. According to the appropriate cutoff value, the patients with GC were divided into two groups: those with a low risk and those with a high risk. The time-dependent ROC curves demonstrated that the new model had satisfactory performance when it came to prognostic prediction. Multivariate assays confirmed that the risk score was an independent marker that may be used to predict the outcome of GC. In addition, the generated nomogram demonstrated a high level of predictive usefulness. Moreover, the scores of immunological infiltration of the majority of immune cells were distinctly different between the two groups, and the low-risk group responded to immunotherapy in a significantly greater degree. According to the results of a functional enrichment study of candidate genes, there are multiple pathways and processes associated with cancer. Taken together, a new gene model associated with the Notch pathway may be utilized for the purpose of predicting the prognosis of GC. One potential method of treatment for GC is to focus on NPRGs.
| S-EPMC9889149 | biostudies-literature
Project description:AimThis study aims to identify pyroptosis-related genes (PRGs), their functional immune characteristics, and distinct pyroptosis-related clusters in periodontitis.MethodsDifferentially expressed (DE)-PRGs were determined by merging the expression profiles of GSE10334, GSE16134, and PRGs obtained from previous literatures and Molecular Signatures Database (MSigDB). Least absolute shrinkage and selection operator (LASSO) regression was applied to screen the prognostic PRGs and develop a prognostic model. Consensus clustering was applied to determine the pyroptosis-related clusters. Functional analysis and single-sample gene set enrichment analysis (ssGSEA) were performed to explore the biological characteristics and immune activities of the clusters. The hub pyroptosis-related modules were defined using weighted correlation network analysis (WGCNA).ResultsOf the 26 periodontitis-related DE-PRGs, the highest positive relevance was for High-Mobility Group Box 1 (HMGB1) and SR-Related CTD Associated Factor 11 (SCAF11). A 14-PRG-based signature was developed through the LASSO model. In addition, three pyroptosis-related clusters were obtained based on the 14 prognostic PRGs. Caspase 3 (CASP3), Granzyme B (GZMB), Interleukin 1 Alpha (IL1A), IL1Beta (B), IL6, Phospholipase C Gamma 1 (PLCG1) and PYD And CARD Domain Containing (PYCARD) were dysregulated in the three clusters. Distinct biological functions and immune activities, including human leukocyte antigen (HLA) gene expression, immune cell infiltration, and immune pathway activities, were identified in the three pyroptosis-related clusters of periodontitis. Furthermore, the pink module associated with endoplasmic stress-related functions was found to be correlated with cluster 2 and was suggested as the hub pyroptosis-related module.ConclusionThe study identified 14 key pyroptosis-related genes, three distinct pyroptosis-related clusters, and one pyroptosis-related gene module describing several molecular aspects of pyroptosis in the pathogenesis and immune micro-environment regulation of periodontitis and also highlighted functional heterogeneity in pyroptosis-related mechanisms.
| S-EPMC9281553 | biostudies-literature
Project description:BackgroundAlthough the application of mesenchymal stem cells (MSCs) in engineered medicine, such as tissue regeneration, is well known, new evidence is emerging that shows that MSCs can also promote cancer progression, metastasis, and drug resistance. However, no large-scale cohort analysis of MSCs has been conducted to reveal their impact on the prognosis of cancer patients.ObjectivesWe propose the MSC score as a novel surrogate for poor prognosis in pan-cancer.MethodsWe used single sample gene set enrichment analysis to quantify MSC-related genes into a signature score and identify the signature score as a potential independent prognostic marker for cancer using multivariate Cox regression analysis. TIDE algorithm and neural network were utilized to assess the predictive accuracy of MSC-related genes for immunotherapy.ResultsMSC-related gene expression significantly differed between normal and tumor samples across the 33 cancer types. Cox regression analysis suggested the MSC score as an independent prognostic marker for kidney renal papillary cell carcinoma, mesothelioma, glioma, and stomach adenocarcinoma. The abundance of fibroblasts was also more representative of the MSC score than the stromal score. Our findings supported the combined use of the TIDE algorithm and neural network to predict the accuracy of MSC-related genes for immunotherapy.ConclusionWe comprehensively characterized the transcriptome, genome, and epigenetics of MSCs in pan-cancer and revealed the crosstalk of MSCs in the tumor microenvironment, especially with cancer-related fibroblasts. It is suggested that this may be one of the key sources of resistance to cancer immunotherapy.
| S-EPMC11327807 | biostudies-literature
Project description:Pathology images capture tumor histomorphological details in high resolution. However, manual detection and characterization of tumor regions in pathology images is labor intensive and subjective. Using a deep convolutional neural network (CNN), we developed an automated tumor region recognition system for lung cancer pathology images. From the identified tumor regions, we extracted 22 well-defined shape and boundary features and found that 15 of them were significantly associated with patient survival outcome in lung adenocarcinoma patients from the National Lung Screening Trial. A tumor region shape-based prognostic model was developed and validated in an independent patient cohort (n?=?389). The predicted high-risk group had significantly worse survival than the low-risk group (p value?=?0.0029). Predicted risk group serves as an independent prognostic factor (high-risk vs. low-risk, hazard ratio?=?2.25, 95% CI 1.34-3.77, p value?=?0.0022) after adjusting for age, gender, smoking status, and stage. This study provides new insights into the relationship between tumor shape and patient prognosis.
| S-EPMC6039531 | biostudies-other
Project description:IntroductionThe migrasome is a newly discovered organelle that resembles extracellular vesicles in structure. However, the function of the migrasome in tumors, particularly in relation to tumor immunity and tumor microenvironment, is unclear.MethodsGene expression data, copy number variation raw data, and methylation data of 33 cancer types were downloaded from The Cancer Genome Atlas database. Immunohistochemistry (IHC) based on 114 case of colorectal cancer was used to validate the expression of the migrasome hub-gene. We analyzed the expression, prognosis, genetic variation, and drug sensitivity profiles of migrasome-related genes (MRGs) in pan-cancer datasets. A migrasome score was constructed based on gene set enrichment analysis, and the correlation of migrasomes with the tumor microenvironment was assessed. The CancerSEA was used to perform a single-cell level functional analysis of the migrasome. Additionally, we also analyzed the correlation between migrasomes and tumor mutational burden (TMB), microsatellite instability (MSI), and tumor immune dysfunction and exclusion scores. Single-cell transcriptome sequencing (scRNA-seq) data was used to assess the activation state of migrasomes in the tumor microenvironment.ResultsPIGK expression was significantly up-regulated in 22 of 33 tumors, and high expression of migrasome was estimated to have contributed to poor prognosis. Missense mutations are the most common type of mutation in MRGs. We identified piperlongumine as a potential drug targeting migrasomes. The migrasome score was significantly and positively correlated with the tumor immunity score and the stroma score. In most tumors, the abundance of macrophages in the tumor microenvironment was significantly and positively correlated with the migrasome score. Additionally, the migrasome scores were significantly correlated with the immune checkpoint genes in pan-cancer as well as immune checkpoint therapy-related markers including TMB and MSI. According to scRNA-seq analysis, migrasome differed significantly among cells of the tumor microenvironment. IHC confirmed low expression of ITGA5 and PIGK in colorectal cancer.DiscussionWe performed the first pan-cancer analysis of migrasomes and discovered that they play an important role in tumor development and immune escape. Our study provides new insights into the role of migrasomes in tumor prognosis and immunotherapy.
| S-EPMC9669594 | biostudies-literature
Project description:BackgroundPrevious studies have reported the potential of aryl hydrocarbon receptor (AhR) in cancer immunotherapy. However, the mechanisms underpinning its therapeutic value have yet to be comprehensively investigated. Thus, this research aimed to explore the underlying association between AhR and cancer immunotherapy in 33 human cancers.MethodsThe gene expression data and clinical characteristics of 33 cancers were retrieved from The Cancer Genome Atlas database. The immunotherapeutic cohorts included GSE67501 and GSE78220 as well as IMvigor210, which were obtained from the Gene Expression Omnibus database and included in a previously published study respectively. Clinical parameters, including patient age, gender, survival, and tumor stage were analyzed to assess the prognostic value of AhR. The activity of AhR was generated by single sample gene set enrichment analysis and used to evaluate the difference between the AhR transcriptome and protein expression level. To better understand the role of AhR in cancer immunotherapy, the correlation between AhR and tumor microenvironment, as well as its relation to immune processes/elements, such as immune cell infiltration, immune inhibitors and stimulators, and the major histocompatibility complex were analyzed. The relevant underlying pathways associated with AhR signaling in cancer were also explored. Furthermore, the correlation between AhR and two immunotherapeutic biomarkers (tumor mutational burden and microsatellite instability) was investigated. Finally, the relationship between AhR and immunotherapeutic response was explored using three independent immunotherapeutic cohorts.ResultsAlthough AhR was not closely associated with age (5/33), gender (3/33), or tumor stage (3/21) in any of the studied human cancers, it exhibited potential prognostic value for predicting patient survival. Consistency has been observed between AhR activity and expression in some cancers (7/33). Generally, AhR presented a robust correlation with immune cell infiltration, immune modulators, and immunotherapeutic markers. Moreover, high AhR expression was significantly related to immune-relevant pathways. However, no significant correlation was observed between AhR and the immunotherapeutic response.ConclusionsThis research investigated the immunotherapeutic value of AhR in 33 human cancers, providing evidence regarding the function of AhR and its role in clinical treatment. However, considering that a bioinformatics approach was adopted, the current results are preliminary and require further validation.
| S-EPMC8287657 | biostudies-literature