Bharathi Laxman

Metabolomic Profiles Delineate Potential Role for Sarcosine in Prostate Cancer Progression

Multiple, complex molecular events characterize cancer development and progression. 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 tumours, 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 1,126 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 increased during prostate cancer progression to metastasis and can be detected non-invasively in urine. Sarcosine levels were also increased in invasive prostate cancer cell lines relative to benign prostate epithelial cells. Knockdown of glycine-N-methyl transferase, 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, induced an invasive phenotype in benign prostate epithelial cells. Androgen receptor and the ERG gene fusion product coordinately regulate components of the sarcosine pathway. Here, by profiling the metabolomic alterations of prostate cancer progression, we reveal sarcosine as a potentially important metabolic intermediary of cancer cell invasion and aggressivity.

Genomic loss of microRNA-101 leads to overexpression of histone methyltransferase EZH2 in cancer.

Enhancer of zeste homolog 2 (EZH2) is a mammalian histone methyltransferase that contributes to the epigenetic silencing of target genes and regulates the survival and metastasis of cancer cells. EZH2 is overexpressed in aggressive solid tumors by mechanisms that remain unclear. Here we show that the expression and function of EZH2 in cancer cell lines are inhibited by microRNA-101 (miR-101). Analysis of human prostate tumors revealed that miR-101 expression decreases during cancer progression, paralleling an increase in EZH2 expression. One or both of the two genomic loci encoding miR-101 were somatically lost in 37.5% of clinically localized prostate cancer cells (6 of 16) and 66.7% of metastatic disease cells (22 of 33). We propose that the genomic loss of miR-101 in cancer leads to overexpression of EZH2 and concomitant dysregulation of epigenetic pathways, resulting in cancer progression.

Distinct classes of chromosomal rearrangements create oncogenic ETS gene fusions in prostate cancer.

Recently, we identified recurrent gene fusions involving the 5′ untranslated region of the androgen-regulated gene TMPRSS2 and the ETS (E26 transformation-specific) family genes ERG, ETV1 or ETV4 in most prostate cancers. Whereas TMPRSS2–ERG fusions are predominant, fewer TMPRSS2–ETV1 cases have been identified than expected on the basis of the frequency of high (outlier) expression of ETV1 (refs 3–13). Here we explore the mechanism of ETV1 outlier expression in human prostate tumours and prostate cancer cell lines. We identified previously unknown 5′ fusion partners in prostate tumours with ETV1 outlier expression, including untranslated regions from a prostate-specific androgen-induced gene (SLC45A3) and an endogenous retroviral element (HERV-K_22q11.23), a prostate-specific androgen-repressed gene (C15orf21), and a strongly expressed housekeeping gene (HNRPA2B1). To study aberrant activation of ETV1, we identified two prostate cancer cell lines, LNCaP and MDA-PCa 2B, that had ETV1 outlier expression. Through distinct mechanisms, the entire ETV1 locus (7p21) is rearranged to a 1.5-megabase prostate-specific region at 14q13.3–14q21.1 in both LNCaP cells (cryptic insertion) and MDA-PCa 2B cells (balanced translocation). Because the common factor of these rearrangements is aberrant ETV1 overexpression, we recapitulated this event in vitro and in vivo, demonstrating that ETV1 overexpression in benign prostate cells and in the mouse prostate confers neoplastic phenotypes. Identification of distinct classes of ETS gene rearrangements demonstrates that dormant oncogenes can be activated in prostate cancer by juxtaposition to tissue-specific or ubiquitously active genomic loci. Subversion of active genomic regulatory elements may serve as a more generalized mechanism for carcinoma development. Furthermore, the identification of androgen-repressed and insensitive 5′ fusion partners may have implications for the anti-androgen treatment of advanced prostate cancer.

Transcriptome sequencing across a prostate cancer cohort identifies PCAT-1 , an unannotated lincRNA implicated in disease progression

Noncoding RNAs (ncRNAs) are emerging as key molecules in human cancer, with the potential to serve as novel markers of disease and to reveal uncharacterized aspects of tumor biology. Here we discover 121 unannotated prostate cancer–associated ncRNA transcripts (PCATs) by ab initio assembly of high-throughput sequencing of polyA+ RNA (RNA-Seq) from a cohort of 102 prostate tissues and cells lines. We characterized one ncRNA, PCAT-1, as a prostate-specific regulator of cell proliferation and show that it is a target of the Polycomb Repressive Complex 2 (PRC2). We further found that patterns of PCAT-1 and PRC2 expression stratified patient tissues into molecular subtypes distinguished by expression signatures of PCAT-1–repressed target genes. Taken together, our findings suggest that PCAT-1 is a transcriptional repressor implicated in a subset of prostate cancer patients. These findings establish the utility of RNA-Seq to identify disease-associated ncRNAs that may improve the stratification of cancer subtypes.High-throughput sequencing of polyA+ RNA (RNA-Seq) in human cancer shows remarkable potential to identify both novel markers of disease and uncharacterized aspects of tumor biology, particularly non-coding RNA (ncRNA) species. We employed RNA-Seq on a cohort of 102 prostate tissues and cells lines and performed ab initio transcriptome assembly to discover unannotated ncRNAs. We nominated 121 such Prostate Cancer Associated Transcripts (PCATs) with cancer-specific expression patterns. Among these, we characterized PCAT-1 as a novel prostate-specific regulator of cell proliferation and target of the Polycomb Repressive Complex 2 (PRC2). We further found that high PCAT-1 and PRC2 expression stratified patient tissues into molecular subtypes distinguished by expression signatures of PCAT-1-repressed target genes. Taken together, the findings presented herein identify PCAT-1 as a novel transcriptional repressor implicated in subset of prostate cancer patients. These findings establish the utility of RNA-Seq to identify disease-associated ncRNAs that may improve the stratification of cancer subtypes.

An Integrated Network of Androgen Receptor, Polycomb, and TMPRSS2-ERG Gene Fusions in Prostate Cancer Progression

Chromosomal rearrangements fusing the androgen-regulated gene TMPRSS2 to the oncogenic ETS transcription factor ERG occur in approximately 50% of prostate cancers, but how the fusion products regulate prostate cancer remains unclear. Using chromatin immunoprecipitation coupled with massively parallel sequencing, we found that ERG disrupts androgen receptor (AR) signaling by inhibiting AR expression, binding to and inhibiting AR activity at gene-specific loci, and inducing repressive epigenetic programs via direct activation of the H3K27 methyltransferase EZH2, a Polycomb group protein. These findings provide a working model in which TMPRSS2-ERG plays a critical role in cancer progression by disrupting lineage-specific differentiation of the prostate and potentiating the EZH2-mediated dedifferentiation program.

Repression of E-cadherin by the polycomb group protein EZH2 in cancer.

Enhancer of zeste homolog 2 (EZH2) is a critical component of the polycomb-repressive complex 2 (PRC2), which is involved in gene silencing and histone H3 lysine 27 methylation. EZH2 has a master regulatory function in controlling such processes as stem cell differentiation, cell proliferation, early embryogenesis and X chromosome inactivation. Although benign epithelial cells express very low levels of EZH2, increased levels of EZH2 have been observed in aggressive solid tumors such as those of the prostate, breast and bladder. The mechanism by which EZH2 mediates tumor aggressiveness is unclear. Here, we demonstrate that EZH2 mediates transcriptional silencing of the tumor suppressor gene E-cadherin by trimethylation of H3 lysine 27. Histone deacetylase inhibitors can prevent EZH2-mediated repression of E-cadherin and attenuate cell invasion, suggesting a possible mechanism that may be useful for the development of therapeutic treatments. Taken together, these observations provide a novel mechanism of E-cadherin regulation and establish a functional link between dysregulation of EZH2 and repression of E-cadherin during cancer progression.

A First-Generation Multiplex Biomarker Analysis of Urine for the Early Detection of Prostate Cancer

Although prostate-specific antigen (PSA) serum level is currently the standard of care for prostate cancer screening in the United States, it lacks ideal specificity and additional biomarkers are needed to supplement or potentially replace serum PSA testing. Emerging evidence suggests that monitoring the noncoding RNA transcript PCA3 in urine may be useful in detecting prostate cancer in patients with elevated PSA levels. Here, we show that a multiplex panel of urine transcripts outperforms PCA3 transcript alone for the detection of prostate cancer. We measured the expression of seven putative prostate cancer biomarkers, including PCA3, in sedimented urine using quantitative PCR on a cohort of 234 patients presenting for biopsy or radical prostatectomy. By univariate analysis, we found that increased GOLPH2, SPINK1, and PCA3 transcript expression and TMPRSS2:ERG fusion status were significant predictors of prostate cancer. Multivariate regression analysis showed that a multiplexed model, including these biomarkers, outperformed serum PSA or PCA3 alone in detecting prostate cancer. The area under the receiver-operating characteristic curve was 0.758 for the multiplexed model versus 0.662 for PCA3 alone (P = 0.003). The sensitivity and specificity for the multiplexed model were 65.9% and 76.0%, respectively, and the positive and negative predictive values were 79.8% and 60.8%, respectively. Taken together, these results provide the framework for the development of highly optimized, multiplex urine biomarker tests for more accurate detection of prostate cancer.

Noninvasive real-time imaging of apoptosis

Strict coordination of proliferation and programmed cell death (apoptosis) is essential for normal physiology. An imbalance in these two opposing processes results in various diseases including AIDS, neurodegenerative disorders, myelodysplastic syndromes, ischemia/reperfusion injury, cancer, autoimmune disease, among others. Objective and quantitative noninvasive imaging of apoptosis would be a significant advance for rapid and dynamic screening as well as validation of experimental therapeutic agents. Here, we report the development of a recombinant luciferase reporter molecule that when expressed in mammalian cells has attenuated levels of reporter activity. In cells undergoing apoptosis, a caspase-3-specific cleavage of the recombinant product occurs, resulting in the restoration of luciferase activity that can be detected in living animals with bioluminescence imaging. The ability to image apoptosis noninvasively and dynamically over time provides an opportunity for high-throughput screening of proapoptotic and antiapoptotic compounds and for target validation in vivo in both cell lines and transgenic animals.

The role of SPINK1 in ETS rearrangement-negative prostate cancers

ETS gene fusions have been characterized in a majority of prostate cancers; however, the key molecular alterations in ETS-negative cancers are unclear. Here we used an outlier meta-analysis (meta-COPA) to identify SPINK1 outlier expression exclusively in a subset of ETS rearrangement-negative cancers ( approximately 10% of total cases). We validated the mutual exclusivity of SPINK1 expression and ETS fusion status, demonstrated that SPINK1 outlier expression can be detected noninvasively in urine, and observed that SPINK1 outlier expression is an independent predictor of biochemical recurrence after resection. We identified the aggressive 22RV1 cell line as a SPINK1 outlier expression model and demonstrate that SPINK1 knockdown in 22RV1 attenuates invasion, suggesting a functional role in ETS rearrangement-negative prostate cancers.

Combining urinary detection of TMPRSS2:ERG and PCA3 with serum PSA to predict diagnosis of prostate cancer

OBJECTIVES We sought to develop a clinical algorithm combining serum PSA with detection of TMPRSS2:ERG fusion and PCA3 in urine collected after digital rectal exam (post-DRE urine) to predict prostate cancer on subsequent biopsy. MATERIALS AND METHODS Post-DRE urine was collected in 48 consecutive patients before prostate biopsy at 2 centers; quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to detect PCA3 and TMPRSS2:ERG fusion transcript expression. Serum PSA was measured by clinical assay. The performance of TMPRSS2:ERG fusion, PCA3, and serum PSA as biomarkers predicting prostate cancer at biopsy was measured; a clinically practical algorithm combining serum PSA with TMPRSS2:ERG and PCA3 in post-DRE urine to predict prostate cancer was developed. RESULTS Post-DRE urine sediment provided informative RNA in 45 patients; prostate cancer was present on subsequent biopsy in 15. TMPRSS2:ERG in post-DRE urine was associated with prostate cancer (OR = 12.02; P < 0.001). PCA3 had the highest sensitivity in predicting prostate cancer diagnosis (93%), whereas TMPRSS2:ERG had the highest specificity (87%). TMPRSS2:ERG had the greatest discriminatory value in predicting prostate cancer (AUC = 0.77 compared with 0.65 for PCA3 and 0.72 for serum PSA alone). Combining serum PSA, PCA3, and TMPRSS2:ERG in a multivariable algorithm optimized for clinical utility improved cancer prediction (AUC = 0.88; specificity = 90% at 80% sensitivity). CONCLUSIONS A clinical algorithm specifying biopsy for all patients with PSA ≥ 10 ng/ml, while restricting biopsy among those with PSA <10 ng/ml to only those with detectable PCA3 or TMPRSS2:ERG in post-DRE urine, performed better than the individual biomarkers alone in predicting prostate cancer.