Expression and Prognostic Characteristics of Ferroptosis-Related Genes in Colon Cancer.
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ABSTRACT:
SUBMITTER: Zhu J
PROVIDER: S-EPMC8199073 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Colon cancer (CC) is a common malignant tumor worldwide, and ferroptosis plays a vital role in the pathology and progression of CC. Effective prognostic tools are required to guide clinical decision-making in CC. In our study, gene expression and clinical data of CC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We identified the differentially expressed ferroptosis-related lncRNAs using the differential expression and gene co-expression analysis. Then, univariate and multivariate Cox regression analyses were used to identify the effective ferroptosis-related lncRNAs for constructing the prognostic model for CC. Gene set enrichment analysis (GSEA) was conducted to explore the functional enrichment analysis. CIBERSORT and single-sample GSEA were performed to investigate the association between our model and the immune microenvironment. Finally, three ferroptosis-related lncRNAs (XXbac-B476C20.9, TP73-AS1, and SNHG15) were identified to construct the prognostic model. The results of the validation showed that our model was effective in predicting the prognosis of CC patients, which also was an independent prognostic factor for CC. The GSEA analysis showed that several ferroptosis-related pathways were significantly enriched in the low-risk group. Immune infiltration analysis suggested that the level of immune cell infiltration was significantly higher in the high-risk group than that in the low-risk group. In summary, we established a prognostic model based on the ferroptosis-related lncRNAs, which could provide clinical guidance for future laboratory and clinical research on CC.
| S-EPMC9470855 | biostudies-literature
Project description:BackgroundColon cancer (CC) is a common gastrointestinal malignant tumor with high heterogeneity in clinical behavior and response to treatment, making individualized survival prediction challenging. Ferroptosis is a newly discovered iron-dependent cell death that plays a critical role in cancer biology. Therefore, identifying a prognostic biomarker with ferroptosis-related genes provides a new strategy to guide precise clinical decision-making in CC patients.MethodsAlteration in the expression profile of ferroptosis-related genes was initially screened in GSE39582 dataset involving 585 CC patients. Univariate Cox regression analysis and LASSO-penalized Cox regression analysis were combined to further identify a novel ferroptosis-related gene signature for overall survival prediction. The prognostic performance of the signature was validated in the GSE17536 dataset by Kaplan-Meier survival curve and time-dependent ROC curve analyses. Functional annotation of the signature was explored by integrating GO and KEGG enrichment analysis, GSEA analysis and ssGSEA analysis. Furthermore, an outcome risk nomogram was constructed considering both the gene signature and the clinicopathological features.ResultsThe prognostic signature biomarker composed of 9 ferroptosis-related genes accurately discriminated high-risk and low-risk patients with CC in both the training and validation datasets. The signature was tightly linked to clinicopathological features and possessed powerful predictive ability for distinct clinical subgroups. Furthermore, the risk score was confirmed to be an independent prognostic factor for CC patients by multivariate Cox regression analysis (p < 0.05). Functional annotation analyses showed that the prognostic signature was closely correlated with pivotal cancer hallmarks, particularly cell cycle, transcriptional regulation, and immune-related functions. Moreover, a nomogram with the signature was also built to quantify outcome risk for each patient.ConclusionThe novel ferroptosis-related gene signature biomarker can be utilized for predicting individualized prognosis, optimizing survival risk assessment and facilitating personalized management of CC patients.
| S-EPMC8280527 | biostudies-literature
Project description:BackgroundAutophagy is an evolutionally highly conserved process, accompanied by the dynamic changes of various molecules, which is necessary for the orderly degradation and recycling of cellular components. The aim of the study was to identify the role of autophagy-related (ATG) genes in the occurrence and development of gastric cancer (GC).MethodsData from Oncomine dataset was used for the differential expression analysis between cancer and normal tissues. The association of ATG genes expression with clinicopathologic indicators was evaluated by The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database. Moreover, using the TCGA datasets, the prognostic role of ATG genes was assessed. A nomogram was further built to assess the independent prognostic factors.ResultsThe expression of autophagy-related genes AMBRA1, ATG4B, ATG7, ATG10, ATG12, ATG16L2, GABARAPL2, GABARAPL1, ULK4 and WIPI2 showed differences between cancer and normal tissues. After verification, ATG14 and ATG4D were significantly associated with TNM stage. ATG9A, ATG2A, and ATG4D were associated with T stage. VMP1 and ATG4A were low-expressed in patients without lymph node metastasis. No gene in autophagy pathway was associated with M stage. Further multivariate analysis suggested that ATG4D and MAP1LC3C were independent prognostic factors for GC. The C-index of nomogram was 0.676 and the 95% CI was 0.628 to 0.724.ConclusionOur study provided a comprehensive illustration of ATG genes expression characteristics in GC. Abnormal expressions of the ubiquitin-like conjugated system in ATG genes plays a key role in the occurrence of GC. ATG8/LC3 sub-system may play an important role in development and clinical outcome of GC. In the future, it is necessary to further elucidate the alterations of specific ATG8/LC3 forms in order to provide insights for the discovery, diagnosis, or targeting for GC.
| S-EPMC7866901 | biostudies-literature
Project description:Background: Every year, nearly 170,000 people die from bladder cancer worldwide. A major problem after transurethral resection of bladder tumor is that 40-80% of the tumors recur. Ferroptosis is a type of regulatory necrosis mediated by iron-catalyzed, excessive oxidation of polyunsaturated fatty acids. Increasing the sensitivity of tumor cells to ferroptosis is a potential treatment option for cancer. Establishing a diagnostic and prognostic model based on ferroptosis-related genes may provide guidance for the precise treatment of bladder cancer. Methods: We downloaded mRNA data in Bladder Cancer from The Cancer Genome Atlas and analyzed differentially expressed genes based on and extract ferroptosis-related genes. We identified relevant pathways and annotate the functions of ferroptosis-related DEGs using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis and Gene Ontology functions. On the website of Search Tool for Retrieving Interacting Genes database (STRING), we downloaded the protein-protein interactions of DEGs, which were drawn by the Cytoscape software. Then the Cox regression analysis were performed so that the prognostic value of ferroptosis-related genes and survival time are combined to identify survival- and ferroptosis-related genes and establish a prognostic formula. Survival analysis and receiver operating characteristic curvevalidation were then performed. Risk curves and nomograms were generated for both groups to predict survival. Finally, RT-qPCR was applied to analyze gene expression. Results: Eight ferroptosis-related genes with prognostic value (ISCU, NFE2L2, MAFG, ZEB1, VDAC2, TXNIP, SCD, and JDP2) were identified. With clinical data, we established a prognostic model to provide promising diagnostic and prognostic information of bladder cancer based on the eight ferroptosis-related genes. RT-qPCR revealed the genes that were differentially expressed between normal and cancer tissues. Conclusion: This study found that the ferroptosis-related genes is associated with bladder cancer, which may serve as new target for the treatment of bladder cancer.
| S-EPMC8635965 | biostudies-literature
Project description:BackgroundThe incidence of colon adenocarcinoma (COAD) has been increasing over time. Although ferroptosis and long noncoding RNAs (lncRNAs) have been extensively reported to participate in the tumorigenesis and development of COAD, few studies have investigated the role of ferroptosis-related lncRNAs in the prognosis of COAD.MethodsGene-sequencing and clinical data for COAD were obtained from The Cancer Genome Atlas database. The coexpression network was constructed using known ferroptosis-related genes. Cox and least absolute shrinkage and selection operator regression were used to screen ferroptosis-related lncRNAs with prognostic value and to identify a predictive model of COAD. Patients with COAD were divided into low- and high-risk groups according to their risk score. Cases of COAD in the International Cancer Genome Consortium database were included as the testing cohort.ResultsIn total, nine lncRNAs (LINC02381, AC105219.1, AC009283.1, LINC01011, ELFN1-AS1, EIF3J-DT, NKILA, LINC01063, and SNHG16) were considered prognostic factors for COAD. Then, a risk score model was established. The overall survival rate of COAD patients was negatively associated with the risk score. Kaplan-Meier analyses in the original and testing cohorts showed similar results. The expression of the lncRNAs in tissue was consistent with the risk score, and the relationship with tumor mutation burden, immunity, and drug sensitivity presented a marked link between the signature and COAD. A nomogram was established for clinical applications.ConclusionsNine ferroptosis-related lncRNAs and the established signature have a certain predictive value for prognosis of COAD patients and can be used as potential research targets for exploring treatment of COAD.
| S-EPMC9012622 | biostudies-literature
Project description:Objectives: To establish a novel risk score model that could predict the survival and immune response of patients with colon cancer. Methods: We used The Cancer Genome Atlas (TCGA) database to get mRNA expression profile data, corresponding clinical information and somatic mutation data of patients with colon cancer. Limma R software package and univariate Cox regression were performed to screen out immune-related prognostic genes. GO (Gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) were used for gene function enrichment analysis. The risk scoring model was established by Lasso regression and multivariate Cox regression. CIBERSORT was conducted to estimate 22 types of tumor-infiltrating immune cells and immune cell functions in tumors. Correlation analysis was used to demonstrate the relationship between the risk score and immune escape potential. Results: 679 immune-related genes were selected from 7846 differentially expressed genes (DEGs). GO and KEGG analysis found that immune-related DEGs were mainly enriched in immune response, complement activation, cytokine-cytokine receptor interaction and so on. Finally, we established a 3 immune-related genes risk scoring model, which was the accurate independent predictor of overall survival (OS) in colon cancer. Correlation analysis indicated that there were significant differences in T cell exclusion potential in low-risk and high-risk groups. Conclusion: The immune-related gene risk scoring model could contribute to predicting the clinical outcome of patients with colon cancer.
| S-EPMC9800979 | biostudies-literature
Project description:ObjectiveThis study examined the mechanism through which plumbagin induces ferroptosis of colon cancer cells.MethodsCCK-8 assay was performed to examine the viability of colon cancer cells (SW480 and HCT116 cells) after they were treated with 0-, 5-, 10-, 15- and 20-μmol/L plumbagin. Colony formation assay and Transwell assay were used to examine the effects of 15-μmol/L plumbagin on the proliferation, invasive ability. The ferroptosis of SW480 and HCT116 cells and the expression of p-p53, p53 and SLC7A11 were analysed. The effects of blocking necrosis, apoptosis and ferroptosis on the anti-cancer effects of plumbagin were examined. After p53 was silenced, the effects of plumbagin on proliferation, invasion, ferroptosis and SLC7A11 expression were assessed. A tumour-bearing nude mouse model was used to examine the effects of p53 silencing and/or plumbagin on tumour growth, ferroptosis and SLC7A11 expression.ResultsPlumbagin inhibited the proliferation of SW480 and HCT116 cells and their invasive and colony-forming abilities. It increased Fe2+ levels but significantly decreased GSH and GPX4 levels. When ferroptosis was inhibited, the effects of plumbagin on colon cancer cells were significantly alleviated. Plumbagin promoted the expression and phosphorylation of p53 and inhibited the mRNA and protein levels of SLC7A11. Silencing of p53 counteracted the effects of plumbagin on the ferroptosis and biological behaviour of SW480 and HCT116 cells. In mouse models of colon cancer, silencing of p53 attenuated the tumour-suppressing effects of plumbagin as well as its inhibitory effects on the protein level of SLC7A11 and restored the expression of GSH and GPX4.ConclusionPlumbagin promotes ferroptosis and inhibits cell proliferation and invasion by decreasing the protein expression of SLC7A11 through p53.
| S-EPMC11002553 | biostudies-literature
Project description:Colon cancer is a common and leading cause of death and malignancy worldwide. N6-methylation of adenosine (m6A) is the most common reversible mRNA modification in eukaryotes, and it plays a crucial role in various biological functions in vivo. Dysregulated expression and genetic changes of m6A regulators have been correlated with tumorigenesis, cancer cell proliferation, tumor microenvironment, and prognosis in cancers. This study used RNA-seq and colon cancer clinical data to explore the relationship between N6-methylation and colon cancer. Based on the seven m6A regulators related to prognosis, three molecular subgroups of colon cancer were identified. Surprisingly, we found that each subgroup had unique survival characteristics. We then identified three subtypes of tumors based on 299 m6A phenotype-related genes, and one subtype was characterized as an immunosuppressive tumor and patients in this subtype may be more suitable for immunotherapy than other subtypes. Finally, using m6A-related genes and clinical information from The Cancer Genome Atlas cohort, we constructed a prognosis model, and this model could be used to predict the prognosis of patients in clinics.
| S-EPMC7926939 | biostudies-literature
Project description:Background The purpose of our study was to construct a prognostic model based on ferroptosis-related gene signature to improve the prognosis prediction of lung squamous carcinoma (LUSC). Methods The mRNA expression profiles and clinical data of LUSC patients were downloaded. LUSC-related essential differentially expressed genes were integrated for further analysis. Prognostic gene signatures were identified through random forest regression and univariate Cox regression analyses for constructing a prognostic model. Finally, in a preliminary experiment, we used the reverse transcription-quantitative polymerase chain reaction assay to verify the relationship between the expression of three prognostic gene features and ferroptosis. Results Fifty-six ferroptosis-related essential genes were identified by using integrated analysis. Among these, three prognostic gene signatures (HELLS, POLR2H, and POLE2) were identified, which were positively affected by LUSC prognosis but negatively affected by immune cell infiltration. Significant overexpression of immune checkpoint genes occurred in the high-risk group. In preliminary experiments, we confirmed that the occurrence of ferroptosis can reduce three prognostic gene signature expression. Conclusions The three ferroptosis-related genes could predict the LUSC prognostic risk of antitumor immunity.
| S-EPMC10615648 | biostudies-literature
Project description:Background: Colon cancer (CC) remains one of the most common malignancies with a poor prognosis. Pyroptosis, referred to as cellular inflammatory necrosis, is thought to influence tumor development. However, the potential effects of pyroptosis-related regulators (PRRs) on the CC immune microenvironment remain unknown. Methods: In this study, 27 PRRs reported in the previous study were used to cluster the 1,334 CC samples into three pyroptosis-related molecular patterns. Through subtype pattern differential analysis and structure network mining using Weighted Gene Co-expression Network Analysis (WGCNA), 854 signature genes associated with the PRRs were discovered. Further LASSO-penalized Cox regression of these genes established an eight-gene assessment model for predicting prognosis. Results: The CC patients were subtyped based on three distinct pyroptosis-related molecular patterns. These pyroptosis-related patterns were correlated with different clinical outcomes and immune cell infiltration characteristics in the tumor microenvironment. The pyroptosis-related eight-signature model was established and used to assess the prognosis of CC patients with medium-to-high accuracy by employing the risk scores, which was named "PRM-scores." Greater inflammatory cell infiltration was observed in tumors with low PRM-scores, indicating a potential benefit of immunotherapy in these patients. Conclusions: This study suggests that PRRs have a significant effect on the tumor immune microenvironment and tumor development. Evaluating the pyroptosis-related patterns and related models will promote our understanding of immune cell infiltration characteristics in the tumor microenvironment and provide a theoretical basis for future research targeting pyroptosis in cancer.
| S-EPMC8546261 | biostudies-literature