Non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) is a low-risk thyroid tumor with a favorable prognosis. Nonetheless, differentiating NIFTP from other thyroid tumors remains challenging, necessitating reliable diagnostic markers. This study is aimed at discovering NIFTP-specific mRNA markers through RNA sequencing analysis of thyroid tumor tissues. We performed mRNA expression profiling for 74 fresh frozen thyroid tissue samples, including NIFTP and benign and malignant follicular-cell-derived tumors. NIFTP/malignant tumors showed 255 downregulated genes and 737 upregulated genes compared to benign tumors. Venn diagram analysis revealed 19 significantly upregulated and 7 downregulated mRNAs in NIFTP. Akaike information criterion analysis allowed us to select OCLN, ZNF423, LYG1, and AQP5 mRNA markers. We subsequently developed a predictive model based on logistic regression analysis using these four mRNAs, which we validated in independent samples (n = 90) using a qRT-PCR assay. This model demonstrated high accuracy in predicting NIFTP in discovery dataset (AUC (area under the receiver operating characteristic) = 0.960) and the validation dataset (AUC = 0.757). Our results suggest that OCLN, ZNF423, LYG1, and AQP5 mRNA markers might serve as reliable molecular markers for identifying NIFTP among other thyroid tumors, ultimately aiding in accurate diagnosis and management of NIFTP patients.

具有乳头状核特征的非侵袭性滤泡性甲状腺肿瘤（NIFTP）是一种低风险的甲状腺肿瘤，预后良好。尽管如此，区分 NIFTP 与其他甲状腺肿瘤仍然具有挑战性，需要可靠的诊断标记物。本研究旨在通过甲状腺肿瘤组织的RNA测序分析发现NIFTP特异性mRNA标记。我们对 74 个新鲜冷冻甲状腺组织样本进行了 mRNA 表达谱分析，其中包括 NIFTP 以及良性和恶性滤泡细胞来源的肿瘤。与良性肿瘤相比，NIFTP/恶性肿瘤显示 255 个下调基因和 737 个上调基因。维恩图分析显示 NIFTP 中有 19 个显着上调和 7 个下调的 mRNA。Akaike 信息标准分析使我们能够选择OCLN、ZNF423、LYG1和AQP5 mRNA 标记。 随后，我们使用这四种 mRNA 开发了基于逻辑回归分析的预测模型，并使用 qRT-PCR 测定在独立样本 ( n = 90) 中进行了验证。该模型在发现数据集（AUC（接收器操作特征下的面积）= 0.960）和验证数据集（AUC = 0.757）中展示了预测 NIFTP 的高精度。我们的结果表明，OCLN、ZNF423、LYG1和AQP5 mRNA 标记物可能作为在其他甲状腺肿瘤中识别 NIFTP 的可靠分子标记物，最终有助于 NIFTP 患者的准确诊断和管理。