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鉴定潜在的新型生物标志物以区分具有细胞学不确定的恶性甲状腺结节。

Identification of potential novel biomarkers to differentiate malignant thyroid nodules with cytological indeterminate.

机构信息

Institute of Life Sciences, Jiangsu University, 301 Xuefu Road, JinKou District, Zhenjiang, 212013, PR China.

Department of Radiology, Affiliated Renmin Hospital of Jiangsu University, Zhenjiang, Jiangsu, PR China.

出版信息

BMC Cancer. 2020 Mar 12;20(1):199. doi: 10.1186/s12885-020-6676-z.

DOI:10.1186/s12885-020-6676-z
PMID:32164602
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7066786/
Abstract

BACKGROUND

The fine-needle aspiration (FNA) biopsy was broadly applied to clinical diagnostics evaluation for thyroid carcinomas nodule, while companioning with higher uncertainty rate (15~30%) to identify malignancy for cytological indeterminate cases. It is requirement to discover novel molecular biomarkers to differentiate malignant thyroid nodule more precise.

METHODS

We employed weighted gene co-expression network analysis (WGCNA) to discover genes significantly associated with malignant histopathology for cytological indeterminate nodules. In addition, identified significantly genes were validated through another independently investigations of thyroid carcinomas patient's samples via cBioportal and Geipa. The key function pathways of significant genes involving were blast through GenClip.

RESULTS

Twenty-four signature genes were identified significantly related to thyroid nodules malignancy. Furthermore, five novel genes with missense mutation, FN1 (R534P), PROS1((K200I), (Q571K)), SCEL (T320S), SLC34A2(T688M) and TENM1 (S1131F), were highlighted as potential biomarkers to rule out nodules malignancy. It was identified that the key functional pathways involving in thyroid carcinomas.

CONCLUSION

These results will be helpful to better understand the mechanism of thyroid nodules malignant transformation and characterize the potentially biomarkers for thyroid carcinomas early diagnostics.

摘要

背景

细针穿刺活检(FNA)广泛应用于甲状腺癌结节的临床诊断评估,而对于细胞学不确定的病例,其识别恶性肿瘤的不确定性率较高(15%~30%)。因此,需要发现新的分子生物标志物来更精确地区分恶性甲状腺结节。

方法

我们采用加权基因共表达网络分析(WGCNA)来发现与细胞学不确定结节恶性组织病理学显著相关的基因。此外,通过 cBioportal 和 Geipa 对甲状腺癌患者样本的另一个独立研究,对鉴定出的显著基因进行验证。通过 GenClip 对涉及的显著基因的关键功能途径进行了分析。

结果

确定了 24 个与甲状腺结节恶性显著相关的特征基因。此外,还突出了五个具有错义突变的新基因(FN1(R534P)、PROS1((K200I)、(Q571K))、SCEL(T320S)、SLC34A2(T688M) 和 TENM1(S1131F))作为潜在的生物标志物,用于排除结节恶性。确定了涉及甲状腺癌的关键功能途径。

结论

这些结果将有助于更好地理解甲状腺结节恶性转化的机制,并表征甲状腺癌早期诊断的潜在生物标志物。

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