A novel DNA damage and repair-related gene signature to improve predictive capacity of overall survival for patients with gliomas.
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ABSTRACT:
SUBMITTER: Li X
PROVIDER: S-EPMC9258707 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: DNA damage repair (DDR) is an important mechanism for the occurrence and development of hepatocellular carcinoma (HCC), but its impact on prognosis has not been fully understood. Materials and methods: A total of 904 HCC patients were included in our study, TCGA (n = 370) and GSE14520 (n = 239) were merged into a large-sample training cohort (n = 609). The training cohort was clustered into C1 and C2 based on prognostic DDR-related genes, the differentially expressed genes (DEGs) between C1 and C2 were identified by the Wilcoxon signed-rank test referred to criteria (|log2FC|≥1 and FDR< 0.05). The univariate Cox analysis was used to screen the prognostic-related DEGs, and Lasso penalized Cox regression analysis was used to construct the risk score. The patients were clarified into high- and low-risk groups based on the median risk score. ICGC (n = 231) and GSE116174 (n = 64) cohorts were used for external validation of the risk score's prognostic value. Results: The Kaplan-Meier survival analysis showed that the high-risk group had a significantly reduced overall survival (OS) compared to the low-risk group in the three independent cohorts, and the time-dependent ROC curve showed that the five-gene (STMN1, PON1, PLOD2, MARCKSL1, and SPP1) risk score with a high accuracy in predicting OS. The patients with AFP >300 ng/ml, tumor poor differentiation (grade 3-4), micro and macro vascular tumor invasion, advanced stage (AJCC III-IV, BCLC stage B-C, and CLIP score >2) exhibited a higher risk score. Subgroup survival analysis found that the risk score was applicable to patients with different clinical characteristics. GO and KEGG functional enrichment analysis revealed that cell cycle, p53 signaling, TNF signaling-related pathways were upregulated in the high-risk group. The higher infiltration level of activated CD4 T cell, CD56 bright natural killer cell, plasmacytoid dendritic cell, and type 2 T helper cells were found to lead an unfavorable impact on the OS of HCC patients, and these four kinds of immune cells exhibited a higher infiltration level in the high-risk group. Conclusion: The five-gene risk score proposed in the research may provide new insights into the individualized evaluation of HCC prognosis.
| S-EPMC8811360 | biostudies-literature
Project description:XPC, a key protein in the nucleotide excision repair (NER) pathway, recognizes damaged DNA and initiates NER. Genetic variations in the XPC gene might be associated with altered DNA repair capacities (DRC). In this study, we genotyped three XPC polymorphisms, Ala499Val (C-->T), PAT (-/+) and Lys939Gln (A-->C), and measured the DNA damage/DRC by alkaline comet assay challenged by BPDE and gamma-radiation in 476 healthy subjects. We also evaluated the associations between DNA damage/DRC and genotypes of XPC polymorphisms. Compared with the XPC Lys939Gln homozygous wild type (AA) subjects, subjects with the variant alleles (AC and CC) had significantly higher DNA damages induced by BPDE (Median and 95% confidence interval [CI]: 3.16 (3.01-3.44) vs. 2.88 (2.51-3.05), P=0.01), and gamma-radiation (4.18 (3.94-4.44) vs. 3.71 (3.49-4.04), P=0.01). However, subjects with the variant alleles (CT and TT) of Ala499Val exhibited a 8.6% and 13.1% decrease in DNA damages induced by BPDE (P=0.05) and gamma-radiation (P=0.001), respectively. Significant correlations were found between genotypes and induced DNA damages in XPC Lys939Gln (For BPDE: R=0.12, P=0.01; for gamma-radiation: R=0.094, P=0.046) and Ala499Val (For BPDE: R=-0.11, P=0.03; for gamma-radiation: R=-0.16, P=0.0009). The haplotypes "T-A" (in the order of Ala499Val-PAT-Lys939Gln) was associated with the lowest DNA damages. Our results suggested that the DRC of host cells might be modulated by specific XPC polymorphisms.
| S-EPMC2254649 | biostudies-literature
Project description:Lower-grade gliomas (LGGs) have a good prognosis with a wide range of overall survival (OS) outcomes. An accurate prognostic system can better predict survival time. An RNA-Sequencing (RNA-seq) prognostic signature showed a better predictive power than clinical predictor models. A signature constructed using gene pairs can transcend changes from biological heterogeneity, technical biases, and different measurement platforms. RNA-seq coupled with corresponding clinical information were extracted from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Immune-related gene pairs (IRGPs) were used to establish a prognostic signature through univariate and multivariate Cox proportional hazards regression. Weighted gene co-expression network analysis (WGCNA) was used to evaluate module eigengenes correlating with immune cell infiltration and to construct gene co-expression networks. Samples in the training and testing cohorts were dichotomized into high- and low-risk groups. Risk score was identified as an independent predictor, and exhibited a closed relationship with prognosis. WGCNA presented a gene set that was positively correlated with age, WHO grade, isocitrate dehydrogenase (IDH) mutation status, 1p/19 codeletion, risk score, and immune cell infiltrations (CD4 T cells, B cells, dendritic cells, and macrophages). A nomogram comprising of age, WHO grade, 1p/19q codeletion, and three gene pairs (BIRC5|SSTR2, BMP2|TNFRSF12A, and NRG3|TGFB2) was established as a tool for predicting OS. The IPGPs signature, which is associated with immune cell infiltration, is a novel tailored tool for individual-level prediction.
| S-EPMC8111095 | biostudies-literature
Project description:ObjectiveThe efficacy of platinum-based chemotherapy (PtCh) for pancreatic cancer (PC) patients with DNA damage repair gene mutations (DDRm) compared to those without DDRm remains uncertain.MethodsAfter a thorough database searching in PubMed, Embase, and Web of Science, a total of 19 studies that met all the inclusion criteria were identified. The primary outcomes were overall survival (OS) and progression-free survival (PFS) for PC patients with DDRm versus those without DDRm after PtCh.ResultsPatients with advanced-stage PC who have DDRm tend to have longer OS compared to patients without DDRm, regardless of their exposure to PtCh (HR=0.63; I2 = 66%). Further analyses indicated that the effectiveness of PtCh for OS was modified by DDRm (HR=0.48; I2 = 59%). After the first- line PtCh (1L-PtCh), the PFS of advanced-stage PC with DDRm was also significantly improved (HR=0.41; I2 = 0%). For patients with resected PC, regardless of their exposure to PtCh, the OS for patients with DDRm was comparable to those without DDRm (HR=0.82; I2 = 71%). Specifically, for patients with resected PC harboring DDRm who received PtCh (HR=0.85; I2 = 65%) and for those after non-PtCh (HR=0.87; I2 = 0%), the presence of DDRm did not show a significant association with longer OS.Conclusion1L-PtCh treatment is correlated with favorable survival for advanced-stage PC patients with DDRm. For resected-stage PC harboring DDRm, adjuvant PtCh had limited effectiveness. The prognostic value of DDRm needs to be further verified by prospective randomized controlled trials.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42022302275.
| S-EPMC10634423 | biostudies-literature
Project description:BackgroundGastric cancer (GC) is believed to be one of the most common digestive tract malignant tumors. The prognosis of GC remains poor due to its high malignancy, high incidence of metastasis and relapse, and lack of effective treatment. The constant progress in bioinformatics and molecular biology techniques has given rise to the discovery of biomarkers with clinical value to predict the GC patients' prognosis. However, the use of a single gene biomarker can hardly achieve the satisfactory specificity and sensitivity. Therefore, it is urgent to identify novel genetic markers to forecast the prognosis of patients with GC.Materials and methodsIn our research, data mining was applied to perform expression profile analysis of mRNAs in the 443 GC patients from The Cancer Genome Atlas (TCGA) cohort. Genes associated with the overall survival (OS) of GC were identified using univariate analysis. The prognostic predictive value of the risk factors was determined using the Kaplan-Meier survival analysis and multivariate analysis. The risk scoring system was built in TCGA dataset and validated in an independent Gene Expression Omnibus (GEO) dataset comprising 300 GC patients. Based on the median of the risk score, GC patients were grouped into high-risk and low-risk groups.ResultsWe identified four genes (GMPPA, GPC3, NUP50, and VCAN) that were significantly correlated with GC patients' OS. The high-risk group showed poor prognosis, indicating that the risk score was an effective predictor for the prognosis of GC patients.ConclusionThe signature consisting of four glycolysis-related genes could be used to forecast the GC patients' prognosis.
| S-EPMC7982000 | biostudies-literature
Project description:AimsWe aimed to create a tumor recurrent-based prediction model to predict recurrence and survival in patients with low-grade glioma.MethodsThis study enrolled 291 patients (188 in the training group and 103 in the validation group) with clinicopathological information and transcriptome sequencing data. LASSO-COX algorithm was applied to shrink predictive factor size and build a predictive recurrent signature. GO, KEGG, and GSVA analyses were performed for function annotations of the recurrent signature. The calibration curves and C-Index were assessed to evaluate the nomogram's performance.ResultsThis study found that DNA repair functions of tumor cells were significantly enriched in recurrent low-grade gliomas. A predictive recurrent signature, built by the LASSO-COX algorithm, was significantly associated with overall survival and progression-free survival in low-grade gliomas. Moreover, function annotations analysis of the predictive recurrent signature exhibited that the signature was associated with DNA repair functions. The nomogram, combining the predictive recurrent signature and clinical prognostic predictors, showed powerful prognostic ability in the training and validation groups.ConclusionAn individualized prediction model was created to predict 1-, 2-, 3-, 5-, and 10-year survival and recurrent rate of patients with low-grade glioma, which may serve as a potential tool to guide postoperative individualized care.
| S-EPMC7816205 | biostudies-literature
Project description:Growing evidence suggests that immune-related genes (IRGs) and long non-coding RNAs (lncRNAs) can serve as prognostic markers of overall survival (OS) in patients with colon cancer. This study aimed to identify an immune-related lncRNA signature for the prospective assessment of prognosis in these patients. Gene expression and clinical data of colon cancer patients were downloaded from The Cancer Genome Atlas (TCGA). Immune-related lncRNAs were identified by a correlation analysis between IRGs and lncRNAs. In total, 447 samples were divided into a training cohort (224 samples) and a testing cohort (223 samples). Univariate, lasso and multivariate Cox regression analyses identified an immune-related nine-lncRNA signature closely related to OS in colon cancer patients in the training dataset. A risk score formula involving nine immune-related lncRNAs was developed to evaluate the prognostic value of the lncRNA signature in the training dataset. Colon cancer patients with a high risk score had poorer OS than those with a low risk score. A multivariate Cox regression analysis confirmed that the immune-related nine-lncRNA signature could be an independent prognostic factor in colon cancer patients. The results were further confirmed in the testing cohort and the entire TCGA cohort. Furthermore, a gene set enrichment analysis revealed several pathways with significant enrichment in the high- and low-risk groups that may be helpful in formulating clinical strategies and understanding the underlying mechanisms. Finally, a quantitative real-time polymerase chain reaction assay found that the nine lncRNAs were significantly differentially expressed in colon cancer cell lines. The results of this study indicate that this signature has important clinical implications for improving predictive outcomes and guiding individualized treatment in colon cancer patients. These lncRNAs could be potential biomarkers affecting the prognosis of colon cancer.
| S-EPMC7203495 | biostudies-literature
Project description:ImportanceBreast cancer (BC), a common malignant tumor, ranks first among cancers in terms of morbidity and mortality among female patients. Currently, identifying effective prognostic models has a significant association with the prediction of the overall survival of patients with BC and guidance of clinicians in early diagnosis and treatment.ObjectivesTo identify a potential DNA repair-related prognostic signature through a comprehensive evaluation and to further improve the accuracy of prediction of the overall survival of patients with BC.Design, setting, and participantsIn this prognostic study, conducted from October 9, 2019, to February 3, 2020, the gene expression profiles and clinical data of patients with BC were collected from The Cancer Genome Atlas database. This study consisted of a training set from The Cancer Genome Atlas database and 2 validation cohorts from the Gene Expression Omnibus, which included 1096 patients with BC. A prognostic signature based on 8 DNA repair-related genes (DRGs) was developed to predict overall survival among female patients with BC.Main outcomes and measuresPrimary screening prognostic biomarkers were analyzed using univariate Cox proportional hazards regression analysis and the least absolute shrinkage and selection operator Cox proportional hazards regression. A risk model was completely established through multivariate Cox proportional hazards regression analysis. Finally, a prognostic nomogram, combining the DRG signature and clinical characteristics of patients, was constructed. To examine the potential mechanisms of the DRGs, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed.ResultsIn this prognostic study based on samples from 1096 women with BC (mean [SD] age, 59.6 [13.1] years), 8 DRGs (MDC1, RPA3, MED17, DDB2, SFPQ, XRCC4, CYP19A1, and PARP3) were identified as prognostic biomarkers. The time-dependent receiver operating characteristic curve analysis suggested that the 8-gene signature had a good predictive accuracy. In the training cohort, the areas under the curve were 0.708 for 3-year survival and 0.704 for 5-year survival. In the validation cohort, the areas under the curve were 0.717 for 3-year survival and 0.772 for 5-year survival in the GSE9893 data set and 0.691 for 3-year survival and 0.718 for 5-year survival in the GSE42568 data set. This DRG signature mainly involved some regulation pathways of vascular endothelial cell proliferation.Conclusions and relevanceIn this study, a prognostic signature using 8 DRGs was developed that successfully predicted overall survival among female patients with BC. This risk model provides new clinical evidence for the diagnostic accuracy and targeted treatment of BC.
| S-EPMC7536586 | biostudies-literature
Project description:BackgroundLower-grade gliomas (LGGs) are less aggressive with a long overall survival (OS) time span. Because of individualized genomic features, a prognostic system incorporating molecular signatures can more accurately predict OS.MethodsDifferential expression analysis between LGGs and normal tissues was performed using the Gene Expression Omnibus (GEO) datasets (GSE4290 and GSE12657). Immune-related differentially expressed genes (ImmPort-DEGs) were analyzed for functional enrichment. The least absolute shrinkage and selection operator (LASSO) analysis was performed to develop an immune risk score signature (IRSS). We extracted information from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) to establish and validate the model. The relationship of model gene sets with immune infiltration was analyzed based on gene set variation analysis (GSVA) scores. Patients were divided into low- and high-risk groups based on the median score. The time-dependent receiver-operating characteristic (ROC) curve and the Kaplan-Meier curve were used to evaluate the model. Then, a precise prognostic nomogram was established, and its efficacy was verified.ResultsA total of 18 related immune genes were identified, building a 6-gene IRSS (BMP2, F2R, FGF13, PCSK1, PRKCB, and PTGER3). DEGs were enriched in T cell and NK cell regulatory pathways. Immune infiltration analysis confirmed that the gene signature correlated with a decrease in innate immune cells. In terms of model evaluation, ROC curves at 1, 3, and 5 years showed moderate predictive ability of IRSS (AUC = 0.930, 0.797, and 0.728). The Cox regression analysis revealed that IRSS was an independent prognostic factor, and the nomogram model had good predictive ability (C - index = 0.828). Meanwhile, the predictive power of IRSS was also confirmed in the training cohort. The Kaplan-Meier results showed that the prognosis of the high-risk group was significantly worse in all cohorts.ConclusionIRSS may serve as a novel survival prediction tool in the classification of LGG patients.
| S-EPMC8856808 | biostudies-literature
Project description:SALL4 is aberrantly expressed in human myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML). We have generated a SALL4 transgenic (SALL4B Tg) mouse model with pre-leukemic MDS-like symptoms that transform to AML over time. This makes our mouse model applicable for studying human MDS/AML diseases. Characterization of the leukemic initiation population in this model leads to the discovery that Fancl (Fanconi anemia, complementation group L) is downregulated in SALL4B Tg leukemic and pre-leukemic cells. Similar to the reported Fanconi anemia (FA) mouse model, chromosomal instability with radial changes can be detected in pre-leukemic SALL4B Tg bone marrow (BM) cells after DNA damage challenge. Results from additional studies using DNA damage repair reporter assays support a role of SALL4 in inhibiting the homologous recombination pathway. Intriguingly, unlike the FA mouse model, after DNA damage challenge, SALL4B Tg BM cells can survive and generate hematopoietic colonies. We further elucidated that the mechanism by which SALL4 promotes cell survival is through Bcl2 activation. Overall, our studies demonstrate for the first time that SALL4 has a negative impact in DNA damage repair, and support the model of dual functional properties of SALL4 in leukemogenesis through inhibiting DNA damage repair and promoting cell survival.
| S-EPMC5093088 | biostudies-literature