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Yuan D, Zhu H, Wang T, Zhang Y, Zheng X, Qu Y. Development and validation of an individualized gene expression-based signature to predict overall survival of patients with high-grade serous ovarian carcinoma. Eur J Med Res 2023; 28:465. [PMID: 37884970 PMCID: PMC10604403 DOI: 10.1186/s40001-023-01376-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 09/18/2023] [Indexed: 10/28/2023] Open
Abstract
BACKGROUND High-grade serious ovarian carcinoma (HGSOC) is a subtype of ovarian cancer with a different prognosis attributable to genetic heterogeneity. The prognosis of patients with advanced HGSOC requires prediction by genetic markers. This study systematically analyzed gene expression profile data to establish a genetic marker for predicting HGSOC prognosis. METHODS The RNA-seq data set and information on clinical follow-up of HGSOC were retrieved from Gene Expression Omnibus (GEO) database, and the data were standardized by DESeq2 as a training set. On the other hand, HGSOC RNA sequence data and information on clinical follow-up were retrieved from The Cancer Genome Atlas (TCGA) as a test set. Additionally, ovarian cancer microarray data set was obtained from GEO as the external validation set. Prognostic genes were screened from the training set, and characteristic selection was performed using the least absolute shrinkage and selection operator (LASSO) with 80% re-sampling for 5000 times. Genes with a frequency of more than 2000 were selected as robust biomarkers. Finally, a gene-related prognostic model was validated in both the test and GEO validation sets. RESULTS A total of 148 genes were found to be significantly correlated with HGSOC prognosis. The expression profile of these genes could stratify HGSOC prognosis and they were enriched to multiple tumor-related regulatory pathways such as tyrosine metabolism and AMPK signaling pathway. AKR1B10 and ANGPT4 were obtained after 5000-time re-sampling by LASSO regression. AKR1B10 was associated with the metastasis and progression of several tumors. In this study, Cox regression analysis was performed to create a 2-gene signature as an independent prognostic factor for HGSOC, which has the ability to stratify risk samples in all three data sets (p < 0.05). The Gene Set Enrichment Analysis (GSEA) discovered abnormally active REGULATION_OF_AUTOPHAGY and OLFACTORY_TRANSDUCTION pathways in the high-risk group samples. CONCLUSION This study resulted in the creation of a 2-gene molecular prognostic classifier that distinguished clinical features and was a promising novel prognostic tool for assessing the prognosis of HGSOC. RiskScore was a novel prognostic model which might be effective in guiding accurate prognosis of HGSOC.
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Affiliation(s)
- Dandan Yuan
- Department of Obstertrics and Gynecology, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China
| | - Hong Zhu
- Department of Gynecological Oncology, Renji Hospital Affiliated to Medical College of Shanghai Jiaotong University, Shanghai, 200000, China
| | - Ting Wang
- Department of Hepatological Surgery, The Third Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Yang Zhang
- Department of Obstertrics and Gynecology, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China
| | - Xin Zheng
- Department of Gynecology, The First Hospital of Jiaxing City, Jiaxing, 314000, China
| | - Yanjun Qu
- Department of Obstertrics and Gynecology, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
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Seborova K, Hlavac V, Holy P, Bjørklund SS, Fleischer T, Rob L, Hruda M, Bouda J, Mrhalova M, Allah MMKAO, Vodicka P, Fiala O, Soucek P, Kristensen VN, Vodickova L, Vaclavikova R. Complex molecular profile of DNA repair genes in epithelial ovarian carcinoma patients with different sensitivity to platinum-based therapy. Front Oncol 2022; 12:1016958. [DOI: 10.3389/fonc.2022.1016958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 11/14/2022] [Indexed: 12/03/2022] Open
Abstract
Epithelial ovarian carcinoma (EOC) is known for high mortality due to diagnosis at advanced stages and frequent therapy resistance. Previous findings suggested that the DNA repair system is involved in the therapeutic response of cancer patients and DNA repair genes are promising targets for novel therapies. This study aimed to address complex inter-relations among gene expression levels, methylation profiles, and somatic mutations in DNA repair genes and EOC prognosis and therapy resistance status. We found significant associations of DUT expression with the presence of peritoneal metastases in EOC patients. The high-grade serous EOC subtype was enriched with TP53 mutations compared to other subtypes. Furthermore, somatic mutations in XPC and PRKDC were significantly associated with worse overall survival of EOC patients, and higher FAAP20 expression in platinum-resistant than platinum-sensitive patients was observed. We found higher methylation of RAD50 in platinum-resistant than in platinum-sensitive patients. Somatic mutations in BRCA1 and RAD9A were significantly associated with higher RBBP8 methylation in platinum-sensitive compared to platinum-resistant EOC patients. In conclusion, we discovered associations of several candidate genes from the DNA repair pathway with the prognosis and platinum resistance status of EOC patients, which deserve further validation as potential predictive biomarkers.
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Fang Y, Zhao J, Guo X, Dai Y, Zhang H, Yin F, Zhang X, Sun C, Han Z, Wang H, Han Y. Establishment, immunological analysis, and drug prediction of a prognostic signature of ovarian cancer related to histone acetylation. Front Pharmacol 2022; 13:947252. [PMID: 36172179 PMCID: PMC9510621 DOI: 10.3389/fphar.2022.947252] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 07/26/2022] [Indexed: 11/17/2022] Open
Abstract
In recent years, epigenetic modifications have been increasingly regarded as an important hallmark of cancer. Histone acetylation, as an important part of epigenetic modification, plays a key role in the progress, treatment, and prognosis of many cancers. In this study, based on the TCGA database, we performed LASSO regression and the Cox algorithm to establish a prognostic signature of ovarian cancer associated with histone acetylation modulator genes and verified it externally in the GEO database. Subsequently, we performed an immunological bioinformatics analysis of the model from multiple perspectives using the CIBERSORT algorithm, ESTIMATE algorithm, and TIDE algorithm to verify the accuracy of the model. Based on the prognostic model, we divided ovarian cancer patients into high-risk and low-risk groups, and assessed survival and the efficacy of accepting immunosuppressive therapy. In addition, based on the analysis of characteristics of the model, we also screened targeted drugs for high-risk patients and predicted potential drugs that inhibit platinum resistance through the connectivity map method. We ultimately constructed a histone acetylation modulator-related signature containing 10 histone acetylation modulators, among which HDAC1, HDAC10, and KAT7 can act as independent prognostic factors for ovarian cancer and are related to poor prognosis. In the analysis of the tumor microenvironment, the proportion of the B-infiltrating cells and the macrophages was significantly different between the high- and low-risk groups. Also, the samples with high-risk scores had higher tumor purity and lower immune scores. In terms of treatment, patients in the high-risk group who received immunotherapy had a higher likelihood of immune escape or rejection and were less likely to respond to platinum/paclitaxel therapy. Finally, we screened 20 potential drugs that could target the model for reference.
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Affiliation(s)
- Yujie Fang
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China
| | - Jing Zhao
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China
| | - Xu Guo
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China
| | - Yunfeng Dai
- Department of Radiotherapy, Yingkou Central Hospital, Yingkou, China
| | - Hao Zhang
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China
| | - Fanxin Yin
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China
| | - Xiaoxu Zhang
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China
| | - Chenxi Sun
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China
| | - Zequan Han
- Department of Pathology, Yingkou Fangda Hospital, Yingkou, China
| | - Hecheng Wang
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China
- *Correspondence: Yanshuo Han, ;, Hecheng Wang,
| | - Yanshuo Han
- School of Life and Pharmaceutical Sciences, Dalian University of Technology, Dalian, China
- *Correspondence: Yanshuo Han, ;, Hecheng Wang,
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4
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Integration of Transcriptome and Epigenome to Identify and Develop Prognostic Markers for Ovarian Cancer. JOURNAL OF ONCOLOGY 2022; 2022:3744466. [PMID: 36081667 PMCID: PMC9448543 DOI: 10.1155/2022/3744466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 06/04/2022] [Accepted: 06/29/2022] [Indexed: 11/21/2022]
Abstract
DNA methylation is a widely researched epigenetic modification. It is associated with the occurrence and development of cancer and has helped evaluate patients' prognoses. However, most existing DNA methylation prognosis models have not simultaneously considered the changes of the downstream transcriptome. Methods. The RNA-Sequencing data and DNA methylation omics data of ovarian cancer patients were downloaded from The Cancer Genome Atlas (TCGA) database. The Consensus Cluster Plus algorithm was used to construct the methylated molecular subtypes of the ovary. Lasso regression was employed to build a multi-gene signature. An independent data set was applied to verify the prognostic value of the signature. The Gene Set Variation Analysis (GSVA) was used to carry out the enrichment analysis of the pathways linked to the gene signature. The IMvigor 210 cohort was used to explore the predictive efficacy of the gene signature for immunotherapy response. Results. We distinguished ovarian cancer samples into two subtypes with different prognosis, based on the omics data of DNA methylation. Differentially expressed genes and enrichment analysis among subtypes indicated that DNA methylation was related to fatty acid metabolism and the extracellular matrix (ECM)-receptor. Furthermore, we constructed an 8-gene signature, which proved to be efficient and stable in predicting prognostics in ovarian cancer patients with different data sets and distinctive pathological characteristics. Finally, the 8-gene signature could predict patients' responses to immunotherapy. The polymerase chain reaction experiment was further used to verify the expression of 8 genes. Conclusion. We analyzed the prognostic value of the related genes of methylation in ovarian cancer. The 8-gene signature predicted the prognosis and immunotherapy response of ovarian cancer patients well and is expected to be valuable in clinical application.
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Wang X, Huang Z, Li L, Wang G, Dong L, Li Q, Yuan J, Li Y. DNA damage repair gene signature model for predicting prognosis and chemotherapy outcomes in lung squamous cell carcinoma. BMC Cancer 2022; 22:866. [PMID: 35941578 PMCID: PMC9361681 DOI: 10.1186/s12885-022-09954-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 07/29/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Lung 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. METHODS The 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. RESULT LUSC 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. CONCLUSION We established a novel prognostic model based on DNA damage repair gene expression that can be used to predict therapeutic efficacy in LUSC patients.
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Affiliation(s)
- Xinshu Wang
- Jinzhou Medical University, Shanghai East Hospital, 200120, Shanghai, China
| | - Zhiyuan Huang
- Research Center for Translational Medicine, East Hospital, Tongji University School of Medicine, Shanghai, 200120, China
| | - Lei Li
- Research Center for Translational Medicine, East Hospital, Tongji University School of Medicine, Shanghai, 200120, China
| | - Guangxue Wang
- Research Center for Translational Medicine, East Hospital, Tongji University School of Medicine, Shanghai, 200120, China
| | - Lin Dong
- Research Center for Translational Medicine, East Hospital, Tongji University School of Medicine, Shanghai, 200120, China.,Department of Cardiothoracic Surgery, East Hospital, Tongji University School of Medicine, Shanghai, 200120, China
| | - Qinchuan Li
- Research Center for Translational Medicine, East Hospital, Tongji University School of Medicine, Shanghai, 200120, China.,Department of Cardiothoracic Surgery, East Hospital, Tongji University School of Medicine, Shanghai, 200120, China
| | - Jian Yuan
- Research Center for Translational Medicine, East Hospital, Tongji University School of Medicine, Shanghai, 200120, China. .,Department of Biochemistry and Molecular Biology, Tongji University School of Medicine, Shanghai, 200120, China. .,Ji'an Hospital, Shanghai East Hospital, Ji'an, 343000, China.
| | - Yunhui Li
- Research Center for Translational Medicine, East Hospital, Tongji University School of Medicine, Shanghai, 200120, China.
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Zhao Y, Qing B, Xu C, Zhao J, Liao Y, Cui P, Wang G, Cai S, Song Y, Cao L, Duan J. DNA Damage Response Gene-Based Subtypes Associated With Clinical Outcomes in Early-Stage Lung Adenocarcinoma. Front Mol Biosci 2022; 9:901829. [PMID: 35813819 PMCID: PMC9257065 DOI: 10.3389/fmolb.2022.901829] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 05/11/2022] [Indexed: 12/04/2022] Open
Abstract
DNA damage response (DDR) pathways play a crucial role in lung cancer. In this retrospective analysis, we aimed to develop a prognostic model and molecular subtype based on the expression profiles of DDR-related genes in early-stage lung adenocarcinoma (LUAD). A total of 1,785 lung adenocarcinoma samples from one RNA-seq dataset of The Cancer Genome Atlas (TCGA) and six microarray datasets of Gene Expression Omnibus (GEO) were included in the analysis. In the TCGA dataset, a DNA damage response gene (DRG)–based signature consisting of 16 genes was constructed to predict the clinical outcomes of LUAD patients. Patients in the low-DRG score group had better outcomes and lower genomic instability. Then, the same 16 genes were used to develop DRG-based molecular subtypes in the TCGA dataset to stratify early-stage LUAD into two subtypes (DRG1 and DRG2) which had significant differences in clinical outcomes. The Kappa test showed good consistency between molecular subtype and DRG (K = 0.61, p < 0.001). The DRG subtypes were significantly associated with prognosis in the six GEO datasets (pooled estimates of hazard ratio, OS: 0.48 (0.41–0.57), p < 0.01; DFS: 0.50 (0.41–0.62), p < 0.01). Furthermore, patients in the DRG2 group benefited more from adjuvant therapy than standard-of-care, which was not observed in the DRG1 group. In summary, we constructed a DRG-based molecular subtype that had the potential to predict the prognosis of early-stage LUAD and guide the selection of adjuvant therapy for early-stage LUAD patients.
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Affiliation(s)
- Yang Zhao
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Bei Qing
- Department of Thoracic Surgery, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Chunwei Xu
- Department of Respiratory Medicine, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
- *Correspondence: Liming Cao, ; Jianchun Duan,
| | - Jing Zhao
- Burning Rock Biotech, Guangzhou, China
| | | | - Peng Cui
- Burning Rock Biotech, Guangzhou, China
| | | | | | - Yong Song
- Department of Respiratory Medicine, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Liming Cao
- Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, China
- *Correspondence: Liming Cao, ; Jianchun Duan,
| | - Jianchun Duan
- CAMS Key Laboratory of Translational Research on Lung Cancer, State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences Peking Union Medical College, Beijing, China
- *Correspondence: Liming Cao, ; Jianchun Duan,
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7
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Song D, Zhang D, Chen S, Wu J, Hao Q, Zhao L, Ren H, Du N. Identification and validation of prognosis-associated DNA repair gene signatures in colorectal cancer. Sci Rep 2022; 12:6946. [PMID: 35484177 PMCID: PMC9050689 DOI: 10.1038/s41598-022-10561-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 04/04/2022] [Indexed: 12/24/2022] Open
Abstract
Colorectal cancer (CRC) is the third most common malignant tumor. DNA damage plays a crucial role in tumorigenesis, and abnormal DNA repair pathways affect the occurrence and progression of CRC. In the current study, we aimed to construct a DNA repair-related gene (DRG) signature to predict the overall survival (OS) of patients with CRC patients. The differentially expressed DRGs (DE-DRGs) were analyzed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The prognostic gene signature was identified by univariate Cox regression and least absolute shrinkage and selection operator (LASSO)-penalized Cox proportional hazards regression analysis. The predictive ability of the model was evaluated using the Kaplan–Meier curves and time-dependent receiver operating characteristic (ROC) curves. The gene set enrichment analysis (GSEA) was performed to explore the underlying biological processes and signaling pathways. ESTIMATE and CIBERSORT were implemented to estimate the tumor immune score and immune cell infiltration status between the different risk group. The half-maximal inhibitory concentration (IC50) was evaluated to representing the drug response of this signature. Nine DE-DRGs (ESCO2, AXIN2, PLK1, CDC25C, IGF1, TREX2, ALKBH2, ESR1 and MC1R) signatures was constructed to classify patients into high- and low-risk groups. The risk score was an independent prognostic indicator of OS (hazard ratio > 1, P < 0.001). The genetic alteration analysis indicated that the nine DE-DRGs in the signature were changed in 63 required samples (100%), and the major alteration was missense mutation. Function enrichment analysis revealed that the immune response and mtotic sister chromatid segregation were the main biological processes. The high-risk group had higher immune score than the low-risk group. What’s more, low-risk patients were more sensitive to selumetinib and dasatinib. The nine DE-DRGs signature was significantly associated with OS and provided a new insight for the diagnosis and treatment of CRC.
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Affiliation(s)
- Dingli Song
- Department of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Dai Zhang
- Department of Oncology, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Sisi Chen
- Department of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Jie Wu
- Department of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China
| | - Qian Hao
- Department of Oncology, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Lili Zhao
- Department of Neurology, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Hong Ren
- Department of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
| | - Ning Du
- Department of Thoracic Surgery, The First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
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8
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Shen W, Jiang W, Ye S, Sun M, Yang H, Shan B. Identification of epigenetic genes for predicting prognosis and immunotherapy response of ovarian cancer. Jpn J Clin Oncol 2022; 52:742-751. [PMID: 35435215 DOI: 10.1093/jjco/hyac051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 03/23/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Epigenetic factors play a critical role in tumour development and progression. The aim of this study was to construct and validate a robust epigenetic gene set-based signature for predicting prognosis of ovarian cancer. METHODS By using LASSO Cox regression model, we screened out the most useful prognostic epigenetic factors and a prognostic signature was developed based on them. Survival receiver operating characteristic was used to test the prognostic accuracy of signature in training and validation sets. The associations between the risk scores and immune cell infiltration, tumour purity, immune checkpoint inhibitor genes expression were also assessed in ovarian cancer . RESULTS A total of 26 epigenetic factors were identified to develop the prognostic signature. In the training set, the prognosis of high-risk patients was strikingly poorer than that of low-risk patients (hazard ratio: 2.11, 95% confidence interval: 1.65-2.72, P < 0.001). Similar results were further observed in the internal validation set (hazard ratio: 1.69, 95% confidence interval: 1.07-2.63, P = 0.020) and external validation set (hazard ratio:1.95, 95% confidence interval: 1.41-2.69; P < 0.001). Survival receiver operating characteristic at 5 year showed the epigenetic signature (area under the curve = 0.700) performed better than other clinical features in predicting prognosis. Distinct difference in immune activation related pathways, immune cells infiltration, tumour purity reflected by immune and stromal score and immune checkpoint inhibitor genes gene expression was observed between high- and low-risk samples. CONCLUSIONS This study constructed an epigenetic signature that was capable of predicting postoperative outcomes and may also serve as potential biomarker for immunotherapy responses for ovarian cancer.
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Affiliation(s)
- Wenbin Shen
- Department of Gynecologic Oncology, Fudan Univeristy Shanghai Cancer Center, Shanghai.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Wei Jiang
- Department of Gynecologic Oncology, Fudan Univeristy Shanghai Cancer Center, Shanghai.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Shuang Ye
- Department of Gynecologic Oncology, Fudan Univeristy Shanghai Cancer Center, Shanghai.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Min Sun
- Department of Gynecologic Oncology, Fudan Univeristy Shanghai Cancer Center, Shanghai.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Huijuan Yang
- Department of Gynecologic Oncology, Fudan Univeristy Shanghai Cancer Center, Shanghai.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
| | - Boer Shan
- Department of Gynecologic Oncology, Fudan Univeristy Shanghai Cancer Center, Shanghai.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People's Republic of China
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9
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Bermúdez-Guzmán L. Pan-cancer analysis of non-oncogene addiction to DNA repair. Sci Rep 2021; 11:23264. [PMID: 34853396 PMCID: PMC8636604 DOI: 10.1038/s41598-021-02773-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 11/23/2021] [Indexed: 12/26/2022] Open
Abstract
Cancer cells usually depend on the aberrant function of one or few driver genes to initiate and promote their malignancy, an attribute known as oncogene addiction. However, cancer cells might become dependent on the normal cellular functions of certain genes that are not oncogenes but ensure cell survival (non-oncogene addiction). The downregulation or silencing of DNA repair genes and the consequent genetic and epigenetic instability is key to promote malignancy, but the activation of the DNA-damage response (DDR) has been shown to become a type of non-oncogene addiction that critically supports tumour survival. In the present study, a systematic evaluation of DNA repair addiction at the pan-cancer level was performed using data derived from The Cancer Dependency Map and The Cancer Genome Atlas (TCGA). From 241 DDR genes, 59 were identified as commonly essential in cancer cell lines. However, large differences were observed in terms of dependency scores in 423 cell lines and transcriptomic alterations across 18 cancer types. Among these 59 commonly essential genes, 14 genes were exclusively associated with better overall patient survival and 19 with worse overall survival. Notably, a specific molecular signature among the latter, characterized by DDR genes like UBE2T, RFC4, POLQ, BRIP1, and H2AFX showing the weakest dependency scores, but significant upregulation was strongly associated with worse survival. The present study supports the existence and importance of non-oncogenic addiction to DNA repair in cancer and may facilitate the identification of prognostic biomarkers and therapeutic opportunities.
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Affiliation(s)
- Luis Bermúdez-Guzmán
- Robotic Radiosurgery Center, International Cancer Center, San José, Costa Rica. .,Section of Genetics and Biotechnology, School of Biology, University of Costa Rica, San Pedro, San José, Costa Rica.
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10
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Zhang D, Li Y, Yang S, Wang M, Yao J, Zheng Y, Deng Y, Li N, Wei B, Wu Y, Zhai Z, Dai Z, Kang H. Identification of a glycolysis-related gene signature for survival prediction of ovarian cancer patients. Cancer Med 2021; 10:8222-8237. [PMID: 34609082 PMCID: PMC8607265 DOI: 10.1002/cam4.4317] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Revised: 08/22/2021] [Accepted: 08/31/2021] [Indexed: 12/17/2022] Open
Abstract
Background Ovarian cancer (OV) is deemed the most lethal gynecological cancer in women. The aim of this study was to construct an effective gene prognostic model for predicting overall survival (OS) in patients with OV. Methods The expression profiles of glycolysis‐related genes (GRGs) and clinical data of patients with OV were extracted from The Cancer Genome Atlas (TCGA) database. Univariate, multivariate, and least absolute shrinkage and selection operator Cox regression analyses were conducted, and a prognostic signature based on GRGs was constructed. The predictive ability of the signature was analyzed using training and test sets. Results A gene risk signature based on nine GRGs (ISG20, CITED2, PYGB, IRS2, ANGPTL4, TGFBI, LHX9, PC, and DDIT4) was identified to predict the survival outcome of patients with OV. The signature showed a good prognostic ability for OV, particularly high‐grade OV, in the TCGA dataset, with areas under the curve (AUC) of 0.709 and 0.762 for 3‐ and 5‐year survival, respectively. Similar results were found in the test sets, and the AUCs of 3‐, 5‐year OS were 0.714 and 0.772 in the combined test set. And our signature was an independent prognostic factor. Moreover, a nomogram combining the prediction model and clinical factors was developed. Conclusion Our study established a nine‐GRG risk model and nomogram to better predict OS in patients with OV. The risk model represents a promising and independent prognostic predictor for patients with OV. Moreover, our study on GRGs could offer guidance for the elucidation of underlying mechanisms in future studies.
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Affiliation(s)
- Dai Zhang
- Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Department of Thyroid, Breast and Vascular Surgery, Xijing Hospital, The Air Force Medical University, Xi'an, China
| | - Yiche Li
- Department of Tumor Surgery, Shaanxi Provincial People's Hospital, Xi'an, China
| | - Si Yang
- Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Meng Wang
- Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jia Yao
- Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Yi Zheng
- Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yujiao Deng
- Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Na Li
- Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Bajin Wei
- Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Ying Wu
- Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Zhen Zhai
- Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Zhijun Dai
- Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Huafeng Kang
- Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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11
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Chen S, Liu W, Huang Y. Identification and external validation of a prognostic signature associated with DNA repair genes in gastric cancer. Sci Rep 2021; 11:7141. [PMID: 33785812 PMCID: PMC8010105 DOI: 10.1038/s41598-021-86504-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 03/15/2021] [Indexed: 12/24/2022] Open
Abstract
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.
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Affiliation(s)
- Shimin Chen
- Department of Gastroenterology, Traditional Chinese Medical Hospital of Taihe Country, No 59, Tuanjie West Road, Taihe County, Fuyang, 236600, Anhui Province, China
| | - Wenbo Liu
- Department of Gastroenterology, Traditional Chinese Medical Hospital of Taihe Country, No 59, Tuanjie West Road, Taihe County, Fuyang, 236600, Anhui Province, China
| | - Yu Huang
- Department of Gastroenterology, Traditional Chinese Medical Hospital of Taihe Country, No 59, Tuanjie West Road, Taihe County, Fuyang, 236600, Anhui Province, China.
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12
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Li H, Wu N, Liu ZY, Chen YC, Cheng Q, Wang J. Development of a novel transcription factors-related prognostic signature for serous ovarian cancer. Sci Rep 2021; 11:7207. [PMID: 33785763 PMCID: PMC8010122 DOI: 10.1038/s41598-021-86294-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 03/12/2021] [Indexed: 12/20/2022] Open
Abstract
Growing evidence suggest that transcription factors (TFs) play vital roles in serous ovarian cancer (SOC). In the present study, TFs mRNA expression profiles of 564 SOC subjects in the TCGA database, and 70 SOC subjects in the GEO database were screened. A 17-TFs related prognostic signature was constructed using lasso cox regression and validated in the TCGA and GEO cohorts. Consensus clustering analysis was applied to establish a cluster model. The 17-TFs related prognostic signature, risk score and cluster models were effective at accurately distinguishing the overall survival of SOC. Analysis of genomic alterations were used to elaborate on the association between the 17-TFs related prognostic signature and genomic aberrations. The GSEA assay results suggested that there was a significant difference in the inflammatory and immune response pathways between the high-risk and low-risk score groups. The potential immune infiltration, immunotherapy, and chemotherapy responses were analyzed due to the significant difference in the regulation of lymphocyte migration and T cell-mediated cytotoxicity between the two groups. The results indicated that patients with low-risk score were more likely to respond anti-PD-1, etoposide, paclitaxel, and veliparib but not to gemcitabine, doxorubicin, docetaxel, and cisplatin. Also, the prognostic nomogram model revealed that the risk score was a good prognostic indicator for SOC patients. In conclusion, we explored the prognostic values of TFs in SOC and developed a 17-TFs related prognostic signature to predict the survival of SOC patients.
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Affiliation(s)
- He Li
- The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha, Changsha, 410008, Hunan, People's Republic of China
| | - Nayiyuan Wu
- The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha, Changsha, 410008, Hunan, People's Republic of China
| | - Zhao-Yi Liu
- The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha, Changsha, 410008, Hunan, People's Republic of China
| | - Yong-Chang Chen
- The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha, Changsha, 410008, Hunan, People's Republic of China
| | - Quan Cheng
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.
| | - Jing Wang
- The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha, Changsha, 410008, Hunan, People's Republic of China.
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13
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Long G, Ouyang W, Zhang Y, Sun G, Gan J, Hu Z, Li H. Identification of a DNA Repair Gene Signature and Establishment of a Prognostic Nomogram Predicting Biochemical-Recurrence-Free Survival of Prostate Cancer. Front Mol Biosci 2021; 8:608369. [PMID: 33778002 PMCID: PMC7991107 DOI: 10.3389/fmolb.2021.608369] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 01/27/2021] [Indexed: 12/13/2022] Open
Abstract
Background: The incidence of prostate cancer (PCa) is high and increasing worldwide. The prognosis of PCa is relatively good, but it is important to identify the patients with a high risk of biochemical recurrence (BCR) so that additional treatment could be applied. Method: Level 3 mRNA expression and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) to serve as training data. The GSE84042 dataset was used as a validation set. Univariate Cox, lasso Cox, and stepwise multivariate Cox regression were applied to identify a DNA repair gene (DRG) signature. The performance of the DRG signature was assessed based on Kaplan–Meier curve, receiver operating characteristic (ROC), and Harrell’s concordance index (C-index). Furtherly, a prognostic nomogram was established and evaluated likewise. Results: A novel four DRG signature was established to predict BCR of PCa, which included POLM, NUDT15, AEN, and HELQ. The ROC and C index presented good performance in both training dataset and validation dataset. The patients were stratified by the signature into high- and low-risk groups with distinct BCR survival. Multivariate Cox analysis revealed that the DRG signature is an independent prognostic factor for PCa. Also, the DRG signature high-risk was related to a higher homologous recombination deficiency (HRD) score. The nomogram, incorporating the DRG signature and clinicopathological parameters, was able to predict the BCR with high efficiency and showed superior performance compared to models that consisted of only clinicopathological parameters. Conclusion: Our study identified a DRG signature and established a prognostic nomogram, which were reliable in predicting the BCR of PCa. This model could help with individualized treatment and medical decision making.
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Affiliation(s)
- Gongwei Long
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wei Ouyang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yucong Zhang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Guoliang Sun
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiahua Gan
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhiquan Hu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Heng Li
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,Hubei Institute of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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14
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A Risk Signature with Nine Stemness Index-Associated Genes for Predicting Survival of Patients with Uterine Corpus Endometrial Carcinoma. JOURNAL OF ONCOLOGY 2021; 2021:6653247. [PMID: 33747079 PMCID: PMC7960070 DOI: 10.1155/2021/6653247] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 01/24/2021] [Accepted: 02/04/2021] [Indexed: 12/23/2022]
Abstract
Purpose To identify mRNA expression-based stemness index- (mRNAsi-) related genes and build an mRNAsi-related risk signature for endometrial cancer. Methods We collected mRNAsi data of endometrial cancer samples from The Cancer Genome Atlas (TCGA) and analyzed their relationship with the main clinicopathological characteristics and prognosis of endometrial cancer patients. We screened the top 50% of the genes in TCGA for weighted gene correlation network analysis (WGCNA) to explore mRNAsi-related gene sets. Among these mRNAsi-related genes, we further screened for those related to the prognosis of endometrial cancer patients via univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Using stepwise multivariate Cox regression analysis, a stemness index-related risk signature was constructed. Finally, we identified potential prognostic biomarkers for endometrial cancer by combining the GEO database and immunohistochemical staining. Results The mRNAsi of endometrial cancer samples was significantly higher than that of normal samples and was related to the International Federation of Gynecology and Obstetrics (FIGO) stage, pathological grade, postoperative tumor status, and overall survival of endometrial cancer patients. We identified 21 mRNAsi-related gene modules, and 1,324 genes were obtained from the most relevant module. TCGA samples were divided into training and validation cohorts, and the training cohort was used to construct a nine-mRNAsi-related gene signature (B3GAT2, CD3EAP, DMC1, FRMPD3, LINC01224, LINC02068, LY6H, NR6A1, and TLE2). High-risk and low-risk patients had significant prognostic differences, and the risk signature could accurately predict their 1-, 3-, and 5-year survival. The nomogram composed of risk score and multiple clinicopathological features could accurately predict 1-, 3-, and 5-year survival. Finally, CD3EAP was found to be a novel prognostic biomarker for endometrial cancer. Conclusion Endometrial cancer cell stemness is related to patient prognosis. The nine-gene risk signature is an independent prognostic factor and can accurately predict endometrial cancer patient prognosis.
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15
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Raja S, Van Houten B. The Multiple Cellular Roles of SMUG1 in Genome Maintenance and Cancer. Int J Mol Sci 2021; 22:ijms22041981. [PMID: 33671338 PMCID: PMC7922111 DOI: 10.3390/ijms22041981] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 02/12/2021] [Accepted: 02/13/2021] [Indexed: 12/20/2022] Open
Abstract
Single-strand selective monofunctional uracil DNA glycosylase 1 (SMUG1) works to remove uracil and certain oxidized bases from DNA during base excision repair (BER). This review provides a historical characterization of SMUG1 and 5-hydroxymethyl-2′-deoxyuridine (5-hmdU) one important substrate of this enzyme. Biochemical and structural analyses provide remarkable insight into the mechanism of this glycosylase: SMUG1 has a unique helical wedge that influences damage recognition during repair. Rodent studies suggest that, while SMUG1 shares substrate specificity with another uracil glycosylase UNG2, loss of SMUG1 can have unique cellular phenotypes. This review highlights the multiple roles SMUG1 may play in preserving genome stability, and how the loss of SMUG1 activity may promote cancer. Finally, we discuss recent studies indicating SMUG1 has moonlighting functions beyond BER, playing a critical role in RNA processing including the RNA component of telomerase.
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Affiliation(s)
- Sripriya Raja
- Molecular Pharmacology Graduate Program, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA;
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Bennett Van Houten
- Molecular Pharmacology Graduate Program, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA;
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Department of Pharmacology and Chemical Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Correspondence: ; Tel.: +1412-623-7762; Fax: +1-412-623-7761
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16
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Zhuang W, Ben X, Zhou Z, Ding Y, Tang Y, Huang S, Deng C, Liao Y, Zhou Q, Zhao J, Wang G, Xu Y, Wen X, Zhang Y, Cai S, Chen R, Qiao G. Identification of a Ten-Gene Signature of DNA Damage Response Pathways with Prognostic Value in Esophageal Squamous Cell Carcinoma. JOURNAL OF ONCOLOGY 2021; 2021:3726058. [PMID: 34976055 PMCID: PMC8716225 DOI: 10.1155/2021/3726058] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 11/27/2021] [Indexed: 02/06/2023]
Abstract
Molecular prognostic signatures are critical for treatment decision-making in esophageal squamous cell cancer (ESCC), but the robustness of these signatures is limited. The aberrant DNA damage response (DDR) pathway may lead to the accumulation of mutations and thus accelerate tumor progression in ESCC. Given this, we applied the LASSO Cox regression to the transcriptomic data of DDR genes, and a prognostic DDR-related gene expression signature (DRGS) consisting of ten genes was constructed, including PARP3, POLB, XRCC5, MLH1, DMC1, GTF2H3, PER1, SMC5, TCEA1, and HERC2. The DRGS was independently associated with overall survival in both training and validation cohorts. The DRGS achieved higher accuracy than six previously reported multigene signatures for the prediction of prognosis in comparable cohorts. Furtherly, a nomogram incorporating DRGS and clinicopathological features showed improved predicting performance. Taken together, the DRGS was identified as a novel, robust, and effective prognostic indicator, which may refine the scheme of risk stratification and management in ESCC patients.
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Affiliation(s)
- Weitao Zhuang
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
- Shantou University Medical College, Shantou 515041, China
| | - Xiaosong Ben
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Zihao Zhou
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Yu Ding
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China
| | - Yong Tang
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Shujie Huang
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
- Shantou University Medical College, Shantou 515041, China
| | - Cheng Deng
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Yuchen Liao
- Burning Rock Biotech, Guangzhou 510300, China
| | | | - Jing Zhao
- Burning Rock Biotech, Guangzhou 510300, China
| | | | - Yu Xu
- Burning Rock Biotech, Guangzhou 510300, China
| | | | - Yuzi Zhang
- Burning Rock Biotech, Guangzhou 510300, China
| | - Shangli Cai
- Burning Rock Biotech, Guangzhou 510300, China
| | - Rixin Chen
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
- Research Center of Medical Sciences, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Guibin Qiao
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
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17
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Zhao X, He M. Comprehensive pathway-related genes signature for prognosis and recurrence of ovarian cancer. PeerJ 2020; 8:e10437. [PMID: 33344083 PMCID: PMC7718801 DOI: 10.7717/peerj.10437] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 11/06/2020] [Indexed: 12/14/2022] Open
Abstract
Background Ovarian cancer (OC) is a highly malignant disease with a poor prognosis and high recurrence rate. At present, there is no accurate strategy to predict the prognosis and recurrence of OC. The aim of this study was to identify gene-based signatures to predict OC prognosis and recurrence. Methods mRNA expression profiles and corresponding clinical information regarding OC were collected from The Cancer Genome Atlas (TCGA) database. Gene set enrichment analysis (GSEA) and LASSO analysis were performed, and Kaplan–Meier curves, time-dependent ROC curves, and nomograms were constructed using R software and GraphPad Prism7. Results We first identified several key signalling pathways that affected ovarian tumorigenesis by GSEA. We then established a nine-gene-based signature for overall survival (OS) and a five-gene-based-signature for relapse-free survival (RFS) using LASSO Cox regression analysis of the TCGA dataset and validated the prognostic value of these signatures in independent GEO datasets. We also confirmed that these signatures were independent risk factors for OS and RFS by multivariate Cox analysis. Time-dependent ROC analysis showed that the AUC values for OS and RFS were 0.640, 0.663, 0.758, and 0.891, and 0.638, 0.722, 0.813, and 0.972 at 1, 3, 5, and 10 years, respectively. The results of the nomogram analysis demonstrated that combining two signatures with the TNM staging system and tumour status yielded better predictive ability. Conclusion In conclusion, the two-gene-based signatures established in this study may serve as novel and independent prognostic indicators for OS and RFS.
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Affiliation(s)
- Xinnan Zhao
- Department of Rheumatology and Immunology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Miao He
- Department of Pharmacology, China Medical University, Shenyang, China
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18
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Wang Y, Zhang M, Hu X, Qin W, Wu H, Wei M. Colon cancer-specific diagnostic and prognostic biomarkers based on genome-wide abnormal DNA methylation. Aging (Albany NY) 2020; 12:22626-22655. [PMID: 33202377 PMCID: PMC7746390 DOI: 10.18632/aging.103874] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 07/25/2020] [Indexed: 12/11/2022]
Abstract
Abnormal DNA methylation is a major early contributor to colon cancer (COAD) development. We conducted a cohort-based systematic investigation of genome-wide DNA methylation using 299 COAD and 38 normal tissue samples from TCGA. Through conditional screening and machine learning with a training cohort, we identified one hypomethylated and nine hypermethylated differentially methylated CpG sites as potential diagnostic biomarkers, and used them to construct a COAD-specific diagnostic model. Unlike previous models, our model precisely distinguished COAD from nine other cancer types (e.g., breast cancer and liver cancer; error rate ≤ 0.05) and from normal tissues in the training cohort (AUC = 1). The diagnostic model was verified using a validation cohort from The Cancer Genome Atlas (AUC = 1) and five independent cohorts from the Gene Expression Omnibus (AUC ≥ 0.951). Using Cox regression analyses, we established a prognostic model based on six CpG sites in the training cohort, and verified the model in the validation cohort. The prognostic model sensitively predicted patients’ survival (p ≤ 0.00011, AUC ≥ 0.792) independently of important clinicopathological characteristics of COAD (e.g., gender and age). Thus, our DNA methylation analysis provided precise biomarkers and models for the early diagnosis and prognostic evaluation of COAD.
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Affiliation(s)
- Yilin Wang
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, Liaoning Province, P. R. China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, Liaoning Province, P. R. China
| | - Ming Zhang
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, Liaoning Province, P. R. China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, Liaoning Province, P. R. China
| | - Xiaoyun Hu
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, Liaoning Province, P. R. China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, Liaoning Province, P. R. China
| | - Wenyan Qin
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, Liaoning Province, P. R. China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, Liaoning Province, P. R. China
| | - Huizhe Wu
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, Liaoning Province, P. R. China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, Liaoning Province, P. R. China
| | - Minjie Wei
- Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang 110122, Liaoning Province, P. R. China.,Liaoning Key Laboratory of Molecular Targeted Anti-Tumor Drug Development and Evaluation, Liaoning Cancer Immune Peptide Drug Engineering Technology Research Center, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, China Medical University, Shenyang 110122, Liaoning Province, P. R. China
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19
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Identification and verification of a ten-gene signature predicting overall survival for ovarian cancer. Exp Cell Res 2020; 395:112235. [DOI: 10.1016/j.yexcr.2020.112235] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 08/09/2020] [Accepted: 08/11/2020] [Indexed: 12/19/2022]
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20
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DNA Repair and Ovarian Carcinogenesis: Impact on Risk, Prognosis and Therapy Outcome. Cancers (Basel) 2020; 12:cancers12071713. [PMID: 32605254 PMCID: PMC7408288 DOI: 10.3390/cancers12071713] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Accepted: 06/24/2020] [Indexed: 12/13/2022] Open
Abstract
There is ample evidence for the essential involvement of DNA repair and DNA damage response in the onset of solid malignancies, including ovarian cancer. Indeed, high-penetrance germline mutations in DNA repair genes are important players in familial cancers: BRCA1, BRCA2 mutations or mismatch repair, and polymerase deficiency in colorectal, breast, and ovarian cancers. Recently, some molecular hallmarks (e.g., TP53, KRAS, BRAF, RAD51C/D or PTEN mutations) of ovarian carcinomas were identified. The manuscript overviews the role of DNA repair machinery in ovarian cancer, its risk, prognosis, and therapy outcome. We have attempted to expose molecular hallmarks of ovarian cancer with a focus on DNA repair system and scrutinized genetic, epigenetic, functional, and protein alterations in individual DNA repair pathways (homologous recombination, non-homologous end-joining, DNA mismatch repair, base- and nucleotide-excision repair, and direct repair). We suggest that lack of knowledge particularly in non-homologous end joining repair pathway and the interplay between DNA repair pathways needs to be confronted. The most important genes of the DNA repair system are emphasized and their targeting in ovarian cancer will deserve further attention. The function of those genes, as well as the functional status of the entire DNA repair pathways, should be investigated in detail in the near future.
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