Differential proteomic alterations between localised and metastatic prostate cancer

Molecular alterations in the prostate cancer proteome mediate the functional and phenotypic transformation from clinically localised to metastatic cancer, a transition that drives patient's mortality and challenges therapeutic intervention. A first approximation of differential proteomic alterations stratified by disease stage has yielded repertoires of potential diagnostic and prognostic markers, multiplex signatures of predictive value, and yield fundamental insight into molecular commonalities in cancer progression. Deciphering these causative proteomic alterations from the molecular noise will continue to mature our understanding of tumour biology and drive new computational and integrative approaches to model a system's view that accommodates the heterogeneity of prostate cancer progression

Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics

Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper, we present an extension of the BHC algorithm. Our Gaussian BHC (GBHC) algorithm represents data as a mixture of Gaussian distributions. It uses normal-gamma distribution as a conjugate prior on the mean and precision of each of the Gaussian components. We tested GBHC over 11 cancer and 3 synthetic datasets. The results on cancer datasets show that in sample clustering, GBHC on average produces a clustering partition that is more concordant with the ground truth than those obtained from other commonly used algorithms. Furthermore, GBHC frequently infers the number of clusters that is often close to the ground truth. In gene clustering, GBHC also produces a clustering partition that is more biologically plausible than several other state-of-the-art methods. This suggests GBHC as an alternative tool for studying gene expression data. The implementation of GBHC is available at https://sites. google.com/site/gaussianbhc

GOLPH2 protein expression as a novel tissue biomarker for prostate cancer: implications for tissue-based diagnostics

GOLPH2 is coding the 73-kDa type II Golgi membrane antigen GOLPH2/GP73. Upregulation of GOLPH2 mRNA has been recently reported in expression array analyses of prostate cancer. As GOLPH2 protein expression in prostate tissues is currently unknown, this study aimed at a comprehensive analysis of GOLPH2 protein in benign and malignant prostate lesions. Immunohistochemically detected GOLPH2 protein expression was compared with the basal cell marker p63 and the prostate cancer marker α-methylacyl-CoA racemase (AMACR) in 614 radical prostatectomy specimens. GOLPH2 exhibited a perinuclear Golgi-type staining pattern and was preferentially seen in prostatic gland epithelia. Using a semiquantitative staining intensity score, GOLPH2 expression was significantly higher in prostate cancer glands compared with normal glands (P<0.001). GOLPH2 protein was upregulated in 567 of 614 tumours (92.3%) and AMACR in 583 of 614 tumours (95%) (correlation coefficient 0.113, P=0.005). Importantly, GOLPH2 immunohistochemistry exhibited a lower level of intratumoral heterogeneity (25 vs 45%). Further, GOLPH2 upregulation was detected in 26 of 31 (84%) AMACR-negative prostate cancer cases. These data clearly suggest GOLPH2 as an additional ancillary positive marker for tissue-based diagnosis of prostate cancer

Targeting DNA-PKcs and ATM with miR-101 Sensitizes Tumors to Radiation

Radiotherapy kills tumor-cells by inducing DNA double strand breaks (DSBs). However, the efficient repair of tumors frequently prevents successful treatment. Therefore, identifying new practical sensitizers is an essential step towards successful radiotherapy. In this study, we tested the new hypothesis: identifying the miRNAs to target DNA DSB repair genes could be a new way for sensitizing tumors to ionizing radiation.HERE, WE CHOSE TWO GENES: DNA-PKcs (an essential factor for non-homologous end-joining repair) and ATM (an important checkpoint regulator for promoting homologous recombination repair) as the targets to search their regulating miRNAs. By combining the database search and the bench work, we picked out miR-101. We identified that miR-101 could efficiently target DNA-PKcs and ATM via binding to the 3'- UTR of DNA-PKcs or ATM mRNA. Up-regulating miR-101 efficiently reduced the protein levels of DNA-PKcs and ATM in these tumor cells and most importantly, sensitized the tumor cells to radiation in vitro and in vivo.These data demonstrate for the first time that miRNAs could be used to target DNA repair genes and thus sensitize tumors to radiation. These results provide a new way for improving tumor radiotherapy

The Marker State Space (MSS) Method for Classifying Clinical Samples

The development of accurate clinical biomarkers has been challenging in part due to the diversity between patients and diseases. One approach to account for the diversity is to use multiple markers to classify patients, based on the concept that each individual marker contributes information from its respective subclass of patients. Here we present a new strategy for developing biomarker panels that accounts for completely distinct patient subclasses. Marker State Space (MSS) defines "marker states" based on all possible patterns of high and low values among a panel of markers. Each marker state is defined as either a case state or a control state, and a sample is classified as case or control based on the state it occupies. MSS was used to define multi-marker panels that were robust in cross validation and training-set/test-set analyses and that yielded similar classification accuracy to several other classification algorithms. A three-marker panel for discriminating pancreatic cancer patients from control subjects revealed subclasses of patients based on distinct marker states. MSS provides a straightforward approach for modeling highly divergent subclasses of patients, which may be adaptable for diverse applications. © 2013 Fallon et al

Six-transmembrane epithelial antigen of the prostate and enhancer of zeste homolog 2 as immunotherapeutic targets for lung cancer

<p>Abstract</p> <p>Background</p> <p>T-cell based immunotherapy for lung cancer (LC) could be a promising and novel therapeutic approach. Six-transmembrane epithelial antigen of the prostate (STEAP) and the polycomb group protein enhancer of zeste homolog 2 (EZH2) are highly expressed in LC and since the expression of molecules in normal tissue is significantly lower as compared to tumor cells, these proteins are considered as potential tumor-associated antigens (TAAs) for developing T-cell based immunotherapy.</p> <p>Methods</p> <p>We assessed the capacity of predicted CD4 T-cell epitopes from STEAP and EZH2 to induce anti-tumor immune responses to LC cell lines.</p> <p>Results</p> <p>Out of several predicted epitopes, two synthetic peptides, STEAP_281-296and EZH2_95-109, were effective in inducing CD4 T-cell responses that were restricted by HLA-DR1, DR15, or DR53 molecules, indicating that the peptides function as promiscuous T-cell epitopes. Moreover, STEAP_281-296and EZH2_95-109-reactive T-cells could directly recognize STEAP or EZH2 expressing LC cells in an HLA-DR restricted manner. In addition, some STEAP-reactive T-cells responded to STEAP+ tumor cell lysates presented by autologous dendric cells. Most significantly, both of these peptides were capable of stimulating <it>in vitro </it>T-cell responses in patients with LC.</p> <p>Conclusions</p> <p>Peptides STEAP_281-296and EZH2_95-109function as strong CD4 T-cell epitopes that can elicit effective anti-tumor T-cell responses against STEAP or EZH2 expressing LC. These observations may facilitate the translation of T-cell based immunotherapy into the clinic for the treatment of LC.</p

Enhancer of zeste homolog 2 (EZH2) expression is an independent prognostic factor in renal cell carcinoma

Background: The enhancer of zeste homolog 2 (EZH2) gene exerts oncogene-like activities and its (over)expression has been linked to several human malignancies. Here, we studied a possible association between EZH2 expression and prognosis in patients with renal cell carcinoma (RCC). Methods: EZH2 protein expression in RCC specimens was analyzed by immunohistochemistry using a tissue microarray (TMA) containing RCC tumor tissue and corresponding normal tissue samples of 520 patients. For immunohistochemical assessment of EZH2 expression, nuclear staining quantity was evaluated using a semiquantitative score. The effect of EZH2 expression on cancer specific survival (CSS) was assessed by univariate and multivariate Cox regression analyses. Results: During follow-up, 147 patients (28%) had died of their disease, median follow-up of patients still alive was 6.0 years (range 0 - 16.1 years). EZH2 nuclear staining was present in tumor cores of 411 (79%) patients. A multivariate Cox regression analysis revealed that high nuclear EZH2 expression was an independent predictor of poor CSS (>25-50% vs. 0%: HR 2.72, p = 0.025) in patients suffering from non-metastatic RCC. Apart from high nuclear EZH2 expression, tumor stage and Fuhrman's grading emerged as significant prognostic markers. In metastatic disease, nuclear EZH2 expression and histopathological subtype were independent predictive parameters of poor CSS (EZH2: 1-5%: HR 2.63, p = 0.043, >5-25%: HR 3.35, p = 0.013, >25%-50%: HR 4.92, p = 0.003, all compared to 0%: HR 0.36, p = 0.025, respectively). Conclusions: This study defines EZH2 as a powerful independent unfavourable prognostic marker of CSS in patients with metastatic and non-metastatic RCC

The Role of EZH2 in the Regulation of the Activity of Matrix Metalloproteinases in Prostate Cancer Cells

Degradation of the extracellular matrix (ECM), a critical step in cancer metastasis, is determined by the balance between MMPs (matrix metalloproteinases) and their inhibitors TIMPs (tissue inhibitors of metalloproteinases). In cancer cells, this balance is shifted towards MMPs, promoting ECM degradation. Here, we show that EZH2 plays an active role in this process by repressing the expression of TIMP2 and TIMP3 in prostate cancer cells. The TIMP genes are derepressed by knockdown of EZH2 expression in human prostate cancer cells but repressed by overexpression of EZH2 in benign human prostate epithelial cells. EZH2 catalyzes H3K27 trimethylation and subsequent DNA methylation of the TIMP gene promoters. Overexpression of EZH2 confers an invasive phenotype on benign prostate epithelial cells; however, this phenotype is suppressed by cooverexpression of TIMP3. EZH2 knockdown markedly reduces the proteolytic activity of MMP-9, thereby decreasing the invasive activity of prostate cancer cells. These results suggest that the transcriptional repression of the TIMP genes by EZH2 may be a major mechanism to shift the MMPs/TIMPs balance in favor of MMP activity and thus to promote ECM degradation and subsequent invasion of prostate cancer cells

The Synovial Sarcoma-Associated SYT-SSX2 Oncogene Antagonizes the Polycomb Complex Protein Bmi1

This study demonstrates deregulation of polycomb activity by the synovial sarcoma-associated SYT-SSX2 oncogene, also known as SS18-SSX2. Synovial sarcoma is a soft tissue cancer associated with a recurrent t(X:18) translocation event that generates one of two fusion proteins, SYT-SSX1 or SYT-SSX2. The role of the translocation products in this disease is poorly understood. We present evidence that the SYT-SSX2 fusion protein interacts with the polycomb repressive complex and modulates its gene silencing activity. SYT-SSX2 causes destabilization of the polycomb subunit Bmi1, resulting in impairment of polycomb-associated histone H2A ubiquitination and reactivation of polycomb target genes. Silencing by polycomb complexes plays a vital role in numerous physiological processes. In recent years, numerous reports have implicated gain of polycomb silencing function in several cancers. This study provides evidence that, in the appropriate context, expression of the SYT-SSX2 oncogene leads to loss of polycomb function. It challenges the notion that cancer is solely associated with an increase in polycomb function and suggests that any imbalance in polycomb activity could drive the cell toward oncogenesis. These findings provide a mechanism by which the SYT-SSX2 chimera may contribute to synovial sarcoma pathogenesis

Expression of the Stress Response Oncoprotein LEDGF/p75 in Human Cancer: A Study of 21 Tumor Types

Oxidative stress-modulated signaling pathways have been implicated in carcinogenesis and therapy resistance. The lens epithelium derived growth factor p75 (LEDGF/p75) is a transcription co-activator that promotes resistance to stress-induced cell death. This protein has been implicated in inflammatory and autoimmune conditions, HIV-AIDS, and cancer. Although LEDGF/p75 is emerging as a stress survival oncoprotein, there is scarce information on its expression in human tumors. The present study was performed to evaluate its expression in a comprehensive panel of human cancers. Transcript expression was examined in the Oncomine cancer gene microarray database and in a TissueScan Cancer Survey Panel quantitative polymerase chain reaction (Q-PCR) array. Protein expression was assessed by immunohistochemistry (IHC) in cancer tissue microarrays (TMAs) containing 1735 tissues representing single or replicate cores from 1220 individual cases (985 tumor and 235 normal tissues). A total of 21 major cancer types were analyzed. Analysis of LEDGF/p75 transcript expression in Oncomine datasets revealed significant upregulation (tumor vs. normal) in 15 out of 17 tumor types. The TissueScan Cancer Q-PCR array revealed significantly elevated LEDGF/p75 transcript expression in prostate, colon, thyroid, and breast cancers. IHC analysis of TMAs revealed significant increased levels of LEDGF/p75 protein in prostate, colon, thyroid, liver and uterine tumors, relative to corresponding normal tissues. Elevated transcript or protein expression of LEDGF/p75 was observed in several tumor types. These results further establish LEDGF/p75 as a cancer-related protein, and provide a rationale for ongoing studies aimed at understanding the clinical significance of its expression in specific human cancers