Cancer-associated changes in the expression of TMPRSS2-ERG, PCA3, and SPINK1 in histologically benign tissue from cancerous vs noncancerous prostatectomy specimens

Genetic signature of prostate cancer mouse models resistant to optimized hK2 targeted α-particle therapy

Hu11B6 is a monoclonal antibody that internalizes in cells expressing androgen receptor (AR)-regulated prostate-specific enzyme human kallikrein-related peptidase 2 (hK2; KLK2). In multiple rodent models, Actinium-225-labeled hu11B6-IgG1 ([225Ac]hu11B6-IgG1) has shown promising treatment efficacy. In the present study, we investigated options to enhance and optimize [225Ac]hu11B6 treatment. First, we evaluated the possibility of exploiting IgG3, the IgG subclass with superior activation of complement and ability to mediate FC-γ-receptor binding, for immunotherapeutically enhanced hK2 targeted α-radioimmunotherapy. Second, we compared the therapeutic efficacy of a single high activity vs. fractionated activity. Finally, we used RNA sequencing to analyze the genomic signatures of prostate cancer that progressed after targeted α-therapy. [225Ac]hu11B6-IgG3 was a functionally enhanced alternative to [225Ac]hu11B6-IgG1 but offered no improvement of therapeutic efficacy. Progression-free survival was slightly increased with a single high activity compared to fractionated activity. Tumor-free animals succumbing after treatment revealed no evidence of treatment-associated toxicity. In addition to up-regulation of canonical aggressive prostate cancer genes, such as MMP7, ETV1, NTS, and SCHLAP1, we also noted a significant decrease in both KLK3 (prostate-specific antigen ) and FOLH1 (prostate-specific membrane antigen) but not in AR and KLK2, demonstrating efficacy of sequential [225Ac]hu11B6 in a mouse model.

Prostate cancer risk SNP rs10993994 is a trans-eQTL for SNHG11 mediated through MSMB

How genome-wide association studies-identified single-nucleotide polymorphisms (SNPs) affect remote genes remains unknown. Expression quantitative trait locus (eQTL) association meta-analysis on 496 prostate tumor and 602 normal prostate samples with 117 SNPs revealed novel cis-eQTLs and trans-eQTLs. Mediation testing and colocalization analysis demonstrate that MSMB is a cis-acting mediator for SNHG11 (P < 0.01). Removing rs10993994 in LNCaP cell lines by CRISPR/Cas9 editing shows that the C-allele corresponds with an over 100-fold increase in MSMB expression and 5-fold increase in SNHG11 compared with the T-allele. Colocalization analysis confirmed that the same set of SNPs associated with MSMB expression is associated with SNHG11 expression (posterior probability of shared variants is 66.6% in tumor and 91.4% in benign). These analyses further demonstrate variants driving MSMB expression differ in tumor and normal, suggesting regulatory network rewiring during tumorigenesis.

Prostate Cancer Risk Stratification in Men With a Clinical Suspicion of Prostate Cancer Using a Unique Biparametric MRI and Expression of 11 Genes in Apparently Benign Tissue: Evaluation Using Machine-Learning Techniques

BACKGROUND

Accurate risk stratification of men with a clinical suspicion of prostate cancer (cSPCa) remains challenging despite the increasing use of MRI.

PURPOSE

To evaluate the diagnostic accuracy of a unique biparametric MRI protocol (IMPROD bpMRI) combined with clinical and molecular markers in men with cSPCa.

STUDY TYPE

Prospective single-institutional clinical trial (NCT01864135).

SUBJECTS

Eighty men with cSPCa.

FIELD STRENGTH/SEQUENCE

3T, surface array coils. Two T₂ -weighted and three diffusion-weighted imaging (DWI) acquisitions: 1) b-values 0, 100, 200, 300, 500 s/mm² ; 2) b-values 0,1500 s/mm² ; 3) b-values 0, 2000 s/mm² .

ASSESSMENT

IMPROD bpMRI examinations were qualitatively (IMPROD bpMRI Likert score) and quantitatively (DWI-based Gleason grade score) prospectively reported. Men with IMPROD bpMRI Likert 3-5 had two targeted biopsies followed by 12-core systematic biopsies (SB); those with IMPROD bpMRI Likert 1-2 had only SB. Additionally, 2-core from normal-appearing prostate areas were obtained for the mRNA expression of ACSM1, AMACR, CACNA1D, DLX1, PCA3, PLA2G7, RHOU, SPINK1, SPON2, TMPRSS2-ERG, and TDRD1 measured by quantitative reverse-transcription polymerase chain reaction.

STATISTICAL TESTS

Univariate and multivariate analysis using regularized least-squares, feature selection and tournament leave-pair-out cross-validation (TLPOCV), as well as 10 random splits of the data in training-testing sets, were used to evaluate the mRNA, clinical and IMPROD bpMRI parameters in detecting clinically significant prostate cancer (SPCa) defined as Gleason score ≥ 3 + 4. The evaluation metric was the area under the curve (AUC).

RESULTS

IMPROD bpMRI Likert demonstrated the highest TLPOCV AUC of 0.92. The tested clinical variables had AUC 0.56-0.73, while the mRNA and additional IMPROD bpMRI parameters had AUC 0.50-0.67 and 0.65-0.89 respectively. The combination of clinical and mRNA biomarkers produced TLPOCV AUC of 0.87, the highest TLPOCV performance without including IMPROD bpMRI Likert.

DATA CONCLUSION

The qualitative IMPROD bpMRI Likert score demonstrated the highest accuracy for SPCa detection compared with the tested clinical variables and mRNA biomarkers.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1540-1553.

Association of multiparametric MRI quantitative imaging features with prostate cancer gene expression in MRI-targeted prostate biopsies

Standard clinicopathological variables are inadequate for optimal management of prostate cancer patients. While genomic classifiers have improved patient risk classification, the multifocality and heterogeneity of prostate cancer can confound pre-treatment assessment. The objective was to investigate the association of multiparametric (mp)MRI quantitative features with prostate cancer risk gene expression profiles in mpMRI-guided biopsies tissues.Global gene expression profiles were generated from 17 mpMRI-directed diagnostic prostate biopsies using an Affimetrix platform. Spatially distinct imaging areas ('habitats') were identified on MRI/3D-Ultrasound fusion. Radiomic features were extracted from biopsy regions and normal appearing tissues. We correlated 49 radiomic features with three clinically available gene signatures associated with adverse outcome. The signatures contain genes that are over-expressed in aggressive prostate cancers and genes that are under-expressed in aggressive prostate cancers. There were significant correlations between these genes and quantitative imaging features, indicating the presence of prostate cancer prognostic signal in the radiomic features. Strong associations were also found between the radiomic features and significantly expressed genes. Gene ontology analysis identified specific radiomic features associated with immune/inflammatory response, metabolism, cell and biological adhesion. To our knowledge, this is the first study to correlate radiogenomic parameters with prostate cancer in men with MRI-guided biopsy.

Diagnostic Value of ERG in Prostate Needle Biopsies Containing Minute Cancer Foci

BACKGROUND

Prostate carcinoma (PC) is the second most diagnosed cancer in men population worldwide. The small amount of the tissue in prostate needle biopsy is often sufficient for the correct interpretation. Novel antibodies, as ERG, could add to the diagnostic value of IHC study in analysing difficult core biopsies.

AIM

The aim of the present study was to establish a diagnostic use of ERG in a work-up of prostate needle biopsies containing minute PC, individually and in combination with AMACR/34βE12.

MATERIALS AND METHODS

From total number of 1710 consecutive prostate needle biopsies based on HE stain 114 biopsies containing minute PC. Selected biopsies were incubated with anti-ERG, AMACR and 34βE12 antibodies using immunohistochemical technique.

RESULTS

Among 98 selected biopsies, 57 showed positive and 41 negative ERG staining. AMACR staining was positively expressed in 86 of the cases and completely absent in remaining 12. In 9 of the AMACR-negative cases the final diagnosis was establish by manifestation of ERG expression in the tumour foci. 95 of the biopsies demonstrated lack of 34βE12 expression and only 3 cases showed weak patchy staining. Among these cases 2 were ERG-positive.

CONCLUSION

ERG antibody could be especially helpful in the cases with controversial expression of AMACR and 34βE12.

Biomarkers for prostate cancer: present challenges and future opportunities

Prostate cancer (PCa) has variable biological potential with multiple treatment options. A more personalized approach, therefore, is needed to better define men at higher risk of developing PCa, discriminate indolent from aggressive disease and improve risk stratification after treatment by predicting the likelihood of progression. This may improve clinical decision-making regarding management, improve selection for active surveillance protocols and minimize morbidity from treatment. Discovery of new biomarkers associated with prostate carcinogenesis present an opportunity to provide patients with novel genetic signatures to better understand their risk of developing PCa and help forecast their clinical course. In this review, we examine the current literature evaluating biomarkers in PCa. We also address current limitations and present several ideas for future studies.

Altered PCA3 and TMPRSS2-ERG expression in histologically benign regions of cancerous prostates: a systematic, quantitative mRNA analysis in five prostates

Background

PCA3 and TMPRSS2-ERG are commonly overexpressed biomarkers in prostate cancer, but reports have emerged demonstrating altered expression also in areas outside the tumour foci in cancerous prostates. Our aim was to measure PCA3 and TMPRSS2-ERG expression systematically in all regions of prostate cross-sections, matching the data to corresponding tissue morphology.

Methods

TMPRSS2-ERG and PCA3 mRNA levels were measured with quantitative reverse-transcription PCR assays in 270 samples from cross-sections of five radical prostatectomy specimens. ERG expression was examined by immunohistochemistry.

Results

TMPRSS2-ERG mRNAs were detected in three patients and in 15 tissue samples in total. These included two carcinoma samples and 13 histologically benign samples, eight of which were located next to malignant tumours or PIN (prostatic intraepithelial neoplasia) lesions and five of which did not reside in the vicinity of any evident carcinoma foci. ERG protein expression was limited to areas of TMPRSS2-ERG mRNA expression, but did not identify all of them. PCA3 expression was detected in all five cross-sections, with statistically significant, three-fold higher expression in carcinoma regions.

Conclusions

TMPRSS2-ERG expression was detected in carcinoma foci, regions next to them, and in samples not adjacent to carcinoma foci. Claimed as a cancer-associated phenomenon, this fusion gene measurement could, if validated with a larger cohort, be utilized as an addition to histological analysis to predict current or future cancer risk in men with negative biopsies. Molecular changes outside the carcinoma foci are also indicated for PCA3, as its expression was only moderately increased in the carcinoma regions.

SPINK1 Promoter Variants Are Associated with Prostate Cancer Predisposing Alterations in Benign Prostatic Hyperplasia Patients

BACKGROUND/AIM

Several studies reported that patients with benign prostatic hyperplasia (BPH) experienced a 10% increased incidence of prostate cancer (PCa) after the first 5 years of diagnosis. We investigated the association between single nucleotide polymorphisms (SNPs) in the promoter of Serine Protease Inhibitor Kazal Type 1 (SPINK1) and the increased risk of BPH and PCa.

MATERIALS AND METHODS

We genotyped three SNPs in a cases-control study, including BPH and PCa cases. Multiple logistic regression models were applied to analyze clinical and genotypic data.

RESULTS

We found an inverse association between SNP rs10035432 and BPH under the log-additive (p=0.007) model. No association was found between these SNPs and PCa risk. However, we observed a possible association between rs1432982 and lower-grade PCa (p=0.05) under the recessive model.

CONCLUSION

SPINK1 promoter variants are likely to be associated with the risk of BPH.

Genomic Predictors of Outcome in Prostate Cancer

CONTEXT

Given the highly variable behavior and clinical course of prostate cancer (PCa) and the multiple available treatment options, a personalized approach to oncologic risk stratification is important. Novel genetic approaches offer additional information to improve clinical decision making.

OBJECTIVE

To review the use of genomic biomarkers in the prognostication of PCa outcome and prediction of therapeutic response.

EVIDENCE ACQUISITION

Systematic literature review focused on human clinical studies reporting outcome measures with external validation. The literature search included all Medline, Embase, and Scopus articles from inception through July 2014.

EVIDENCE SYNTHESIS

An improved understanding of the genetic basis of prostate carcinogenesis has produced an increasing number of potential prognostic and predictive tools, such as transmembrane protease, serine2:v-ets avian erythroblastosis virus E26 oncogene homolog (TMPRSS2:ERG) gene fusion status, loss of the phosphatase and tensin homolog (PTEN) gene, and gene expression signatures utilizing messenger RNA from tumor tissue. Several commercially available gene panels with external validation are now available, although most have yet to be widely used. The most studied commercially available gene panels, Prolaris, Oncotype DX Genomic Prostate Score, and Decipher, may be used to estimate disease outcome in addition to clinical parameters or clinical nomograms. ConfirmMDx is an epigenetic test used to predict the results of repeat prostate biopsy after an initial negative biopsy. Additional future strategies include using genetic information from circulating tumor cells in the peripheral blood to guide treatment decisions at the initial diagnosis and at subsequent decision points.

CONCLUSIONS

Major advances have been made in our understanding of PCa biology in recent years. Our field is currently exploring the early stages of a personalized approach to augment traditional clinical decision making using commercially available genomic tools. A more comprehensive appreciation of value, limitations, and cost is important.

PATIENT SUMMARY

We summarized current advances in genomic testing in prostate cancer with a special focus on the estimation of disease outcome. Several commercial tests are currently available, but further understanding is needed to appreciate the potential benefits and limitations of these novel tests.

A panel of DNA methylation markers reveals extensive methylation in histologically benign prostate biopsy cores from cancer patients

BACKGROUND

Men with a negative first prostate biopsy will undergo one or more additional biopsies if they remain at high suspicion of prostate cancer. To date, there are no diagnostic tests capable of identifying patients at risk for a positive diagnosis with the predictive power needed to eliminate unnecessary repeat biopsies. Efforts to develop clinical tests using the epigenetic signature of cores recovered from first biopsies have been limited to a few markers and lack the sensitivity and specificity needed for widespread clinical adoption.

METHODS

We developed methylation-specific quantitative polymerase chain reaction assays for a panel of 24 markers that are preferentially methylated in prostate cancer. We modified the bisulfite conversion conditions to allow the integration of the methylation information from multiple markers. We determined the methylation status of the 24 markers in 213 prostate biopsy cores from 104 patients, 37 prostate cancer patients and 67 controls. We performed logistic regression on combinations of markers as well as the entire panel of 24 markers to identify the best candidates for a diagnostic test.

RESULTS

The marker panel differentiated between cancer cores and benign cores from non-cancer patients with 100% sensitivity and 97% specificity. Furthermore, the panel detected significant methylation in benign cores from prostate cancer patients that was not present in controls. Using methylation of 5 out of 24 to define a cancer case, the analysis of a single benign biopsy core identified 62% of prostate cancer patients undergoing repeat biopsies. ROC curve analysis showed that markers commonly methylated in benign cores from cancer patients are the best candidates for a diagnostic test. The results suggest that 5 to 10 markers will be needed to achieve optimal predictive power.

CONCLUSIONS

This study shows that epigenetic field effects differ significantly between cancer patients and controls. Their detection in benign biopsy cores can form the basis of diagnostic tests to identify patients in need of repeat biopsies, reducing the cost of continued PCA screening by up to 40%. They could also be used to identify prostate cancer patients with low grade disease who are likely candidates for active surveillance or focal therapy.

Detection of TMPRSS2-ERG fusion gene in benign prostatic hyperplasia

The Ets-related gene fusions are among the most common molecular alterations in prostate cancer (PCa) and are detected in more than 50 % of PCas. Transmembrane protease serine 2 and Ets-related gene fusion (TMPRSS2-ERG) is the most frequently identified chimeric gene and has been associated with undifferentiated and invasive phenotypes. TMPRSS2-ERG has also been detected in prostate intraepithelial neoplasia (PIN) lesions and more rarely in benign prostatic hyperplasia (BPH) regions mainly in PCa-bearing glands. The possibility that the fusion TMPRSS2-ERG may be present in BPH samples in the absence of apparent PCa was addressed. Out of 115 BPH samples, three were found positive employing RT-PCR. The presence of the fusion gene was confirmed by FISH for these samples, and an additional four samples were found to carry the TMPRSS2-ERG fusion out of 43 tested by the later approach. The presence of the TMPRSS2-ERG fusion did not result in altered expression of 12 putative downstream targets. These findings indicate that TMPRSS2-ERG may or may not lead to PCa development.

The role of biomarkers in the assessment of prostate cancer risk prior to prostate biopsy: which markers matter and how should they be used?

Prostate cancer (PCa) screening has been substantially influenced by the clinical implementation of serum prostate-specific antigen (PSA). In this context, improvement of early PCa detection and stage migration as well as reduced PCa mortality were achieved, and up-to-date PSA represents the gold standard biomarker of PCa diagnosis together with clinical findings. Nonetheless, PSA shows weakness in discriminating between malign and benign prostatic disease or indolent and aggressive cancers. As a result, the expansion of PSA screening is extensively debated with regard to overdetection and ultimately overtreatment, keeping in mind that PCa is still the third leading cause of cancer-specific mortality in the Western male population. Consequently, today's task is to increase the accuracy of PCa detection and furthermore to allow stratification for indolent PCa that might permit active surveillance and to filter out aggressive cancers necessitating treatment. Thus, novel biomarkers, especially in combination with approved clinical risk factors (e.g., age or family history of PCa), within multivariable prediction models carry the potential to improve many aspects of PCa diagnosis and to enable risk classification in clinical practice. Multivariable models lead to superior accuracy for PCa prediction instead of the use of a single risk factor. The aim of this article was to present an overview of known risk factors for PCa together with new promising blood- and urine-based biomarkers and their application within risk models that may allow risk stratification for PCa prior to prostate biopsy. Risk models may optimize PCa detection and classification with regard to improved PCa risk assessment and avoidance of unnecessary prostate biopsies.