Sivendran Shanthi, Chang Rui, Pham Lisa, Phelps Robert G, Harcharik Sara T, Hall Lawrence D, Bernardo Sebastian G, Moskalenko Marina M, Sivendran Meera, Fu Yichun, de Moll Ellen H, Pan Michael, Moon Jee Young, Arora Sonali, Cohain Ariella, DiFeo Analisa, Ferringer Tammie C, Tismenetsky Mikhail, Tsui Cindy L, Friedlander Philip A, Parides Michael K, Banchereau Jacques, Chaussabel Damien, Lebwohl Mark G, Wolchok Jedd D, Bhardwaj Nina, Burakoff Steven J, Oh William K, Palucka Karolina, Merad Miriam, Schadt Eric E, Saenger Yvonne M
Division of Hematology and Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Hematology/Oncology Medical Specialists, Lancaster General Health, Lancaster, Pennsylvania, USA.
Department of Genetics and Genomic Science, Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
J Invest Dermatol. 2014 Aug;134(8):2202-2211. doi: 10.1038/jid.2014.85. Epub 2014 Feb 12.
Patients with resected stage II-III cutaneous melanomas remain at high risk for metastasis and death. Biomarker development has been limited by the challenge of isolating high-quality RNA for transcriptome-wide profiling from formalin-fixed and paraffin-embedded (FFPE) primary tumor specimens. Using NanoString technology, RNA from 40 stage II-III FFPE primary melanomas was analyzed and a 53-immune-gene panel predictive of non-progression (area under the curve (AUC)=0.920) was defined. The signature predicted disease-specific survival (DSS P<0.001) and recurrence-free survival (RFS P<0.001). CD2, the most differentially expressed gene in the training set, also predicted non-progression (P<0.001). Using publicly available microarray data from 46 primary human melanomas (GSE15605), a coexpression module enriched for the 53-gene panel was then identified using unbiased methods. A Bayesian network of signaling pathways based on this data identified driver genes. Finally, the proposed 53-gene panel was confirmed in an independent test population of 48 patients (AUC=0.787). The gene signature was an independent predictor of non-progression (P<0.001), RFS (P<0.001), and DSS (P=0.024) in the test population. The identified driver genes are potential therapeutic targets, and the 53-gene panel should be tested for clinical application using a larger data set annotated on the basis of prospectively gathered data.
已切除的II - III期皮肤黑色素瘤患者仍面临转移和死亡的高风险。生物标志物的开发受到从福尔马林固定石蜡包埋（FFPE）原发性肿瘤标本中分离高质量RNA以进行全转录组分析的挑战的限制。使用NanoString技术，对40例II - III期FFPE原发性黑色素瘤的RNA进行了分析，并定义了一个预测无进展的53免疫基因panel（曲线下面积（AUC）=0.920）。该特征预测疾病特异性生存（DSS，P<0.001）和无复发生存（RFS，P<0.001）。CD2是训练集中差异表达最显著的基因，也预测无进展（P<0.001）。然后，利用来自46例原发性人类黑色素瘤的公开可用微阵列数据（GSE15605），使用无偏方法鉴定了一个富含53基因panel的共表达模块。基于这些数据的信号通路贝叶斯网络确定了驱动基因。最后，在48例患者的独立测试人群中证实了所提出的53基因panel（AUC=0.787）。该基因特征是测试人群中无进展（P<0.001）、RFS（P<0.001）和DSS（P=0.024）的独立预测因子。所确定的驱动基因是潜在的治疗靶点，应使用基于前瞻性收集数据注释的更大数据集对53基因panel进行临床应用测试。
