A signature of four ferroptosis-related genes in laryngeal squamous cell carcinoma
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SUBMITTER: Zhao R
PROVIDER: S-EPMC11231803 | biostudies-literature | 2024 Jun
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND Immune-related genes (IRGs) are closely related to the incidence and progression of tumors, potentially indicating that IRGs play an important role in laryngeal squamous cell carcinoma (LSCC). MATERIAL AND METHODS An RNA sequencing dataset containing 123 samples was collected from The Cancer Genome Atlas. Based on immune-related differentially expressed genes (IRDEGs), a potential molecular mechanism of LSCC was explored through analysis of information in the Gene Ontology (GO) resource and the Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interactions (PPIs). A regulatory network of transcriptional regulators and IRDEGs was constructed to explore the underlying molecular mechanism of LSCC at the upstream level. Candidates from IRDEGs for signature were screened via univariate Cox analysis and using the least absolute shrinkage and selection operator (LASSO) technique. The IRDEG signature of LSCC was constructed by using a multivariate Cox proportional hazards model. RESULTS GO and KEGG analysis showed that IRDEGs may participate in the progression of LSCC through immune-related reactions. PPI analysis demonstrated that, among the IRDEGs in LSCC, the Kininogen 1; C-X-X motif chemokine ligand 10; elastase, neutrophil expressed; and LYZ genes are hub genes in the development of LSCC. At the upstream level, SPI1, SP140, signal transducer and activator of transcription 4, zinc finger E-box binding homeobox, and Ikaros family zinc finger 2 are the hub transcriptional regulators of IRDEGs. The risk score based on the IRDEG signature was able to distinguish prognosis in patients with LSCC and represents an independent prognostic risk factor for LSCC. CONCLUSIONS From the perspective of IRGs, we first constructed an IRDEG signature related to the prognosis of LSCC, which can be used as a novel marker to predict prognosis in patients with LSCC.
| S-EPMC7772955 | biostudies-literature
Project description:Researches have suggested that aerobic glycolysis can reflect the development and progression of most carcinomas. We aimed to investigate whether glycolysis-related genes (GRGs) are associated with overall survival in laryngeal squamous cell carcinoma (LSCC). Here, we identified differentially expressed GRGs in TCGA dataset and microarray sample of GSE27020 from GEO database. A set of two glycolytic gene signatures, including DDIT4 and PLOD2 was screened through Cox and Lasso regression. The risk score was calculated using the gene expression of the two GRGs. The high-risk group presented a poor prognosis through Kaplan-Meier method. The ROC curve indicated good prediction performance in survival based on the validation of four cohorts. Univariate and multivariate Cox regression analyses suggested that two-gene signature could be an independent risk factor in LSCC. A total of 17 LSCC patients were enrolled to clarify the genetic expression through using reverse transcription-polymerase chain reaction (RT-PCR). A visualized nomogram was then constructed to predict 1-, 3-, and 5-year overall survival. Taken together, two novel glycolytic gene signatures were discovered and validated, providing a potential therapeutic and overall survival (OS)-prediction biomarker for LSCC.
| S-EPMC8806568 | biostudies-literature
Project description:Pyroptosis, a pro-inflammatory form of programmed cell death, is associated with carcinogenesis and progression. However, there is little information concerning pyroptosis-related genes (PRGs) in laryngeal squamous cell carcinoma (LSCC). Herein, we aim to explore the prognostic value of PRGs in LSCC. The expression and clinical data of 47 PRGs in LSCC patients were obtained from The Cancer Genome Atlas. A novel prognostic PRG signature was constructed using least absolute shrinkage and selection operator analysis. Receiver operating characteristic (ROC) curves were drawn, and Kaplan-Meier survival Cox proportional hazard regression analyses were performed to measure the predictive capacity of the PRG signature. Furthermore, we constructed a six-PRG signature to divide LSCC patients into high- and low-risk groups. Patients in the high-risk group had worse overall survival than the low-risk group. The area under the time-dependent ROC curve was 0.696 for 1 year, 0.784 for 3 years, and 0.738 for 5 years. We proved that the PRGs signature was an independent predictor for LSCC. Functional enrichment analysis indicated that several immune-related pathways were significantly enriched in the low-risk group. Consistent with this, patients with low-risk scores had higher immune scores and better immunotherapeutic responses than the high-risk group. In conclusion, we established a novel PRGs signature that can predict outcome and response to immunotherapy of LSCC, pyroptosis may be a potential target for LSCC.
| S-EPMC8751611 | 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:BackgroundOral squamous cell carcinoma (OSCC) is one of the most common maligancies of the head and neck. The prognosis was is significantly different among OSCC patients. This study aims to identify new biomarkers to establish a prognostic model to predict the survival of OSCC patients.MethodsThe mRNA expression and corresponding clinical information of OSCC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus. Additionally, a total of 26 hypoxia-related genes were also obtained from a previous study. Univariate Cox regression analysis and LASSO Cox regression analysis were performed to screen the optimal hypoxia-related genes which were associated with the prognosis of OSCC. to establish the predictive model (Risk Score) was established for estimating the patient's overall survival (OS). Multivariate Cox regression analysis was used to determine whether the Risk Score was an independent prognostic factor. Based on all the independent prognostic factors, nomogram was established to predict the OS probability of OSCC patients. The relative proportion of 22 immune cell types in each patient was evaluated by CIBERSORT software.ResultsWe determined that a total of four hypoxia-related genes including ALDOA, P4HA1, PGK1 and VEGFA were significantly associated with the prognosis of OSCC patients. The nomogram established based on all the independent factors could reliably predict the long-term OS of OSCC patients. In addition, our resluts indicated that the inferior prognosis of OSCC patients with high Risk Score might be related to the immunosuppressive microenvironments.ConclusionThis study shows that high expression of hypoxia-related genes including ALDOA, P4HA1, PGK1 and VEGFA is associated with poor prognosis in OSCC patients, and they can be used as potential markers for predicting prognosis in OSCC patients.
| S-EPMC8094530 | biostudies-literature
Project description:ObjectivesThis study aimed to investigate the prognostic value of miRNAs and ferroptosis-related genes in cervical squamous cell carcinoma.MethodsWe mined data from public databases for differentially expressed miRNAs, ferroptosis-related genes, and clinical parameters and constructed a prognostic risk model. The predictive performance of the model was evaluated using survival and receiver operating characteristic curve analyses. We combined the clinicopathological features to construct a nomogram and evaluated its efficacy using calibration and clinical decision curves. The correlation between miRNA characteristics, risk score, and the tumor microenvironment was also studied. Next, consensus and key genes were screened, and their biological functions were analyzed using KEGG, GO, GSEA, and drug sensitivity analysis. Finally, the expression of miRNAs and key genes was detected using qRT-PCR and western blotting to verify the prediction results.ResultsSeven miRNA signatures (miR-100-3p, miR-301a-5p, miR-331-3p, miR-425-5p, miR-502-3p, miR-505-5p, and miR-629-3p) were generated, and prognostic risk and nomogram models were successfully constructed. These models exhibited good accuracy. miRNA signatures correlated with the tumor microenvironment. Twelve consensus genes and three key genes (SLC2A1, ANO6, and TXNIP) were screened and their biofunctional diversity was identified using various analytical methods. qRT-PCR and western blotting were used to verify the expression of miR-301a-5p, miR-505-5p, SLC2A1, and TXNIP in cervical squamous carcinoma. The results were consistent with those of bioinformatics analyses.ConclusionsSeven miRNAs may serve as prognostic biomarkers of cervical squamous cell carcinoma. SLC2A1, ANO6, and TXNIP are associated with cervical squamous cell carcinoma and may serve as ferroptosis-related markers of the disease.
| S-EPMC11551785 | biostudies-literature
Project description:BackgroundLung squamous cell carcinoma (LUSC), one of the main pathological types of lung cancer, has led to consequential socioeconomic burden. Ferroptosis is an iron-dependent form of cell death process with potentials for therapeutic target in various kinds of tumors. However, whether ferroptosis-related genes (FRGs) are associated with the prognosis of LUSC patients is still unclear. The aim of this study was to establish a FRGs-based signature which could stratify patients with LUSC.MethodsThe RNA sequencing profiles and corresponding clinical data of LUSC patients were retrieved from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) dataset. A FRG-based signature was developed using the TCGA-LUSC cohort and validated in the GEO cohort. Gene set enrichment analysis (GSEA) and analysis of immune cell characteristics were conducted to assess the relationship between FRGs and biological function or immune status. A nomogram based on selected clinical factors and the risk scores which were generated from the FRG-based signature was developed using the TCGA cohort and validated in the GEO cohort.ResultsA set of 16 FRGs, significantly associated with overall survival (OS) in the TCGA cohort, was identified and could classify LUSC patients into two risk groups. Kaplan-Meier analysis illustrated that the survival rate of the high-risk group was significantly lower than the low-risk group. Assessment and external validation of the signature showed that the survival predictive performance of this signature was adequate. Additionally, multiple pathways and functions were enriched through GSEA and the analysis of immune cell characteristics showed significantly different abundances of immune cells among the two risk groups. Finally, a nomogram integrating the FRG-based signature and selected clinical factors was also developed and assessed in both the TCGA and GEO cohort.ConclusionThis study indicated the association between the FRGs and prognosis of patients with LUSC. Targeting ferroptosis may serve as a novel potential therapeutic alternative for LUSC.
| S-EPMC8636213 | biostudies-literature
Project description:BackgroundThe prognosis of oral squamous cell carcinoma (OSCC) patients is difficult to predict or describe due to its high-level heterogeneity and complex aetiologic factors. Ferroptosis is a novel form of iron-dependent cell death that is closely related to tumour growth and progression. This study aims to clarify the predictive value of ferroptosis-related genes (FRGs) on the overall survival(OS) of OSCC patients.MethodsThe mRNA expression profile of FRGs and clinical information of patients with OSCC were collected from the TCGA database. Candidate differentially expressed ferroptosis-related genes (DE-FRGs) were identified by analysing differences between OSCC and adjacent normal tissues. A gene signature of prognosis-related DE-FRGs was established by univariate Cox analysis and LASSO analysis in the training set. Patients were then divided into high- and low-risk groups according to the cut-off value of risk scores, A nomogram was constructed to quantify the contributions of gene signature and clinical parameters to OS. Then several bioinformatics analyses were used to verify the reliability and accuracy of the model in the validation set. Finally, single-sample gene set enrichment analysis (ssGSEA) was also performed to reveal the underlying differences in immune status between different risk groups.ResultsA prognostic model was constructed based on 10 ferroptosis-related genes. Patients in high-risk group had a significantly worse OS (p < 0.001). The gene signature was verified as an independent predictor for the OS of OSCC patients (HR > 1, p < 0.001). The receiver operating characteristic curve displayed the favour predictive performance of the risk model. The prediction nomogram successfully quantified each indicator's contribution to survival and the concordance index and calibration plots showed its superior predictive capacity. Finally, ssGSEA preliminarily indicated that the poor prognosis in the high-risk group might result from the dysregulation of immune status.ConclusionThis study established a 10-ferroptosis-releated gene signature and nomogram that can be used to predict the prognosis of OSCC patients, which provides new insight for future anticancer therapies based on potential FRG targets.
| S-EPMC8290602 | 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:BackgroundLung squamous cell carcinoma (LUSC) represents 30% of all non-small cell lung carcinoma. Targeted therapy is not sufficient for LUSC patients because of the low frequency of targeted-effective mutation in LUSC whereas immunotherapy offers more options for patients with LUSC. We explored a ferroptosis-related prognostic signature that can potentially assess the prognosis and immunotherapy efficacy of LUSC patients.MethodsA total of 502 LUSC patients were downloaded from The Cancer Genome Atlas (TCGA). The external validation data were obtained from the Gene Expression Omnibus (GEO): GSE73403. Then, we identified the candidate genes and constructed the prognostic signature through the Cox survival regression analyses and least absolute shrinkage and selection operator (LASSO). Risk score plot, Kaplan-Meier curve, and ROC curve were used to assess the prognostic power and performance of the model. The CIBERSORT algorithm estimated the fraction of immune cell types. TIDE was utilized to predict the response to immunotherapy. IMvigor210 was used to explore the association between the risk scores and immunotherapy outcomes. A nomogram combined selected clinical characteristics, and the risk scores were constructed.ResultsWe screened 132 differentially expressed ferroptosis-related genes. According to KEGG and GO pathway analyses, these genes were mainly engaged in the positive regulation of cytokine production, cytokine metabolic process, and oxidoreductase activity. We then constructed a prognostic model via LASSO regression. The proportions of CD8+ T cells, CD4+ activated T cells, and follicular helper T cells were significantly different between low-risk and high-risk groups. TIDE algorithm indicated that low-risk LUSC patients might profit more from immune checkpoint inhibitors. The predictive value of the ferroptosis gene model in immunotherapy response was further confirmed in IMvigor210. Finally, we combined the clinical characteristics with a LASSO regression model to construct a nomogram that could be easily applied in clinical practice.ConclusionWe identified a prognostic model that provides an accurate and objective basis for guiding individualized treatment decisions for LUSC.
| S-EPMC9330609 | biostudies-literature