Gene expression profiling allows distinction between primary and metastatic squamous cell carcinomas in the lung

被引:125
作者
Talbot, SG
Estilo, C
Maghami, E
Sarkaria, IS
Pham, DK
O-charoenrat, P
Socci, ND
Ngai, I
Carlson, D
Ghossein, R
Viale, A
Park, BJ
Rusch, VW
Singh, B
机构
[1] Mem Sloan Kettering Canc Ctr, Head & Neck Serv, Lab Epithelial Canc Biol, New York, NY 10021 USA
[2] Mem Sloan Kettering Canc Ctr, Thorac Oncol Serv, New York, NY 10021 USA
[3] Mem Sloan Kettering Canc Ctr, Dental Serv, New York, NY 10021 USA
[4] Mem Sloan Kettering Canc Ctr, Dept Surg, New York, NY 10021 USA
[5] Mem Sloan Kettering Canc Ctr, Dept Pathol, New York, NY 10021 USA
[6] Mem Sloan Kettering Canc Ctr, Computat Biol Ctr, New York, NY 10021 USA
[7] Mem Sloan Kettering Canc Ctr, Genom Core Lab, New York, NY 10021 USA
[8] Siriraj Hosp, Dept Head & Neck Surg, Bangkok, Thailand
关键词
D O I
10.1158/0008-5472.CAN-04-1985
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Lung neoplasms commonly develop in patients previously treated for head and neck carcinomas. The derivation of these tumors, either as new primary lung cancers or as metastatic head and neck cancers, is difficult to establish based on clinical or histopathologic criteria since both are squamous cell carcinomas and have identical features under light microscopy. However, this distinction has significant treatment and prognostic implications. Gene expression profiling was performed on a panel of 52 sequentially collected patients with either primary lung (n = 21) or primary head and neck (n = 31) carcinomas using the Affymetrix HG_U95Av2 high-density oligonucleotide microarray. Unsupervised hierarchical clustering with Ward linkage and the Pearson correlation metric was performed. To assess robustness, bootstrap resampling was performed with 1,000 iterations. A t test of the normalized values for each gene was used to determine the genes responsible for segregating head and neck from lung primary carcinomas, and those with the most differential expression were used for later analyses. In the absence of a large "test" set of tumors, we used a supervised leave-one-out cross-validation to test how well we could predict the tumor origin. Once a gene expression profile was established, 12 lung lesions taken from patients with previously treated head and neck cancers were similarly analyzed by gene expression profiling to determine their sites of origin. Unsupervised clustering analysis separated the study cohort into two distinct groups which reliably remained segregated with bootstrap resampling. Group 1 consisted of 30 tongue carcinomas. Group 2 consisted of 21 lung cancers and 1 tongue carcinoma. The clustering was not changed even when normal lung or tongue profiles were subtracted from the corresponding carcinomatous lesions, and a leave-one-out cross-validation showed a 98% correct prediction (see Supplementary Data 1). A minimum set of 500 genes required to distinguish these groups was established. Given the ability to segregate these lesions using molecular profiling, we analyzed the lung tumors of undetermined origin. All cases clearly clustered with either lung or tongue tumor subsets, strongly supporting our hypothesis that this technique could elucidate the tissue of origin of metastatic lesions. Although histologically similar, squamous cell carcinomas have distinct gene expression profiles based on their anatomic sites of origin. Accordingly, the application of gene expression profiling may be useful in identifying the derivation of lung nodules and consequently enhances treatment planning.
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页码:3063 / 3071
页数:9
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