Elevated Serum MicroRNA Levels Associate with Absence of High-Grade Prostate Cancer in a Retrospective Cohort

To reduce treatment of indolent prostate cancer (PCa), biomarkers are needed to improve identification of patients with a low-risk of having aggressive disease. Over-treatment of these patients occurs because of uncertainty in the aggressiveness of the entire tumor based on the biopsies, which do not accurately sample multifocal tumors. Circulating microRNAs (miRNAs) are stable serum markers and differential miRNA levels occur in men with PCa. The goal of this study was to identify circulating miRNAs that were associated with aggressive or indolent PCa. We measured circulating miRNAs in 150 patients prior to surgery and compared the miRNA levels to the pathology of the entire radical prostatectomy specimen. For this study we used an exceptionally well-characterized cohort of patients who had benign prostatic hyperplasia (BPH), low-grade or high-grade PCa. Low-grade was defined as patients with 100% Gleason grade 3 tumor as determined by step-wise sectioning. High-grade PCa patients had 30-90% Gleason grade 4+5 in the tumor. BPH patients had at least two biopsies negative for PCa. Twenty one miRNAs were selected for analysis. The miRNAs were quantified by RT-qPCR and analyzed by logistic regression. High levels of 14 miRNAs were exclusively present in the serum from patients with low-grade PCa or BPH, compared to men with high-grade PCa who had consistently low levels. The expression levels of the 14 miRNAs were combined into a “miR Score” which had a negative predictive value (NPV) of 0.939 to predict absence of high-grade PCa among PCa and BPH patients. Biochemical recurrence (BCR) was known for the PCa patients and a combined “miR Risk Score” accurately classified a subset of patients with low risk of BCR (NPV 0.941). In summary, measurement of serum miRNAs may have pre-surgical utility in combination with clinical risk calculators to identify patients with low risk of harboring aggressive PCa.     

CD44 and PTGS2 Methylation are Independent Prognostic Markers for Biochemical Recurrence Among Prostate Cancer Patients with Clinically Localized Disease

Up to 30% of men with clinically localized disease who receive radical prostatectomy develop a biochemical recurrence. Gene methylation in tumor tissue may distinguish men with aggressive cancer. This study evaluated methylation of GSTP1, RARβ2, CD44 and PTGS2 with biochemical recurrence among 60 patients who underwent radical prostatectomy using logistic regression and Kaplan Meier time to event analysis. Methylation of GSTP1 and RARβ2 was not associated with recurrence, however, CD44 and PTGS2 methylation were significant predictors. In multivariate models adjusting for Gleason grade, methylation profile of CD44 and PTGS2 combined was an independent predictor of biochemical recurrence (associated with 9-fold increased risk). In addition, Kaplan Meier analysis showed CD44 and PTGS2 methylation was associated with shorter time to recurrence. CD44 and PTGS2 methylation may predict biochemical recurrence in prostate cancer patients undergoing radical prostatectomy and if validated in larger studies, may identify patients with aggressive cancer.     

Serum methionine metabolites are risk factors for metastatic prostate cancer progression

Background

Clinical decision for primary treatment for prostate cancer is dictated by variables with insufficient specificity. Early detection of prostate cancer likely to develop rapid recurrence could support neo-adjuvant therapeutics and adjuvant options prior to frank biochemical recurrence. This study compared markers in serum and urine of patients with rapidly recurrent prostate cancer to recurrence-free patients after radical prostatectomy. Based on previous identification of urinary sarcosine as a metastatic marker, we tested whether methionine metabolites in urine and serum could serve as pre-surgical markers for aggressive disease.

Methodology/Principal Findings

Urine and serum samples (n = 54 and 58, respectively), collected at the time of prostatectomy were divided into subjects who developed biochemical recurrence within 2 years and those who remained recurrence-free after 5 years. Multiple methionine metabolites were measured in urine and serum by GC-MS. The role of serum metabolites and clinical variables (biopsy Gleason grade, clinical stage, serum prostate specific antigen [PSA]) on biochemical recurrence prediction were evaluated. Urinary sarcosine and cysteine levels were significantly higher (p = 0.03 and p = 0.007 respectively) in the recurrent group. However, in serum, concentrations of homocysteine (p = 0.003), cystathionine (p = 0.007) and cysteine (p<0.001) were more abundant in the recurrent population. The inclusion of serum cysteine to a model with PSA and biopsy Gleason grade improved prediction over the clinical variables alone (p<0.001).

Conclusions

Higher serum homocysteine, cystathionine, and cysteine concentrations independently predicted risk of early biochemical recurrence and aggressiveness of disease in a nested case control study. The methionine metabolites further supplemented known clinical variables to provide superior sensitivity and specificity in multivariable prediction models for rapid biochemical recurrence following prostatectomy.     

TGF-β regulates DNA methyltransferase expression in prostate cancer, correlates with aggressive capabilities, and predicts disease recurrence

Background

DNA methyltransferase (DNMT) is one of the major factors mediating the methylation of cancer related genes such as TGF-β receptors (TβRs). This in turn may result in a loss of sensitivity to physiologic levels of TGF-β in aggressive prostate cancer (CaP). The specific mechanisms of DNMT''s role in CaP remain undetermined. In this study, we describe the mechanism of TGF-β-mediated DNMT in CaP and its association with clinical outcomes following radical prostatectomy.

Methodology/Principal Findings

We used human CaP cell lines with varying degrees of invasive capability to describe how TGF-β mediates the expression of DNMT in CaP, and its effects on methylation status of TGF-β receptors and the invasive capability of CaP in vitro and in vivo. Furthermore, we determined the association between DNMT expression and clinical outcome after radical prostatectomy. We found that more aggressive CaP cells had significantly higher TGF-β levels, increased expression of DNMT, but reduced TβRs when compared to benign prostate cells and less aggressive prostate cancer cells. Blockade of TGF-β signaling or ERK activation (p-ERK) was associated with a dramatic decrease in the expression of DNMT, which results in a coincident increase in the expression of TβRs. Blockade of either TGF-β signaling or DNMT dramatically decreased the invasive capabilities of CaP. Inhibition of TGF-β in an TRAMP-C2 CaP model in C57BL/6 mice using 1D11 was associated with downregulation of DNMTs and p-ERK and impairment in tumor growth. Finally, independent of Gleason grade, increased DNMT1 expression was associated with biochemical recurrence following surgical treatment for prostate cancer.

Conclusions and Significance

Our findings demonstrate that CaP derived TGF-β may induce the expression of DNMTs in CaP which is associated with methylation of its receptors and the aggressive potential of CaP. In addition, DNMTs is an independent predictor for disease recurrence after prostatectomy, and may have clinical implications for CaP prognostication and therapy.     

Discovery and Validation of a Prostate Cancer Genomic Classifier that Predicts Early Metastasis Following Radical Prostatectomy

Purpose

Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis.

Methods

A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry who underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 who experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set.

Results

Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67–0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression.

Conclusion

A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer.     

DNA methylation profiles in African American prostate cancer patients in relation to disease progression

This study examined whether differential DNA methylation is associated with clinical features of more aggressive disease at diagnosis and prostate cancer recurrence in African American men, who are more likely to die from prostate cancer than other populations. Tumor tissues from 76 African Americans diagnosed with prostate cancer who had radical prostatectomy as their primary treatment were profiled for epigenome-wide DNA methylation levels. Long-term follow-up identified 19 patients with prostate cancer recurrence. Twenty-three CpGs were differentially methylated (FDR q ≤ 0.25, mean methylation difference ≥ 0.10) in patients with vs. without recurrence, including CpGs in GCK, CDKL2, PRDM13, and ZFR2. Methylation differences were also observed between men with metastatic-lethal prostate cancer vs. no recurrence (five CpGs), regional vs. local pathological stage (two CpGs), and higher vs. lower tumor aggressiveness (one CpG). These results indicate that differentially methylated CpG sites identified in tumor tissues of African American men may contribute to prostate cancer aggressiveness.     

A Systems Genetics Approach Identifies CXCL14, ITGAX,and LPCAT2 as Novel Aggressive Prostate Cancer Susceptibility Genes

Although prostate cancer typically runs an indolent course, a subset of men develop aggressive, fatal forms of this disease. We hypothesize that germline variation modulates susceptibility to aggressive prostate cancer. The goal of this work is to identify susceptibility genes using the C57BL/6-Tg(TRAMP)8247Ng/J (TRAMP) mouse model of neuroendocrine prostate cancer. Quantitative trait locus (QTL) mapping was performed in transgene-positive (TRAMPxNOD/ShiLtJ) F2 intercross males (n = 228), which facilitated identification of 11 loci associated with aggressive disease development. Microarray data derived from 126 (TRAMPxNOD/ShiLtJ) F2 primary tumors were used to prioritize candidate genes within QTLs, with candidate genes deemed as being high priority when possessing both high levels of expression-trait correlation and a proximal expression QTL. This process enabled the identification of 35 aggressive prostate tumorigenesis candidate genes. The role of these genes in aggressive forms of human prostate cancer was investigated using two concurrent approaches. First, logistic regression analysis in two human prostate gene expression datasets revealed that expression levels of five genes (CXCL14, ITGAX, LPCAT2, RNASEH2A, and ZNF322) were positively correlated with aggressive prostate cancer and two genes (CCL19 and HIST1H1A) were protective for aggressive prostate cancer. Higher than average levels of expression of the five genes that were positively correlated with aggressive disease were consistently associated with patient outcome in both human prostate cancer tumor gene expression datasets. Second, three of these five genes (CXCL14, ITGAX, and LPCAT2) harbored polymorphisms associated with aggressive disease development in a human GWAS cohort consisting of 1,172 prostate cancer patients. This study is the first example of using a systems genetics approach to successfully identify novel susceptibility genes for aggressive prostate cancer. Such approaches will facilitate the identification of novel germline factors driving aggressive disease susceptibility and allow for new insights into these deadly forms of prostate cancer.     

Detection of aggressive prostate cancer associated glycoproteins in urine using glycoproteomics and mass spectrometry

Clinical management of prostate cancer remains a significant challenge due to the lack of available tests for guiding treatment decisions. The blood prostate‐specific antigen test has facilitated early detection and intervention of prostate cancer. However, blood prostate‐specific antigen levels are less effective in distinguishing aggressive from indolent prostate cancers and other benign prostatic diseases. Thus, the development of novel approaches specific for prostate cancer that can differentiate aggressive from indolent disease remains an urgent medical need. In the current study, we evaluated urine specimens from prostate cancer patients using LC‐MS/MS, with the aim of identifying effective urinary prostate cancer biomarkers. Glycoproteins from urine samples of prostate cancer patients with different Gleason scores were characterized via solid phase extraction of N‐linked glycosite‐containing peptides and LC‐MS/MS. A total of 2923 unique glycosite‐containing peptides were identified. Glycoproteomic comparison on urine and tissues from aggressive and non‐aggressive prostate cancers as well as sera from prostate cancer patients revealed that the majority of AG prostate cancer associated glycoproteins were more readily detected in patient's urine than serum samples. Our data collectively indicate that urine provides a potential source for biomarker testing in patients with AG prostate cancer.     

Pathways affected by asbestos exposure in normal and tumour tissue of lung cancer patients

Background:

The early detection of prostate cancer has resulted in an increase in the number of patients with localized prostate cancer and has paralleled the reported reduction in prostate cancer mortality. The increased rate of detection of patients with localized prostate cancer may also increase the risk of potentially morbid therapy in a patient with indolent cancer. Defining the biomarker correlates of prostate cancer virulence will facilitate the appropriate application and development of therapy for patients with early disease.

Methods:

A 255 core prostate cancer tissue microarray (TMA) from 47 prostatectomy specimens with organ confined tumor was constructed. Prostate cancer foci of transition and peripheral zone origin were represented on the TMA. Further, replicate cores of the two Gleason grades comprising the Gleason score, representative of Gleason scores 5-9, were arrayed from each prostatectomy specimen. Standard immunohistochemical techniques were used to assess expression of nine, cell death and cell cycle regulatory proteins implicated in the pathogenesis of prostate cancer (bax, bcl-2, bcl-x_L, bin1, CD95, mdm2, p21, p53, and NFkB).

Results:

The Spearman correlation coefficient revealed a strong correlation of bax, bin1, FAS, p65 and p21 expression with Gleason grade. Spearman correlation coefficients showed that expression of, bax and bin1, bax and MDM2, Bax and p21, and bax and p65 NFkB was highly associated. Other significant associations were identified between bin1 and p21, bin1 and MDM2, bin1 and p65 NFkB and between p21 and p65 NFκB. A model for predicting the biological potential of Gleason score 7 prostate cancer using multivariable logistic regression methods was developed. The findings also indicate that the profile of specific markers for Gleason grade 3 prostate cancer correlates with the overall context of the Gleason score.

Conclusion:

These data support the view that important molecular differences exist among and between the Gleason scores. Furthermore, there is significant molecular heterogeneity among prostatectomy specimens containing Gleason grade 3 cancer. This observation may have broader implications regarding the determination of risk among patients with prostate cancer that is currently considered to be of either good prognosis or unclear prognosis, i.e. Gleason score 7 tumors.     

Co-Occurring Gland Angularity in Localized Subgraphs: Predicting Biochemical Recurrence in Intermediate-Risk Prostate Cancer Patients

Quantitative histomorphometry (QH) refers to the application of advanced computational image analysis to reproducibly describe disease appearance on digitized histopathology images. QH thus could serve as an important complementary tool for pathologists in interrogating and interpreting cancer morphology and malignancy. In the US, annually, over 60,000 prostate cancer patients undergo radical prostatectomy treatment. Around 10,000 of these men experience biochemical recurrence within 5 years of surgery, a marker for local or distant disease recurrence. The ability to predict the risk of biochemical recurrence soon after surgery could allow for adjuvant therapies to be prescribed as necessary to improve long term treatment outcomes. The underlying hypothesis with our approach, co-occurring gland angularity (CGA), is that in benign or less aggressive prostate cancer, gland orientations within local neighborhoods are similar to each other but are more chaotically arranged in aggressive disease. By modeling the extent of the disorder, we can differentiate surgically removed prostate tissue sections from (a) benign and malignant regions and (b) more and less aggressive prostate cancer. For a cohort of 40 intermediate-risk (mostly Gleason sum 7) surgically cured prostate cancer patients where half suffered biochemical recurrence, the CGA features were able to predict biochemical recurrence with 73% accuracy. Additionally, for 80 regions of interest chosen from the 40 studies, corresponding to both normal and cancerous cases, the CGA features yielded a 99% accuracy. CGAs were shown to be statistically signicantly () better at predicting BCR compared to state-of-the-art QH methods and postoperative prostate cancer nomograms.     

Expression changes in the stroma of prostate cancer predict subsequent relapse

Biomarkers are needed to address overtreatment that occurs for the majority of prostate cancer patients that would not die of the disease but receive radical treatment. A possible barrier to biomarker discovery may be the polyclonal/multifocal nature of prostate tumors as well as cell-type heterogeneity between patient samples. Tumor-adjacent stroma (tumor microenvironment) is less affected by genetic alteration and might therefore yield more consistent biomarkers in response to tumor aggressiveness. To this end we compared Affymetrix gene expression profiles in stroma near tumor and identified a set of 115 probe sets for which the expression levels were significantly correlated with time-to-relapse. We also compared patients that chemically relapsed shortly after prostatectomy (<1 year), and patients that did not relapse in the first four years after prostatectomy. We identified 131 differentially expressed microarray probe sets between these two categories. 19 probe sets (15 genes overlapped between the two gene lists with p<0.0001). We developed a PAM-based classifier by training on samples containing stroma near tumor: 9 rapid relapse patient samples and 9 indolent patient samples. We then tested the classifier on 47 different samples, containing 90% or more stroma. The classifier predicted the risk status of patients with an average accuracy of 87%. This is the first general tumor microenvironment-based prognostic classifier. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for predicting outcomes for patients.     

前列腺癌患者前列腺体积与肿瘤分级之间关系探讨

目的:探讨国人前列腺癌患者前列腺体积与肿瘤分级之间的关系。方法:回顾我院及武汉大学人民医院2005年1月-2011年10月70例确诊为前列腺癌并行根治性前列腺切除术(RP)患者的临床病理资料,采用SPSS13.0软件总结并分析前列腺癌患者前列腺体积与肿瘤分级之间的关系。结果:经直肠前列腺穿刺活检获得肿瘤病理分级与根治性前列切除术获得最终病理分级具有显著差异(P=0.003);在活检及根治性前列腺切除标本中,前列腺体积与高级别肿瘤发生率均呈负相关(P<0.05);小前列腺与阳性手术切缘、前列腺外侵犯及高级别肿瘤在单变量分析中具有相关性(P<0.05),而与精囊腺侵犯及淋巴结侵犯则无相关性(P>0.05);在校正了年龄、体重指数及术前前列腺特异性抗原水平后,前列腺体积与阳性手术切缘、前列腺外侵犯、精囊腺侵犯及高级别肿瘤发生率均呈负相关(OR<1,P<0.05),而与淋巴结侵犯则无相关性(P>0.05)。结论:前列腺体积是高级别前列腺癌的重要预测因子,利用其对高级别肿瘤风险的预测能力可帮助选择最佳治疗方案并进一步提高治疗效果。     

Long Noncoding RNAs AC009014.3 and Newly Discovered XPLAID Differentiate Aggressive and Indolent Prostate Cancers

INTRODUCTION: The molecular mechanisms underlying aggressive versus indolent disease are not fully understood. Recent research has implicated a class of molecules known as long noncoding RNAs (lncRNAs) in tumorigenesis and progression of cancer. Our objective was to discover lncRNAs that differentiate aggressive and indolent prostate cancers. METHODS: We analyzed paired tumor and normal tissues from six aggressive Gleason score (GS) 8-10 and six indolent GS 6 prostate cancers. Extracted RNA was split for poly(A)+ and ribosomal RNA depletion library preparations, followed byRNA sequencing (RNA-Seq) using an Illumina HiSeq 2000. We developed an RNA-Seq data analysis pipeline to discover and quantify these molecules. Candidate lncRNAs were validated using RT-qPCR on 87 tumor tissue samples: 28 (GS 6), 28 (GS 3+4), 6 (GS 4+3), and 25 (GS 8-10). Statistical correlations between lncRNAs and clinicopathologic variables were tested using ANOVA. RESULTS: The 43 differentially expressed (DE) lncRNAs between aggressive and indolent prostate cancers included 12 annotated and 31 novel lncRNAs. The top six DE lncRNAs were selected based on large, consistent fold-changes in the RNA-Seq results. Three of these candidates passed RT-qPCR validation, including AC009014.3 (P < .001 in tumor tissue) and a newly discovered X-linked lncRNA named XPLAID (P = .049 in tumor tissue and P = .048 in normal tissue). XPLAID and AC009014.3 show promise as prognostic biomarkers. CONCLUSIONS: We discovered several dozen lncRNAs that distinguish aggressive and indolent prostate cancers, of which four were validated using RT-qPCR. The investigation into their biology is ongoing.     

DNA methylation changes correlate with Gleason score and tumor stage in prostate cancer

DNA methylation, a widely used epigenetic mark, has been associated with many tumors. However, few studies have addressed the role of cell-free plasma DNA methylation in discriminating aggressive prostate cancer (PCa) from indolent cases. We conducted a case series and a case-control study among histologically confirmed stage II/III cases and matched controls recruited at Columbia University Medical Center. The aim of this study was to investigate whether plasma DNA methylation levels are appropriate surrogate biomarker of PCa tumor tissue levels and whether these markers are associated with worse clinicopathological tumor characteristics, which correlate with poorer prognosis. Quantitative pyrosequencing was used to detect methylation levels of p16 (CDKN4A), APC, GSTP1, and LINE-1 in 24 pairs of prostate tumor and adjacent tissues, as well as 27 plasma samples of PCa patients and 24 of controls. DNA methylation levels were significantly higher in tumor tissue than in adjacent nontumor tissue for p16 (CDKN4A), GSTP1, and APC; GSTP1 had a higher average percentage methylation in tumor tissue (38.9%) compared with p16 (CDKN4A) (5.9%) and APC (14.5%). GSTP1, p16 (CDKN4A), and APC methylation in tumor tissue was statistically significantly higher for cases with Gleason score ≥7 compared with those with Gleason score <7 [49.0% vs. 21.9% (p=0.01), 6.6% vs. 4.5% (p=0.04), and 19.1% vs. 7.4% (p=0.02), respectively]. Plasma LINE-1 methylation levels were higher in those with higher Gleason (67.6%) than in those with Gleason's below 7 (64.6%, p=0.03). Significant plasma-tissue correlations were observed for GSTP1 and LINE-1 methylation. These data, although preliminary, suggest that aberrant methylation may be a useful marker to identify PCa patients with clinically aggressive disease.     

Evaluation and treatment of men with biochemical prostate-specific antigen recurrence following definitive therapy for clinically localized prostate cancer

Early detection and monitoring by serum prostate-specific antigen (PSA) measurement has increased the number of men presenting with potentially curable prostate cancer. Most will choose radical prostatectomy or some form of radiation therapy for treatment, but some will have evidence of biochemical disease recurrence following therapy, shown by a rising PSA level without other clinical evidence of disease. Radical prostatectomy involves the removal of all prostate tissue, causing the serum PSA to decline to undetectable levels within four to six weeks following surgery; a subsequent rise in the serum PSA to a detectable level indicates disease recurrence. Patients should be evaluated to assess whether rising PSA levels indicate local recurrence or early metastatic disease. The advantages of salvage radiation, endocrine therapy, and other treatment modalities in local disease recurrence must be weighed against potential side effects and the resulting decrease in quality of life. Radiation therapy does not immediately eradicate all PSA-producing cells; therefore the persistence of a detectable PSA does not necessarily imply residual cancer, but rising PSA levels indicate treatment failure. Salvage surgery can be performed after radiotherapy for the purpose of removing all viable cancer cells, but should be weighed against a higher incidence of surgical complications; cryoablation offers a less invasive therapeutic modality.     

Spermine and Citrate as Metabolic Biomarkers for Assessing Prostate Cancer Aggressiveness

Separating indolent from aggressive prostate cancer is an important clinical challenge for identifying patients eligible for active surveillance, thereby reducing the risk of overtreatment. The purpose of this study was to assess prostate cancer aggressiveness by metabolic profiling of prostatectomy tissue and to identify specific metabolites as biomarkers for aggressiveness. Prostate tissue samples (n = 158, 48 patients) with a high cancer content (mean: 61.8%) were obtained using a new harvesting method, and metabolic profiles of samples representing different Gleason scores (GS) were acquired by high resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS). Multivariate analysis (PLS, PLS-DA) and absolute quantification (LCModel) were used to examine the ability to predict cancer aggressiveness by comparing low grade (GS = 6, n = 30) and high grade (GS≥7, n = 81) cancer with normal adjacent tissue (n = 47). High grade cancer tissue was distinguished from low grade cancer tissue by decreased concentrations of spermine (p = 0.0044) and citrate (p = 7.73·10⁻⁴), and an increase in the clinically applied (total choline+creatine+polyamines)/citrate (CCP/C) ratio (p = 2.17·10⁻⁴). The metabolic profiles were significantly correlated to the GS obtained from each tissue sample (r = 0.71), and cancer tissue could be distinguished from normal tissue with sensitivity 86.9% and specificity 85.2%. Overall, our findings show that metabolic profiling can separate aggressive from indolent prostate cancer. This holds promise for the benefit of applying in vivo magnetic resonance spectroscopy (MRS) within clinical MR imaging investigations, and HR-MAS analysis of transrectal ultrasound-guided biopsies has a potential as an additional diagnostic tool.     

Proteomic Profiling of Androgen-independent Prostate Cancer Cell Lines Reveals a Role for Protein S during the Development of High Grade and Castration-resistant Prostate Cancer

Androgen deprivation constitutes the principal therapy for advanced and metastatic prostate cancers. However, this therapeutic intervention usually results in the transition to a more aggressive androgen-independent prostate cancer. The elucidation of molecular alterations during the progression to androgen independence is an integral step toward discovering more effective targeted therapies. With respect to identifying crucial mediators of this transition, we compared the proteomes of androgen-independent (PC3, DU145, PPC1, LNCaP-SF, and 22Rv1) and androgen-dependent (LNCaP and VCaP) and/or normal prostate epithelial (RWPE) cell lines using mass spectrometry. We identified more than 100 proteins that were differentially secreted in the androgen-independent cell lines. Of these, Protein S (PROS1) was elevated in the secretomes of all of the androgen-independent prostate cancer cell lines, with no detectable secretion in normal and androgen-dependent cell lines. Using quantitative PCR, we observed significantly higher (p < 0.05) tissue expression levels of PROS1 in prostate cancer samples, further indicating its importance in prostate cancer progression. Similarly, immunohistochemistry analysis revealed elevation of PROS1 in high grade prostate cancer (Gleason grade ≥8), and further elevation in castration-resistant metastatic prostate cancer lesions. We also observed its significant (p < 0.05) elevation in high grade prostate cancer seminal plasma samples. Taken together, these results show that PROS1 is elevated in high grade and castration-resistant prostate cancer and could serve as a potential biomarker of aggressive disease.