However, extensive genome-wide gene Indoprofen expression Octinoxate characterization between these cell lines and LNCaP, have found them to be most similar to one another vs. other androgen sensitive cell lines, LAPC4 or 22Rv1 or vs. AR-null cell lines PC3 and DU145. Thus, if this differential hormone stimulation experiment were to be performed using MDA-PCa-2a or -2b cell lines, we would identify the same AR protein complexes in vitro, as LNCaP, and would also predict disease survival in vivo from clinical population data. We subsequently determined whether these predictive gene-sets were cancer specific and extracted gene expression datasets with available clinical outcome profiles for breast, lymphoma, lung and medulloblastoma clinical samples. The gene-sets illustrated in Figure 4 did not give significant outcome values for any of the four other cancers. Furthermore, the remaining 8 gene-sets, described above, also lacked significant predictive outcomes for the same 4 non-prostate cancers analyzed. In hormone-dependent breast cancer, certain ethnic population differences have been observed, with higher incidences of breast cancer occurring in African-American woman vs. other groups, but similar population demographic data used for the CaP cohort analyzed within our study was not available for the non-CaP cancers used in this analysis. Such genetic expression data would have been useful for further confirmatory follow-up studies. However, the expression of the AR has been described in a number of non-CaP cancers, especially breast cancer. It has also been shown that several cell lines from these non-CaP cancers show androgen sensitivity and androgen-dependent gene expression profiles similar to CaP cell lines. However, we have identified AR interactome gene-sets that can that can differentiate between CaP and non-CaP disease survival which suggests that there are unique molecular characteristics of AR function in CaP and part of a CaP-specific pathway in neoplastic development, and also that these gene-sets can be used to predict CaP disease outcomes between genetically diverse groups.