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Zhao S, Francois A, Kidane D. Inhibition of DHODH Enhances Replication-Associated Genomic Instability and Promotes Sensitivity in Endometrial Cancer. Cancers (Basel) 2023; 15:5727. [PMID: 38136273 PMCID: PMC10741824 DOI: 10.3390/cancers15245727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 11/28/2023] [Accepted: 12/04/2023] [Indexed: 12/24/2023] Open
Abstract
Endometrial carcinoma (EC) is the most common gynecological malignancy in the United States. De novo pyrimidine synthesis pathways generate nucleotides that are required for DNA synthesis. Approximately 38% of human endometrial tumors present with an overexpression of human dihydroorotate dehydrogenase (DHODH). However, the role of DHODH in cancer cell DNA replication and its impact on modulating a treatment response is currently unknown. Here, we report that endometrial tumors with overexpression of DHODH are associated with a high mutation count and chromosomal instability. Furthermore, tumors with an overexpression of DHODH show significant co-occurrence with mutations in DNA replication polymerases, which result in a histologically high-grade endometrial tumor. An in vitro experiment demonstrated that the inhibition of DHODH in endometrial cancer cell lines significantly induced replication-associated DNA damage and hindered replication fork progression. Furthermore, endometrial cancer cells were sensitive to the DHODH inhibitor either alone or in combination with the Poly (ADP-ribose) polymerase 1 inhibitor. Our findings may have important clinical implications for utilizing DHODH as a potential target to enhance cytotoxicity in high-grade endometrial tumors.
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Affiliation(s)
- Shengyuan Zhao
- Division of Pharmacology and Toxicology, Dell Pediatric Research Institute, College of Pharmacy, The University of Texas at Austin, 1400 Barbara Jordan Blvd. R1800, Austin, TX 78723, USA
| | - Aaliyah Francois
- Division of Pharmacology and Toxicology, Dell Pediatric Research Institute, College of Pharmacy, The University of Texas at Austin, 1400 Barbara Jordan Blvd. R1800, Austin, TX 78723, USA
| | - Dawit Kidane
- Division of Pharmacology and Toxicology, Dell Pediatric Research Institute, College of Pharmacy, The University of Texas at Austin, 1400 Barbara Jordan Blvd. R1800, Austin, TX 78723, USA
- Department of Physiology and Biophysics, College of Medicine, Howard University, 520 W Street N.W., Washington, DC 20059, USA
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Wang T, Ji M, Liu W, Sun J. Development and validation of a novel DNA damage repair-related long non-coding RNA signature in predicting prognosis, immunity, and drug sensitivity in uterine corpus endometrial carcinoma. Comput Struct Biotechnol J 2023; 21:4944-4959. [PMID: 37876625 PMCID: PMC10590872 DOI: 10.1016/j.csbj.2023.10.025] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 10/13/2023] [Accepted: 10/13/2023] [Indexed: 10/26/2023] Open
Abstract
Background DNA damage response (DDR) confer resistance to chemoradiotherapy in cancer cells. However, the role of DDR-related lncRNAs (DRLs) in uterine corpus endometrial carcinoma (UCEC) is poorly understood. In this study, we aimed to identify a DRL-related prognostic signature that could guide the clinical treatment of UCEC. Methods We extracted transcriptome and clinical data of patients with UCEC from The Cancer Genome Atlas (TCGA) database and identified DRLs using Spearman correlation analysis. Univariate and multivariate Cox analyses were used to determine candidate prognostic DRLs. The samples were randomly divided into training and test cohorts in a 1:1 ratio. A DRL-related risk signature was constructed from the training cohort data using the least absolute shrinkage and selection operator (LASSO) algorithm, and validated using the test and entire cohorts. Subsequently, a prognostic nomogram was developed using a multivariate Cox regression analysis. The functional annotation, immune microenvironment, tumor mutation burden (TMB), immune checkpoint blockade (ICB) efficacy, and drug sensitivity were also comprehensively analyzed between different risk groups. Finally, the function of AC019069.1 was validated in vitro. Results A novel risk signature was developed based on nine DRLs. The risk score efficiently predicted the prognosis of patients with UCEC. Based on the median risk score, two subgroups were identified. The DDR-related pathways were upregulated in the high-risk group. Additionally, high-risk patients have low immune activity, poor response to ICB, and weak sensitivity to chemotherapeutic agents, possibly because of the proficient DDR system. Finally, we demonstrated AC019069.1 could promote cell proliferation, decrease apoptosis and maintain genome stability of UCEC cells. Conclusions The developed DRL-related signature can predict the prognosis, immune microenvironment, immunotherapy, and chemoradiotherapy responsiveness of UCEC. Our study also revealed the potential value of DDR-targeted therapy in treating high-risk patients with UCEC.
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Affiliation(s)
- Tao Wang
- Department of Gynecology, Shanghai Key Laboratory of Maternal-Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Mei Ji
- Department of Gynecology, Shanghai Key Laboratory of Maternal-Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Wenwen Liu
- Department of Gynecology, Shanghai Key Laboratory of Maternal-Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Jing Sun
- Department of Gynecology, Shanghai Key Laboratory of Maternal-Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
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3
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Gu J, Wang Z, Wang BO, Ma X. ImmuneScore of eight-gene signature predicts prognosis and survival in patients with endometrial cancer. Front Oncol 2023; 13:1097015. [PMID: 36937436 PMCID: PMC10020521 DOI: 10.3389/fonc.2023.1097015] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Accepted: 02/16/2023] [Indexed: 03/06/2023] Open
Abstract
Background Endometrial cancer (EC) is a common gynecological cancer worldwide and the sixth most common female malignant tumor. A large number of studies conducted through database mining have identified many biomarkers that may be related to survival and prognosis. However, the predictive ability of single-gene biomarkers is not sufficiently accurate. In recent years, tumors have been shown to interact closely with their microenvironment, and tumor-infiltrating immune cells in the tumor microenvironment were associated with therapeutic effects. Furthermore, sequencing technology has evolved and allowed the identification of genetic signatures that may improve prediction results. The purpose of this research was to discover the Cancer Genome Atlas (TCGA) data to evaluate new genetic features that can predict the prognosis of EC. Methods mRNA expression profiling was analyzed in patients with EC identified in the TCGA database (n = 530). Differentially expressed genes at different stages of EC were screened using the immune cell enrichment score (ImmuneScore). Univariate and multivariate Cox regression analyses was applied to evaluate genes significantly related to overall survival and establish the prognostic risk parameter formula. Kaplan-Meier survival curves and the logarithmic rank method were applied to verify the importance of risk parameters for the prognostic forecast. The accuracy of survival prediction was confirmed using the nomogram and Receiver Operating Characteristic (ROC) curve analysis. The mRNA expression of eight genes were measured by qRT-PCR. According to COX and HR values, NBAT1, a representative gene among 8 genes, was selected for CCK-8 assay, colony formation assay and transwell invasion assay to verify the effect on survival. Results Eight related genes (NBAT1, GFRA4, PTPRT, DLX4, RANBP3L, UNQ6494, KLRB1, and PRAC1) were discovered to be significantly associated with the overall survival rate. According to these eight-gene signatures, 530 patients with EC were assigned to high- and low-risk subgroups. The prognostic capability of the eight-gene signature was not influenced by other elements. Conclusions Eight related gene markers were identified using ImmuneScore, which could predict prognosis and survival in patients with EC. These findings provide a basis for understanding the application of biological information in tumors and identifying the poor prognosis of EC.
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Hu Y, Zheng M, Zhang D, Gou R, Liu O, Wang S, Lin B. Identification of the prognostic value of a 2-gene signature of the WNT gene family in UCEC using bioinformatics and real-world data. Cancer Cell Int 2021; 21:516. [PMID: 34565373 PMCID: PMC8474865 DOI: 10.1186/s12935-021-02215-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 09/15/2021] [Indexed: 12/29/2022] Open
Abstract
Background The WNT gene family plays an important role in the occurrence and development of malignant tumors, but its involvement has not been systematically analyzed in uterine corpus endometrial carcinoma (UCEC). This study aimed to evaluate the prognostic value of the WNT gene family in UCEC. Methods Pan-cancer transcriptome data of the UCSC Xena database and Genotype-Tissue Expression (GTEx) normal tissue data were downloaded to analyze the expression and prognosis of 19 WNT family genes in UCEC. A cohort from The Cancer Genome Atlas-Uterine Corpus Endometrial Carcinoma (TCGA-UCEC) was used to analyze the expression of the WNT gene family in different immune subtypes and clinical subgroups. The STRING database was used to analyze the interaction of the WNT gene family and its biological function. Univariate Cox regression analysis and Lasso cox analysis were used to identify the genes associated with significant prognosis and to construct multi signature prognosis model. An immunohistochemical assay was used to verify the predictive ability of the model. Risk score and the related clinical features were used to construct a nomogram. Results The expression levels of WNT2, WNT3, WNT3A, WNT5A, WNT7A, and WNT10A were significantly different among different immune subtypes and correlated with TP53 mutation. According to the WNT family genes related to the prognosis of UCEC, UCEC was classified into two subtypes (C1, C2). The prognosis of subtype C1 was significantly better than that of subtype C2. A 2-gene signature (WNT2 and WNT10A) was constructed and the two significantly prognostic groups can be divided based on median Risk score. These results were verified using real-world data, and the nomogram constructed using clinical features and Risk score had good prognostic ability. Conclusions The 2-gene signature including WNT2 and WNT10A can be used to predict the prognosis of patients with UCEC, which is important for clinical decision-making and individualized therapy for patients with UCEC.
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Affiliation(s)
- Yuexin Hu
- Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Shenyang, China.,Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Benxi, China.,Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, Benxi, China
| | - Mingjun Zheng
- Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Shenyang, China.,Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Benxi, China.,Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, Benxi, China.,Department of Obstetrics and Gynecology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
| | - Dandan Zhang
- Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Shenyang, China.,Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Benxi, China.,Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, Benxi, China
| | - Rui Gou
- Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Shenyang, China.,Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Benxi, China.,Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, Benxi, China
| | - Ouxuan Liu
- Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Shenyang, China.,Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Benxi, China.,Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, Benxi, China
| | - Shuang Wang
- Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Shenyang, China.,Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Benxi, China.,Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, Benxi, China
| | - Bei Lin
- Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Shenyang, China. .,Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Benxi, China. .,Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, Benxi, China. .,4th Gynecological Ward, Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, 36 Sanhao Street, Liaoning, 110004, Shenyang, People's Republic of China.
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Zheng M, Hu Y, Gou R, Li S, Nie X, Li X, Lin B. Development of a seven-gene tumor immune microenvironment prognostic signature for high-risk grade III endometrial cancer. MOLECULAR THERAPY-ONCOLYTICS 2021; 22:294-306. [PMID: 34553020 PMCID: PMC8426172 DOI: 10.1016/j.omto.2021.07.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 07/02/2021] [Indexed: 02/06/2023]
Abstract
Uterine corpus endometrial carcinoma locally infiltrates numerous immune cells and other tumor immune microenvironment components. These cells are involved in malignant tumor growth and proliferation and the process of resistance toward immunotherapies. Here, we aimed to develop a tumor immune microenvironment-related prognostic signature for high-risk grade III endometrial carcinoma based on The Cancer Genome Atlas. The signature was systematically correlated with immune infiltration characteristics of the tumor microenvironment. The seven-gene Riskscore signature was robust and performed well in training, testing, and Gene Expression Omnibus-independent cohorts. A nomogram comprising the gene signature accurately predicted patient prognosis, with our model performing better than other endometrial cancer-related signatures. Analysis of the IMvigor210 immunotherapy cohort revealed that subgroups with a low Riskscore had a better prognosis than subgroups with a high Riskscore. Subgroups with a low Riskscore exhibited immune cell infiltration and inflammatory profiles, whereas subgroups with a high Riskscore experienced progressive disease. The receiver operating characteristic curve indicated that risk score, neoantigen, and tumor mutation burden models together accurately predicted treatment response. Taken together, we developed a tumor microenvironment-based seven-gene prognostic stratification system to predict the prognosis of patients with high-risk endometrial cancer and guide more effective immunotherapy strategies.
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Affiliation(s)
- Mingjun Zheng
- Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Liaoning 110004, China.,Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, China.,Department of Obstetrics and Gynecology, University Hospital, LMU Munich, Maistrasse 11, 80337 Munich, Germany
| | - Yuexin Hu
- Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Liaoning 110004, China.,Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, China
| | - Rui Gou
- Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Liaoning 110004, China.,Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, China
| | - Siting Li
- Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Liaoning 110004, China.,Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, China
| | - Xin Nie
- Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Liaoning 110004, China.,Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, China
| | - Xiao Li
- Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Liaoning 110004, China.,Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, China
| | - Bei Lin
- Department of Gynecology and Obstetrics, Shengjing Hospital of China Medical University, Liaoning 110004, China.,Key Laboratory of Maternal-Fetal Medicine of Liaoning Province, Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, China
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Yang F, Zhao R, Huang X, Wang Y. Diagnostic and prognostic factors, and two nomograms for endometrial cancer patients with bone metastasis: A large cohort retrospective study. Medicine (Baltimore) 2021; 100:e27185. [PMID: 34516519 PMCID: PMC8428737 DOI: 10.1097/md.0000000000027185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 08/19/2021] [Indexed: 01/05/2023] Open
Abstract
Patients with endometrial cancer (EC) who develop bone metastasis (BM) always imply a poorer prognosis. However, reliable predictive models associated with BM from EC are currently limited.We retrospectively analyzed data on 54,077 patients diagnosed with primary EC in the Surveillance, Epidemiology, and End Results database. Multivariate logistic regression analysis was used to determine independent predictors of BM from EC. Univariate and multivariate Cox regression analyses were used to determine independent prognostic factors for EC with BM. Based on independent predictors and prognostic factors, we constructed a diagnostic nomogram and prognostic nomogram separately. Besides, calibration curves, receiver operating characteristic curves, and decision curve analysis were used to evaluate the models.A total of 54,077 patients with EC from the Surveillance, Epidemiology, and End Results database were included in this study, 364 of whom had BM. Multivariate analysis in the logistic model showed that lung metastasis, liver metastasis, brain metastasis, N stage, T stage, histologic grade, and race were risk factors for BM from EC. Multivariate analysis in the Cox model showed that liver metastasis, brain metastasis, chemotherapy, surgery, and histologic type had a significant effect on overall survival. Moreover, the receiver operating characteristic curve, calibration curve, and decision curve analysis indicated the good performance of both diagnostic and prognostic nomograms.Two clinical prediction model was constructed and validated to predict individual risk and overall survival for EC with BM, respectively. Diagnostic nomogram and prognostic nomogram are complementary, improving the clinician's ability to assess the patient's prognosis and enhancing prognosis-based decision making.
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Affiliation(s)
- Fengkai Yang
- Department of Postgraduate Medical School, Chengde Medical College, Chengde, Hebei Province, China
| | - Ruhan Zhao
- Department of Oncology, Affiliated Hospital of Chengde Medical University, Chengde, Hebei Province, China
| | - Xiaohui Huang
- Hangzhou Medical College, Hangzhou, Zhejiang Province, China
| | - Yucheng Wang
- Department of Orthopedics, Taizhou Municipal Hospital, Taizhou, Zhejiang Province, China
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Tang S, Zhuge Y. An immune-related pseudogene signature to improve prognosis prediction of endometrial carcinoma patients. Biomed Eng Online 2021; 20:64. [PMID: 34193185 PMCID: PMC8243762 DOI: 10.1186/s12938-021-00902-7] [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: 12/15/2020] [Accepted: 06/20/2021] [Indexed: 12/14/2022] Open
Abstract
Background Pseudogenes show multiple functions in various cancer types, and immunotherapy is a promising cancer treatment. Therefore, this study aims to identify immune-related pseudogene signature in endometrial cancer (EC). Methods Gene transcriptome data of EC tissues and corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA) through UCSC Xena browser. Spearman correlation analysis was performed to identify immune-related pseudogenes (IRPs) between the immune genes and pseudogenes. Univariate Cox regression, LASSO, and multivariate were performed to develop a risk score signature to investigate the different overall survival (OS) between high- and low-risk groups. The prognostic significance of the signature was assessed by the Kaplan–Meier curve, time-dependent receiver operating characteristic (ROC) curve. The abundance of 22 immune cell subtypes of EC patients was evaluated using CIBERSORT. Results Nine IRPs were used to build a prognostic signature. Survival analysis revealed that patients in the low-risk group presented longer OS than those in the high-risk group as well as in multiple subgroups. The signature risk score was independent of other clinical covariates and was associated with several clinicopathological variables. The prognostic signature reflected infiltration by multiple types of immune cells and revealed the immunotherapy response of patients with anti-programmed death-1 (PD-1) and anti-programmed cell death 1 ligand 1 (PD-L1) therapy. Function enrichment analysis revealed that the nine IRPs were mainly involved in multiple cancer-related pathways. Conclusion We identified an immune-related pseudogene signature that was strongly correlated with the prognosis and immune response to EC. The signature might have important implications for improving the clinical survival of EC patients and provide new strategies for cancer treatment.
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Affiliation(s)
- Shanshan Tang
- Department of Gynecology, Hangzhou Women's Hospital, No. 369 Kunpeng Road, Shangcheng District, Hangzhou, 310008, Zhejiang, China
| | - Yiyi Zhuge
- Department of Gynecology, Hangzhou Women's Hospital, No. 369 Kunpeng Road, Shangcheng District, Hangzhou, 310008, Zhejiang, China.
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