Departments of Pathology and Dermatology, School of Medicine, Indiana University, 350W 11th Street, Indianapolis, IN, 46202, USA.
Departments of Dermatology and Pathology, University of North Carolina at Chapel Hill, 410 Market Street Suite 400, Chapel Hill, NC, 27516, USA.
Mod Pathol. 2020 Jul;33(7):1307-1317. doi: 10.1038/s41379-020-0499-y. Epub 2020 Feb 17.
Increasingly, molecular methods are being utilized in the workup of melanocytic neoplasms. To this end, we sought to correlate data from a single nucleotide polymorphism (SNP) array platform based on molecular inversion probes with clinical data. Copy number variation (CNV) data were obtained on 95 melanocytic tumors (6 ordinary nevi, 15 atypical nevi, 34 ambiguous neoplasms, and 40 melanomas) from 92 patients. The average number of significant CNVs was 0 for nevi, 0.6 for atypical nevi (range 0-3), 2.8 for ambiguous neoplasms (range 0-17), and 18.1 for melanomas (range 0-69). Clinical follow-up data were available in 57 of 95 lesions (56 of 92 patients). Tumors from patients with adverse events demonstrated an average number of CNVs of 24.5 (range 6-69) as compared with 7.9 (range 0-35) among tumors without an associated adverse event (p ≤ 0.001). No adverse events were observed in nevi including atypical nevi. Adverse events were found in 2 of 19 ambiguous neoplasms and 10 of 32 melanomas with follow up. In these two latter groups of neoplasms, the correlation between adverse events and the average number of CNVs remained statistically significant even when controlled for Breslow depth (21.5 versus 8.7, p value = 0.036). No neoplasm with adverse events had ≤3 CNVs. These results provide further evidence that SNP array testing for CNVs may be helpful in the classification and prognostication of ambiguous neoplasms. Based on these results, an algorithmic approach to challenging melanocytic neoplasms using CNV data is suggested, using as cutoff of >3 CNVs with some caveats, as the threshold for a positive result. Future clinical validation, using a larger cohort of relevant tumors, will be necessary.
越来越多的分子方法被应用于黑色素细胞肿瘤的研究。为此，我们试图将基于分子反转探针的单核苷酸多态性（SNP）阵列平台的数据与临床数据相关联。从 92 名患者的 95 个黑色素细胞肿瘤（6 个普通痣、15 个非典型痣、34 个交界性肿瘤和 40 个黑色素瘤）中获得了拷贝数变异（CNV）数据。痣的显著 CNV 平均数为 0，非典型痣为 0.6（范围 0-3），交界性肿瘤为 2.8（范围 0-17），黑色素瘤为 18.1（范围 0-69）。57 个病变（92 个患者中的 56 个）有临床随访数据。有不良事件的患者的肿瘤平均 CNV 数为 24.5（范围 6-69），而无相关不良事件的肿瘤为 7.9（范围 0-35）（p≤0.001）。包括非典型痣在内的普通痣均未发生不良事件。19 个交界性肿瘤中有 2 个和 32 个黑色素瘤中有 10 个发生了不良事件。在后两组肿瘤中，即使控制 Breslow 深度，不良事件与平均 CNV 数之间的相关性仍然具有统计学意义（21.5 与 8.7，p 值=0.036）。没有一个有不良事件的肿瘤的 CNV 数≤3。这些结果进一步证明，SNP 阵列检测 CNV 可能有助于交界性肿瘤的分类和预后。基于这些结果，建议提出一种使用 CNV 数据对具有挑战性的黑色素细胞肿瘤进行分析的算法方法，使用>3 个 CNV 作为阳性结果的截断值，但需要注意一些问题。未来需要使用更大的相关肿瘤队列进行临床验证。
