Banizs Anna B, Silverman Jan F
Department of Pathology, Allegheny General Hospital, Pittsburgh, Pennsylvania.
Diagn Cytopathol. 2019 Apr;47(4):268-274. doi: 10.1002/dc.24087. Epub 2018 Nov 22.
Real-world clinical results of (1) Bethesda categorization, (2) mutation analysis, and (3) a microRNA classifier were correlated to show the utility of molecular analysis in assessing malignancy risk of indeterminate thyroid nodules.
Cytology and molecular results of clinically tested thyroid nodules were compared. An additional microRNA threshold was determined based on nodules with known disease status, establishing a 3-tiered microRNA approach to clinical risk assessments. Expected rate of malignancy given mutation panel and 3-tiered microRNA approach was validated in an independent cohort of atypia of undetermined significance or follicular lesion of undetermined significance (AUS/FLUS) and follicular neoplasm or suspicious for follicular neoplasm (FN/SFN) nodules with surgically derived outcomes.
In 2685 patients clinically tested, PIK3CA, PAX8/PPARγ, and RET/PTC mutations occurred in less than 1%. Of note, 2% had BRAFV600E mutation and 82% lacked mutations. The maximum expected risk of malignancy in nodules lacking mutations was 9% and 17% for AUS/FLUS and FN/SFN nodules, respectively. Positive microRNA status further increased risk, with the most worrisome status (level-3) elevating risk to 36% and 54%, respectively. RAS mutations occurred in 15% of nodules tested clinically, including in 8% of those that were cytologically benign. The maximum expected risk of malignancy in nodules with RAS or PAX8/PPARγ mutations was 49% and 65% for AUS/FLUS and FN/SFN nodules, respectively. Positive microRNA status further increased risk, with the most worrisome microRNA status (level-3) elevating risk to 85% and 91%, respectively.
Mutation panels alone do not sufficiently risk stratify thyroid nodular disease. microRNA classification complements cytology and mutation analysis with the capacity to better differentiate nodules at high risk of malignancy.
将（1）贝塞斯达分类、（2）突变分析和（3）微小RNA分类器的真实世界临床结果进行关联，以显示分子分析在评估甲状腺结节恶性风险中的实用性。
比较经临床检测的甲状腺结节的细胞学和分子结果。基于已知疾病状态的结节确定了一个额外的微小RNA阈值，建立了一种用于临床风险评估的三级微小RNA方法。在一组具有手术结果的意义未明的非典型性或意义未明的滤泡性病变（AUS/FLUS）以及滤泡性肿瘤或可疑滤泡性肿瘤（FN/SFN）结节的独立队列中，验证了给定突变组和三级微小RNA方法时的预期恶性率。
在2685例经临床检测的患者中，PIK3CA、PAX8/PPARγ和RET/PTC突变的发生率低于1%。值得注意的是，2%的患者有BRAFV600E突变，82%的患者没有突变。对于AUS/FLUS和FN/SFN结节，无突变结节的最大预期恶性风险分别为9%和17%。微小RNA阳性状态进一步增加风险，最令人担忧的状态（3级）分别将风险提高到36%和54%。在临床检测的结节中，15%发生了RAS突变，其中8%在细胞学上为良性。对于AUS/FLUS和FN/SFN结节，有RAS或PAX8/PPARγ突变的结节的最大预期恶性风险分别为49%和65%。微小RNA阳性状态进一步增加风险，最令人担忧的微小RNA状态（3级）分别将风险提高到85%和91%。
仅靠突变组不足以对甲状腺结节疾病进行风险分层。微小RNA分类可补充细胞学和突变分析，具有更好地区分恶性风险高的结节的能力。
