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Wei X, Sun D, Gao J, Zhang J, Zhu M, Yu C, Ma Z, Fu Y, Ji C, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Jin G, Chen Z, Hu Z, Li L, Shen H, Lv J, Ma H. Development and evaluation of a polygenic risk score for lung cancer in never-smoking women: A large-scale prospective Chinese cohort study. Int J Cancer 2024; 154:807-815. [PMID: 37846649 DOI: 10.1002/ijc.34765] [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: 06/02/2023] [Revised: 08/30/2023] [Accepted: 09/13/2023] [Indexed: 10/18/2023]
Abstract
The proportion of lung cancer in never smokers is rising, especially among Asian women, but there is no effective early detection tool. Here, we developed a polygenic risk score (PRS), which may help to identify the population with higher risk of lung cancer in never-smoking women. We first performed a large GWAS meta-analysis (8595 cases and 8275 controls) to systematically identify the susceptibility loci for lung cancer in never-smoking Asian women and then generated a PRS using GWAS datasets. Furthermore, we evaluated the utility and effectiveness of PRS in an independent Chinese prospective cohort comprising 55 266 individuals. The GWAS meta-analysis identified eight known loci and a novel locus (5q11.2) at the genome-wide statistical significance level of P < 5 × 10-8 . Based on the summary statistics of GWAS, we derived a polygenic risk score including 21 variants (PRS-21) for lung cancer in never-smoking women. Furthermore, PRS-21 had a hazard ratio (HR) per SD of 1.29 (95% CI = 1.18-1.41) in the prospective cohort. Compared with participants who had a low genetic risk, those with an intermediate (HR = 1.32, 95% CI: 1.00-1.72) and high (HR = 2.09, 95% CI: 1.56-2.80) genetic risk had a significantly higher risk of incident lung cancer. The addition of PRS-21 to the conventional risk model yielded a modest significant improvement in AUC (0.697 to 0.711) and net reclassification improvement (24.2%). The GWAS-derived PRS-21 significantly improves the risk stratification and prediction accuracy for incident lung cancer in never-smoking Asian women, demonstrating the potential for identification of high-risk individuals and early screening.
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Affiliation(s)
- Xiaoxia Wei
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Jiaxin Gao
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jing Zhang
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Meng Zhu
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Zhimin Ma
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yating Fu
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Chen Ji
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Iona Y Millwood
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Robin G Walters
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Guangfu Jin
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Zhibin Hu
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- State Key Laboratory of Reproductive Medicine, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Hongbing Shen
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Hongxia Ma
- Department of Epidemiology and Biostatistics, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
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The roles of MASPIN expression and subcellular localization in non-small cell lung cancer. Biosci Rep 2021; 40:224103. [PMID: 32391558 PMCID: PMC7251327 DOI: 10.1042/bsr20200743] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 04/29/2020] [Accepted: 05/01/2020] [Indexed: 02/06/2023] Open
Abstract
Accumulating studies have confirmed that mammary serine protease inhibitor (MASPIN) plays an essential role in non-small cell lung cancer (NSCLC). However, results are still controversial or inconsistent. In the present study, we attempted to identify the clinical significance of MASPIN and its potential molecular roles in NSCLC. The correlation of MASPIN with prognosis and clinicopathological characteristics was assessed by meta-analysis. Additionally, the potential molecular mechanisms of MASPIN in NSCLC was also investigated through several online databases. A total of 2220 NSCLC patients from 12 high quality studies were included and the results indicated that up-regulated MASPIN nucleus and cytoplasm expression was associated with poor overall survival (OS) (hazard ratio (HR) = 1.43, 95% confidence interval (CI) = 1.01–2.04, P<0.05), elevated MASPIN cytoplasm expression was associated with poor OS (HR = 1.45, 95% CI = 1.01–2.07, P<0.05), disease-free survival (DFS) (HR = 1.95, 95% CI = 1.31–2.88, P=0.001), and disease-specific survival (DSS) (HR = 2.17, 95% CI = 1.18–3.99, P=0.013). MASPIN both nucleus and cytoplasm location were associated with clinicopathological characteristics. Bioinformatics analysis validated the above results and suggested that human serpin family B member 5 (SERPINB5) hypomethylated levels were negatively correlated with its mRNA expression. Bioinformatics analysis also revealed the 85 most frequently altered neighboring genes of SERPINB5, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed 20 GO terms and 3 KEGG pathways with statistical significance. MASPIN had a statistically negative correlation with NSCLC prognosis, functioning as an oncoprotein by hypomethylation and influencing specific pathways involving the 85 genes identified herein. MASPIN might be a promising prognostic signature in NSCLC.
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Hsien Lai S, Zervoudakis G, Chou J, Gurney ME, Quesnelle KM. PDE4 subtypes in cancer. Oncogene 2020; 39:3791-3802. [PMID: 32203163 PMCID: PMC7444459 DOI: 10.1038/s41388-020-1258-8] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 03/02/2020] [Accepted: 03/03/2020] [Indexed: 12/22/2022]
Abstract
Cyclic nucleotide phosphodiesterases (PDE) break down cyclic nucleotides such as cAMP and cGMP, reducing the signaling of these important intracellular second messengers. Several unique families of phosphodiesterases exist, and certain families are clinically important modulators of vasodilation. In the current work, we have summarized the body of literature that describes an emerging role for the PDE4 subfamily of phosphodiesterases in malignancy. We have systematically investigated PDE4A, PDE4B, PDE4C, and PDE4D isoforms and found evidence associating them with several cancer types including hematologic malignancies and lung cancers, among others. In this review, we compare the evidence examining the functional role of each PDE4 subtype across malignancies, looking for common signaling themes, signaling pathways, and establishing the case for PDE4 subtypes as a potential therapeutic target for cancer treatment.
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Affiliation(s)
- Samuel Hsien Lai
- Department of Biomedical Sciences, Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, MI, USA
| | - Guston Zervoudakis
- Department of Biomedical Sciences, Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, MI, USA
| | - Jesse Chou
- Department of Biomedical Sciences, Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, MI, USA
| | | | - Kelly M Quesnelle
- Department of Biomedical Sciences, Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, MI, USA.
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Yang X, Huang WT, He RQ, Ma J, Lin P, Xie ZC, Ma FC, Chen G. Determining the prognostic significance of alternative splicing events in soft tissue sarcoma using data from The Cancer Genome Atlas. J Transl Med 2019; 17:283. [PMID: 31443718 PMCID: PMC6708253 DOI: 10.1186/s12967-019-2029-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Accepted: 08/18/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Surgery, adjuvant chemotherapy, and radiotherapy are the primary treatment options for soft tissue sarcomas (STSs). However, identifying ways to improve the prognosis of patients with STS remains a considerable challenge. Evidence shows that the dysregulation of alternative splicing (AS) events is involved in tumor pathogenesis and progression. The present study objective was to identify survival-associated AS events that could serve as prognostic biomarkers and potentially serve as tumor-selective STS drug targets. METHODS STS-specific 'percent spliced in' (PSI) values for splicing events in 206 STS samples were downloaded from The Cancer Genome Atlas SpliceSeq® database. Prognostic analyses were performed on seven types of AS events to determine their prognostic value in STS patients, for which prediction models were constructed with the risk score formula [Formula: see text]. Prediction models were also constructed to determine the prognostic value of AS events, and Spearman's rank correlation coefficients were calculated to determine the degree of correlation between splicing factor expression and the PSI values. RESULTS A total 10,439 events were found to significantly correlate with patient survival rates. The area under the time-dependent receiver operating characteristic curve for the prognostic predictor of STS overall survival was 0.826. Notably, the splicing events of certain STS key genes were significantly associated with STS 2-year overall survival in the present study, including exon skip (ES) events in MDM2 and EWSR1, alternate terminator events in CDKN2A and HMGA2 for dedifferentiated liposarcoma, ES in MDM2 and alternate promoter events in CDKN2A for leiomyosarcoma, and ES in EWSR1 for undifferentiated pleomorphic sarcoma. Moreover, splicing correlation networks between AS events and splicing factors revealed that almost all of the AS events showed negatively correlations with the expression of splicing factors. CONCLUSION An in-depth analysis of alternative RNA splicing could provide new insights into the mechanisms of STS oncogenesis and the potential for novel approaches to this type of cancer therapy.
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Affiliation(s)
- Xia Yang
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Wen-Ting Huang
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Rong-Quan He
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Jie Ma
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Peng Lin
- Department of Medical Ultrasonics, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Zu-Cheng Xie
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Fu-Chao Ma
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China
| | - Gang Chen
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.
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Ma FC, He RQ, Lin P, Zhong JC, Ma J, Yang H, Hu XH, Chen G. Profiling of prognostic alternative splicing in melanoma. Oncol Lett 2019; 18:1081-1088. [PMID: 31423168 PMCID: PMC6607279 DOI: 10.3892/ol.2019.10453] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Accepted: 04/12/2019] [Indexed: 12/18/2022] Open
Abstract
Alternative splicing can lead to the coding of proteins that act as promoters of cancer, which is associated with the progression of cancer. However, to the best of our knowledge, no systematic survival analysis of alternative splicing in melanoma has previously been reported. The present study conducted an in-depth analysis of integrated alternative splicing events detected in 96 patients with melanoma using data obtained from The Cancer Genome Atlas. Prognostic models and an alternative splicing correlation network were built for patients with melanoma. A total of 41,446 mRNA splicing events were detected in 9,780 genes and 2,348 alternative splicing events were identified to be significantly associated with overall survival of patients with melanoma. Of all the events used in the prognostic model, the model with alternate terminator alternative splicing events exhibited the highest efficiency for evaluating the outcome of patients with melanoma, with an area under the curve of 0.902. The present study identified prognostic predictors for melanoma and revealed alternative splicing networks in melanoma that could indicate underlying mechanisms.
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Affiliation(s)
- Fu-Chao Ma
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Rong-Quan He
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Peng Lin
- Ultrasonics Division of Radiology Department, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Jin-Cai Zhong
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Jie Ma
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Hong Yang
- Ultrasonics Division of Radiology Department, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Xiao-Hua Hu
- Department of Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Gang Chen
- Department of Pathology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
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Baty F, Joerger M, Früh M, Klingbiel D, Zappa F, Brutsche M. 24h-gene variation effect of combined bevacizumab/erlotinib in advanced non-squamous non-small cell lung cancer using exon array blood profiling. J Transl Med 2017; 15:66. [PMID: 28359318 PMCID: PMC5372268 DOI: 10.1186/s12967-017-1174-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 03/27/2017] [Indexed: 11/10/2022] Open
Abstract
Background The SAKK 19/05 trial investigated the safety and efficacy of the combined targeted therapy bevacizumab and erlotinib (BE) in unselected patients with advanced non-squamous non-small cell lung cancer (NSCLC). Although activating EGFR mutations were the strongest predictors of the response to BE, some patients not harboring driver mutations could benefit from the combined therapy. The identification of predictive biomarkers before or short after initiation of therapy is therefore paramount for proper patient selection, especially among EGFR wild-types. The first aim of this study was to investigate the early change in blood gene expression in unselected patients with advanced non-squamous NSCLC treated by BE. The second aim was to assess the predictive value of blood gene expression levels at baseline and 24h after BE therapy. Methods Blood samples from 43 advanced non-squamous NSCLC patients taken at baseline and 24h after initiation of therapy were profiled using Affymetrix’ exon arrays. The 24h gene dysregulation was investigated in the light of gene functional annotations using gene set enrichment analysis. The predictive value of blood gene expression levels was assessed and validated using an independent dataset. Results Significant gene dysregulations associated with the 24h-effect of BE were detected from blood-based whole-genome profiling. BE had a direct effect on “Pathways in cancer”, by significantly down-regulating genes involved in cytokine–cytokine receptor interaction, MAPK signaling pathway and mTOR signaling pathway. These pathways contribute to phenomena of evasion of apoptosis, proliferation and sustained angiogenesis. Other signaling pathways specifically reflecting the mechanisms of action of erlotinib and the anti-angiogenesis effect of bevacizumab were activated. The magnitude of change of the most dysregulated genes at 24h did not have a predictive value regarding the patients’ response to BE. However, predictive markers were identified from the gene expression levels at 24h regarding time to progression under BE. Conclusions The 24h-effect of the combined targeted therapy BE could be accurately monitored in advanced non-squamous NSCLC blood samples using whole-genome exon arrays. Putative predictive markers at 24h could reflect patients’ response to BE after adjusting for their mutational status. Trial registration ClinicalTrials.gov: NCT00354549 Electronic supplementary material The online version of this article (doi:10.1186/s12967-017-1174-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Florent Baty
- Department of Pulmonary Medicine, Cantonal Hospital St. Gallen, Roschacherstrasse 95, 9007, St. Gallen, Switzerland.
| | - Markus Joerger
- Department of Medical Oncology and Hematology, Cantonal Hospital St. Gallen, Roschacherstrasse 95, 9007, St. Gallen, Switzerland
| | - Martin Früh
- Department of Medical Oncology and Hematology, Cantonal Hospital St. Gallen, Roschacherstrasse 95, 9007, St. Gallen, Switzerland
| | - Dirk Klingbiel
- Swiss Group for Clinical Cancer Research, Effingerstrasse 40, 3008, Bern, Switzerland
| | - Francesco Zappa
- Oncology Institute of Southern Switzerland, Ospedale Regionale San Giovanni, 6500, Belinzona, Switzerland
| | - Martin Brutsche
- Department of Pulmonary Medicine, Cantonal Hospital St. Gallen, Roschacherstrasse 95, 9007, St. Gallen, Switzerland
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Yu X, Zhai C, Fan Y, Zhang J, Liang N, Liu F, Cao L, Wang J, Du J. TUSC3: a novel tumour suppressor gene and its functional implications. J Cell Mol Med 2017; 21:1711-1718. [PMID: 28272772 PMCID: PMC5571513 DOI: 10.1111/jcmm.13128] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2016] [Accepted: 01/13/2017] [Indexed: 12/31/2022] Open
Abstract
The tumour suppressor candidate 3 (TUSC3) gene is located on chromosome region 8p22 and encodes the 34 kD TUSC3 protein, which is a subunit of the oligosaccharyl transferase responsible for the N‐glycosylation of nascent proteins. Known to be related to autosomal recessive mental retardation for several years, TUSC3 has only recently been identified as a potential tumour suppressor gene. Based on the structure and function of TUSC3, specific mechanisms in various diseases have been investigated. Several studies have demonstrated that TUSC3 is an Mg2+‐transporter involved in magnesium transport and homeostasis, which is important for learning and memory, embryonic development and testis maturation. Moreover, dysfunction or deletion of TUSC3 exerts its oncological effects as a modulator by inhibiting glycosylation efficiency and consequently inducing endoplasmic reticulum stress and malignant cell transformation. In this study, we summarize the advances in the studies of TUSC3 and comment on the potential roles of TUSC3 in diagnosis and treatment of TUSC3‐related diseases, especially cancer.
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Affiliation(s)
- Xinshuang Yu
- Department of Radiation Oncology, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, China
| | - Chunjuan Zhai
- Department of Cardiology, Shandong Provincial Hospital affiliated to Shandong University, Shandong University, Jinan, China
| | - Yujun Fan
- Medical Management Service Center of Shandong Provincial Health and Family Planning Commission, Jinan, China
| | - Jiandong Zhang
- Department of Radiation Oncology, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, China
| | - Ning Liang
- Department of Radiation Oncology, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, China
| | - Fengjun Liu
- Department of Radiation Oncology, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, China
| | - Lili Cao
- Medical Research Center, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, China
| | - Jia Wang
- China Institute of Veterinary Drugs Control, Beijing, China
| | - Juan Du
- Department of Radiation Oncology, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, China.,Medical Research Center, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, China
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