4.7 Article

Molecular profiling of laser-microdissected matched tumor and normal breast tissue identifies karyopherin α2 as a potential novel prognostic marker in breast cancer

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CLINICAL CANCER RESEARCH
卷 12, 期 13, 页码 3950-3960

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AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1078-0432.CCR-05-2090

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Purpose: The aim of the present study was to identify human genes that might prove useful in the diagnosis and therapy of primary breast cancer. Experimental Design: Twenty-four matched pairs of invasive ductal breast cancer and corresponding benign breast tissue were investigated by a combination of laser microdissection and gene expression profiling. Differential expression of candidate genes was validated by dot blot analysis of cDNA in 50 pairs of matching benign and malignant breast tissue. Cellular expression of candidate genes was further validated by RNA in situ hybridization, quantitative reverse transcription-PCR, and immunohistochemistry using tissue microarray analysis of 272 nonselected breast cancers. Multivariate analysis of factors on overall survival and recurrence-free survival was done. Results: Fifty-four genes were found to be up-regulated and 78 genes were found to be downregulated. Dot blot analysis reduced the number of up-regulated genes to 15 candidate genes that showed at least a 2-fold overexpression in) >15 of 50 (30%) tumor/normal pairs. We selected phosphatidic acid phosphatase type 2 domain containing 1A (PPAPDC1A) and karyopherin alpha 2 (KPNA2) for further validation. PPAPDC1A and KPNA2 RNA was up-regulated (fold change >2) in 84% and 32% of analyzed tumor/normal pairs, respectively. Nuclear protein expression of KPNA2 was significantly associated with shorter overall survival and recurrence-free survival. Testing various multivariate Cox regression models, KPNA2 expression remained a highly significant, independent and adverse risk factor for overall survival. Conclusions: Gene expression profiling of laser-microdissected breast cancer tissue revealed novel genes that may represent potential molecular targets for breast cancer therapy and prediction of outcome.

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