Prognostic and therapeutic insights into colorectal carcinoma through immunogenic cell death gene profiling
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ABSTRACT:
SUBMITTER: Yu J
PROVIDER: S-EPMC11210462 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:ObjectiveStudies have firmly established the pivotal role of the immunogenic cell death (ICD) in the development of tumors. This study seeks to develop a risk model related to ICD to predict the prognosis of patients with endometrial carcinoma (EC).Materials and methodsRNA-seq data of EC retrieved from TCGA database were analyzed using R software. We determined clusters based on ICD-related genes (ICDRGs) expression levels. Cox and LASSO analyses were further used to build the prediction model, and its accuracy was evaluated in the train and validation sets. Finally, in vitro and in vivo experiments were conducted to confirm the impact of the high-risk gene IFNA2 on EC.ResultsPatients were sorted into two ICD clusters, with survival analysis revealing divergent prognoses between the clusters. The Cox regression analysis identified prognostic risk genes, and the LASSO analysis constructed a model based on 9 of these genes. Notably, this model displayed excellent predictive accuracy when validated. Finally, increased IFNA2 levels led to decreased vitality, proliferation, and invasiveness in vitro. IFNA2 also has significant tumor inhibiting effect in vivo.ConclusionsThe ICD-related model can accurately predict the prognosis of patients with EC, and IFNA2 may be a potential treatment target.
| S-EPMC10968672 | biostudies-literature
Project description:BackgroundClear cell renal cell carcinoma (ccRCC) remains a challenging cancer type due to its resistance to standard treatments. Immunogenic cell death (ICD) has the potential to activate anti-tumor immunity, presenting a promising avenue for ccRCC therapies.MethodsWe analyzed data from GSE29609, TCGA-KIRC, and GSE159115 to identify ICD-related prognostic genes in ccRCC. By applying consensus clustering, patients were categorized based on ICD modification patterns, and an ICD signature (ICDS) model was developed using a PCA approach. Functional studies were conducted with FOXP3 knockdown in ccRCC cell lines to explore its impact on cell behavior.ResultsEleven ICD-related genes were identified as key prognostic indicators in ccRCC, with high ICDS linked to worse survival outcomes. High ICDS also correlated with increased levels of immune-suppressive cells within the tumor microenvironment. FOXP3 was highlighted as a critical gene influencing ICD, where its knockdown significantly reduced ccRCC cell proliferation and migration, underscoring its role in tumor progression.ConclusionsThis study establishes FOXP3 as a pivotal factor in ICD regulation and ccRCC progression. Targeting FOXP3 and other ICD pathways could enhance treatment efficacy in ccRCC, providing a foundation for ICD-based therapeutic strategies. Evaluating ICD patterns in ccRCC may guide patient-specific interventions, paving the way for improved management of this aggressive cancer.
| S-EPMC11782763 | biostudies-literature
Project description:Immunotherapy is a promising treatment for advanced colorectal cancers (CRCs). However, immunotherapy resistance remains a common problem. Immunogenic cell death (ICD), a form of regulated cell death, induces adaptive immunity, thereby enhancing anti-tumor immunity. Research increasingly suggests that inducing ICD is a promising avenue for cancer immunotherapy and identifying ICD-related biomarkers for CRCs would create a new direction for targeted therapies. Thus, this study used bioinformatics to address these questions and create a prognostic signature, aiming to improve individualized CRC treatment. We identified two ICD -related molecular subtypes of CRCs. The high subtype showed pronounced immune cell infiltration, high immune activity, and high expression of human leukocyte antigen and immune checkpoints genes. Subsequently, we constructed and validated a prognostic signature comprising six genes (CD1A, TSLP, CD36, TIMP1, MC1R, and NRG1) using random survival forest analyses. Further analysis using this prediction model indicated that patients with CRCs in the low-risk group exhibited favorable clinical outcomes and better immunotherapy responses than those in the high-risk group. Our findings provide novel insights into determining the prognosis and design of personalized immunotherapeutic strategies for patients with CRCs.
| S-EPMC10655694 | biostudies-literature
Project description:IntroductionThis study leverages bioinformatics and medical big data to integrate datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), providing a comprehensive overview of immunogenic cell death (ICD)-related gene expression in colorectal cancer (CRC). The research aims to elucidate the molecular pathways and gene networks associated with ICD in CRC, with a focus on the therapeutic potential of cell death inducers, including ferroptosis agents, and their implications for precision medicine.MethodsWe conducted differential expression analysis and utilized advanced bioinformatic techniques to analyze ICD-related gene expression in CRC tissues. Unsupervised consensus clustering was applied to categorize CRC patients into distinct ICD-associated subtypes, followed by an in-depth immune microenvironment analysis and single-cell RNA sequencing to investigate immune responses and cell infiltration patterns. Experimental validation was performed to assess the impact of cell death inducers on ICD gene expression and their interaction with ferroptosis inducers in combination with other clinical drugs.ResultsDistinct ICD gene expression profiles were identified in CRC tissues, revealing molecular pathways and intricate gene networks. Unsupervised consensus clustering refined the CRC cohort into unique ICD-associated subtypes, each characterized by distinct clinical and immunological features. Immune microenvironment analysis and single-cell RNA sequencing revealed significant variations in immune responses and cell infiltration patterns across these subtypes. Experimental validation confirmed that cell death inducers directly affect ICD gene expression, highlighting their therapeutic potential. Additionally, combinatorial therapies with ferroptosis inducers and clinical drugs were shown to influence drug sensitivity and resistance in CRC.DiscussionOur findings underscore the importance of ICD-related genes in CRC prognosis and therapeutic targeting. The study provides actionable insights into the efficacy of cell death-inducing therapies, particularly ferroptosis inducers, and their regulatory mechanisms in CRC. These discoveries support the development of precision medicine strategies targeting ICD genes and offer valuable guidance for translating these therapies into clinical practice, with the potential to enhance CRC treatment outcomes and patient survival.
| S-EPMC11449742 | biostudies-literature
Project description:Treatments with cytotoxic agents or viruses may cause Immunogenic Cell Death (ICD) that immunize tumor-bearing hosts but do not cause complete regression of tumor. We postulate that combining two ICD inducers may cause durable regression in immunocompetent mice. ICD was optimized in vitro by maximizing calreticulin externalization in human colorectal carcinoma (CRC) cells by exposure to mixtures of Oxaliplatin (OX) and human adenovirus (AdV). Six mm diameter CT26 or 4T1 carcinomas in flanks of BALB/c mice were injected once intratumorally (IT) with OX, AdV or their mixture. Tumor growth, Tumor-Infiltrating Lymphocytes (TIL), nodal cytotoxicity, and rejection of a viable cell challenge were measured. Tumors injected IT once with an optimum mixture of 80 µM OX - AdV 25 Multiplicity of Infection (MOI) in PBS buffer were 17-29% the volume of control tumors. When buffer was changed from PBS to 5% dextrose in water (D5W), volumes of tumors injected IT with 80 µM OX-AdV 25 MOI were 10% while IT OX or AdV alone were 32% and 40% the volume of IT buffer-treated tumors. OX-AdV IT increased CD3+ TIL by 4-fold, decreased CD8+ PD-1+ TIL from 79% to 19% and induced cytotoxicity to CT26 cells in draining node lymphocytes while lymphocytes from CT26-bearing untreated mice were not cytotoxic. OX-AdV IT in D5W caused complete regression in 40% of mice. Long-term survivors rejected a contralateral challenge of CT26. The buffer for Oxaliplatin is critical. The two ICD inducer mixture is promising as an agnostic sensitizer for carcinomas like colorectal carcinoma.
| S-EPMC7227684 | biostudies-literature
Project description:BackgroundBoth immunogenic cell death (ICD) and long noncoding RNAs (lncRNAs) are strongly associated with tumor development, but the mechanism of action of ICD-associated lncRNAs in hepatocellular carcinoma (HCC) remains unclear.MethodsWe collected data from 365 HCC patients from The Cancer Genome Atlas (TCGA) database. We formulated a prognostic signature of ICD-associated lncRNAs and a nomogram to predict prognosis. To explore the potential mechanisms and provide clinical guidance, survival analysis, enrichment analysis, tumor microenvironment analysis, tumor mutation burden (TMB), and drug sensitivity prediction were conducted based on the subgroups obtained from the risk score.ResultsA prognostic signature of seven ICD-associated lncRNAs was constructed. Kaplan-Meier (K-M) survival curves showed a more unfavorable outcome in high-risk patients. The nomogram had a higher predictive value than the nomogram constructed without the risk model. Enrichment analysis confirmed that risk lncRNAs were closely associated with cell proliferation and mitosis. Most of the immune checkpoints currently used in therapy (e.g., PDCD1 and CTLA4) appeared to be elevated in high-risk patients. Tumor microenvironment analysis showed differential expression of lymphocytes (including natural killer cells, regulatory T cells, etc.) in the high-risk group. TMB had a higher incidence of mutations in the high-risk group (P=0.004). Chemotherapy drug sensitivity prediction provides effective guidelines for individual therapy. RT-qPCR of human HCC tissues verified the accuracy of the model.ConclusionWe constructed an effective prognostic signature for patients with HCC using seven ICD-lncRNAs, which provides guidance for the prognostic assessment and personalized treatment of patients.
| S-EPMC10500227 | biostudies-literature
Project description:Colorectal cancer (CRC) is a major cause of cancer-related death in the world. Emerging evidence suggests that the clinical success of conventional chemotherapy does not merely rely on cell toxicity, but also results from the restoration of tumor immune surveillance. Anti-tumor immune response can be primed by immunogenic cell death (ICD), a form of apoptosis associated with endoplasmic reticulum stress (ERS) induction and the expression/release of specific damage-associated molecular patterns (DAMPs). Unfortunately, a limited number of ICD inducers have been identified so far. The anti-helmintic drug rafoxanide has recently showed anti-tumor activity in different cancer types, including CRC. As such latter effects relied on ERS activation, we here investigated whether rafoxanide could promote ICD of CRC cells. The potential of rafoxanide to induce ICD-related DAMPs in both human and mouse CRC cells was assessed by flow-cytometry, chemiluminescent assay and ELISA. In addition, the immunogenic potential of rafoxanide was assessed in vivo using a vaccination assay. Rafoxanide induced all the main DAMPs (ecto-calreticulin exposure, adenosine triphosphate (ATP)/high mobility group box 1 (HMGB1) release) required for ICD. We observed a marked increase of tumor-free survival among immunocompetent mice immunized with rafoxanide-treated dying tumor cells as compared with sham. Altogether, our data indicate rafoxanide as a bona fide ICD inducer.
| S-EPMC7281008 | biostudies-literature
Project description:BackgroundImmunogenic cell death (ICD) plays a vital role in tumor progression and immune response. However, the integrative role of ICD-related genes and subtypes in the tumor microenvironment (TME) in prostate cancer (PCa) remains unknown.Materials and methodsThe sample data were obtained from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Memorial Sloan Kettering Cancer Center (MSKCC) prostate cancer-related databases. We first divided the subtypes based on ICD genes from 901 PCa patients and then identified the prognosis- related genes (PRGs) between different ICD subtypes. Subsequently, all the patients were randomly split into the training and test groups. We developed a risk signature in the training set by least absolute shrinkage and selection operator (LASSO)-Cox regression. Following this, we verified this prognostic signature in both the training test and external test sets. The relationships between the different subgroups and clinical pathological characteristics, immune infiltration characteristics, and mutation status of the TME were examined. Finally, the artificial neural network (ANN) and fundamental experiment study were constructed to verify the accuracy of the prognostic signature.ResultsWe identified two ICD clusters with immunological features and three gene clusters composed of PRGs. Additionally, we demonstrated that the risk signature can be used to evaluate tumor immune cell infiltration, prognostic status, and an immune checkpoint inhibitor. The low-risk group, which has a high overlap with group C of the gene cluster, is characterized by high ICD levels, immunocompetence, and favorable survival probability. Furthermore, the tumor progression genes selected by the ANN also exhibit potential associations with risk signature genes.ConclusionThis study identified individuals with high ICD levels in prostate cancer who may have more abundant immune infiltration and revealed the potential effects of risk signature on the TME, immune checkpoint inhibitor, and prognosis of PCa.
| S-EPMC10279955 | biostudies-literature
Project description:BackgroundMitochondrial metabolic reprogramming (MMR)-mediated immunogenic cell death (ICD) is closely related to the tumor microenvironment (TME). Our purpose was to reveal the TME characteristics of clear cell renal cell carcinoma (ccRCC) by using them.MethodsTarget genes were obtained by intersecting ccRCC differentially expressed genes (DEGs, tumor VS normal) with MMR and ICD-related genes. For the risk model, univariate COX regression and K-M survival analysis were used to identify genes most associated with overall survival (OS). Differences in the TME, function, tumor mutational load (TMB), and microsatellite instability (MSI) between high and low-risk groups were subsequently compared. Using risk scores and clinical variables, a nomogram was constructed. Predictive performance was evaluated by calibration plots and receiver operating characteristics (ROC).ResultsWe screened 140 DEGs, including 12 prognostic genes for the construction of risk models. We found that the immune score, immune cell infiltration abundance, and TMB and MSI scores were higher in the high-risk group. Thus, high-risk populations would benefit more from immunotherapy. We also identified the three genes (CENPA, TIMP1, and MYCN) as potential therapeutic targets, of which MYCN is a novel biomarker. Additionally, the nomogram performed well in both TCGA (1-year AUC=0.862) and E-MTAB-1980 cohorts (1-year AUC=0.909).ConclusionsOur model and nomogram allow accurate prediction of patients' prognoses and immunotherapy responses.
| S-EPMC10196130 | biostudies-literature
Project description: Not available
| S-EPMC10986630 | biostudies-literature