A novel pyroptosis-related gene signature to predict outcomes in laryngeal squamous cell carcinoma.
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ABSTRACT:
SUBMITTER: Zhou C
PROVIDER: S-EPMC8751611 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundDiagnosis of early stage lung squamous cell carcinoma (LUSC) has improved; however, a comprehensive analysis of prognostic signatures is needed.PurposeTo identify, establish, and validate a signature model based on pyroptosis-related genes for prognostic predictions of early stage LUSC.Patients and methodsTwo independent cohorts were included. RNA-seq transcriptome data from patients with early stage LUSC were obtained from The Cancer Genome Atlas (TCGA) database. Thirty-three pyroptosis-related genes were analyzed between early stage LUSC and normal lung tissues. Cox regression analysis, random survival forest, and least absolute shrinkage and selection operator algorithms established a three-gene signature. Kaplan-Meier survival and receiver-operating characteristic curves assessed the prognostic efficacy of the model. Single-sample gene set enrichment analysis (ssGSEA) assessed the relationship between pyroptosis and immune cells. Patients with early stage LUSC from the GSE74777 dataset were used for validation. Pyroptosis-related genes were verified by RT-qPCR and Western blotting.ResultsTwenty-three differentially expressed pyroptosis-related genes were identified in the LUSC and adjacent normal tissues. Three differentially expressed pyroptosis-related genes were identified as hub genes in early stage LUSC. Patients with early stage LUSC in the TCGA cohort were classified into low- and high-risk subgroups according to the risk score. Overall survival (OS) was significantly short in the high-risk subgroup versus the low-risk subgroup. A similar result was found for the GSE74777 dataset. ssGSEA of immune cells and immune-related pathways between the low- and high-risk subgroups may explain the different OS for patients with early-stage LUSC. IL-6 expression was upregulated, which was inconsistent with the bioinformatic analysis. NOD1 and CASP4 were downregulated in LUSC (all P < 0.05) versus normal lung tissues.ConclusionDifferentially expressed pyroptosis-related genes may be involved in early stage LUSC. Pyroptosis-related genes are important in tumor immunity and may be potential prognostic predictors for early stage LUSC.
| S-EPMC8502038 | biostudies-literature
Project description:BackgroundHead and neck squamous cell carcinoma (HNSCC) is an extremely heterogeneous malignant cancer with poor prognosis. Pyroptosis is defined as a novel inflammation-dependent programmed cell death. However, the pyroptosis-associated gene expression in HNSCC and their relationship with prognosis are still indistinct.Material and methodsWe acquired the mRNA expression information of HNSCC patients from publicly available TCGA and GEO databases. We compared the tumor issues and adjacent normal tissues in terms of the gene expression for the purpose of identifying differentially expressed genes (DEGs). Based on these genes, we established a risk signature by the LASSO Cox regression in the TCGA cohort and validated the results in a GEO cohort. We also verified the levels of relevant mRNA expression in the model by RT-qPCR analysis. Eventually, functional enrichment approach was carried out to explore the potential mechanisms.ResultsOur team found a total of 18 differentially expressed genes (DEGs) between the HNSCC and healthy samples, and 4 DEGs displayed a remarkable association with the overall survival (OS) (P < 0.05). A 4-gene signature was constructed, presenting beneficial forecast power in both TCGA and GEO cohorts. Our team categorized patients into a group with high risk and another group with low risk as per the average risk value of the 4-gene feature. The individuals in the low risk group displayed a notably greater OS compared with the high risk one (P < 0.01). The Cox regression study demonstrated the independent forecast capability of the risk score. The receiver operating characteristic approach facilitated the verification of the forecast function of the gene signature. Posterior to verification, 4 genes were aberrantly expressed in the HNSCC and healthy samples. Functional study displayed that these groups presented diverse immunity conditions.ConclusionPyroptosis-associated genes are pivotal for the prognosis of HNSCC and can serve as potential therapeutic targets.
| S-EPMC8575318 | biostudies-literature
Project description:BackgroundA growing body of evidence has suggested the involvement of metabolism in the occurrence and development of tumors. But the link between metabolism and laryngeal squamous cell carcinoma (LSCC) has rarely been reported. This study seeks to understand and explain the role of metabolic biomarkers in predicting the prognosis of LSCC.MethodsWe identified the differentially expressed metabolism-related genes (MRGs) through RNA-seq data of The Cancer Genome Atlas (TCGA) and Gene set enrichment analysis (GSEA). After the screening of protein-protein interaction (PPI), hub MRGs were analyzed by least absolute shrinkage and selection operator (LASSO) and Cox regression analyses to construct a prognostic signature. Kaplan-Meier survival analysis and the receiver operating characteristic (ROC) was applied to verify the effectiveness of the prognostic signature in four cohorts (TCGA cohort, GSE27020 cohort, TCGA-sub1 cohort and TCGA-sub2 cohort). The expressions of the hub MRGs in LSCC cell lines and clinical samples were verified by quantitative reverse transcriptase PCR (qRT-PCR). The immunofluorescence staining of the tissue microarray (TMA) was carried out to further verify the reliability and validity of the prognostic signature. Cox regression analysis was then used to screen for independent prognostic factors of LSCC and a nomogram was constructed based on the results.ResultsAmong the 180 differentially expressed MRGs, 14 prognostic MRGs were identified. A prognostic signature based on two MRGs (GPT and SMS) was then constructed and verified via internal and external validation cohorts. Compared to the adjacent normal tissues, SMS expression was higher while GPT expression was lower in LSCC tissues, indicating poorer outcomes. The prognostic signature was proven as an independent risk factor for LSCC in both internal and external validation cohorts. A nomogram based on these results was developed for clinical application.ConclusionsDifferentially expressed MRGs were found and proven to be related to the prognosis of LSCC. We constructed a novel prognostic signature based on MRGs in LSCC for the first time and verified it via different cohorts from both databases and clinical samples. A nomogram based on this prognostic signature was developed.
| S-EPMC9270735 | biostudies-literature
Project description:Objective: Immune landscape is a key feature that affects cancer progression, survival, and treatment response. Herein, this study sought to comprehensively characterize the immune-related genes (IRGs) in oral squamous cell carcinoma (OSCC) and conduct an immune-related risk score (IRS) model for prognosis and therapeutic response prediction. Methods: Transcriptome profiles and follow-up data of OSCC cohorts were curated from TCGA, GSE41613, and IMvigor210 datasets. An IRS model was established through univariate Cox, Random Survival Forest, and multivariate Cox analyses. Prognostic significance was evaluated with Kaplan-Meier curves, ROC, uni- and multivariate Cox, and subgroup analyses. A nomogram was conducted and assessed with C-index, ROC, calibration curves, and decision curve analyses. Immune cell infiltration and immune response were estimated with ESTIMATE and ssGSEA methods. Results: An IRS model was constructed for predicting the overall survival and disease-free survival of OSCC, containing MASP1, HBEGF, CCL22, CTSG, LBP, and PLAU. High-risk patients displayed undesirable prognosis, and the predictive efficacy of this model was more accurate than conventional clinicopathological indicators. Multivariate Cox analyses demonstrated that this model was an independent risk factor. The nomogram combining IRS, stage, and age possessed high clinical application values. The IRS was positively associated with a nonflamed tumor microenvironment. Moreover, this signature enabled to predict immunotherapeutic response and sensitivity to chemotherapeutic agents (methotrexate and paclitaxel). Conclusion: Collectively, our study developed a robust IRS model with machine learning method to stratify OSCC patients into subgroups with distinct prognosis and benefits from immunotherapy, which might assist identify biomarkers and targets for immunotherapeutic schemes.
| S-EPMC9289552 | biostudies-literature
Project description:Background Oral squamous cell carcinoma (OSCC), as the most common oral cancer globally, is very harmful to people’s health. Hypoxia is closely related to many cancers. In this study, we have conducted a comprehensive exploration of the impact of hypoxia on OSCC. Methods First, we calculated the enrichment score (ES) of hypoxia-related genes in the sample based on the enrichment analysis of the single sample Gene Set Enrichment Analysis (ssGSEA) and expressed it as a potential hypoxia index (HPI). We first identified the relationship between HPI and survival time in OSCC tumor samples. Then we assessed the correlation between hypoxia and the degree of infiltration of various immune cells in OSCC tissues, and screened out gene mutations that may be related to HPI in OSCC. Finally, we constructed a prognostic model of hypoxia-related genes. Results In the immune cell infiltration of OSCC, we found that hypoxia was significantly related to the infiltration of eosinophils, macrophages, neutrophils, T helper cells and Th1 cells. In addition, NSD1 mutations may become a signal to suggest that patients with OSCC have higher HPI. Finally, we constructed a prognostic model of 6 sets of hypoxia-related genes (PGK1, JMJD6, S100A4, SLC2A3, DDIT4 and HK1) in OSCC. Conclusions Hypoxia is closely related to immune cell infiltration, gene mutation, and prognosis in OSCC patients.
| S-EPMC8576654 | biostudies-literature
Project description:The clinical TNM staging system is currently used to evaluate the prognosis of head and neck squamous cell carcinoma (HNSCC). The 5-year survival rate for patients with HNSCC is less than 50%, which is attributed to the lack of reliable prognostic biomarkers. Ferroptosis-related genes (FRGs) regulate cancer initiation and progression. Therefore, we analyzed the correlation between FRGs and the clinical outcomes of patients with HNSCC. A typical prognostic model of FRGs for HNSCC was constructed using bioinformatics tools and data from public databases, including The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and GeneCards. The model was generated based on the following six FRGs: ATG5, PRDX6, OTUB1, FTH1, SOCS1, and MAP3K5. The accuracy of model prediction was analyzed systematically. The overall survival (OS) of the high-risk group was significantly lower than that of the low-risk group. The AUC for 1-year, 3-year, and 5-year survival were 0.645, 0.721, and 0.737, respectively, in the training set (TCGA cohort) and 0.726, 0.620, and 0.584, respectively, in the validation set (GSE65858). The multivariate Cox regression analysis revealed that the risk score was an independent prognostic factor for HNSCC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that six FRGs were enriched in the ferroptosis pathway. A novel FRG prognostic signature model was established for HNSCC. The findings of this study reveal that FRGs are potential biomarkers for HNSCC.
| S-EPMC8629675 | biostudies-literature
Project description:Purpose Oral squamous cell carcinoma (OSCC) is the most common oral cancer worldwide. Pyroptosis is a type of programmed cell death mediated by caspase, accompanied by an inflammatory response, and plays an important role in cancer progression. The purpose of this study was to explore and identify potential biomarkers and further elucidate the potential role of cell pyroptosis in OSCC. Methods We regarded the samples from The Cancer Genome Atlas database as a training dataset, screened differentially expressed genes (DEGs), and further screened out OSCC phenotypic characteristic genes by using weighted gene co-expression network analysis. The analysis of 42 known pyroptosis-related genes showed that Psuch genes were widely expressed, mutated, and methylated in OSCC samples. Results Through correlation analysis, we identified our OSCC pyroptosis-related DEGs. To further evaluate the prognostic value of pyroptosis-related regulators, we constructed a seven gene-based prognostic signature using Cox univariate analysis and least absolute shrinkage and selection operator Cox regression analysis. Meanwhile, we found that patients in the low-risk group had higher immune infiltration. Moreover, our results also indicated significant differences in sensitivity to cisplatin and gefitinib between the high-risk and low-risk groups. Conclusion Our study successfully constructed the pyroptosis-related prognostic signature, which might play a potential prediction role in OSCC prognosis. Our findings also suggested that pyroptosis-related regulators might be novel biomarkers for tumor diagnosis and treatment in OSCC.
| S-EPMC9437919 | biostudies-literature
Project description:Esophageal squamous cell carcinoma (ESCC) accounts for the main esophageal cancer (ESCA) type, which is also associated with the greatest malignant grade and low survival rates worldwide. Ferroptosis is recently discovered as a kind of programmed cell death, which is indicated in various reports to be involved in the regulation of tumor biological behaviors. This work focused on the comprehensive evaluation of the association between ferroptosis-related gene (FRG) expression profiles and prognosis in ESCC patients based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). ALOX12, ALOX12B, ANGPTL7, DRD4, MAPK9, SLC38A1, and ZNF419 were selected to develop a novel ferroptosis-related gene signature for GEO and TCGA cohorts. The prognostic risk model exactly classified patients who had diverse survival outcomes. In addition, this study identified the ferroptosis-related signature as a factor to independently predict the risk of ESCC. Thereafter, we also constructed the prognosis nomogram by incorporating clinical factors and risk score, and the calibration plots illustrated good prognostic performance. Moreover, the association of the risk score with immune checkpoints was observed. Collectively, the proposed ferroptosis-related gene signature in our study is effective and has a potential clinical application to predict the prognosis of ESCC.
| S-EPMC8287967 | biostudies-literature
Project description:ObjectiveThis study aimed to develop a novel ferroptosis-related gene-based prognostic signature for esophageal carcinoma (ESCA).MethodsThe TCGA-ESCA gene expression profiles and corresponding clinical data were downloaded from the TCGA database. Ferroptosis-related genes were identified from the literature and public databases, which were intersected with the differentially expressed genes between ESCA and normal samples. After univariate Cox regression and random forest analyses, several ferroptosis-related feature genes were identified and used to construct a prognostic signature. Then, the prognostic value of the complex value and the correlation of the complex value with immune cell infiltration were analyzed. Moreover, function analysis, mutation analysis, and molecular docking on the ferroptosis-related feature genes were performed.ResultsBased on the TCGA dataset and ferroptosis pathway genes, 1929 ferroptosis-related genes were preliminarily selected. Following univariate Cox regression analysis and survival analysis, 14 genes were obtained. Then, random forest analysis identified 10 ferroptosis key genes. These 10 genes were used to construct a prognostic complex value. It was found that low complex value indicated better prognosis compared with high complex value. In different ESCA datasets, there were similar differences in the proportion of immune cell distribution between the high and low complex value groups. Furthermore, TNKS1BP1, AC019100.7, KRI1, BCAP31, and RP11-408E5.5 were significantly correlated with ESCA tumor location, lymph node metastasis, and age of patients. KRI1 had the highest mutation frequency. BCAP31 had the strongest binding ability with small molecules DB12830, DB05812, and DB07307.ConclusionWe constructed a novel ferroptosis-related gene signature, which has the potential to predict patient survival and tumor-infiltrating immune cells of ESCA.
| S-EPMC9270146 | biostudies-literature
Project description:Background: Hepatocellular carcinoma (HCC) is characterized by a poor prognosis and accounts for the fourth common cause of cancer-related deaths. Recently, pyroptosis has been revealed to be involved in the progression of multiple cancers. However, the role of pyroptosis in the HCC prognosis remains elusive. Methods: The clinical information and RNA-seq data of the HCC patients were collected from the TCGA-LIHC datasets, and the differential pyroptosis-related genes (PRG) were firstly explored. The univariate Cox regression and consensus clustering were applied to recognize the HCC subtypes. The prognostic PRGs were then submitted to the LASSO regression analysis to build a prognostic model in the TCGA training cohort. We further evaluated the predictive model in the TCGA test cohort and ICGC validation cohort (LIRI-JP). The accuracy of prediction was validated using the Kaplan-Meier (K-M) and receiver operating characteristic (ROC) analyses. The single-sample gene set enrichment analysis (ssGSEA) was used to determine the differential immune cell infiltrations and related pathways. Finally, the expression of the prognostic genes was validated by qRT-PCR in vivo and in vitro. Results: We identified a total of 26 differential PRGs, among which three PRGs comprising GSDME, GPX4, and SCAF11 were subsequently chosen for constructing a prognostic model. This model significantly distinguished the HCC patients with different survival years in the TCGA training, test, and ICGC validation cohorts. The risk score of this model was confirmed as an independent prognostic factor. A nomogram was generated indicating the survival years for each HCC patient. The ssGSEA demonstrated several tumor-infiltrating immune cells to be remarkably associated with the risk scores. The qRT-PCR results also showed the apparent dysregulation of PRGs in HCC. Finally, the drug sensitivity was analyzed, indicating that Lenvatinib might impact the progression of HCC via targeting GSDME, which was also validated in human Huh7 cells. Conclusion: The PRG signature comprised of GSDME, GPX4, and SCAF11 can serve as an independent prognostic factor for HCC patients, which would provide further evidence for more clinical and functional studies.
| S-EPMC8606409 | biostudies-literature