Kidd Mark, Modlin Irvin M, Drozdov Ignat, Aslanian Harry, Bodei Lisa, Matar Somer, Chung Kyung-Min
Wren Laboratories, Brandford, CT, USA.
Yale University School of Medicine, New Haven, CT, USA.
Oncotarget. 2017 Dec 29;9(6):7182-7196. doi: 10.18632/oncotarget.23820. eCollection 2018 Jan 23.
No effective blood biomarker exists to detect and clinically manage bronchopulmonary (BP) neuroendocrine tumors (NET). We developed a blood-based 51 NET-specific transcript set for diagnosis and monitoring and evaluated clinical performance metrics. It accurately diagnosed the tumor and differentiated stable from progressive disease as determined by RECIST criteria. Gene expression was evaluated in: a) publicly available BPNET transcriptomes (GSE35679); b) two BPNET cell-lines; and c) BPNET tissue with paired blood ( = 7). Blood gene expression was assessed in 194 samples including controls, benign lung diseases, malignant lung diseases and small bowel NETs. A separate validation study in 25 age- and gender-matched BPNETs/controls was performed. Gene expression measured by real-time PCR was scored (0-100%; normal: < 14%). Regression analyses, Principal Component Analysis (PCA), hierarchical clustering, Fisher's and non-parametric evaluations were undertaken. All 51 genes were identified in BPNET transcriptomes, tumor samples and cell-lines. Significant correlations were evident between paired tumor and blood (R2:0.63-0.91, < 0.001). PCA and hierarchical clustering identified blood gene expression was significantly different between lung cancers and benign diseases, including BPNETs. Gene expression was highly correlated (R: 0.91, = 1.7 × 10-) between small bowel and BPNET. For validation, all 25 BPNETs were positive compared to 20% controls ( < 0.0001). Scores were significantly elevated ( < 0.0001) in BPNETs (57 ± 28%) compared to controls (4 ± 5%). BPNETs with progressive disease (85 ± 11%) exhibited higher scores than stable disease (32 ± 7%, < 0.0001). Blood measurements accurately diagnosed bronchopulmonary carcinoids, distinguishing stable from progressive disease. This marker panel will have clinical utility as a diagnostic liquid biopsy able to define disease activity and progression in real-time.
目前尚无有效的血液生物标志物可用于检测和临床管理支气管肺(BP)神经内分泌肿瘤(NET)。我们开发了一种基于血液的51个NET特异性转录本集用于诊断和监测,并评估了临床性能指标。它能准确诊断肿瘤,并根据RECIST标准区分疾病稳定和进展情况。基因表达在以下方面进行了评估:a)公开可用的BPNET转录组(GSE35679);b)两种BPNET细胞系;c)BPNET组织及配对血液(n = 7)。在194个样本中评估了血液基因表达,包括对照、良性肺病、恶性肺病和小肠NET。在25例年龄和性别匹配的BPNET/对照中进行了单独的验证研究。通过实时PCR测量的基因表达进行评分(0 - 100%;正常:< 14%)。进行了回归分析、主成分分析(PCA)、层次聚类、Fisher检验和非参数评估。在BPNET转录组、肿瘤样本和细胞系中均鉴定出所有51个基因。配对的肿瘤和血液之间存在显著相关性(R2:0.63 - 0.91,P < 0.001)。PCA和层次聚类表明,肺癌与良性疾病(包括BPNET)之间的血液基因表达存在显著差异。小肠NET和BPNET之间的基因表达高度相关(R:0.91,P = 1.7 × 10-)。在验证中,所有25例BPNET均为阳性,而对照为20%阳性(P < 0.0001)。与对照(4 ± 5%)相比,BPNET的评分显著升高(P < 0.0001)(57 ± 28%)。疾病进展的BPNET(85 ± 11%)的评分高于疾病稳定的BPNET(32 ± 7%,P < 0.0001)。血液检测能准确诊断支气管肺类癌,区分疾病稳定和进展情况。该标志物组合将具有临床实用性,作为一种诊断性液体活检能够实时定义疾病活动和进展。