DNA microarrays have been widely applied to cancer transcriptome analysis; however, the majority of such data are not easily accessible or comparable. Furthermore, several important analytic approaches have been applied to microarray analysis; however, their application is often limited. To overcome these limitations, we have developed Oncomine, a bioinformatics initiative aimed at collecting, standardizing, analyzing, and delivering cancer transcriptome data to the biomedical research community. Our analysis has identified the genes, pathways, and networks deregulated across 18,000 cancer gene expression microarrays, spanning the majority of cancer types and subtypes. Here, we provide an update on the initiative, describe the database and analysis modules, and highlight several notable observations. Results from this comprehensive analysis are available at http://www.oncomine.org.

Multiple, complex molecular events characterize cancer development and progression1,2. Deciphering the molecular networks that distinguish organ-confined disease from metastatic disease may lead to the identification of critical biomarkers for cancer invasion and disease aggressiveness. Although gene and protein expression have been extensively profiled in human tumors, little is known about the global metabolomic alterations that characterize neoplastic progression. Using a combination of high throughput liquid and gas chromatography-based mass spectrometry, we profiled more than 1126 metabolites across 262 clinical samples related to prostate cancer (42 tissues and 110 each of urine and plasma). These unbiased metabolomic profiles were able to distinguish benign prostate, clinically localized prostate cancer, and metastatic disease. Sarcosine, an N-methyl derivative of the amino acid glycine, was identified as a differential metabolite that was highly elevated during prostate cancer progression to metastasis and can be detected non-invasively in urine. Sarcosine levels were also elevated in invasive prostate cancer cell lines relative to benign prostate epithelial cells. Knockdown of glycine-N-methyl transferase (GNMT), the enzyme that generates sarcosine from glycine, attenuated prostate cancer invasion. Addition of exogenous sarcosine or knockdown of the enzyme that leads to sarcosine degradation, sarcosine dehydrogenase (SARDH), induced an invasive phenotype in benign prostate epithelial cells. Androgen receptor and the ERG gene fusion product coordinately regulate components of the sarcosine pathway. Taken together, we profiled the metabolomic alterations of prostate cancer progression revealing sarcosine as a potentially important metabolic intermediary of cancer cell invasion and aggressivity.

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Despite efforts to profile prostate cancer, the genetic alterations and biological processes that correlate with the observed histological progression are unclear. Using laser-capture microdissection to isolate 101 cell populations, we have profiled prostate cancer progression from benign epithelium to metastatic disease. By analyzing expression signatures in the context of over 14,000 'molecular concepts', or sets of biologically connected genes, we generated an integrative model of progression. Molecular concepts that demarcate critical transitions in progression include protein biosynthesis, E26 transformation-specific (ETS) family transcriptional targets, androgen signaling and cell proliferation. Of note, relative to low-grade prostate cancer (Gleason pattern 3), high-grade cancer (Gleason pattern 4) shows an attenuated androgen signaling signature, similar to metastatic prostate cancer, which may reflect dedifferentiation and explain the clinical association of grade with prognosis. Taken together, these data show that analyzing gene expression signatures in the context of a compendium of molecular concepts is useful in understanding cancer biology.