Dataset Information

The use of DNA repair genes as prognostic indicators of gastric cancer.

ABSTRACT: DNA repair genes can be used as prognostic biomarkers in many types of cancer. We aimed to identify prognostic DNA repair genes in patients with gastric cancer (GC) by systematically bioinformatic approaches using web-based database. Global gene expression profiles from altogether 1,325 GC patients' samples from six independent datasets were included in the study. Clustering analysis was performed to screen potentially abnormal DNA repair genes related to the prognosis of GC, followed by unsupervised clustering analysis to identify molecular subtypes of GC. Characteristics and prognosis differences were analyzed among these molecular subtypes, and modular key genes in molecular subtypes were identified based on changes in expression correlation. Multivariate Cox proportional hazard analysis was used to find the independent prognostic gene. Kaplan-Meier method and log-rank test was used to estimate correlations of key DNA repair genes with GC patients'overall survival. There were 57 key genes significantly associated to GC patients' prognosis, and patients were stratified into three molecular clusters based on their expression profiles, in which patients in Cluster 3 showed the best survival (P < 0.05). After a three-phase training, test and validation process, the expression profile of 13 independent key DNA repair genes were identified can classify the prognostic risk of patients. Compared with patients with low-risk score, patients with high risk score in the training set had shorter overall survival (P < 0.0001). Furthermore, we verified equivalent findings by these key DNA repair genes in the test set (P < 0.0001) and the independent validation set (P = 0.0024). Our results suggest a great potential for the use of DNA repair gene profiling as a powerful marker in prognostication and inform treatment decisions for GC patients.

SUBMITTER: Jinjia C

PROVIDER: S-EPMC6775511 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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The use of DNA repair genes as prognostic indicators of gastric cancer.

Jinjia Chang C Xiaoyu Wang W Hui Sun S Wenhua Li L Zhe Zhang Z Xiaodong Zhu Z Midie Xu X

Journal of Cancer 20190827 20

DNA repair genes can be used as prognostic biomarkers in many types of cancer. We aimed to identify prognostic DNA repair genes in patients with gastric cancer (GC) by systematically bioinformatic approaches using web-based database. Global gene expression profiles from altogether 1,325 GC patients' samples from six independent datasets were included in the study. Clustering analysis was performed to screen potentially abnormal DNA repair genes related to the prognosis of GC, followed by unsuper ...[more]

PMID: 31598158

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Project description:The aim of this study was to construct and validate a DNA repair-related gene signature for evaluating the overall survival (OS) of patients with gastric cancer (GC). Differentially expressed DNA repair genes between GC and normal gastric tissue samples obtained from the TCGA database were identified. Univariate Cox analysis was used to screen survival-related genes and multivariate Cox analysis was applied to construct a DNA repair-related gene signature. An integrated bioinformatics approach was performed to evaluate its diagnostic and prognostic value. The prognostic model and the expression levels of signature genes were validated using an independent external validation cohort. Two genes (CHAF1A, RMI1) were identified to establish the prognostic signature and patients ware stratified into high- and low-risk groups. Patients in high-risk group presented significant shorter survival time than patients in the low-risk group in both cohorts, which were verified by the ROC curves. Multivariate analysis showed that the prognostic signature was an independent predictor for patients with GC after adjustment for other known clinical parameters. A nomogram incorporating the signature and known clinical factors yielded better performance and net benefits in calibration plot and decision curve analyses. Further, the logistic regression classifier based on the two genes presented an excellent diagnostic power in differentiating early HCC and normal tissues with AUCs higher than 0.9. Moreover, Gene Set Enrichment Analysis revealed that diverse cancer-related pathways significantly clustered in the high-risk and low-risk groups. Immune cell infiltration analysis revealed that CHAF1A and RMI1 were correlated with several types of immune cell subtypes. A prognostic signature using CHAF1A and RMI1 was developed that effectively predicted different OS rates among patients with GC. This risk model provides new clinical evidence for the diagnostic accuracy and survival prediction of GC.

Project description:DNA repair mechanisms have been proven to be essential for cells, and abnormalities in DNA repair could cause various diseases, such as cancer. However, the diversity and complexity of DNA repair mechanisms obscure the functions of DNA repair in cancers. In addition, the relationships between DNA repair, the tumor mutational burden (TMB), and immune infiltration are still ambiguous. In the present study, we evaluated the prognostic values of various types of DNA repair mechanisms and found that double-strand break repair through single-strand annealing (SSA) and nonhomologous end-joining (NHEJ) was the most prognostic DNA repair processes in gastric cancer (GC) patients. Based on the activity of these two approaches and expression profiles, we constructed a HR-LR model, which could accurately divide patients into high-risk and low-risk groups with different probabilities of survival and recurrence. Similarly, we also constructed a cancer-normal model to estimate whether an individual had GC or normal health status. The prognostic value of the HR-LR model and the accuracy of the cancer-normal model were validated in several independent datasets. Notably, low-risk samples, which had higher SSA and NHEJ activities, had more somatic mutations and less immune infiltration. Furthermore, the analysis found that low-risk samples had higher and lower methylation levels in CpG islands (CGIs) and open sea regions respectively, and had higher expression levels of programmed death-ligand 1 (PD-L1) and lower methylation levels in the promoter of the gene encoding PD-L1. Moreover, low-risk samples were characterized primarily by higher levels of CD4+ memory T cells, CD8+ naive T cells, and CD8+ TEM cells than those in high-risk samples. Finally, we proposed a decision tree and nomogram to help predict the clinical outcome of an individual. These results provide an improved understanding of the complexity of DNA repair, the TMB, and immune infiltration in GC, and present an accurate prognostic model for use in GC patients.

Project description:Bladder cancer (BCa) is the tenth most common tumor in humans. DNA damage repair genes (DDRGs) play important roles in many malignant tumors; thus, their functions in BCa should also be explored. We performed a comprehensive analysis of the expression profiles of DDRGs in 410 BCa tumors and 19 normal tissues from The Cancer Genome Atlas database. We identified 123 DDRGs differentially expressed between BCa tumors and normal tissues, including 95 upregulated and 28 downregulated genes. We detected 22 DDRGs associated with overall survival (OS) of patients with BCa by performing univariate Cox regression analysis. To explore the interactions between OS-associated DDRGs, we constructed a PPI network, which showed that the top six DDRGs (CDCA2, FOXM1, PBK, RRM2, ORC1, and HDAC4) with the highest scores in the PPI network might play significant roles in OS of BCa. Moreover, to investigate the latent regulatory mechanism of these OS-associated DDRGs, we analyzed the transcription factors (TFs)-DDRGs regulatory network. The core seven TFs (NCAPG, DNMT1, LMNB1, BRCA1, E2H2, CENPA, and E2F7) were shown to be critical regulators of the OS-related DDRGs. The 22 DDRGs were incorporated into a stepwise multivariable Cox analysis. Then, we built the index of risk score based on the expression of 8 DDRGs (CAD, HDAC10, JDP2, LDLR, PDGFRA, POLA2, SREBF1, and STAT1). The p-value < 0.0001 in the Kaplan-Meier survival plot and an area under the ROC curve (AUC) of 0.771 in TCGA-BLCA training dataset suggested the high specificity and sensitivity of the prognostic index. Furthermore, we validated the risk score in the internal TCGA-BLCA and an independent GSE32894 dataset, with AUC of 0.743 and 0.827, respectively. More importantly, the multivariate Cox regression and stratification analysis demonstrated that the predictor was independent of various clinical parameters, including age, tumor stage, grade, and number of positive tumor lymph nodes. In summary, a panel of 8 DNA damage repair genes associated with overall survival in bladder cancer may be a useful prognostic tool.

Dataset Information

The use of DNA repair genes as prognostic indicators of gastric cancer.

Publications

The use of DNA repair genes as prognostic indicators of gastric cancer.

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