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Fawzy MS, Ibrahiem AT, Osman DM, Almars AI, Alshammari MS, Almazyad LT, Almatrafi NDA, Almazyad RT, Toraih EA. Angio-Long Noncoding RNA MALAT1 (rs3200401) and MIAT (rs1061540) Gene Variants in Ovarian Cancer. Epigenomes 2024; 8:5. [PMID: 38390896 PMCID: PMC10885055 DOI: 10.3390/epigenomes8010005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 01/04/2024] [Accepted: 01/23/2024] [Indexed: 02/24/2024] Open
Abstract
The genotyping of long non-coding RNA (lncRNA)-related single-nucleotide polymorphisms (SNPs) could be associated with cancer risk and/or progression. This study aimed to analyze the angiogenesis-related lncRNAs MALAT1 (rs3200401) and MIAT (rs1061540) variants in patients with ovarian cancer (OC) using "Real-Time allelic discrimination polymerase chain reaction" in 182 formalin-fixed paraffin-embedded (FFPE) samples of benign, borderline, and primary malignant ovarian tissues. Differences in the genotype frequencies between low-grade ovarian epithelial tumors (benign/borderline) and malignant tumors and between high-grade malignant epithelial tumors and malignant epithelial tumors other than high-grade serous carcinomas were compared. Odds ratios (ORs)/95% confidence intervals were calculated as measures of the association strength. Additionally, associations of the genotypes with the available pathological data were analyzed. The heterozygosity of MALAT1 rs3200401 was the most common genotype (47.8%), followed by C/C (36.3%). Comparing the study groups, no significant differences were observed regarding this variant. In contrast, the malignant epithelial tumors had a higher frequency of the MIAT rs1061540 C/C genotype compared to the low-grade epithelial tumor cohorts (56.7% vs. 37.6, p = 0.031). The same genotype was significantly higher in high-grade serous carcinoma than its counterparts (69.4% vs. 43.8%, p = 0.038). Multivariate Cox regression analysis showed that the age at diagnosis was significantly associated with the risk of OC development. In contrast, the MIAT T/T genotype was associated with a low risk of malignant epithelial tumors under the homozygote comparison model (OR = 0.37 (0.16-0.83), p = 0.017). Also, MIAT T allele carriers were less likely to develop high-grade serous carcinoma under heterozygote (CT vs. CC; OR = 0.33 (0.12-0.88), p = 0.027) and homozygote (TT vs. CC; OR = 0.26 (0.07-0.90), p = 0.034) comparison models. In conclusion, our data provide novel evidence for a potential association between the lncRNA MIAT rs1061540 and the malignant condition of ovarian cancer, suggesting the involvement of such lncRNAs in OC development.
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Affiliation(s)
- Manal S Fawzy
- Department of Biochemistry, Faculty of Medicine, Northern Border University, Arar 73213, Saudi Arabia
- Unit of Medical Research and Postgraduate Studies, Faculty of Medicine, Northern Border University, Arar 73213, Saudi Arabia
| | - Afaf T Ibrahiem
- Department of Pathology, Faculty of Medicine, Northern Border University, Arar 73213, Saudi Arabia
| | - Dalia Mohammad Osman
- Department of Medical Laboratories Technology, Faculty of Applied Medical Sciences, Northern Border University, Arar 73213, Saudi Arabia
| | - Amany I Almars
- Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Hematology Research Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | | | | | | | - Renad Tariq Almazyad
- Faculty of Applied Medical Sciences, Northern Border University, Arar 73213, Saudi Arabia
| | - Eman A Toraih
- Division of Endocrine and Oncologic Surgery, Department of Surgery, School of Medicine, Tulane University, New Orleans, LA 70112, USA
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Gao C, He Z, Li J, Li X, Bai Q, Zhang Z, Zhang X, Wang S, Xiao X, Wang F, Yan Y, Li D, Chen L, Zeng X, Xiao Y, Dong G, Zheng Y, Wang Q, Chen W. Specific long non-coding RNAs response to occupational PAHs exposure in coke oven workers. Toxicol Rep 2016; 3:160-166. [PMID: 28959535 PMCID: PMC5615781 DOI: 10.1016/j.toxrep.2015.12.011] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2015] [Revised: 12/29/2015] [Accepted: 12/29/2015] [Indexed: 11/21/2022] Open
Abstract
To explore whether the alteration of lncRNA expression is correlated with polycyclic aromatic hydrocarbons (PAHs) exposure and DNA damage, we examined PAHs external and internal exposure, DNA damage and lncRNAs (HOTAIR, MALAT1, TUG1 and GAS5) expression in peripheral blood lymphocytes (PBLCs) of 150 male coke oven workers and 60 non-PAHs exposure workers. We found the expression of HOTAIR, MALAT1, and TUG1 were enhanced in PBLCs of coke oven workers and positively correlated with the levels of external PAHs exposure (adjusted Ptrend < 0.001 for HOTAIR and MALAT1, adjusted Ptrend = 0.006 for TUG1). However, only HOTAIR and MALAT1 were significantly associated with the level of internal PAHs exposure (urinary 1-hydroxypyrene) with adjusted β = 0.298, P = 0.024 for HOTAIR and β = 0.090, P = 0.034 for MALAT1. In addition, the degree of DNA damage was positively associated with MALAT1 and HOTAIR expression in PBLCs of all subjects (adjusted β = 0.024, P = 0.002 for HOTAIR and β = 0.007, P = 0.003 for MALAT1). Moreover, we revealed that the global histone 3 lysine 27 trimethylation (H3K27me3) modification was positively associated with the degree of genetic damage (β = 0.061, P < 0.001) and the increase of HOTAIR expression (β = 0.385, P = 0.018). Taken together, our findings suggest that altered HOTAIR and MALAT1 expression might be involved in response to PAHs-induced DNA damage.
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Affiliation(s)
- Chen Gao
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Zhini He
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Jie Li
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xiao Li
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Qing Bai
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Zhengbao Zhang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xiao Zhang
- Key Laboratory of Chemical Safety and Health, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shan Wang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xinhua Xiao
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Fangping Wang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yan Yan
- Department of Nutrition, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Daochuan Li
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Liping Chen
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xiaowen Zeng
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yongmei Xiao
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Guanghui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yuxin Zheng
- Key Laboratory of Chemical Safety and Health, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Qing Wang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Wen Chen
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
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