Polymorphic Single-Nucleotide Variants in miRNA Genes and the Susceptibility to Colorectal Cancer: Combined Evaluation by Pairwise and Network Meta-Analysis, Thakkinstian's Algorithm and FPRP Criterium

IF 2.9 2区医学 Q2 ONCOLOGY

Cancer Medicine Pub Date : 2025-01-22 DOI:10.1002/cam4.70621

Qing Liu, Ivan Archilla, Sandra Lopez-Prades, Ferran Torres, Jordi Camps, Miriam Cuatrecasas

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引用次数: 0

Abstract

Background

Considerable epidemiological studies have examined the correlation between polymorphic single-nucleotide variants (SNPs) in miRNA genes and colorectal carcinoma (CRC) risk, yielding inconsistent results. Herein, we sought to systematically investigate the association between miRNA-SNPs and CRC susceptibility by combined evaluation using pairwise and network meta-analysis, the FPRP analysis (false positive report probability), and the Thakkinstian's algorithm.

Methods

The MEDLINE, EMBASE, WOS, and Cochrane Library databases were searched through May 2024 to find relevant association literatures. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were computed by the pairwise meta-analysis. Network meta-analysis and the Thakkinstian's method were applied for determining the potentially optimal genetic models; additionally, the FPRP was used to identify noteworthy associations.

Results

Totally, 39 case–control trials involving 18,028 CRC cases, and 21,816 normal participants were included in the study. Eleven SNPs within nine genes were examined for their predisposition to CRC. miR-27a (rs895819) was found to significantly increase CRC risk among overall population (OR 1.58, 95% CI: 1.32–1.89) and Asians (OR 1.62, 95% CI: 1.31–2.01), with the recessive models identified as the optimal models. Furthermore, miR-196a2 (rs11614913), miR-143/145 (rs41291957), and miR-34b/c (rs4938723) were significantly related to reduced CRC risk among Asian descendants under the optimal dominant (OR 0.75, 95% CI: 0.65–0.86), recessive (OR 0.72, 95% CI: 0.60–0.85), and recessive models (OR 0.69, 95% CI: 0.56–0.85), respectively. The results were also proposed by the network meta-analysis or the Thakkinstian's method and confirmed by the FPRP criterion.

Conclusion

The miR-27a (rs895819) is correlated with elevated CRC risk among overall population and Asians, and the recessive model is found to be optimal for predicting CRC risk. Additionally, the miR-196a2 (rs11614913), miR-143/145 (rs41291957), and miR-34b/c (rs4938723), with the dominant, recessive, and recessive models identified as the optimal, might confer protective effects against CRC among Asians.

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miRNA基因多态单核苷酸变异与结直肠癌易感性：两两和网络meta分析、Thakkinstian算法和FPRP标准联合评估

背景：大量流行病学研究已经研究了miRNA基因多态性单核苷酸变异（snp）与结直肠癌（CRC）风险之间的相关性，但结果不一致。在此，我们试图通过使用两两和网络meta分析、FPRP分析（假阳性报告概率）和Thakkinstian算法的联合评估，系统地研究mirna - snp与CRC易感性之间的关系。方法：检索截至2024年5月的MEDLINE、EMBASE、WOS和Cochrane图书馆数据库，查找相关关联文献。通过两两荟萃分析计算合并优势比（ORs）和95%置信区间（ci）。采用网络元分析和Thakkinstian方法确定潜在的最优遗传模型；此外，FPRP被用于识别值得注意的关联。结果：本研究共纳入39项病例对照试验，涉及18028例结直肠癌病例和21816名正常受试者。9个基因中的11个snp检测了它们对CRC的易感性。研究发现，miR-27a （rs895819）在总体人群（OR 1.58, 95% CI: 1.32-1.89）和亚洲人（OR 1.62, 95% CI: 1.31-2.01）中显著增加结直肠癌风险，其中隐性模型被确定为最佳模型。此外，miR-196a2 （rs11614913）、miR-143/145 （rs41291957）和miR-34b/c （rs4938723）在最佳显性模型（OR 0.75, 95% CI: 0.65-0.86）、隐性模型（OR 0.72, 95% CI: 0.60-0.85）和隐性模型（OR 0.69, 95% CI: 0.56-0.85）下分别与降低亚洲后代结直肠癌风险显著相关。结果也由网络元分析或Thakkinstian的方法提出，并由FPRP标准证实。结论：miR-27a （rs895819）与总体人群和亚洲人CRC风险升高相关，隐性模型是预测CRC风险的最佳模型。此外，miR-196a2 （rs11614913）、miR-143/145 （rs41291957）和miR-34b/c (rs4938723)，其中显性、隐性和隐性模型被认为是最佳的，可能对亚洲人的结直肠癌具有保护作用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cancer Medicine ONCOLOGY-

CiteScore

5.50

自引率

2.50%

发文量

907

审稿时长

19 weeks

期刊介绍： Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas: Clinical Cancer Research Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations Cancer Biology: Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery. Cancer Prevention: Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach. Bioinformatics: Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers. Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.