Loss of Cytoplasmic CDK1 Predicts Poor Survival in Human Lung Cancer and Confers Chemotherapeutic Resistance
Author(s) -
Chunyu Zhang,
Abdel Elkahloun,
Matthew Robertson,
Joell J. Gills,
Junji Tsurutani,
Joanna H. Shih,
Junya Fukuoka,
M. Christine Hollander,
Curtis C. Harris,
William D. Travis,
Jin Jen,
Phillip A. Dennis
Publication year - 2011
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0023849
Subject(s) - lung cancer , cyclin dependent kinase 1 , carcinogenesis , biology , cancer research , microarray , cancer , tissue microarray , targeted therapy , microarray analysis techniques , biomarker , cell cycle , gene , bioinformatics , medicine , oncology , gene expression , genetics
The dismal lethality of lung cancer is due to late stage at diagnosis and inherent therapeutic resistance. The incorporation of targeted therapies has modestly improved clinical outcomes, but the identification of new targets could further improve clinical outcomes by guiding stratification of poor-risk early stage patients and individualizing therapeutic choices. We hypothesized that a sequential, combined microarray approach would be valuable to identify and validate new targets in lung cancer. We profiled gene expression signatures during lung epithelial cell immortalization and transformation, and showed that genes involved in mitosis were progressively enhanced in carcinogenesis. 28 genes were validated by immunoblotting and 4 genes were further evaluated in non-small cell lung cancer tissue microarrays. Although CDK1 was highly expressed in tumor tissues, its loss from the cytoplasm unexpectedly predicted poor survival and conferred resistance to chemotherapy in multiple cell lines, especially microtubule-directed agents. An analysis of expression of CDK1 and CDK1-associated genes in the NCI60 cell line database confirmed the broad association of these genes with chemotherapeutic responsiveness. These results have implications for personalizing lung cancer therapy and highlight the potential of combined approaches for biomarker discovery.
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