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.
Integrative microarray analysis of pathways dysregulated in metastatic prostate cancer.
Demichelis, Francesca;
2007-01-01
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione