Evaluation of Salivary, Plasma, and Tissue ITGB8 and MIAT-lncRNA Expression as a Biomarker in Oral Squamous Cell Carcinoma: A Cross-Sectional Study.

IF 1.6 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Mina Khayamzadeh, Sayyed Mohammad Hossein Ghaderian, Ata Garajei, Mohammad Sajad Jolani, Afagh Tavassoli, Pegah Khodaee
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引用次数: 0

Abstract

Squamous cell carcinoma of the lips and oral cavity (OSCC) contributes to 90% of the nonmelanocytic tumors of these anatomical regions. Liquid biopsy is a new, relatively noninvasive, and effective method for screening, diagnosing, and classifying tumors. Considering the role of integrin β8 subunit (ITGB8) and Myocardial infarction-associated transcript (MIAT) lncRNA in the pathogenesis and progression of different types of cancer, we aimed to evaluate the probable differences in the level of expression of these two biomarkers in control and OSCC cases and evaluate their diagnostic potential as a biomarker in tissue and liquid samples (blood and saliva) biopsy. Tissue, blood, and saliva samples from 60 participants (30 in each study group) were obtained for precise evaluation. Using extracted RNA from the samples and PCR assay, the expression level of these biomarkers was measured in control and case group samples. Parametric and nonparametric tests were equipped for the evaluation of the results. ROC analysis was done to determine the diagnostic potential of these biomarkers. Our results claimed significant differences in the level of expression of ITGB8 and MIAT-lncRNA among our study cohorts' samples. The ROC analysis revealed the valuable potential of these factors in the diagnosis of disease in tissue and blood samples. The results of the analysis for the saliva samples suggest a satisfactory diagnostic value for ITGB8 but nonsignificant diagnostic value for the MIAT-lncRNA. ITGB8 and MIAT-lncRNA expression levels could be considered in the evaluation of suspicious oral cavity lesions, especially in the tissue and blood samples.

唾液、血浆和组织中ITGB8和MIAT-lncRNA表达作为口腔鳞状细胞癌生物标志物的评估:一项横断面研究
唇口腔鳞状细胞癌(OSCC)占这些解剖区域非黑素细胞性肿瘤的90%。液体活检是一种新的、相对无创的、有效的肿瘤筛查、诊断和分类方法。考虑到整合素β8亚基(ITGB8)和心肌梗死相关转录物(MIAT) lncRNA在不同类型癌症的发病和进展中的作用,我们旨在评估这两种生物标志物在对照和OSCC病例中的表达水平可能存在的差异,并评估它们在组织和液体样本(血液和唾液)活检中作为生物标志物的诊断潜力。从60名参与者(每个研究组30名)中获得组织、血液和唾液样本进行精确评估。利用从样本中提取的RNA和PCR检测,在对照组和病例组样本中测量这些生物标志物的表达水平。对结果进行了参数和非参数检验。进行ROC分析以确定这些生物标志物的诊断潜力。我们的研究结果表明,在我们的研究队列样本中,ITGB8和mat - lncrna的表达水平存在显著差异。ROC分析揭示了这些因素在组织和血液样本中诊断疾病的有价值的潜力。唾液样本的分析结果表明,ITGB8的诊断价值令人满意,但对MIAT-lncRNA的诊断价值不显著。ITGB8和MIAT-lncRNA表达水平可作为评估口腔可疑病变的参考,尤其是在组织和血液样本中。
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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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