Torres Alba, Alshalalfa Mohammed, Tomlins Scott A, Erho Nicholas, Gibb Ewan A, Chelliserry Jijumon, Lim Lony, Lam Lucia L C, Faraj Sheila F, Bezerra Stephania M, Davicioni Elai, Yousefi Kasra, Ross Ashley E, Netto George J, Schaeffer Edward M, Lotan Tamara L
Department of Pathology, Johns Hopkins School of Medicine, Baltimore, Maryland.
GenomeDx Biosciences, Vancouver, British Columbia, Canada.
J Mol Diagn. 2017 May;19(3):475-484. doi: 10.1016/j.jmoldx.2017.01.007. Epub 2017 Mar 21.
ETS family gene fusions are common in prostate cancer and molecularly define a tumor subset. ERG is the most commonly rearranged, leading to its overexpression, followed by ETV1, ETV4, and ETV5, and these alterations are generally mutually exclusive. We validated the Decipher prostate cancer assay to detect ETS alterations in a Clinical Laboratory Improvement Amendments-accredited laboratory. Benchmarking against ERG immunohistochemistry and ETV1/4/5 RNA in situ hybridization, we examined the accuracy, precision, and reproducibility of gene expression ETS models using formalin-fixed, paraffin-embedded samples. The m-ERG model achieved an area under curve of 95%, with 93% sensitivity and 98% specificity to predict ERG immunohistochemistry status. The m-ETV1, -ETV4, and -ETV5 models achieved areas under curve of 98%, 88%, and 99%, respectively. The models had 100% robustness for ETS status, and scores were highly correlated across sample replicates. Models predicted 41.5% of a prospective radical prostatectomy cohort (n = 4036) to be ERG, 6.3% ETV1, 1% ETV4, and 0.4% ETV5. Of prostate tumor biopsy samples (n = 509), 41.2% were ERG, 8.6% ETV1, 0.4% ETV4, and none ETV5. Higher Decipher risk status tumors were more likely to be ETS (ERG or ETV1/4/5) in the radical prostatectomy and the biopsy cohorts (P < 0.05). These results support the utility of microarray-based ETS status prediction models for molecular classification of prostate tumors.
ETS家族基因融合在前列腺癌中很常见，并且在分子水平上定义了一个肿瘤亚群。ERG是最常发生重排的基因，导致其过度表达，其次是ETV1、ETV4和ETV5，并且这些改变通常是相互排斥的。我们在一个获得临床实验室改进修正案认可的实验室中验证了Decipher前列腺癌检测法以检测ETS改变。以ERG免疫组织化学和ETV1/4/5 RNA原位杂交为基准，我们使用福尔马林固定、石蜡包埋的样本检查了基因表达ETS模型的准确性、精密度和可重复性。m-ERG模型的曲线下面积达到95%，预测ERG免疫组织化学状态的灵敏度为93%，特异性为98%。m-ETV1、m-ETV4和m-ETV5模型的曲线下面积分别为98%、88%和99%。这些模型对ETS状态具有100%的稳健性，并且样本重复间的分数高度相关。模型预测前瞻性根治性前列腺切除术队列（n = 4036）中41.5%为ERG、6.3%为ETV1、1%为ETV4以及0.4%为ETV5。在前列腺肿瘤活检样本（n = 509）中，41.2%为ERG、8.6%为ETV1、0.4%为ETV4，且无ETV5。在根治性前列腺切除术和活检队列中，Decipher风险状态较高的肿瘤更可能为ETS（ERG或ETV1/4/5）（P < 0.05）。这些结果支持基于微阵列的ETS状态预测模型在前列腺肿瘤分子分类中的实用性。
