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Xie Y, Xie J, Li L. The Role of Methylation in Ferroptosis. J Cardiovasc Transl Res 2024:10.1007/s12265-024-10539-1. [PMID: 39075241 DOI: 10.1007/s12265-024-10539-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 06/21/2024] [Indexed: 07/31/2024]
Abstract
Methylation modification is a crucial epigenetic alteration encompassing RNA methylation, DNA methylation, and histone methylation. Ferroptosis represents a newly discovered form of programmed cell death (PCD) in 2012, which is characterized by iron-dependent lipid peroxidation. The comprehensive investigation of ferroptosis is therefore imperative for a more profound comprehension of the pathological and pathophysiological mechanisms implicated in a wide array of diseases. Researches show that methylation modifications can exert either promotive or inhibitory effects on cell ferroptosis. Consequently, this review offers a comprehensive overview of the pivotal role played by methylation in ferroptosis, elucidating its associated factors and underlying mechanisms.
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Affiliation(s)
- Yushu Xie
- Class of Clinical Medicine, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China
| | - Jie Xie
- Class of Excellent Doctor, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China
| | - Liang Li
- Department of Physiology, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
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Xu L, Wang L, Gan Y, Lin J, Ning S, Deng J, Ning Y, Feng W. Interference with ANXA8 inhibits the malignant progression of ovarian cancer by suppressing the activation of the Wnt/β-catenin signaling pathway via UCHL5. Aging (Albany NY) 2024; 16:11275-11288. [PMID: 39068672 DOI: 10.18632/aging.205991] [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: 01/15/2024] [Accepted: 05/30/2024] [Indexed: 07/30/2024]
Abstract
Ovarian cancer (OC), which threatens women's lives, is a common tumor of the female reproductive system. Annexin A8 (ANXA8) is highly expressed in OC. However, the mechanism of ANXA8 in OC remains unclear. This study investigated the potential mechanisms of ANXA8 in OC. The expression of ANXA8 in OC cells was determined by qRT-PCR and western blotting. ANXA8 interference plasmid was constructed. Moreover, CCK-8, EDU staining, TUNEL staining, western blotting, wound healing, and transwell assays were used to detect cell proliferation, apoptosis, migration, and invasion, respectively. Next, the relationship between ANXA8 and ubiquitin C-terminal hydrolase L5 (UCHL5) was verified through Co-IP. Finally, western blotting was used to detect the expression of Wnt/β-catenin signaling-related proteins. Additionally, we further interfered ANXA8 in nude mice with OC, and detected the expression of ANXA8, UCHL5 and the signaling pathway-related proteins by immunohistochemistry and western blotting. Our results suggested that ANXA8 expression was significantly increased in OC cells. ANXA8 interference significantly attenuated the proliferative, invasive, and migratory capabilities and promoted the apoptotic ability of OC cells. Moreover, the expression of UCHL5 in OC was significantly increased. ANXA8 bound to UCHL5 in OC cells. Knockdown of ANXA8 attenuated OC cell malignant progression by downregulating the expression of UCHL5. Furthermore, ANXA8 affected the expression of Wnt/β-catenin signaling pathway-related proteins in OC cells via UCHL5. Collectively, ANXA8 interference suppressed the activation of Wnt/β-catenin signaling pathway via UCHL5 to inhibit cell proliferation, invasion, migration and induce cell apoptosis in OC, thus presenting a potential therapeutic strategy for OC treatment.
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Affiliation(s)
- Li Xu
- Department of Gynaecology and Obstetrics, The First Affiliated Hospital of Jinan University, Guangzhou 510632, Guangdong, China
- Department of Gynaecology and Obstetrics, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, Guangdong, China
| | - Liang Wang
- Guangdong Guojian Pharmaceutical Consulting Co., Ltd., Guangzhou 510030, China
| | - Yaping Gan
- Department of Gynaecology and Obstetrics, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, Guangdong, China
| | - Jiazhi Lin
- Department of Gynaecology and Obstetrics, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, Guangdong, China
| | - Shuting Ning
- Department of Gynaecology and Obstetrics, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, Guangdong, China
| | - Jinjin Deng
- Department of Gynaecology and Obstetrics, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, Guangdong, China
| | - Yingxia Ning
- Department of Gynaecology and Obstetrics, The First Affiliated Hospital of Jinan University, Guangzhou 510632, Guangdong, China
- Department of Gynaecology and Obstetrics, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, Guangdong, China
| | - Weifeng Feng
- Department of Traditional Chinese Medicine, The First Affiliated Hospital of Jinan University, Guangzhou 510632, Guangdong, China
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Zhao P, Meng D, Hu Z, Liang Y, Feng Y, Sun T, Cheng L, Zheng X, Li H. Intra-sample reversed pairs based on differentially ranked genes reveal biosignature for ovarian cancer. Comput Biol Med 2024; 172:108208. [PMID: 38484696 DOI: 10.1016/j.compbiomed.2024.108208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 02/08/2024] [Accepted: 02/25/2024] [Indexed: 03/26/2024]
Abstract
Ovarian cancer, a major gynecological malignancy, often remains undetected until advanced stages, necessitating more effective early screening methods. Existing biomarker based on differential genes often suffers from variations in clinical practice. To overcome the limitations of absolute gene expression values including batch effects and biological heterogeneity, we introduced a pairwise biosignature leveraging intra-sample differentially ranked genes (DRGs) and machine learning for ovarian cancer detection across diverse cohorts. We analyzed ten cohorts comprising 872 samples with 796 ovarian cancer and 76 normal. Our method, DRGpair, involves three stages: intra-sample ranking differential analysis, reversed gene pair analysis, and iterative LASSO regression. We identified four DRG pairs, demonstrating superior diagnostic performance compared to current state-of-the-art biomarkers and differentially expressed genes in seven independent cohorts. This rank-based approach not only reduced computational complexity but also enhanced the specificity and effectiveness of biomarkers, revealing DRGs as promising candidates for ovarian cancer detection and offering a scalable model adaptable to varying cohort characteristics.
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Affiliation(s)
- Pengfei Zhao
- School of Medicine, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People's Hospital, Shenzhen, China
| | - Dian Meng
- School of Computing and Information Technology, Great Bay University, Guangdong, China
| | - Zunkai Hu
- School of Medicine, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People's Hospital, Shenzhen, China
| | - Yining Liang
- School of Medicine, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People's Hospital, Shenzhen, China
| | - Yating Feng
- School of Medicine, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People's Hospital, Shenzhen, China
| | - Tongjie Sun
- School of Medicine, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People's Hospital, Shenzhen, China
| | - Lixin Cheng
- School of Medicine, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People's Hospital, Shenzhen, China
| | - Xubin Zheng
- School of Computing and Information Technology, Great Bay University, Guangdong, China; Great Bay Institute for Advanced Study, Guangdong, China
| | - Haili Li
- School of Medicine, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People's Hospital, Shenzhen, China.
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Zhu L, Yuan F, Wang X, Zhu R, Guo W. Cuproptosis-related gene-located DNA methylation in lower-grade glioma: Prognosis and tumor microenvironment. Cancer Biomark 2024; 40:185-198. [PMID: 38578883 DOI: 10.3233/cbm-230341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2024]
Abstract
Cuproptosis a novel copper-dependent cell death modality, plays a crucial part in the oncogenesis, progression and prognosis of tumors. However, the relationships among DNA-methylation located in cuproptosis-related genes (CRGs), overall survival (OS) and the tumor microenvironment remain undefined. In this study, we systematically assessed the prognostic value of CRG-located DNA-methylation for lower-grade glioma (LGG). Clinical and molecular data were sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We employed Cox hazard regression to examine the associations between CRG-located DNA-methylation and OS, leading to the development of a prognostic signature. Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) analyses were utilized to gauge the accuracy of the signature. Gene Set Enrichment Analysis (GSEA) was applied to uncover potential biological functions of differentially expressed genes between high- and low-risk groups. A three CRG-located DNA-methylation prognostic signature was established based on TCGA database and validated in GEO dataset. The 1-year, 3-year, and 5-year area under the curve (AUC) of ROC curves in the TCGA dataset were 0.884, 0.888, and 0.859 while those in the GEO dataset were 0.943, 0.761 and 0.725, respectively. Cox-regression-analyses revealed the risk signature as an independent risk factor for LGG patients. Immunogenomic profiling suggested that the signature was associated with immune infiltration level and immune checkpoints. Functional enrichment analysis indicated differential enrichment in cell differentiation in the hindbrain, ECM receptor interactions, glycolysis and reactive oxygen species pathway across different groups. We developed and verified a novel CRG-located DNA-methylation signature to predict the prognosis in LGG patients. Our findings emphasize the potential clinical implications of CRG-located DNA-methylation indicating that it may serve as a promising therapeutic target for LGG patients.
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Affiliation(s)
- Liucun Zhu
- School of Life Sciences, Shanghai University, Shanghai, China
- School of Life Sciences, Shanghai University, Shanghai, China
| | - Fa Yuan
- School of Life Sciences, Shanghai University, Shanghai, China
- School of Life Sciences, Shanghai University, Shanghai, China
| | - Xue Wang
- School of Life Sciences, Zhengzhou University, Zhengzhou, Henan, China
| | - Rui Zhu
- School of Life Sciences, Shanghai University, Shanghai, China
- Department of Clinical Laboratory Medicine, Shanghai Tenth People's Hospital of Tongji University, Shanghai, China
| | - Wenna Guo
- School of Life Sciences, Zhengzhou University, Zhengzhou, Henan, China
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Li M, Zhu C, Xue Y, Miao C, He R, Li W, Zhang B, Yu W, Huang X, Lv M, Xu Y, Huang Q. A DNA methylation signature for the prediction of tumour recurrence in stage II colorectal cancer. Br J Cancer 2023; 128:1681-1689. [PMID: 36828869 PMCID: PMC10133253 DOI: 10.1038/s41416-023-02155-8] [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: 06/13/2022] [Revised: 01/05/2023] [Accepted: 01/11/2023] [Indexed: 02/26/2023] Open
Abstract
BACKGROUND A major challenge in stage II colorectal carcinoma is to identify patients with increased risk of recurrence. Biomarkers that distinguish patients with poor prognosis from patients without recurrence are currently lacking. This study aims to develop a robust DNA methylation classifier that allows the prediction of recurrence and chemotherapy benefit in patients with stage II colorectal cancer. We performed a genome-wide DNA methylation capture sequencing in 243 stage II colorectal carcinoma samples and identified a relapse-specific DNA methylation signature consisting of eight CpG sites. METHODS Two hundred and forty-three patients with stage II CRC were enrolled in this study. In order to select differential methylation sites among recurrence and non-recurrence stage II CRC samples, DNA methylation profiles of 62 tumour samples including 31 recurrence and 31 nonrecurrence samples were analysed using the Agilent SureSelectXT Human Methyl-Seq, a comprehensive target enrichment system to analyse CpG methylation. Pyrosequencing was applied to quantify the methylation level of candidate DNA methylation sites in 243 patients. Least absolute shrinkage and selection operator (LASSO) method was employed to build the disease recurrence prediction classifier. RESULTS We identified a relapse-related DNA methylation signature consisting of eight CpG sites in stage II CRC by DNA methylation capture sequencing. The classifier showed significantly higher prognostic accuracy than any clinicopathological risk factors. The Kaplan-Meier survival curve showed an association of high-risk score with poor prognosis. In multivariate analysis, the signature was the most significant prognosis factor, with an HR of 2.80 (95% CI, 1.71-4.58, P < 0.001). The signature could identify patients who are suitable candidates for adjuvant chemotherapy. CONCLUSIONS An eight-CpG DNA methylation signature is a reliable prognostic and predictive tool for disease recurrence in patients with stage II CRC.
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Affiliation(s)
- Min Li
- Cancer Center, Zhongshan Hospital, Fudan University, 180 Fenglin Road, 200032, Shanghai, P. R. China
- Institute of Clinical Sciences, Zhongshan Hospital, Fudan University, 180 Fenglin Road, 200032, Shanghai, P. R. China
| | - Congcong Zhu
- Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, 270 Dong'An Road, 200032, Shanghai, P. R. China
- Department of Oncology, Shanghai Medical College, Fudan University, 270 Dong'An Road, 200032, Shanghai, P. R. China
| | - Ying Xue
- Cancer Center, Zhongshan Hospital, Fudan University, 180 Fenglin Road, 200032, Shanghai, P. R. China
- Institute of Clinical Sciences, Zhongshan Hospital, Fudan University, 180 Fenglin Road, 200032, Shanghai, P. R. China
| | - Changhong Miao
- Cancer Center, Zhongshan Hospital, Fudan University, 180 Fenglin Road, 200032, Shanghai, P. R. China
- Department of Anesthesiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, 200032, Shanghai, P. R. China
| | - Ruiping He
- Cancer Center, Zhongshan Hospital, Fudan University, 180 Fenglin Road, 200032, Shanghai, P. R. China
- Institute of Clinical Sciences, Zhongshan Hospital, Fudan University, 180 Fenglin Road, 200032, Shanghai, P. R. China
| | - Wei Li
- Laboratory of RNA Epigenetics, Institute of Biomedical Sciences, Fudan University, 130 Dong'An Road, 200032, Shanghai, P. R. China
| | - Baolong Zhang
- Laboratory of RNA Epigenetics, Institute of Biomedical Sciences, Fudan University, 130 Dong'An Road, 200032, Shanghai, P. R. China
| | - Wenqiang Yu
- Laboratory of RNA Epigenetics, Institute of Biomedical Sciences, Fudan University, 130 Dong'An Road, 200032, Shanghai, P. R. China
| | - Xingxu Huang
- School of Life Science and Technology, ShanghaiTech University, 201210, Shanghai, P. R. China
| | - Minzhi Lv
- Institute of Clinical Sciences, Zhongshan Hospital, Fudan University, 180 Fenglin Road, 200032, Shanghai, P. R. China.
- Department of Biostatistics, Clinical Research Unit, Zhongshan Hospital, Fudan University, 180 Fenglin Road, 200032, Shanghai, P. R. China.
| | - Ye Xu
- Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, 270 Dong'An Road, 200032, Shanghai, P. R. China.
- Department of Oncology, Shanghai Medical College, Fudan University, 270 Dong'An Road, 200032, Shanghai, P. R. China.
| | - Qihong Huang
- Cancer Center, Zhongshan Hospital, Fudan University, 180 Fenglin Road, 200032, Shanghai, P. R. China.
- Institute of Clinical Sciences, Zhongshan Hospital, Fudan University, 180 Fenglin Road, 200032, Shanghai, P. R. China.
- Shanghai Respiratory Research Institute, 180 Fenglin Road, 200032, Shanghai, P. R. China.
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Wang S, Fu J, Fang X. A novel DNA methylation-related gene signature for the prediction of overall survival and immune characteristics of ovarian cancer patients. J Ovarian Res 2023; 16:62. [PMID: 36978087 PMCID: PMC10053775 DOI: 10.1186/s13048-023-01142-0] [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: 04/13/2022] [Accepted: 03/19/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND Ovarian cancer (OC) is one of the most life-threatening cancers affecting women worldwide. Recent studies have shown that the DNA methylation state can be used in the diagnosis, treatment and prognosis prediction of diseases. Meanwhile, it has been reported that the DNA methylation state can affect the function of immune cells. However, whether DNA methylation-related genes can be used for prognosis and immune response prediction in OC remains unclear. METHODS In this study, DNA methylation-related genes in OC were identified by an integrated analysis of DNA methylation and transcriptome data. Prognostic values of the DNA methylation-related genes were investigated through least absolute shrinkage and selection operator (LASSO) and Cox progression analyses. Immune characteristics were investigated by CIBERSORT, correlation analysis and weighted gene co-expression network analysis (WGCNA). RESULTS Twelve prognostic genes (CA2, CD3G, HABP2, KCTD14, PI3, SERPINB5, SLAMF7, SLC9A2, STC2, TBP, TREML2 and TRIM27) were identified and a risk score signature and a nomogram based on prognostic genes and clinicopathological features were constructed for the survival prediction of OC patients in the training and two validation cohorts. Subsequently, the differences in the immune landscape between the high- and low-risk score groups were systematically investigated. CONCLUSIONS Taken together, our study explored a novel efficient risk score signature and a nomogram for the survival prediction of OC patients. In addition, the differences of the immune characteristics between the two risk groups were clarified preliminarily, which will guide the further exploration of synergistic targets to improve the efficacy of immunotherapy in OC patients.
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Affiliation(s)
- Sixue Wang
- Department of Obstetrics and Gynecology, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Jie Fu
- Department of General Surgery, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
| | - Xiaoling Fang
- Department of Obstetrics and Gynecology, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
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Identification and Validation of Ferroptosis-Related DNA Methylation Signature for Predicting the Prognosis and Guiding the Treatment in Cutaneous Melanoma. Int J Mol Sci 2022; 23:ijms232415677. [PMID: 36555319 PMCID: PMC9778758 DOI: 10.3390/ijms232415677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 11/29/2022] [Accepted: 12/05/2022] [Indexed: 12/14/2022] Open
Abstract
Cutaneous melanoma (CM) is one of the most aggressive skin tumors with a poor prognosis. Ferroptosis is a newly discovered form of regulated cell death that is closely associated with cancer development and immunotherapy. The aim of this study was to establish and validate a ferroptosis-related gene (FRG) DNA methylation signature to predict the prognosis of CM patients using data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. A reliable four-FRG DNA methylation prognostic signature was constructed via Cox regression analysis based on TCGA database. Kaplan-Meier analysis showed that patients in the high-risk group tended to have a shorter overall survival (OS) than the low-risk group in both training TCGA and validation GEO cohorts. Time-dependent receiver operating characteristic (ROC) analysis showed the areas under the curve (AUC) at 1, 3, and 5 years were 0.738, 0.730, and 0.770 in TCGA cohort and 0.773, 0.775, and 0.905 in the validation cohort, respectively. Univariate and multivariate Cox regression analyses indicated that the signature was an independent prognostic indicator of OS in patients with CM. Immunogenomic profiling showed the low-risk group of patients had a higher immunophenoscore, and most immune checkpoints were negatively associated with the risk signature. Functional enrichment analysis revealed that immune response and immune-related pathways were enriched in the low-risk group. In conclusion, we established and validated a four-FRG DNA methylation signature that independently predicts prognosis in CM patients. This signature was strongly correlated with the immune landscape, and may serve as a biomarker to guide clinicians in making more precise and personalized treatment decisions for CM patients.
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Huo X, Guo T, Wang K, Yao B, Li D, Li H, Chen W, Wang L, Wu Z. Methylation-based reclassification and risk stratification of skull-base chordomas. Front Oncol 2022; 12:960005. [PMID: 36439461 PMCID: PMC9691996 DOI: 10.3389/fonc.2022.960005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 10/11/2022] [Indexed: 10/04/2023] Open
Abstract
BACKGROUND Skull-base chordomas are rare malignant bone cancers originating from the remnant of the notochord. Survival is variable, and clinical or molecular factors cannot reliably predict their outcomes. This study therefore identified epigenetic subtypes that defined new chordoma epigenetic profiles and their corresponding characteristics. METHODS Methylation profiles of 46 chordoma-resected neoplasms between 2008 and 2014, along with clinical information, were collected. K-means consensus clustering and principal component analysis were used to identify and validate the clusters. Single-sample gene set enrichment analysis, methylCIBERSORT algorithm, and copy number analysis were used to identify the characteristics of the clusters. RESULTS Unsupervised clustering analysis confirmed two clusters with a progression-free survival difference. Gene set enrichment analysis indicated that the early and late estrogen response pathways and the hypoxia pathway were activated whereas the inflammatory and interferon gamma responses were suppressed. Forty-six potential therapeutic targets corresponding to differentially methylated sites were identified from chordoma patients. Subgroups with a worse outcome were characterized by low immune cell infiltration, higher tumor purity, and higher stemness indices. Moreover, copy number amplifications mostly occurred in cluster 1 tumors and the high-risk group. Additionally, the presence of a CCNE1 deletion was exclusively found in the group of chordoma patients with better outcome, whereas RB1 and CDKN2A/2B deletions were mainly found in the group of chordoma patients with worse outcome. CONCLUSIONS Chordoma prognostic epigenetic subtypes were identified, and their corresponding characteristics were found to be variable.
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Affiliation(s)
- Xulei Huo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China
| | - Tengxian Guo
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Ke Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China
| | - Bohan Yao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China
| | - Da Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China
| | - Huan Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China
| | - Wei Chen
- Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Liang Wang
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Zhen Wu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China
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Identification and validation of a gene-based signature reveals SLC25A10 as a novel prognostic indicator for patients with ovarian cancer. J Ovarian Res 2022; 15:106. [PMID: 36114504 PMCID: PMC9482156 DOI: 10.1186/s13048-022-01039-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 09/06/2022] [Indexed: 11/10/2022] Open
Abstract
Background Ovarian cancer is a common gynecological cancer with poor prognosis and poses a serious threat to woman life and health. In this study, we aimed to establish a prognostic signature for the risk assessment of ovarian cancer. Methods The Cancer Genome Atlas (TCGA) dataset was used as the training set and the International Cancer Genome Consortium (ICGC) dataset was set as an independent external validation. A multi-stage screening strategy was used to determine the prognostic features of ovarian cancer with R software. The relationship between the prognosis of ovarian cancer and the expression level of SLC25A10 was selected for further analysis. Results A total of 16 prognosis-associated genes were screened to construct the risk score signature. Survival analysis showed that patients in the high-risk score group had a poor prognosis compared to the low-risk group. Accuracy of this prognostic signature was confirmed by the receiver operating characteristic (ROC) curve and decision curve analysis (DCA), and validated with ICGC cohort. This signature was identified as an independent factor for predicting overall survival (OS). Nomogram constructed by multiple clinical parameters showed excellent performance for OS prediction. Finally, it’s found that patients with low expression of SLC25A10 generally had poor survival and higher resistance to most chemotherapeutic drugs. Conclusions In sum, we developed a 16-gene prognostic signature, which could serve as a promising tool for the prognostic prediction of ovarian cancer, and the expression level of SLC25A10 was tightly associated with OS of the patients.
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Plasma cfDNA methylation markers for the detection and prognosis of ovarian cancer. EBioMedicine 2022; 83:104222. [PMID: 35973389 PMCID: PMC9396542 DOI: 10.1016/j.ebiom.2022.104222] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 07/22/2022] [Accepted: 07/29/2022] [Indexed: 12/24/2022] Open
Abstract
Background Plasma cell-free DNA (cfDNA) methylation has shown the potential in the detection and prognostic testing in multiple cancers. Herein, we thoroughly investigate the performance of cfDNA methylation in the detection and prognosis of ovarian cancer (OC). Methods The OC-specific differentially methylated regions (DMRs) were identified by sequencing ovarian tissue samples from OC (n = 61), benign ovarian disease (BOD, n = 49) and healthy controls (HC, n = 37). Based on 1,272 DMRs, a cfDNA OC detection model (OC-D model) was trained and validated in plasma samples from patients of OC (n = 104), BOD (n = 56) and HC (n = 56) and a prognostic testing model (OC-P model) was developed in plasma samples in patients with high-grade serous OC (HG-SOC) in the training cohort and then tested the rationality of this model with International Cancer Genome Consortium (ICGC) tissue methylation data. Mechanisms were investigated in the TCGA-OC cohort. Findings In the validation cohort, the cfDNA OC-D model consisting of 18 DMRs achieved a sensitivity of 94.7% (95% CI: 85.4%‒98.9%) at a specificity of 88.7% (95% CI: 78.7%‒94.9%), which outperformed CA 125 (AUC: 0.967 vs 0.905, P = 0.03). Then the cfDNA OC-P model consisting of 15 DMRs was constructed and associated with a better prognosis of HG-SOC in multivariable Cox regression analysis (HR: 0.29, 95% CI, 0.11‒0.78, P = 0.01) in the training cohort, which was also observed in the ICGC cohort using tissue methylation (HR: 0.56, 95% CI, 0.32‒0.98, P = 0.04). Investigation into mechanisms revealed that the low-risk group had higher homologous recombination deficiency and immune cell infiltration (P < 0.05). Interpretation Our study demonstrated the potential utility of cfDNA methylation in the detection and prognostic testing in OC. Future studies with a larger population are warranted. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sector.
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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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Vega-Benedetti AF, Loi E, Zavattari P. DNA methylation alterations caused by Leishmania infection may generate a microenvironment prone to tumour development. Front Cell Infect Microbiol 2022; 12:984134. [PMID: 36105147 PMCID: PMC9465093 DOI: 10.3389/fcimb.2022.984134] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 08/10/2022] [Indexed: 01/10/2023] Open
Abstract
DNA methylation is an epigenetic signature consisting of a methyl group at the 5’ cytosine of CpG dinucleotides. Modifications in DNA methylation pattern have been detected in cancer and infectious diseases and may be associated with gene expression changes. In cancer development DNA methylation aberrations are early events whereas in infectious diseases these epigenetic changes may be due to host/pathogen interaction. In particular, in leishmaniasis, a parasitic disease caused by the protozoan Leishmania, DNA methylation alterations have been detected in macrophages upon infection with Leishmania donovani and in skin lesions from patients with cutaneous leishmaniasis. Interestingly, different types of cancers, such as cutaneous malignant lesions, lymphoma and hepatocellular carcinoma, have been diagnosed in patients with a history of leishmaniasis. In fact, it is known that there exists an association between cancer and infectious diseases. Leishmania infection may increase susceptibility to develop cancer, but the mechanisms involved are not entirely clear. Considering these aspects, in this review we discuss the hypothesis that DNA methylation alterations induced by Leishmania may trigger tumorigenesis in long term infection since these epigenetic modifications may enhance and accumulate during chronic leishmaniasis.
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Li H, Zheng X, Gao J, Leung KS, Wong MH, Yang S, Liu Y, Dong M, Bai H, Ye X, Cheng L. Whole transcriptome analysis reveals non-coding RNA's competing endogenous gene pairs as novel form of motifs in serous ovarian cancer. Comput Biol Med 2022; 148:105881. [DOI: 10.1016/j.compbiomed.2022.105881] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 06/30/2022] [Accepted: 07/16/2022] [Indexed: 11/03/2022]
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Chen D, Wu Y, Tilley RD, Gooding JJ. Rapid and ultrasensitive electrochemical detection of DNA methylation for ovarian cancer diagnosis. Biosens Bioelectron 2022; 206:114126. [PMID: 35240438 DOI: 10.1016/j.bios.2022.114126] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 02/18/2022] [Accepted: 02/21/2022] [Indexed: 01/04/2023]
Abstract
Alterations in DNA methylation, a stable epigenetic marker, are important components in the development of cancer. It is vital to develop diagnostic systems with the ability to rapidly quantify DNA methylation with high sensitivity and selectivity. However, the analysis of DNA methylation must address two main challenges: (i) ultralow abundance and (ii) differentiating methylated cytosine from normal cytosine on target DNA sequence in the presence of an overwhelming background of circulating cell-free DNA. Here we report the development of an ultrasensitive and highly-selective electrochemical biosensor for the rapid detection of DNA methylation in blood. The sensing of DNA methylation involves the hybridization on a network of probe DNA modified gold-coated magnetic nanoparticles (DNA-Au@MNPs) complementary to target DNA, and subsequently enzymatic cleavage to differentiate methylated DNA strands from corresponding unmethylated DNA strands. The biosensor presents a dynamic range from 2 aM to 20 nM for 110 nucleotide DNA sequences containing a single-site methylation with the lowest detected concentration of 2 aM. This DNA-Au@MNPs based sensor provides a promising method to achieve 35 min response time and minimally invasive diagnosis of ovarian cancer.
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Affiliation(s)
- Dongfei Chen
- School of Chemistry, Australian Centre for NanoMedicine, and Australian Research Council Centre of Excellence in Convergent Bio-Nano Science and Technology, The University of New South Wales, Sydney, New South Wales, 2052, Australia
| | - Yanfang Wu
- School of Chemistry, Australian Centre for NanoMedicine, and Australian Research Council Centre of Excellence in Convergent Bio-Nano Science and Technology, The University of New South Wales, Sydney, New South Wales, 2052, Australia.
| | - Richard D Tilley
- School of Chemistry, Australian Centre for NanoMedicine, Electron Microscope Unit, Mark Wainwright Analytical Centre, The University of New South Wales, Sydney, NSW, 2052, Australia
| | - J Justin Gooding
- School of Chemistry, Australian Centre for NanoMedicine, and Australian Research Council Centre of Excellence in Convergent Bio-Nano Science and Technology, The University of New South Wales, Sydney, New South Wales, 2052, Australia.
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15
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Xu Y, Hong M, Kong D, Deng J, Zhong Z, Liang J. Ferroptosis-associated DNA methylation signature predicts overall survival in patients with head and neck squamous cell carcinoma. BMC Genomics 2022; 23:63. [PMID: 35042463 PMCID: PMC8767683 DOI: 10.1186/s12864-022-08296-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Accepted: 01/05/2022] [Indexed: 01/12/2023] Open
Abstract
Background Head and neck squamous cell carcinoma (HNSCC) is a common cancer characterized by late diagnosis and poor prognosis. The aim of this study was to identify a novel ferroptosis-related DNA methylation signature as an alternative diagnosis index for patients with HNSCC. Methods Methylome and transcriptome data of 499 HNSCC patients, including 275 oral squamous cell carcinoma (OSCC) samples, were obtained from The Cancer Genome Atlas (TCGA). An additional independent methylation dataset of 50 OSCC patients from the NCBI Gene Expression Omnibus (GEO) database was used for validation. As an index of ferroptosis activity, the ferroptosis score (FS) of each patient was inferred from the transcriptome data using single-sample gene set enrichment analysis. Univariate, multivariate, and LASSO Cox regression analyses were used to select CpG sites for the construction of a ferroptosis-related DNA methylation signature for diagnosis of patients. Results We initially inferred the FS of each TCGA HNSCC patient and divided the samples into high- and low-FS subgroups. Results showed that the high-FS subgroup displayed poor overall survival. Moreover, 378 differentially methylated CpG sites (DMCs) were identified between the two HNSCC subgroups, with 16 selected to construct a 16-DNA methylation signature for risk prediction in HNSCC patients using the LASSO and multivariate Cox regression models. Relative operating characteristic (ROC) curve analysis showed great predictive efficiency for 1-, 3-, and 5-year HNSCC survival using the 16-DNA methylation signature. Its predictive efficiency was also observed in OSCC patients from the TCGA and GEO databases. In addition, we found that the signature was associated with the fractions of immune types in the tumor immune microenvironment (TIME), suggesting potential interactions between ferroptosis and TIME in HNSCC progression. Conclusions We established a novel ferroptosis-related 16-DNA methylation signature that could be applied as an alternative tool to predict prognosis outcome in patients with HNSCC, including OSCC. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08296-z.
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16
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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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Malik JA, Lone R. Heat shock proteins with an emphasis on HSP 60. Mol Biol Rep 2021; 48:6959-6969. [PMID: 34498161 DOI: 10.1007/s11033-021-06676-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 08/23/2021] [Indexed: 02/08/2023]
Abstract
Heat shock phenomenon is a process by which cells express a set of proteins called heat shock proteins (HSPs) against heat stress. HSPs include several families depending upon the molecular weight of the respective protein. Among the different HSPs, The HSP60 is one of the main components representing the framework of chaperone system. HSP60 plays a myriad number of roles like chaperoning, thermotolerance, apoptosis, cancer, immunology and embryonic development. In this review we discussed briefly the general knowledge and focussed on HSP60 in terms of structure, regulation and function in various physiological and pathological conditions.
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Affiliation(s)
- Javid Ahmad Malik
- Pharmacology and Toxicology Laboratory, Department of Zoology, Guru Ghasidas Vishwavidyalaya, Bilaspur, Chhattisgarh, India
| | - Rafiq Lone
- Department of Botany, Central University of Kashmir, Jammu and Kashmir, India.
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18
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Wu Y, Sa Y, Guo Y, Li Q, Zhang N. Identification of WHO II/III gliomas by 16 prognostic-related gene signatures using machine learning methods. Curr Med Chem 2021; 29:1622-1639. [PMID: 34455959 DOI: 10.2174/0929867328666210827103049] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 05/27/2021] [Accepted: 05/28/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND It is found that the prognosis of gliomas of the same grade has large differences among World Health Organization(WHO) grade II and III in clinical observation. Therefore, a better understanding of the genetics and molecular mechanisms underlying WHO grade II and III gliomas is required, with the aim of developing a classification scheme at the molecular level rather than the conventional pathological morphology level. METHOD We performed survival analysis combined with machine learning methods of Least Absolute Shrinkage and Selection Operator using expression datasets downloaded from the Chinese Glioma Genome Atlas as well as The Cancer Genome Atlas. Risk scores were calculated by the product of expression level of overall survival-related genes and their multivariate Cox proportional hazards regression coefficients. WHO grade II and III gliomas were categorized into the low-risk subgroup, medium-risk subgroup, and high-risk subgroup. We used the 16 prognostic-related genes as input features to build a classification model based on prognosis using a fully connected neural network. Gene function annotations were also performed. RESULTS The 16 genes (AKNAD1, C7orf13, CDK20, CHRFAM7A, CHRNA1, EFNB1, GAS1, HIST2H2BE, KCNK3, KLHL4, LRRK2, NXPH3, PIGZ, SAMD5, ERINC2, and SIX6) related to the glioma prognosis were screened. The 16 selected genes were associated with the development of gliomas and carcinogenesis. The accuracy of an external validation data set of the fully connected neural network model from the two cohorts reached 95.5%. Our method has good potential capability in classifying WHO grade II and III gliomas into low-risk, medium-risk, and high-risk subgroups. The subgroups showed significant (P<0.01) differences in overall survival. CONCLUSION This resulted in the identification of 16 genes that were related to the prognosis of gliomas. Here we developed a computational method to discriminate WHO grade II and III gliomas into three subgroups with distinct prognoses. The gene expression-based method provides a reliable alternative to determine the prognosis of gliomas.
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Affiliation(s)
- YaMeng Wu
- Department of Biomedical Engineering, Tianjin Key Lab of BME Measurement, Tianjin University, Tianjin. China
| | - Yu Sa
- Department of Biomedical Engineering, Tianjin Key Lab of BME Measurement, Tianjin University, Tianjin. China
| | - Yu Guo
- Department of Biomedical Engineering, Tianjin Key Lab of BME Measurement, Tianjin University, Tianjin. China
| | - QiFeng Li
- Department of Biomedical Engineering, Tianjin Key Lab of BME Measurement, Tianjin University, Tianjin. China
| | - Ning Zhang
- Department of Biomedical Engineering, Tianjin Key Lab of BME Measurement, Tianjin University, Tianjin. China
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Chen H, Li H, Wang L, Li Y, Yang C. A 5-gene DNA methylation signature is a promising prognostic biomarker for early-stage cervical cancer. J OBSTET GYNAECOL 2021; 42:327-332. [PMID: 34082663 DOI: 10.1080/01443615.2021.1907563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
The demographic information and overall survival (OS) of patients with cervical cancer (CC) (pathological stage: IA-IIA) were extracted from the TCGA database. A univariate and multivariate Cox proportional hazard model was performed to identify methylation markers significantly associated with the OS of patients in the training dataset. Then such a prognostic classifier was tested on the validation set and all subgroups. The Kaplan-Meier analysis and ROC analysis were performed to detect the ability to discriminate between patients with different risks and different OS. A DNA methylation signature which contained five genes was found to be significantly associated with the OS of CC patients by the Cox regression analysis in the training dataset. Such a signature could efficiently distinguish the patients into two risk groups with significantly different OS in both datasets. The receiver operating characteristic (ROC) analysis showed it had high sensitivity and specificity. Moreover, such a prognostic model also could be effectively applied to different subgroups, including groups of different ages, tumour sizes, histologic types, etc. A 5-DNA methylation signature identified by this study may act as a novel prognostic indicator for early-stage CC, and it may be helpful for the timely diagnosis and intervention of CC at pathological stages IA-IIA.Impact StatementWhat is already known on this subject? Cervical cancer (CC) is one of the most common gynaecological malignant tumours.What the results of this study add? This study constructed a risk model based on a 5-DNA methylation signature for early-stage CC patients' survival prediction.What the implications are of these findings for clinical practice and/or further research? Methylated markers have the potential to discriminate patients of different risks and different OS. Our results may shed new light on the early diagnosis and intervention, and potential therapeutic targets for CC patients at pathological stages IA-IIA.
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Affiliation(s)
- Hongxia Chen
- Department of Pathophysiology, School of Basic Medicine, Hubei University of Science and Technology, Xianning, China
| | - Hongying Li
- Maternal and Child Health Hospital of Hubei Province, Hongshan District, Wuhan, Hubei, China.,Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Wuhan University of Science and Technology, Wuhan, Hubei, China
| | - Lei Wang
- School of Laboratory Medicine, Hubei University of Chinese Medicine, Wuhan, China
| | - Yaxiong Li
- Information Center of Hubei University of Science and Technology, Xianning, China
| | - ChunYan Yang
- Department of Public Health Management, School of Basic Medicine, Hubei University of Science and Technology, Xianning, China
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Wang H, Wei C, Pan P, Yuan F, Cheng J. Identification of a methylomics-associated nomogram for predicting overall survival of stage I-II lung adenocarcinoma. Sci Rep 2021; 11:9938. [PMID: 33976305 PMCID: PMC8113535 DOI: 10.1038/s41598-021-89429-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 04/26/2021] [Indexed: 11/30/2022] Open
Abstract
The aim of this paper was to identify DNA methylation based biomarkers for predicting overall survival (OS) of stage I–II lung adenocarcinoma (LUAD) patients. Methylation profile data of patients with stage I–II LUAD from The Cancer Genome Atlas (TCGA) database was used to determine methylation sites-based hallmark for stage I–II LUAD patients’ OS. The patients were separated into training and validation datasets by using median risk score as cutoff. Univariate Cox, least absolute shrinkage and selection operator (LASSO) and multivariate Cox analyses were employed to develop a DNA methylation signature for OS of patients with stage I–II LUAD. As a result, an 11-DNA methylation signature was determined to be critically associated with the OS of patients with stage I–II LUAD. Analysis of receiver operating characteristics (ROC) suggested a high prognostic effectiveness of the 11-DNA methylation signature in patients with stage I–II LUAD (AUC at 1, 3, 5 years in training set were (0.849, 0.879, 0.831, respectively), validation set (0.742, 0.807, 0.904, respectively), entire TCGA dataset (0.747, 0.818, 0.870, respectively). Kaplan–Meier survival analyses exhibited that survival was significantly longer in the low-risk cohort compared to the high-risk cohort in the training dataset (P = 7e − 07), in the validation dataset (P = 1e − 08), and in the all-cohort dataset (P = 6e − 14). In addition, a nomogram was developed based on molecular factor (methylation risk score) as well as clinical factors (age and cancer status) (AUC at 1, 3, 5 years entire TCGA dataset were 0.770, 0.849, 0.979, respectively). The result verified that our methylomics-associated nomogram had a strong robustness for predicting stage I–II LUAD patients’ OS. Furthermore, the nomogram combined clinical and molecular factors to determine an individualized probability of recurrence for patients with stage I–II LUAD, which stood for a major advance in the field of personalized medicine for pulmonary oncology. Collectively, we successfully identified a DNA methylation biomarker and a DNA methylation-based nomogram to predict the OS of patients with stage I–II LUAD.
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Affiliation(s)
- Heng Wang
- Department of Cardiothoracic Surgery, Zhengzhou Central Hospital Affiliated To Zhengzhou University, Zhengzhou, 450000, China
| | - Chuangye Wei
- Department of Thoracic Surgery, Zhengzhou Central Hospital Affiliated To Zhengzhou University, Zhengzhou, 450000, China
| | - Peng Pan
- Department of Mood Disorders, Nankai University Affiliated Anding Hospital, Tianjin Mental Health Center, Mental Health Teaching Hospital, Tianjin Medical University, Tianjin, 300222, China
| | - Fengfeng Yuan
- Department of Cardiothoracic Surgery, Zhengzhou Central Hospital Affiliated To Zhengzhou University, Zhengzhou, 450000, China
| | - Jiancheng Cheng
- Department of Cardiothoracic Surgery, Zhengzhou Central Hospital Affiliated To Zhengzhou University, Zhengzhou, 450000, China.
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Novel prognostic prediction model constructed through machine learning on the basis of methylation-driven genes in kidney renal clear cell carcinoma. Biosci Rep 2021; 40:225719. [PMID: 32633782 PMCID: PMC7374278 DOI: 10.1042/bsr20201604] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 06/24/2020] [Accepted: 07/06/2020] [Indexed: 02/06/2023] Open
Abstract
Kidney renal clear cell carcinoma (KIRC) is a common tumor with poor prognosis and is closely related to many aberrant gene expressions. DNA methylation is an important epigenetic modification mechanism and a novel research target. Thus, exploring the relationship between methylation-driven genes and KIRC prognosis is important. The methylation profile, methylation-driven genes, and methylation characteristics in KIRC was revealed through the integration of KIRC methylation, RNA-seq, and clinical information data from The Cancer Genome Atlas. The Lasso regression was used to establish a prognosis model on the basis of methylation-driven genes. Then, a trans-omics prognostic nomogram was constructed and evaluated by combining clinical information and methylated prognosis model. A total of 242 methylation-driven genes were identified. The Gene Ontology terms of these methylation-driven genes mainly clustered in the activation, adhesion, and proliferation of immune cells. The methylation prognosis prediction model that was established using the Lasso regression included four genes in the methylation data, namely, FOXI2, USP44, EVI2A, and TRIP13. The areas under the receiver operating characteristic curve of 1-, 3-, and 5-year survival rates were 0.810, 0.824, and 0.799, respectively, in the training group and 0.794, 0.752, and 0.731, respectively, in the testing group. An easy trans-omics nomogram was successfully established. The C-indices of the nomogram in the training and the testing groups were 0.8015 and 0.8389, respectively. The present study revealed the overall perspective of methylation-driven genes in KIRC and can help in the evaluation of the prognosis of KIRC patients and provide new clues for further study.
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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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Suman M, Dugué PA, Wong EM, Joo JE, Hopper JL, Nguyen-Dumont T, Giles GG, Milne RL, McLean C, Southey MC. Association of variably methylated tumour DNA regions with overall survival for invasive lobular breast cancer. Clin Epigenetics 2021; 13:11. [PMID: 33461604 PMCID: PMC7814464 DOI: 10.1186/s13148-020-00975-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 11/10/2020] [Indexed: 12/12/2022] Open
Abstract
Background Tumour DNA methylation profiling has shown potential to refine disease subtyping and improve the diagnosis and prognosis prediction of breast cancer. However, limited data exist regarding invasive lobular breast cancer (ILBC). Here, we investigated the genome-wide variability of DNA methylation levels across ILBC tumours and assessed the association between methylation levels at the variably methylated regions and overall survival in women with ILBC. Methods Tumour-enriched DNA was prepared by macrodissecting formalin-fixed paraffin embedded (FFPE) tumour tissue from 130 ILBCs diagnosed in the participants of the Melbourne Collaborative Cohort Study (MCCS). Genome-wide tumour DNA methylation was measured using the HumanMethylation 450K (HM450K) BeadChip array. Variably methylated regions (VMRs) were identified using the DMRcate package in R. Cox proportional hazards regression models were used to assess the association between methylation levels at the ten most significant VMRs and overall survival. Gene set enrichment analyses were undertaken using the web-based tool Metaspace. Replication of the VMR and survival analysis findings was examined using data retrieved from The Cancer Genome Atlas (TCGA) for 168 ILBC cases. We also examined the correlation between methylation and gene expression for the ten VMRs of interest using TCGA data. Results We identified 2771 VMRs (P < 10−8) in ILBC tumours. The ten most variably methylated clusters were predominantly located in the promoter region of the genes: ISM1, APC, TMEM101, ASCL2, NKX6, HIST3H2A/HIST3H2BB, HCG4P3, HES5, CELF2 and EFCAB4B. Higher methylation level at several of these VMRs showed an association with reduced overall survival in the MCCS. In TCGA, all associations were in the same direction, however stronger than in the MCCS. The pooled analysis of the MCCS and TCGA data showed that methylation at four of the ten genes was associated with reduced overall survival, independently of age and tumour stage; APC: Hazard Ratio (95% Confidence interval) per one-unit M-value increase: 1.18 (1.02–1.36), TMEM101: 1.23 (1.02–1.48), HCG4P3: 1.37 (1.05–1.79) and CELF2: 1.21 (1.02–1.43). A negative correlation was observed between methylation and gene expression for CELF2 (R = − 0.25, P = 0.001), but not for TMEM101 and APC. Conclusions Our study identified regions showing greatest variability across the ILBC tumour genome and found methylation at several genes to potentially serve as a biomarker of survival for women with ILBC.
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Affiliation(s)
- Medha Suman
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, 3010, Australia.,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, 3168, Australia
| | - Pierre-Antoine Dugué
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, 3168, Australia.,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, 3004, Australia.,Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Ee Ming Wong
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, 3010, Australia.,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, 3168, Australia
| | - JiHoon Eric Joo
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - John L Hopper
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, 3004, Australia.,Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Tu Nguyen-Dumont
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, 3010, Australia.,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, 3168, Australia
| | - Graham G Giles
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, 3168, Australia.,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, 3004, Australia.,Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Roger L Milne
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, 3168, Australia.,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, 3004, Australia.,Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Catriona McLean
- Anatomical Pathology, Alfred Health, The Alfred Hospital, Melbourne, VIC, 3181, Australia
| | - Melissa C Southey
- Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, 3010, Australia. .,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, 3168, Australia. .,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, 3004, Australia.
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Hu J, Zhao FY, Huang B, Ran J, Chen MY, Liu HL, Deng YS, Zhao X, Han XF. An Eight-CpG-based Methylation Classifier for Preoperative Discriminating Early and Advanced-Late Stage of Colorectal Cancer. Front Genet 2021; 11:614160. [PMID: 33519917 PMCID: PMC7838682 DOI: 10.3389/fgene.2020.614160] [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: 10/05/2020] [Accepted: 12/14/2020] [Indexed: 11/28/2022] Open
Abstract
Aim To develop and validate a CpG-based classifier for preoperative discrimination of early and advanced-late stage colorectal cancer (CRC). Methods We identified an epigenetic signature based on methylation status of multiple CpG sites (CpGs) from 372 subjects in The Cancer Genome Atlas (TCGA) CRC cohort, and an external cohort (GSE48684) with 64 subjects by LASSO regression algorithm. A classifier derived from the methylation signature was used to establish a multivariable logistic regression model to predict the advanced-late stage of CRC. A nomogram was further developed by incorporating the classifier and some independent clinical risk factors, and its performance was evaluated by discrimination and calibration analysis. The prognostic value of the classifier was determined by survival analysis. Furthermore, the diagnostic performance of several CpGs in the methylation signature was evaluated. Results The eight-CpG-based methylation signature discriminated early stage from advanced-late stage CRC, with a satisfactory AUC of more than 0.700 in both the training and validation sets. This methylation classifier was identified as an independent predictor for CRC staging. The nomogram showed favorable predictive power for preoperative staging, and the C-index reached 0.817 (95% CI: 0.753–0.881) and 0.817 (95% CI: 0.721–0.913) in another training set and validation set respectively, with good calibration. The patients stratified in the high-risk group by the methylation classifier had significantly worse survival outcome than those in the low-risk group. Combination diagnosis utilizing only four of the eight specific CpGs performed well, even in CRC patients with low CEA level or at early stage. Conclusions Our classifier is a valuable predictive indicator that can supplement established methods for more accurate preoperative staging and also provides prognostic information for CRC patients. Besides, the combination of multiple CpGs has a high value in the diagnosis of CRC.
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Affiliation(s)
- Ji Hu
- Department of General Surgery, The First People's Hospital of Chongqing Liang Jiang New Area, Chongqing, China
| | - Fu-Ying Zhao
- Department of Medical Laboratory, The First People's Hospital of Chongqing Liang Jiang New Area, Chongqing, China
| | - Bin Huang
- Department of General Surgery, Daping Hospital, Army Medical University, Chongqing, China
| | - Jing Ran
- Department of Pathology, The First People's Hospital of Chongqing Liang Jiang New Area, Chongqing, China
| | - Mei-Yuan Chen
- Department of General Surgery, The First People's Hospital of Chongqing Liang Jiang New Area, Chongqing, China
| | - Hai-Lin Liu
- Department of Clinical Pharmacy, The First People's Hospital of Chongqing Liang Jiang New Area, Chongqing, China
| | - You-Song Deng
- Department of General Surgery, The First People's Hospital of Chongqing Liang Jiang New Area, Chongqing, China
| | - Xia Zhao
- Department of Microbiology, Army Medical University, Chongqing, China
| | - Xiao-Fan Han
- Department of General Surgery, The First People's Hospital of Chongqing Liang Jiang New Area, Chongqing, China
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25
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Zhao W, Rong Z, Wang W, Li S, Lu Y, Cao L, Zhang L, Yang K, Deng K, Yang C, Li K. Methylation biomarkers with discriminating ability are potential therapeutic targets in lung adenocarcinoma. Epigenomics 2020; 14:469-480. [PMID: 33290106 DOI: 10.2217/epi-2019-0142] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Aims: Given the reversibility of methylation, biomarkers with discriminating ability are of great interest for targeted therapeutic sites. Materials & methods: Methylation array data of 461 lung adenocarcinoma (LUAD) patients comprising of 458 tumor and 32 LUAD paracancerous samples were compared using partial least squares discrimination analysis and receiver operating characteristics analysis. Results: A six-DNA methylation signature (corresponding to five genes) was found to significantly discriminate normal and LUAD samples. Kyoto Encyclopedia of Genes and Genomes analysis indicated enrichment of methylation sites in the Wnt pathway in LUAD compared with controls. Conclusion: This six-DNA methylation signature demonstrated potential as a novel biomarker for diagnosis and therapeutic targets. Further, inhibition of Wnt signaling pathway may be an important step in LUAD progression.
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Affiliation(s)
- Weiwei Zhao
- Department of Epidemiology & Biostatistics, School of Public Health, Harbin Medical University, Harbin 150086, PR China
| | - Zhiwei Rong
- Department of Epidemiology & Biostatistics, School of Public Health, Harbin Medical University, Harbin 150086, PR China
| | - Wenjie Wang
- Department of Epidemiology & Biostatistics, School of Public Health, Harbin Medical University, Harbin 150086, PR China
| | - Shuang Li
- Department of Epidemiology & Biostatistics, School of Public Health, Harbin Medical University, Harbin 150086, PR China
| | - Yaxin Lu
- Department of Epidemiology & Biostatistics, School of Public Health, Harbin Medical University, Harbin 150086, PR China
| | - Lei Cao
- Department of Epidemiology & Biostatistics, School of Public Health, Harbin Medical University, Harbin 150086, PR China
| | - Liuchao Zhang
- Department of Epidemiology & Biostatistics, School of Public Health, Harbin Medical University, Harbin 150086, PR China
| | - Kai Yang
- Department of Epidemiology & Biostatistics, School of Public Health, Harbin Medical University, Harbin 150086, PR China
| | - Kui Deng
- Department of Epidemiology & Biostatistics, School of Public Health, Harbin Medical University, Harbin 150086, PR China
| | - Chunyan Yang
- Department of Epidemiology & Biostatistics, School of Public Health, Harbin Medical University, Harbin 150086, PR China
| | - Kang Li
- Department of Epidemiology & Biostatistics, School of Public Health, Harbin Medical University, Harbin 150086, PR China
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Sun J, Yu X, Xue L, Li S, Li J, Tong D, Du Y. TP53-Associated Ion Channel Genes Serve as Prognostic Predictor and Therapeutic Targets in Head and Neck Squamous Cell Carcinoma. Technol Cancer Res Treat 2020; 19:1533033820972344. [PMID: 33243093 PMCID: PMC7705194 DOI: 10.1177/1533033820972344] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
TP53 mutations are the most occurred mutation in HNSCC which might affect the ion channel genes. We aim to investigate the ion channel gene alteration under TP53 mutation and their prognostic implication. The overall mutation status of HNSCC were explored. By screening the TP53-associated ion channel genes (TICGs), an ion channel prognostic signature (ICPS) was established through a series of machine learning algorithms. The ICPS was then evaluated and its clinical significance was explored. 82 TICGs differentially expressed between TP53WT and TP53MUT were screened. Using univariate regression analysis and LASSO regression analysis and multivariate regression analysis, an ICPS containing 7 ion channel genes was established. A series of evaluation was carried out which proved the predictive ability of ICPS. Functional analysis of ICPS revealed that cancer-related pathways were enriched in high-risk group. Next, for clinical application, a nomogram was constructed based on ICPS and other independent clinicopathological factors. TP53 mutation status strongly affects the expression of ion channel genes. The ICPM we have identified is a strong indicator for HNSCC prognosis and could help with patient stratification as well as identification of novel drug targets.
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Affiliation(s)
- Jing Sun
- Department of Periodontology, Jinan Stomatological Hospital, Jinan, Shandong, China.,Jing Sun and Xijiao Yu contributed equally to this work
| | - Xijiao Yu
- Department of Endodontics, Jinan Stomatological Hospital, Jinan, Shandong, China.,Jing Sun and Xijiao Yu contributed equally to this work
| | - Lande Xue
- Department of Periodontology, Jinan Stomatological Hospital, Jinan, Shandong, China
| | - Shu Li
- Hospital of Stomatology, 12589Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Jinan, Shandong, China
| | - Jianxia Li
- Department of Periodontology, Jinan Stomatological Hospital, Jinan, Shandong, China
| | - Dongdong Tong
- Department of Oral and Maxillofacial, School and Hospital of Stomatology, 12589Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Jinan, Shandong, China
| | - Yi Du
- Department of Endodontics, Jinan Stomatological Hospital, Jinan, Shandong, China
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27
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The Development of Three-DNA Methylation Signature as a Novel Prognostic Biomarker in Patients with Colorectal Cancer. BIOMED RESEARCH INTERNATIONAL 2020; 2020:3497810. [PMID: 33294438 PMCID: PMC7714567 DOI: 10.1155/2020/3497810] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 10/18/2020] [Accepted: 10/28/2020] [Indexed: 11/25/2022]
Abstract
Aims The prognosis of colorectal cancer (CRC) remains poor. This study aimed to develop and validate DNA methylation-based signature model to predict overall survival of CRC patients. Methods The methylation array data of CRC patients were retrieved from The Cancer Genome Atlas (TCGA) database. These patients were divided into training and validation datasets. A risk score model was established based on Kaplan-Meier and multivariate Cox regression analysis of training cohort and tested in validation cohort. Results Among total 14,626 DNA methylation candidate markers, we found that a three-DNA methylation signature (NR1H2, SCRIB, and UACA) was significantly associated with overall survival of CRC patients. Subgroup analysis indicated that this signature could predict overall survival of CRC patients regardless of age and gender. Conclusions We established a prognostic model consisted of 3-DNA methylation sites, which could be used as potential biomarker to evaluate the prognosis of CRC patients.
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28
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Chen H, Ma X, Yang M, Wang M, Li L, Huang T. A methylomics-associated nomogram predicts recurrence-free survival of thyroid papillary carcinoma. Cancer Med 2020; 9:7183-7193. [PMID: 32783399 PMCID: PMC7541134 DOI: 10.1002/cam4.3388] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 07/13/2020] [Accepted: 07/22/2020] [Indexed: 12/12/2022] Open
Abstract
Background Thyroid papillary carcinoma (TPC) is the most common type of thyroid cancer (TC). The prognosis of TPC patients with tumor‐cell metastasis is poor. Therefore, this study aims to develop a model for predicting TPC patients' recurrence‐free survival (RFS). Methods We included 546 TPC patients who were clinically and pathologically diagnosed with TPC. The methylation biomarkers that associate with RFS were explored. These 546 samples were divided into training dataset (first 70%) and validation dataset (remaining 30%) randomly. The training dataset was used to identify prognostic biomarkers and construct risk prediction model, in addition, the validation dataset was used to verify the predictive performance of the model. We used Cox proportional hazard analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to identify the significant predictive biomarkers, and establish the relapse risk prediction model from the identified biomarkers. Results A 6‐DNA methylation signature yielded a high evaluative performance for RFS. The Kaplan‐Meier analysis indicated that the 6‐DNA methylation signature could significantly distinguish the high‐ and low‐risk patients in training, validation and entire sets. In addition, a nomogram was constructed based on risk score, metastasis status and residual tumor status, and C‐index, receiver operating characteristic (ROC) and the calibration plots analysis which demonstrated the good performance and clinical utility of the nomogram. Conclusions The results suggested that the 6‐DNA methylation signature is the independent prognostic marker for RFS and functioned as a significant tool for guiding the clinical treatment of TPC patients.
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Affiliation(s)
- Hengyu Chen
- Department of Pancreatic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,NHC Key Laboratory of Hormones and Development, Tianjin Institute of Endocrinology, Tianjin Medical University Chu Hsien-I Memorial Hospital, Tianjin, China
| | - Xianxiong Ma
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ming Yang
- Department of Pancreatic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Mengyi Wang
- Department of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lei Li
- Department of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tao Huang
- Department of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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29
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Ma X, Cheng J, Zhao P, Li L, Tao K, Chen H. DNA methylation profiling to predict recurrence risk in stage Ι lung adenocarcinoma: Development and validation of a nomogram to clinical management. J Cell Mol Med 2020; 24:7576-7589. [PMID: 32530136 PMCID: PMC7339160 DOI: 10.1111/jcmm.15393] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 04/23/2020] [Accepted: 04/27/2020] [Indexed: 12/16/2022] Open
Abstract
Increasing evidence suggested DNA methylation may serve as potential prognostic biomarkers; however, few related DNA methylation signatures have been established for prediction of lung cancer prognosis. We aimed at developing DNA methylation signature to improve prognosis prediction of stage I lung adenocarcinoma (LUAD). A total of 268 stage I LUAD patients from the Cancer Genome Atlas (TCGA) database were included. These patients were separated into training and internal validation datasets. GSE39279 was used as an external validation set. A 13‐DNA methylation signature was identified to be crucially relevant to the relapse‐free survival (RFS) of patients with stage I LUAD by the univariate Cox proportional hazard analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis and multivariate Cox proportional hazard analysis in the training dataset. The Kaplan‐Meier analysis indicated that the 13‐DNA methylation signature could significantly distinguish the high‐ and low‐risk patients in entire TCGA dataset, internal validation and external validation datasets. The receiver operating characteristic (ROC) analysis further verified that the 13‐DNA methylation signature had a better value to predict the RFS of stage I LUAD patients in internal validation, external validation and entire TCGA datasets. In addition, a nomogram combining methylomic risk scores with other clinicopathological factors was performed and the result suggested the good predictive value of the nomogram. In conclusion, we successfully built a DNA methylation‐associated nomogram, enabling prediction of the RFS of patients with stage I LUAD.
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Affiliation(s)
- Xianxiong Ma
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiancheng Cheng
- Department of Cardiovascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Peng Zhao
- Department of Hepatobiliary surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lei Li
- Department of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kaixiong Tao
- Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hengyu Chen
- Department of Pancreatic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.,NHC Key Laboratory of Hormones and Development, Tianjin Institute of Endocrinology, Tianjin Medical University Chu Hsien-I Memorial Hospital, Tianjin, China
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30
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Yang S, Wu Y, Wang S, Xu P, Deng Y, Wang M, Liu K, Tian T, Zhu Y, Li N, Zhou L, Dai Z, Kang H. HPV-related methylation-based reclassification and risk stratification of cervical cancer. Mol Oncol 2020; 14:2124-2141. [PMID: 32408396 PMCID: PMC7463306 DOI: 10.1002/1878-0261.12709] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 04/01/2020] [Accepted: 05/09/2020] [Indexed: 12/16/2022] Open
Abstract
Human papillomavirus (HPV) is a clear etiology of cervical cancer (CC). However, the associations between HPV infection and DNA methylation have not been thoroughly investigated. Additionally, it remains unknown whether HPV‐related methylation signatures can identify subtypes of CC and stratify the prognosis of CC patients. DNA methylation profiles were obtained from The Cancer Genome Atlas to identify HPV‐related methylation sites. Unsupervised clustering analysis of HPV‐related methylation sites was performed to determine the different CC subtypes. CC patients were categorized into cluster 1 (Methylation‐H), cluster 2 (Methylation‐M), and cluster 3 (Methylation‐L). Compared to Methylation‐M and Methylation‐L, Methylation‐H exhibited a significantly improved overall survival (OS). Gene set enrichment analysis (GSEA) was conducted to investigate the functions that correlated with different CC subtypes. GSEA indicated that the hallmarks of tumors, including KRAS signaling, TNFα signaling via NF‐κB, inflammatory response, epithelial–mesenchymal transition, and interferon‐gamma response, were enriched in Methylation‐M and Methylation‐L. Based on mutation and copy number variation analyses, we found that aberrant mutations, amplifications, and deletions among the MYC, Notch, PI3K‐AKT, and RTK‐RAS pathways were most frequently detected in Methylation‐H. Additionally, mutations, amplifications, and deletions within the Hippo, PI3K‐AKT, and TGF‐β pathways were presented in Methylation‐M. Genes within the cell cycle, Notch, and Hippo pathways possessed aberrant mutations, amplifications, and deletions in Methylation‐L. Moreover, the analysis of tumor microenvironments revealed that Methylation‐H was characterized by a relatively low degree of immune cell infiltration. Finally, a prognostic signature based on six HPV‐related methylation sites was developed and validated. Our study revealed that CC patients could be classified into three heterogeneous clusters based on HPV‐related methylation signatures. Additionally, we derived a prognostic signature using six HPV‐related methylation sites that stratified the OS of patients with CC into high‐ and low‐risk groups.
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Affiliation(s)
- Si Yang
- 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
| | - 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
| | - Shuqian Wang
- Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Peng Xu
- 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.,Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Meng Wang
- Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Kang Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Tian Tian
- Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yuyao Zhu
- 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
| | - Na Li
- 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
| | - Linghui Zhou
- 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
| | - 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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Wei B, Wang R, Wang L, Du C. Prognostic factor identification by analysis of the gene expression and DNA methylation data in glioma. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2020; 17:3909-3924. [PMID: 32987560 DOI: 10.3934/mbe.2020217] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Objective: This study was aimed to identify prognostic factors in glioma by analysis of the gene expression and DNA methylation data. Methods: The RNAseq and DNA methylation data associated with glioma were downloaded from GEO and TCGA databases to analyze the differentially expressed genes (DEGs) and methylated genes between tumor and normal tissues. Function and pathway analyses, co-expression network and survival analysis were performed based on these DEGs. The intersection genes of DEGs and differentially methylated genes were obtained followed by function analysis. Results: Total 2190 DEGs were identified between tumor and normal tissues, which were significantly enriched in neuron differentiation associated functions, as well as ribosome pathway. There were 6186 methylation sites (2834 up-regulated and 3352 down-regulated) with significant differences in tumor vs. normal. In the constructed co-expression network, DPP6, MAPK10 and RPL3 were hub genes. Survival analysis of 20 DEGs obtained 18 prognostic genes, among which 9 were differentially methylated, such as LHFPL tetraspan subfamily member 3 (LHFPL3), cadherin 20 (CDH20), complexin 2 (CPLX2), and tenascin R (TNR). The intersection of DEGs and differentially methylated genes (632 genes) were significantly enriched in functions of neuron differentiation. Conclusion: DPP6, MAPK10 and RPL3 may play important roles in tumorigenesis of glioma. Additionally, methylation of LHFPL3, CDH20, CPLX2, and TNR may serve as prognostic factors of glioma.
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Affiliation(s)
- Bo Wei
- Department of Neurosurgery, The Third Hospital of Jilin University, Changchun 130033, China
| | - Rui Wang
- Departments of Radiology, The Third Hospital of Jilin University, Changchun 130033, China
| | - Le Wang
- Departments of Ophthalmology, The Third Hospital of Jilin University, Changchun 130033, China
| | - Chao Du
- Department of Neurosurgery, The Third Hospital of Jilin University, Changchun 130033, China
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32
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Wang X, Wang D, Liu J, Feng M, Wu X. A novel CpG-methylation-based nomogram predicts survival in colorectal cancer. Epigenetics 2020; 15:1213-1227. [PMID: 32396412 DOI: 10.1080/15592294.2020.1762368] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Aberrant DNA methylation is significantly associated with the prognosis of patients with colorectal cancer (CRC). Therefore, the aim of this study was to develop a CpG-methylation-based nomogram for prognostic prediction in CRC. First, 378 CRC patients with methylation data from The Cancer Genome Atlas were randomly divided into training cohort (n = 249) and test cohort (n = 129). A multistep screening strategy was performed to identify six CpG sites that were significantly associated with overall survival in the training cohort. Then, Cox regression modelling was performed to construct a prognostic signature based on the candidate CpG sites. The six-CpG signature successfully separated patients into high-risk and low-risk groups in both training and test cohorts, and its performance was superior to that of previously published methylation markers (P < 0.05). Furthermore, we established a prognostic nomogram incorporating this signature, TNM stage, and age. The nomogram exhibited better prediction for overall survival in comparison with the three independent prognostic factors in the training cohort (C-index: 0.798 vs 0.620 to 0.737; P < 0.001). In the test cohort, the performance of nomogram was also superior to that of the three independent prognostic factors (C-index: 0.715 vs 0.590 to 0.665; P < 0.05). Meanwhile, the calibration curves for survival probability showed good agreement between prediction by nomogram and actual observation in both training and test cohorts. Together, the present study provides a novel CpG-methylation-based nomogram as a promising predictor for overall survival of CRC patients, which may help improve decision-making regarding the personalized treatments of patients with CRC.
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Affiliation(s)
- Xiaokang Wang
- Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital , Tianjin, China
| | - Danwen Wang
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Clinical Medical Research Center of Peritoneal Cancer of Wuhan, Key Laboratory of Tumor Biological Behavior of Hubei Province, Clinical Cancer Study Center of Hubei Province , Wuhan, China
| | - Jinfeng Liu
- Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital , Tianjin, China
| | - Maohui Feng
- Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Clinical Medical Research Center of Peritoneal Cancer of Wuhan, Key Laboratory of Tumor Biological Behavior of Hubei Province, Clinical Cancer Study Center of Hubei Province , Wuhan, China
| | - Xiongzhi Wu
- Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital , Tianjin, China.,Cancer Center, Tianjin Nankai Hospital , Tianjin, China
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Zhang J, Luo L, Dong J, Liu M, Zhai D, Huang D, Ling L, Jia X, Luo K, Zheng G. A prognostic 11-DNA methylation signature for lung squamous cell carcinoma. J Thorac Dis 2020; 12:2569-2582. [PMID: 32642165 PMCID: PMC7330303 DOI: 10.21037/jtd.2020.03.31] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Background Lung squamous cell carcinoma (LUSC), as the second frequent subtype of lung cancer, causes lots of mortalities primarily due to a lack of precise prognostic markers and timely treatment intervention. Previous studies have constructed several risk prognostic models based on DNA methylation sites in multiple tumors, whereas, DNA methylation signature of LUSC remains to be built, and its predictive value need to be evaluated. Methods The genome-wide DNA methylation data of LUSC samples was obtained from The Cancer Genome Atlas dataset. Univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) were implemented to identify DNA methylation sites related to overall survival of LUSC patients. Thus, we performed multivariate Cox regression to establish a DNA methylation signature. The Kaplan-Meier (K-M) survival curves and time-dependent receiver operating characteristic (ROC) curves were plotted to estimate the prognostic power of the signature. Comparison with other known prognostic biomarkers, our DNA methylation signature showed higher predictive specificity and sensitivity. In addition, multivariate Cox regression screened out independent prognostic factors and constructed a nomogram. Results Several statistical methods were performed to construct an 11-DNA methylation signature. LUSC patients were divided into low- and high-risk group based on risk score, and high-risk group had a shorter survival time. According to the results of K-M and ROC analyses, the 11-DNA methylation signature showed significant sensitivity and specificity in predicting the LUSC patients’ overall survival. Finally, we integrated some independent prognostic factors (risk score, metastasis stage, and tobacco smoking history) to construct a nomogram, which has excellent prognostic power and may provide guidance for the therapeutic strategies. Conclusions We constructed the first risk prognosis model based on DNA methylation site in LUSC, which showed better predictive ability. In addition, a nomogram integrating the DNA methylation signature, metastasis stage, and tobacco smoking history was developed.
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Affiliation(s)
- Jianlei Zhang
- Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou 510095, China
| | - Liyun Luo
- Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou 510095, China
| | - Jing Dong
- Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou 510095, China
| | - Meijun Liu
- Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou 510095, China
| | - Dongfeng Zhai
- Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou 510095, China
| | - Danqing Huang
- Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou 510095, China
| | - Li Ling
- Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou 510095, China
| | - Xiaoting Jia
- Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou 510095, China
| | - Kai Luo
- Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou 510095, China
| | - Guopei Zheng
- Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou 510095, China
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Maeda K, Sasaki H, Ueda S, Miyamoto S, Terada S, Konishi H, Kogata Y, Ashihara K, Fujiwara S, Tanaka Y, Tanaka T, Hayashi M, Ito Y, Kondo Y, Ochiya T, Ohmichi M. Serum exosomal microRNA-34a as a potential biomarker in epithelial ovarian cancer. J Ovarian Res 2020; 13:47. [PMID: 32336272 PMCID: PMC7184688 DOI: 10.1186/s13048-020-00648-1] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2019] [Accepted: 04/14/2020] [Indexed: 02/07/2023] Open
Abstract
Background Ovarian cancer (OC) is a leading cause of cancer-related death in women, and thus an accurate diagnosis of the predisposition and its early detection is necessary. The aims of this study were to determine whether serum exosomal microRNA-34a (miR-34a) in ovarian cancer could be used as a potential biomarker. Methods Exosomes from OC patients’ serum were collected, and exosomal miRNAs were extracted. The relative expression of miR-34a was calculated from 58 OC samples by quantitative real-time polymerase chain reaction. Results Serum exosomal miR-34a levels were significantly increased in early-stage OC patients compared with advanced-stage patients. Its levels were significantly lower in patients with lymph node metastasis than in those with no lymph node metastasis. Furthermore, its levels in the recurrence group were significantly lower than those in the recurrence-free group. Conclusions Serum exosomal miR-34a could be a potential biomarker for improving the diagnostic efficiency of OC.
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Affiliation(s)
- Kazuya Maeda
- Department of Obstetrics and Gynecology, Osaka Medical College, Osaka, Japan.
| | - Hiroshi Sasaki
- Department of Obstetrics and Gynecology, Osaka Medical College, Osaka, Japan
| | - Shoko Ueda
- Department of Obstetrics and Gynecology, Osaka Medical College, Osaka, Japan
| | - Shunsuke Miyamoto
- Department of Obstetrics and Gynecology, Osaka Medical College, Osaka, Japan
| | - Shinichi Terada
- Department of Obstetrics and Gynecology, Osaka Medical College, Osaka, Japan
| | - Hiromi Konishi
- Department of Obstetrics and Gynecology, Osaka Medical College, Osaka, Japan
| | - Yuhei Kogata
- Department of Obstetrics and Gynecology, Osaka Medical College, Osaka, Japan
| | - Keisuke Ashihara
- Department of Obstetrics and Gynecology, Osaka Medical College, Osaka, Japan
| | - Satoe Fujiwara
- Department of Obstetrics and Gynecology, Osaka Medical College, Osaka, Japan
| | - Yoshimichi Tanaka
- Department of Obstetrics and Gynecology, Osaka Medical College, Osaka, Japan
| | - Tomohito Tanaka
- Department of Obstetrics and Gynecology, Osaka Medical College, Osaka, Japan
| | - Masami Hayashi
- Department of Obstetrics and Gynecology, Osaka Medical College, Osaka, Japan
| | - Yuko Ito
- Department of Anatomy and Cell Biology, Osaka Medical College, Osaka, Japan
| | - Yoichi Kondo
- Department of Anatomy and Cell Biology, Osaka Medical College, Osaka, Japan
| | - Takahiro Ochiya
- Division of Molecular and Cellular Medicine, National Cancer Center Research Institute, Tokyo, Japan
| | - Masahide Ohmichi
- Department of Obstetrics and Gynecology, Osaka Medical College, Osaka, Japan
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Li C, Zheng Y, Pu K, Zhao D, Wang Y, Guan Q, Zhou Y. A four-DNA methylation signature as a novel prognostic biomarker for survival of patients with gastric cancer. Cancer Cell Int 2020; 20:88. [PMID: 32206039 PMCID: PMC7085204 DOI: 10.1186/s12935-020-1156-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 02/26/2020] [Indexed: 12/24/2022] Open
Abstract
Background Gastric cancer (GC) is the fifth most frequently diagnosed cancer and the third leading cause of cancer-related mortality. Lack of prognostic indicators for patient survival hinders GC treatment and survival. Methods and results Methylation profile data of patients with GC obtained from The Cancer Genome Atlas (TCGA) database were analyzed to identify methylation sites as biomarkers for GC prognosis. The cohort was divided into training and validation sets. Univariate Cox, LASSO regression,and multivariate Cox analyses revealed a close correlation of a four-DNA methylation signature as a risk score model with the overall survival of patients with GC. The survival between high-risk and low-risk score patients with GC was significantly different. Analyses of receiver operating characteristics revealed a high prognostic accuracy of the four-DNA methylation signature in patients with GC. The subgroup analysis indicated that the accuracy included that for anatomical region, histologic grade, TNM stage, pathological stage, and sex. The GC prognosis based on the four-DNA methylation signature was more precise than that based on known biomarkers. Conclusions The four-DNA methylation signature could serve as a novel independent prognostic factor that could be an important tool to predict the prognostic outcome of GC patients. This potential must be verified in a large-scale population cohort study and through basic research studies.
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Affiliation(s)
- Chunmei Li
- 1Key Laboratory for Gastrointestinal Diseases, Gansu Province, The First Hospital of Lanzhou University, Lanzhou, China.,2Department of Oncology, The First Hospital of Lanzhou University, Lanzhou, China
| | - Ya Zheng
- 1Key Laboratory for Gastrointestinal Diseases, Gansu Province, The First Hospital of Lanzhou University, Lanzhou, China.,3Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou, China
| | - Ke Pu
- 1Key Laboratory for Gastrointestinal Diseases, Gansu Province, The First Hospital of Lanzhou University, Lanzhou, China.,3Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou, China
| | - Da Zhao
- 2Department of Oncology, The First Hospital of Lanzhou University, Lanzhou, China
| | - Yuping Wang
- 1Key Laboratory for Gastrointestinal Diseases, Gansu Province, The First Hospital of Lanzhou University, Lanzhou, China.,3Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou, China
| | - Quanlin Guan
- 4Department of Oncology Surgery, The First Hospital of Lanzhou University, Lanzhou, China
| | - Yongning Zhou
- 1Key Laboratory for Gastrointestinal Diseases, Gansu Province, The First Hospital of Lanzhou University, Lanzhou, China.,3Department of Gastroenterology, The First Hospital of Lanzhou University, Lanzhou, China
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Ha M, Kim J, Park SM, Hong CM, Han ME, Song P, Kang CD, Lee D, Kim YH, Hur J, Oh SO. Prognostic Role of Zinc Finger Homeobox 4 in Ovarian Serous Cystadenocarcinoma. Genet Test Mol Biomarkers 2020; 24:145-149. [PMID: 32105524 DOI: 10.1089/gtmb.2019.0185] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Abstract
Introduction: The zinc finger homeobox 4 (ZFHX4) protein is a crucial molecular regulator of tumor-initiating stem cell-like functions. Objective: This study aimed to determine the role of ZFHX4 in the progression of ovarian serous cystadenocarcinoma (OSC). Methods: Differential gene expression ZFHX4 among low-stage (stages I and II), high-stage (stages III and IV), low-grade (grades I and II), and high-grade (grades III and IV) OSC patients was identified using four independent cohorts from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). We compared ZFHX4 expression as a prognostic factor using Kaplan-Meier survival curves, multivariate analysis, the time-dependent area under the curve (AUC) of Uno's C-index, and the AUC of the receiver operating characteristics at 4 years post diagnosis. Results: ZFHX4 gene expression in high-stage tumors is significantly higher than in low-stage tumors (TCGA, p = 0.007; GSE9891, p = 0.001). A Kaplan-Meier analysis revealed that elevated expression of ZFHX4 was associated with a poor prognosis in OSC patients for all cohorts, regardless of stage and grade (TCGA, p = 1e-04; GSE9891, p = 0.0044; GSE13876, p = 0.00078; GSE26712, p = 0.039). Analysis of C-indices and the area under the receiver operating characteristic curve further supported this result (C-index: TCGA, 0.599; GSE9891, 0.642; GSE13876, 0.585; GSE26712, 0.597). Moreover, univariate and multivariate Cox hazards analyses confirmed the prognostic significance of ZFHX4 levels. Conclusion: Collectively, these findings suggest that ZFHX4 is a prognostic factor for OSC.
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Affiliation(s)
- Mihyang Ha
- Department of Anatomy, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Jayoung Kim
- Department of Convergence Medicine, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Su Min Park
- Department of Convergence Medicine, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Chae Mi Hong
- Department of Convergence Medicine, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Myoung-Eun Han
- Department of Anatomy, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Parkyong Song
- Department of Convergence Medicine, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Chi-Dug Kang
- Department of Convergence Medicine, Pusan National University School of Medicine, Yangsan, Republic of Korea.,Department of Biochemistry, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Dongjun Lee
- Department of Convergence Medicine, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Yun Hak Kim
- Department of Anatomy, Biomedical Research Institute, Pusan National University School of Medicine, Yangsan, Republic of Korea.,Department of Biomedical Informatics, Biomedical Research Institute, Pusan National University School of Medicine, Yangsan, Republic of Korea.,Biomedical Research Institute, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Jin Hur
- Department of Convergence Medicine, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Sae-Ock Oh
- Department of Anatomy, Pusan National University School of Medicine, Yangsan, Republic of Korea
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Xing L, Guo M, Zhang X, Zhang X, Liu F. A transcriptional metabolic gene-set based prognostic signature is associated with clinical and mutational features in head and neck squamous cell carcinoma. J Cancer Res Clin Oncol 2020; 146:621-630. [DOI: 10.1007/s00432-020-03155-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2019] [Accepted: 02/11/2020] [Indexed: 12/14/2022]
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38
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Xing L, Zhang X, Zhang X, Tong D. Expression scoring of a small-nucleolar-RNA signature identified by machine learning serves as a prognostic predictor for head and neck cancer. J Cell Physiol 2020; 235:8071-8084. [PMID: 31943178 PMCID: PMC7540035 DOI: 10.1002/jcp.29462] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Accepted: 01/07/2020] [Indexed: 02/05/2023]
Abstract
Head and neck squamous cell carcinoma (HNSCC) is a common malignancy with high mortality and poor prognosis due to a lack of predictive markers. Increasing evidence has demonstrated small nucleolar RNAs (snoRNAs) play an important role in tumorigenesis. The aim of this study was to identify a prognostic snoRNA signature of HNSCC. Survival-related snoRNAs were screened by Cox regression analysis (univariate, least absolute shrinkage and selection operator, and multivariate). The predictive value was validated in different subgroups. The biological functions were explored by coexpression analysis and gene set enrichment analysis (GSEA). One hundred and thirteen survival-related snoRNAs were identified, and a five-snoRNA signature predicted prognosis with high sensitivity and specificity. Furthermore, the signature was applicable to patients of different sexes, ages, stages, grades, and anatomic subdivisions. Coexpression analysis and GSEA revealed the five-snoRNA are involved in regulating malignant phenotype and DNA/RNA editing. This five-snoRNA signature is not only a promising predictor of prognosis and survival but also a potential biomarker for patient stratification management.
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Affiliation(s)
- Lu Xing
- Shandong Key Laboratory of Oral Tissue Regeneration, School of Stomatology, Shandong University, Jinan, Shandong, China
| | - Xiaoqi Zhang
- State Key Laboratory of Oral Disease, Department of Orthodontics, West China Hospital Stomatology, Sichuan University, Chengdu, Sichuan, China
| | - Xiaoqian Zhang
- Department of Stomatology, Haiyuan College of Kunming Medical University, Kunming, Yunnan, China
| | - Dongdong Tong
- Department of Oral and Maxillofacial Surgery, School and Hospital of Stomatology, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Jinan, Shandong, China
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39
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Zhang L, Zhang Z, Yu Z. Identification of a novel glycolysis-related gene signature for predicting metastasis and survival in patients with lung adenocarcinoma. J Transl Med 2019; 17:423. [PMID: 31847905 PMCID: PMC6916245 DOI: 10.1186/s12967-019-02173-2] [Citation(s) in RCA: 115] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 12/06/2019] [Indexed: 12/18/2022] Open
Abstract
Background Lung cancer (LC) is one of the most lethal and most prevalent malignant tumors, and its incidence and mortality are increasing annually. Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. Several biomarkers have been confirmed by data excavation to be related to metastasis, prognosis and survival. However, the moderate predictive effect of a single gene biomarker is not sufficient. Thus, we aimed to identify new gene signatures to better predict the possibility of LUAD. Methods Using an mRNA-mining approach, we performed mRNA expression profiling in large LUAD cohorts (n = 522) from The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) was performed, and connections between genes and glycolysis were found in the Cox proportional regression model. Results We confirmed a set of nine genes (HMMR, B4GALT1, SLC16A3, ANGPTL4, EXT1, GPC1, RBCK1, SOD1, and AGRN) that were significantly associated with metastasis and overall survival (OS) in the test series. Based on this nine-gene signature, the patients in the test series could be divided into high-risk and low-risk groups. Additionally, multivariate Cox regression analysis revealed that the prognostic power of the nine-gene signature is independent of clinical factors. Conclusion Our study reveals a connection between the nine-gene signature and glycolysis. This research also provides novel insights into the mechanisms underlying glycolysis and offers a novel biomarker of a poor prognosis and metastasis for LUAD patients.
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Affiliation(s)
- Lei Zhang
- Department of Breast Surgery, The First Hospital Affiliated China Medical University, No. 155 Nanjing Street, Heping District, Shenyang, 110001, Liaoning, China
| | - Zhe Zhang
- Department of Thoracic Surgery, The First Hospital Affiliated China Medical University, No. 155 Nanjing Street, Heping District, Shenyang, 110001, Liaoning, China
| | - Zhenglun Yu
- Department of Thoracic Surgery, The First Hospital Affiliated China Medical University, No. 155 Nanjing Street, Heping District, Shenyang, 110001, Liaoning, China.
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Singh A, Gupta S, Sachan M. Epigenetic Biomarkers in the Management of Ovarian Cancer: Current Prospectives. Front Cell Dev Biol 2019; 7:182. [PMID: 31608277 PMCID: PMC6761254 DOI: 10.3389/fcell.2019.00182] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Accepted: 08/19/2019] [Indexed: 12/15/2022] Open
Abstract
Ovarian cancer (OC) causes significant morbidity and mortality as neither detection nor screening of OC is currently feasible at an early stage. Difficulty to promptly diagnose OC in its early stage remains challenging due to non-specific symptoms in the early-stage of the disease, their presentation at an advanced stage and poor survival. Therefore, improved detection methods are urgently needed. In this article, we summarize the potential clinical utility of epigenetic signatures like DNA methylation, histone modifications, and microRNA dysregulation, which play important role in ovarian carcinogenesis and discuss its application in development of diagnostic, prognostic, and predictive biomarkers. Molecular characterization of epigenetic modification (methylation) in circulating cell free tumor DNA in body fluids offers novel, non-invasive approach for identification of potential promising cancer biomarkers, which can be performed at multiple time points and probably better reflects the prevailing molecular profile of cancer. Current status of epigenetic research in diagnosis of early OC and its management are discussed here with main focus on potential diagnostic biomarkers in tissue and body fluids. Rapid and point of care diagnostic applications of DNA methylation in liquid biopsy has been precluded as a result of cumbersome sample preparation with complicated conventional methods of isolation. New technologies which allow rapid identification of methylation signatures directly from blood will facilitate sample-to answer solutions thereby enabling next-generation point of care molecular diagnostics. To date, not a single epigenetic biomarker which could accurately detect ovarian cancer at an early stage in either tissue or body fluid has been reported. Taken together, the methodological drawbacks, heterogeneity associated with ovarian cancer and non-validation of the clinical utility of reported potential biomarkers in larger ovarian cancer populations has impeded the transition of epigenetic biomarkers from lab to clinical settings. Until addressed, clinical implementation as a diagnostic measure is a far way to go.
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Affiliation(s)
- Alka Singh
- Department of Biotechnology, Motilal Nehru National Institute of Technology, Allahabad, India
| | - Sameer Gupta
- Department of Surgical Oncology, King George Medical University, Lucknow, India
| | - Manisha Sachan
- Department of Biotechnology, Motilal Nehru National Institute of Technology, Allahabad, India
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Dvorská D, Braný D, Nagy B, Grendár M, Poka R, Soltész B, Jagelková M, Zelinová K, Lasabová Z, Zubor P, Danková Z. Aberrant Methylation Status of Tumour Suppressor Genes in Ovarian Cancer Tissue and Paired Plasma Samples. Int J Mol Sci 2019; 20:ijms20174119. [PMID: 31450846 PMCID: PMC6747242 DOI: 10.3390/ijms20174119] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 08/17/2019] [Accepted: 08/19/2019] [Indexed: 02/06/2023] Open
Abstract
Ovarian cancer is a highly heterogeneous disease and its formation is affected by many epidemiological factors. It has typical lack of early signs and symptoms, and almost 70% of ovarian cancers are diagnosed in advanced stages. Robust, early and non-invasive ovarian cancer diagnosis will certainly be beneficial. Herein we analysed the regulatory sequence methylation profiles of the RASSF1, PTEN, CDH1 and PAX1 tumour suppressor genes by pyrosequencing in healthy, benign and malignant ovarian tissues, and corresponding plasma samples. We recorded statistically significant higher methylation levels (p < 0.05) in the CDH1 and PAX1 genes in malignant tissues than in controls (39.06 ± 18.78 versus 24.22 ± 6.93; 13.55 ± 10.65 versus 5.73 ± 2.19). Higher values in the CDH1 gene were also found in plasma samples (22.25 ± 14.13 versus 46.42 ± 20.91). A similar methylation pattern with positive correlation between plasma and benign lesions was noted in the CDH1 gene (r = 0.886, p = 0.019) and malignant lesions in the PAX1 gene (r = 0.771, p < 0.001). The random forest algorithm combining methylation indices of all four genes and age determined 0.932 AUC (area under the receiver operating characteristic (ROC) curve) prediction power in the model classifying malignant lesions and controls. Our study results indicate the effects of methylation changes in ovarian cancer development and suggest that the CDH1 gene is a potential candidate for non-invasive diagnosis of ovarian cancer.
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Affiliation(s)
- Dana Dvorská
- Division of Molecular Medicine, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Dušan Braný
- Division of Molecular Medicine, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia.
| | - Bálint Nagy
- Department of Human Genetics, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary
| | - Marián Grendár
- Bioinformatic Unit, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Robert Poka
- Institute of Obstetrics and Gynecology, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary
| | - Beáta Soltész
- Department of Human Genetics, Faculty of Medicine, University of Debrecen, H-4032 Debrecen, Hungary
| | - Marianna Jagelková
- Department of Gynaecology and Obstetrics, Martin University Hospital, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
- Division of Oncology, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Katarína Zelinová
- Department of Gynaecology and Obstetrics, Martin University Hospital, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
- Division of Oncology, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Zora Lasabová
- Division of Oncology, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Pavol Zubor
- Department of Gynaecology and Obstetrics, Martin University Hospital, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
| | - Zuzana Danková
- Division of Oncology, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, 036 01 Martin, Slovakia
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Su YY, Sun L, Guo ZR, Li JC, Bai TT, Cai XX, Li WH, Zhu YF. Upregulated expression of serum exosomal miR-375 and miR-1307 enhance the diagnostic power of CA125 for ovarian cancer. J Ovarian Res 2019; 12:6. [PMID: 30670062 PMCID: PMC6341583 DOI: 10.1186/s13048-018-0477-x] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2018] [Accepted: 12/14/2018] [Indexed: 12/13/2022] Open
Abstract
Background Ovarian cancer (OC) is associated with high mortality in gynecological oncology; this is mainly due to the low diagnosis rate. Exosomal miRNA has demonstrated potential as a tumor biomarker. We aimed to explore the diagnostic potential of serum exosomal miR-1307 and miR-375 for OC. Methods The first six candidate miRNAs were selected from the previous literature. The relative quantification of qRT-PCR was used to screen for the stability of exosomal miRNAs, followed by validation of the cohort. ROC analysis was employed to analyze the specificity and sensitivity of exosomal miRNA. Results MiR-1307 and miR-375 were confirmed stably existing in serum exosomes of OC. Moreover, miR-1307 and miR-375 were both significantly up-regulated in serum exosomes of OC compared to ovarian benign and healthy groups. The overexpressed miRNAs showed independent diagnostic power and enhanced the diagnostic accuracy of traditional biomarkers when combined with CA-125 and HE4. MiR-1307 was associated with tumor staging, and miR-375 was associated with lymph node metastasis of OC. Conclusion Our results suggest that serum exosomal miR-1307 and miR-375 could serve as potential tumor biomarkers to improve diagnostic efficiency for OC.
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Affiliation(s)
- Ying Ying Su
- The Second Affiliated Hospital, Nanjing Medical University, Nanjing, 210011, Jiangsu, China
| | - Li Sun
- The Second Affiliated Hospital, Nanjing Medical University, Nanjing, 210011, Jiangsu, China
| | - Zhi Rui Guo
- The Second Affiliated Hospital, Nanjing Medical University, Nanjing, 210011, Jiangsu, China
| | - Jin Chang Li
- The Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Traditional Chinese Medicine, Nanjing, China
| | - Ting Ting Bai
- The Second Affiliated Hospital, Nanjing Medical University, Nanjing, 210011, Jiangsu, China
| | - Xiao Xiao Cai
- The Second Affiliated Hospital, Nanjing Medical University, Nanjing, 210011, Jiangsu, China
| | - Wen Han Li
- The Second Affiliated Hospital, Nanjing Medical University, Nanjing, 210011, Jiangsu, China
| | - Ye Fei Zhu
- The Second Affiliated Hospital, Nanjing Medical University, Nanjing, 210011, Jiangsu, China.
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