Dataset Information

M⁷G-Related DNA Damage Repair Genes are Potential Biomarkers for Predicting Prognosis and Immunotherapy Effectiveness in Colon Cancer Patients.

ABSTRACT: Objective: m⁷G is a post-transcriptional modification modality, however, limited research has been conducted on its role in colon cancer. DNA damage repair (DDR) is an important factor that contributes to colon cancer development, growth and chemoresistance. This study aimed to explore whether m⁷G-related DNA damage repair genes may be used as biomarkers to predict the prognosis of colon cancer patients. Methods: We use non-negative matrix factorization (NMF) to type CRC patients into. Risk models were constructed using different expression genes in two clusters. We assessed the reliability of risk models with DCA curves, and a Nomogram. Meanwhile, The receiver operating characteristic and C-index curves were used to compare the predictive significance of the constructed risk models with other studies. In additional, we examined the significance of risk models on patients' immunity microenvironment and response to immune therapy. Finally, we used a series of cellular experiments to validate the effect of model genes on the malignant progression of CRC cells. Results: Twenty-eight m⁷G genes were obtained from the GSEA database. Multivariate Cox and LASSO Cox regression analysis was performed and eleven m⁷G-related DDR genes were identified for constructing the risk model. Survival and stage of CRC patients were worser in the high-risk group than in the low-risk group for both the training and test sets. Additionally, the different immune microenvironment status of patients in the high- and low-risk groups, suggesting that patients in the low-risk group may be more sensitive to immunotherapy, particularly immune checkpoint inhibitors. Finally, we found that depletion of ATP2A1, one of the risk genes in our model, influence the biologic behaviour of CRC cells significantly. Conclusion: The m⁷G-related DDR genes can be used as important markers for predicting patient prognosis and immunotherapy response. Our data suggest that ATP2A1 may promote the proliferation of colon cancer cells. These findings may provide new therapeutic targets for the treatment of colon cancer.

SUBMITTER: Chen S

PROVIDER: S-EPMC9218807 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The DNA damage repair (DDR) pathway is one of the pathways of tumor pathogenesis, but its relationship with the immunophenotype has not been clarified in colon cancer (CC). We identified the differentially expressed immune-related genes (DEIRGs) between two DDR molecular subtypes, namely, C1 and C2, and used univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) penalized Cox regression analysis to construct the risk score in the training cohort [n=1,009, a combination of The Cancer Genome Atlas (TCGA) and GSE39582]. Regarding the median risk score as the unified cutoff to classify the patients into high- and low-risk groups. Two independent cohorts (GSE17538, n=232; GSE38832, n=122) were used for external validation of the prognostic value of the risk score. The IMvigor210 cohort (n=348) was used to test the predictive value of the risk score for immunotherapy response. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were performed to discover the underlying mechanism. Immune cell infiltration was quantified by the single sample gene set enrichment analysis (ssGSEA) algorithm. The high-risk group showed significantly reduced overall survival (OS), disease-specific survival (DSS), disease-free survival (DFS), progression-free survival (PFS), and relapse-free survival (RFS) compared to the low-risk group, and the two groups differed significantly in lymphatic invasion, American Joint Committee on Cancer (AJCC) TNM stage, preoperative carcinoembryonic antigen (CEA) level, etc. The enrichment levels of pathways related to colorectal cancer, epithelial-mesenchymal transition (EMT), angiogenesis, hypoxia, P53, TGF-β, KRAS signaling, etc., were upregulated in the high-risk group, but DDR-related pathways were defective in the high-risk group. The immunophenotypes of the high-risk group tended to be desert and excluded, and the risk score of patients who responded to immunotherapy was significantly lower than that of patients who did not respond to immunotherapy. The higher the infiltration levels of gamma delta T cells (γδ T cells), immature dendritic cells, and T follicular helper (Tfh) cells, the more significant adverse impact on the prognosis of CC patients was exhibited and an obviously positive correlation with the risk score was showed. An immune gene risk score associated with the DDR molecular subtype was built and verified herein; that is applicable to the prognosis and immunotherapy response prediction in CC.

Project description:Immune checkpoint inhibitors(ICIs) that activate tumor-specific immune responses bring new hope for the treatment of hepatocellular carcinoma(HCC). However, there are still some problems, such as uncertain curative effects and low objective response rates, which limit the curative effect of immunotherapy. Therefore, it is an urgent problem to guide the use of ICIs in HCC based on molecular typing. We downloaded the The Cancer Genome Atlas-Liver hepatocellular carcinoma(TCGA-LIHC) and Mongolian-LIHC cohort. Unsupervised clustering was applied to the highly variable data regarding expression of DNA damage repair(DDR). The CIBERSORT was used to evaluate the proportions of immune cells. The connectivity map(CMap) and pRRophetic algorithms were used to predict the drug sensitivity. There were significant differences in DDR molecular subclasses in HCC(DDR1 and DDR2), and DDR1 patients had low expression of DDR-related genes, while DDR2 patients had high expression of DDR-related genes. Of the patients who received traditional treatment, DDR2 patients had significantly worse overall survival(OS) than DDR1 patients. In contrast, of the patients who received ICIs, DDR2 patients had significantly prolonged OS compared with DDR1 patients. Of the patients who received traditional treatment, patients with high DDR scores had worse OS than those with low DDR scores. However, the survival of patients with high DDR scores after receiving ICIs was significantly higher than that of patients with low DDR scores. The DDR scores of patients in the DDR2 group were significantly higher than those of patients in the DDR1 group. The tumor microenvironment(TME) of DDR2 patients was highly infiltrated by activated immune cells, immune checkpoint molecules and proinflammatory molecules and antigen presentation-related molecules. In this study, HCC patients were divided into the DDR1 and DDR2 group. Moreover, DDR status may serve as a potential biomarker to predict opposite clinical prognosis immunotherapy and non-immunotherapy in HCC.

Project description:Background: Glioblastoma is a common malignant neuroepithelial neoplasm with poor clinical outcomes and limited treatment options. It is extremely important to search and confirm diverse hub genes that are effective in the advance and prediction of glioblastoma. Methods: We analyzed GSE50161, GSE4290, and GSE68848, the three microarray datasets retrieved from the GEO database. GO function and KEGG pathway enrichment analyses for differentially expressed genes (DEGs) were performed using DAVID. The PPI network of the DEGs was analyzed using the Search Tool for the Retrieval of Interacting Genes database and visualized by Cytoscape software. Hub genes were identified through the PPI network and a robust rank aggregation method. The Cancer Genome Atlas (TCGA) and the Oncomine database were used to validate the hub genes. In addition, a survival curve analysis was conducted to verify the correlation between the expression of hub genes and patient prognosis. Human glioblastoma cells and normal cells were collected, and then RT-PCR, Western blot, and immunofluorescence were conducted to validate the expression of the NDC80 gene. A cell proliferation assay was used to detect the proliferation of glioma cells. The effects of NDC80 expression on migration and invasion of GBM cell lines were evaluated by conducting scratch and transwell assays. Results: A total of 716 DEGs were common to all three microarray datasets, which included 188 upregulated DEGs and 528 downregulated DEGs. Furthermore, we found that among the common DEGs, 10 hub genes showed a high degree of connectivity. The expression of the 10 hub genes in TCGA and the Oncomine database was significantly overexpressed in glioblastoma compared with normal genes. Additionally, the survival analysis showed that the patients with low expression of six genes (BIR5C, CDC20, NDC80, CDK1, TOP2A, and MELK) had a significantly favorable prognosis (p < 0.01). We discovered that NDC80, which has been shown to be important in other cancers, also has an important role in malignant gliomas. The RT-PCR, Western blot, and immunofluorescence results showed that the expression level of NDC80 was significantly higher in human glioblastoma cells than in normal cells. Moreover, we identified that NDC80 increased the proliferation and invasion abilities of human glioblastoma cells. Conclusion: The six genes identified here may be utilized to form a panel of disease progression and predictive biomarkers of glioblastoma for clinical purposes. NDC80, one of the six genes, was discovered to have a potentially important role in GBM, a finding that needs to be further studied.

Project description:BackgroundLung squamous cell carcinoma (LUSC) is prone to metastasis and likely to develop resistance to chemotherapeutic drugs. DNA repair has been reported to be involved in the progression and chemoresistance of LUSC. However, the relationship between LUSC patient prognosis and DNA damage repair genes is still unclear.MethodsThe clinical information of LUSC patients and tumour gene expression level data were downloaded from the TCGA database. Unsupervised clustering and Cox regression were performed to obtain molecular subtypes and prognosis-related significant genes based on a list including 150 DNA damage repair genes downloaded from the GSEA database. The coefficients determined by the multivariate Cox regression analysis and the expression level of prognosis-related DNA damage repair genes were employed to calculate the risk score, which divided LUSC patients into two groups: the high-risk group and the low-risk group. Immune viability, overall survival, and anticarcinogen sensitivity analyses of the two groups of LUSC patients were performed by Kaplan-Meier analysis with the log rank test, ssGSEA and the pRRophetic package in R software. A time-dependent ROC curve was applied to compare the survival prediction ability of the risk score, which was used to construct a survival prediction model by multivariate Cox regression. The prediction model was used to build a nomogram, the discriminative ability of which was confirmed by C-index assessment, and its calibration was validated by calibration curve analysis. Differentially expressed DNA damage repair genes in LUSC patient tissues were retrieved by the Wilcoxon test and validated by qRT-PCR and IHC.ResultLUSC patients were separated into two clusters based on molecular subtypes, of which Cluster 2 was associated with worse overall survival. A prognostic prediction model for LUSC patients was constructed and validated, and a risk score calculated based on the expression levels of ten DNA damage repair genes was employed. The clinical utility was evaluated by drug sensitivity and immune filtration analyses. Thirteen-one genes were upregulated in LUSC patient samples, and we selected the top four genes that were validated by RT-PCR and IHC.ConclusionWe established a novel prognostic model based on DNA damage repair gene expression that can be used to predict therapeutic efficacy in LUSC patients.

Dataset Information

M⁷G-Related DNA Damage Repair Genes are Potential Biomarkers for Predicting Prognosis and Immunotherapy Effectiveness in Colon Cancer Patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

M7G-Related DNA Damage Repair Genes are Potential Biomarkers for Predicting Prognosis and Immunotherapy Effectiveness in Colon Cancer Patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

M⁷G-Related DNA Damage Repair Genes are Potential Biomarkers for Predicting Prognosis and Immunotherapy Effectiveness in Colon Cancer Patients.