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A novel ferroptosis-related gene signature for predicting outcomes in cervical cancer.

ABSTRACT: Ferroptosis, a newly discovered iron-dependent form of cell death, contributes to various pathologies; however, the prognostic value of ferroptosis-related genes (FRGs) in cervical cancer (CC) remains unclear. Herein, we identified 15 differentially expressed FRGs based on data from The Cancer Genome Atlas database. Ten FRGs that correlated with prognosis were screened by univariate Cox regression analysis. The least absolute shrinkage and selection operator regression model was performed to develop a novel prognostic signature. A four-gene model was built to separate samples into high-risk and low-risk groups. Overall survival was lower in the high-risk group than in the low-risk group (p < 0.05). Receiver operating characteristic curve showed a good diagnostic efficiency of the signature. The risk score was identified as an independent prognostic factor via multivariate Cox regression. A functional analysis further revealed a difference in the immune status between the two risk groups. To conclude, we constructed a novel prognostic signature based on FRGs. Targeting ferroptosis may represent a promising approach for the treatment of CC.

SUBMITTER: Qi X

PROVIDER: S-EPMC8806749 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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A novel ferroptosis-related gene signature for predicting outcomes in cervical cancer.

Qi Xingling X Fu Yipeng Y Sheng Jia J Zhang Meng M Zhang Mingxing M Wang Yumeng Y Li Guiling G

Bioengineered 20211201 1

Ferroptosis, a newly discovered iron-dependent form of cell death, contributes to various pathologies; however, the prognostic value of ferroptosis-related genes (FRGs) in cervical cancer (CC) remains unclear. Herein, we identified 15 differentially expressed FRGs based on data from The Cancer Genome Atlas database. Ten FRGs that correlated with prognosis were screened by univariate Cox regression analysis. The least absolute shrinkage and selection operator regression model was performed to dev ...[more]

PMID: 33989111

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Project description:BackgroundMultiple myeloma (MM) is a highly malignant hematological tumor with a poor overall survival (OS). Due to the high heterogeneity of MM, it is necessary to explore novel markers for the prognosis prediction for MM patients. Ferroptosis is a form of regulated cell death, playing a critical role in tumorigenesis and cancer progression. However, the predictive role of ferroptosis-related genes (FRGs) in MM prognosis remains unknown.MethodsThis study collected 107 FRGs previously reported and utilized the least absolute shrinkage and selection operator (LASSO) cox regression model to construct a multi-genes risk signature model upon FRGs. The ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA) were carried out to evaluate immune infiltration level. Drug sensitivity was assessed based on the Genomics of Drug Sensitivity in Cancer database (GDSC). Then the synergy effect was determined with Cell counting kit-8 (CCK-8) assay and SynergyFinder software.ResultsA 6-gene prognostic risk signature model was constructed, and MM patients were divided into high and low risk groups. Kaplan-Meier survival curves showed that patients in the high risk group had significantly reduced OS compared with patients in the low risk group. Besides, the risk score was an independent predictor for OS. Receiver operating characteristic (ROC) curve analysis confirmed the predictive capacity of the risk signature. Combination of risk score and ISS stage had better prediction performance. Enrichment analysis revealed immune response, MYC, mTOR, proteasome and oxidative phosphorylation were enriched in high risk MM patients. We found high risk MM patients had lower immune scores and immune infiltration levels. Moreover, further analysis found that MM patients in high risk group were sensitive to bortezomib and lenalidomide. At last, the results of the in vitro experiment showed that ferroptosis inducers (RSL3 and ML162) may synergistically enhance the cytotoxicity of bortezomib and lenalidomide against MM cell line RPMI-8226.ConclusionThis study provides novel insights into roles of ferroptosis in MM prognosis prediction, immune levels and drug sensitivity, which complements and improves current grading systems.

Project description:BackgroundFerroptosis is a newly found non-apoptotic forms of cell death that plays an important role in tumors. However, the prognostic value of ferroptosis-related genes (FRG) in bladder cancer (BLCA) have not been well examined.MethodsFRG data and clinical information were collected from The Cancer Genome Atlas (TCGA). Then, significantly different FRGs were investigated by functional enrichment analyses. The prognostic FRG signature was identified by univariate cox regression and least absolute shrinkage and selection operator (LASSO) analysis, which was validated in TCGA cohort and Gene Expression Omnibus (GEO) cohort. Subsequently, the nomogram integrating risk scores and clinical parameters were established and evaluated. Additionally, Gene Set Enrichment Analyses (GSEA) was performed to explore the potential molecular mechanisms underlying our prognostic FRG signature. Finally, the expression of three key FRGs was verified in clinical specimens.ResultsThirty-two significantly different FRGs were identified from TCGA-BLCA cohort. Enrichment analyses showed that these genes were mainly related to the ferroptosis. Seven genes (TFRC, G6PD, SLC38A1, ZEB1, SCD, SRC, and PRDX6) were then identified to develop a prognostic signature. The Kaplan-Meier analysis confirmed the predictive value of the signature for overall survival (OS) in both TCGA and GEO cohort. A nomogram integrating age and risk scores was established and demonstrated high predictive accuracy, which was validated through calibration curves and receiver operating characteristic (ROC) curve [area under the curve (AUC) = 0.690]. GSEA showed that molecular alteration in the high- or low-risk group was closely associated with ferroptosis. Finally, experimental results confirmed the expression of SCD, SRC, and PRDX6 in BLCA.ConclusionHerein, we identified a novel FRG prognostic signature that maybe involved in BLCA. It showed high values in predicting OS, and targeting these FRGs may be an alternative for BLCA treatment. Further experimental studies are warranted to uncover the mechanisms that these FRGs mediate BLCA progression.

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A novel ferroptosis-related gene signature for predicting outcomes in cervical cancer.

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A novel ferroptosis-related gene signature for predicting outcomes in cervical cancer.

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