Setlur Sunita R, Royce Thomas E, Sboner Andrea, Mosquera Juan-Miguel, Demichelis Francesca, Hofer Matthias D, Mertz Kirsten D, Gerstein Mark, Rubin Mark A
Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Cancer Res. 2007 Nov 1;67(21):10296-303. doi: 10.1158/0008-5472.CAN-07-2173.
Microarrays have been used to identify genes involved in cancer progression. We have now developed an algorithm that identifies dysregulated pathways from multiple expression array data sets without a priori definition of gene expression thresholds. Integrative microarray analysis of pathways (IMAP) was done using existing expression array data from localized and metastatic prostate cancer. Comparison of metastatic cancer and localized disease in multiple expression array profiling studies using the IMAP approach yielded a list of about 100 pathways that were significantly dysregulated (P < 0.05) in prostate cancer metastasis. The pathway that showed the most significant dysregulation, HIV-I NEF, was validated at both the transcript level and the protein level by quantitative PCR and immunohistochemical analysis, respectively. Validation by unsupervised analysis on an independent data set using the gene expression signature from the HIV-I NEF pathway verified the accuracy of our method. Our results indicate that this pathway is especially dysregulated in hormone-refractory prostate cancer.
微阵列已被用于识别参与癌症进展的基因。我们现已开发出一种算法，可从多个表达阵列数据集中识别失调的信号通路，而无需事先定义基因表达阈值。利用来自局限性和转移性前列腺癌的现有表达阵列数据进行了信号通路的综合微阵列分析（IMAP）。采用IMAP方法对多个表达阵列分析研究中的转移性癌症和局限性疾病进行比较，得出了约100条在前列腺癌转移中显著失调（P < 0.05）的信号通路清单。失调最显著的信号通路HIV-I NEF，分别通过定量PCR和免疫组化分析在转录水平和蛋白水平得到了验证。使用HIV-I NEF信号通路的基因表达特征在独立数据集上进行无监督分析的验证，证实了我们方法的准确性。我们的结果表明，该信号通路在激素难治性前列腺癌中尤其失调。
