Current perspectives on Gleason grading of prostate cancer

Identification of Plausible Candidates in Prostate Cancer Using Integrated Machine Learning Approaches

Background

Currently, prostate-specific antigen (PSA) is commonly used as a prostate cancer (PCa) biomarker. PSA is linked to some factors that frequently lead to erroneous positive results or even needless biopsies of elderly people.

Objectives

In this pilot study, we undermined the potential genes and mutations from several databases and checked whether or not any putative prognostic biomarkers are central to the annotation. The aim of the study was to develop a risk prediction model that could help in clinical decision-making.

Methods

An extensive literature review was conducted, and clinical parameters for related comorbidities, such as diabetes, obesity, as well as PCa, were collected. Such parameters were chosen with the understanding that variations in their threshold values could hasten the complicated process of carcinogenesis, more particularly PCa. The gathered data was converted to semi-binary data (-1, -0.5, 0, 0.5, and 1), on which machine learning (ML) methods were applied. First, we cross-checked various publicly available datasets, some published RNA-seq datasets, and our whole-exome sequencing data to find common role players in PCa, diabetes, and obesity. To narrow down their common interacting partners, interactome networks were analysed using GeneMANIA and visualised using Cytoscape, and later cBioportal was used (to compare expression level based on Z scored values) wherein various types of mutation w.r.t their expression and mRNA expression (RNA seq FPKM) plots are available. The GEPIA 2 tool was used to compare the expression of resulting similarities between the normal tissue and TCGA databases of PCa. Later, top-ranking genes were chosen to demonstrate striking clustering coefficients using the Cytoscape-cytoHubba module, and GEPIA 2 was applied again to ascertain survival plots.

Results

Comparing various publicly available datasets, it was found that BLM is a frequent player in all three diseases, whereas comparing publicly available datasets, GWAS datasets, and published sequencing findings, SPFTPC and PPIMB were found to be the most common. With the assistance of GeneMANIA, TMPO and FOXP1 were found as common interacting partners, and they were also seen participating with BLM.

Conclusion

A probabilistic machine learning model was achieved to identify key candidates between diabetes, obesity, and PCa. This, we believe, would herald precision scale modeling for easy prognosis.

JPX and LINC00641 ncRNAs expression in prostate tissue: a case-control study

Background and purpose

Prostate cancer (PC) is the second most prevalent cancer in men. Prostate-specific antigen (PSA) is the main biomarker for screening PC. An increase in PSA could lead to false-positive results. Thus, more appropriate markers should be investigated. In the present study, JPX and LINC00641 expression levels were measured in tumoral prostate tissue compared with the non-tumor tissue.

Experimental approach

43 pairs of prostate tumoral and non-tumor tissue were prepared. The expression levels of JPX and LINC00641 were investigated by RT-qPCR.

Findings/Results

Significant upregulation of LINC00641 (2.47 ± 0.5 vs 1.41 ± 0.2) and downregulation of JPX (1.42 ± 0.6 vs 2.83 ± 1.0) were observed in PC tissues compared with the normal tissues (their adjacent non-tumoral tissues).

Conclusion and implications

Dysregulation of JPX and LINC00641 in PC patients could be used in the future as a prognostic biomarker in PC.

Initial Evaluation of Rapid, Direct-to-Digital Prostate Biopsy Pathology

CONTEXT.—

Pathologist interobserver discordance is significant in grading of prostate cancer, limiting reliability. Diagnostic reproducibility may be improved with digital images, but adoption faces workflow, cost, and quality challenges. A novel digital method using an alternative tissue processing approach and novel laser microscopy system potentially addresses these issues.

OBJECTIVE.—

To evaluate the capability of this new method for primary diagnostic interpretation in clinical prostate biopsy specimens.

DESIGN.—

Forty patients with a high likelihood of prostate cancer based on magnetic resonance imaging consented to investigational core biopsy. A subset of samples was used for direct comparison of physical slide preparation effects and time-tracking determination with multiphoton microscopy. Twenty samples were processed for diagnostic comparison between multilevel digital slides and subsequently produced physical slides. A reference diagnosis based on all data was established using grade groups. Level of diagnostic match and requests for immunohistochemistry were compared between physical and digital diagnoses. Immunohistochemical staining and length measurements were secondary outcomes.

RESULTS.—

Interpretations based on direct multiphoton imaging yielded diagnoses that were at least as accurate as standard histology; cancer diagnosis correlation was 89% (51 of 57) by physical slides and 95% (53 of 56) by multiphoton microscopy. Grade-level concordance was 73% (44 of 60) by either method. Immunohistochemistry for routine prostate cancer-associated markers on these alternatively processed tissues was unaffected. Alternatively processed tissues resulted in longer measured core and cancer lengths, suggestive of improved orientation and visualization.

CONCLUSIONS.—

Findings support high potential for complete interpretation of prostate core biopsies using solely multiphoton microscopy of intact specimens, with potential diagnostic benefits as well as reduced processing time and reduced processing complexity.

Exploration on Gleason score variation trend of patients with prostate carcinoma from 1996 to 2019: a retrospective single center study

Background

Gleason score (GS) is one of the stronger prognostic factors and is integral to the management of prostate carcinoma. Subsequent modifications, recommended by the International Society of Urological Pathology in 2005 and 2014, enabled accurate prediction of prognosis. The present study investigated GS variation trend of patients with prostate carcinoma from 1996 to 2019 and offered an overview of GS changes with age, specimen type, histopathological type and serum prostate specific antigen (PSA).

Methods

One thousand three hundred and seventy-six patients, admitted to Peking University People's Hospital in 1996 to 2019, were divided into 1996 to 2006, 2007 to 2015 and 2016 to 2019 groups. Data, including demographic characteristics, GS, primary and secondary grade and percentage of primary and secondary grade of each group, were collected and analyzed. The population distribution and average of GS was evaluated, after segmented and stratified by age, type of specimen, histopathological type and PSA.

Results

The average of age and PSA of each cohort had no obvious change. The average of total GS fluctuated among three cohorts with statistically significant differences. The distribution of age and PSA did not differ among cohorts. The distribution of total and primary GS shifted, with more patients detected as total GS higher than 6 (86.1%), and more primary grade higher than 3 (56.7%) in 2016-2019. After segmented and stratified by age, specimen type, histological type and PSA, the population percentage of GS over 6 was significantly higher in 2016-2019 than 1996-2006 and 2007-2015 in patients aged younger than 80 years (age <60, 89.6%, age 60-69, 82.0%, age 70-79, 87.7%). Patients, aged below 80 years in 2016-2019, were detected with higher total GS.

Conclusions

In the present study, GS in patients with prostate carcinoma showed a upward trend. Primary grade, age, serum PSA and specimen type were the main reasons for GS changing while secondary grade, tissue types and diagnostic criteria influenced less.

Epithelial splicing regulatory protein 1 and 2 (ESRP1 and ESRP2) upregulation predicts poor prognosis in prostate cancer

Background

Epithelial splicing regulatory protein 1 (ESRP1) and 2 (ESRP2) regulate alternative splicing events of various pre-mRNAs. Some of these targets play a role in cancer-associated processes, including cytoskeleton reorganization and DNA-repair processes. This study was undertaken to estimate the impact of ESRP1 and ESRP2 alterations on prostate cancer patient prognosis.

Methods

A tissue microarray made from 17,747 individual cancer samples with comprehensive, pathological, clinical and molecular data was analyzed by immunohistochemistry for ESRP1 and ESRP2.

Results

Nuclear staining for ESRP1 was seen in 38.6% (36.0% low, 2.6% high) of 12,140 interpretable cancers and in 41.9% (36.4% low, 5.3% high) of 12,962 interpretable cancers for ESRP2. Nuclear protein expression was linked to advanced tumor stage, high Gleason score, presence of lymph node metastasis, early biochemical recurrence, and ERG-positive cancers (p < 0.0001 each). Expression of ESRPs was significantly linked to 11 (ESRP1)/9 (ESRP2) of 11 analyzed deletions in all cancers and to 8 (ESRP1)/9 (ESRP2) of 11 deletions in ERG-negative cancers portending a link to genomic instability. Combined ESRPs expression analysis suggested an additive effect and showed the worst prognosis for cancers with high ESRP1 and ESRP2 expression. Multivariate analyses revealed that the prognostic impact of ESRP1, ESRP2 and combined ESRP1/ESRP2 expression was independent of all established pre- and postoperative prognostic features.

Conclusions

Our data show a striking link between nuclear ESRP expression and adverse features in prostate cancer and identifies expression of ESRP1 and/or ESRP2 as independent prognostic markers with a potential for routine application.

High B7-H3 expression is linked to increased risk of prostate cancer progression

B7-H3 is a member of the B7 superfamily of immune checkpoint molecules. B7-H3 up regulation has been linked to cancer development and progression in many tumors including prostate cancer. To clarify the potential utility of B7-H3 as a prognostic biomarker, B7-H3 expression was analyzed by immunohistochemistry in more than 17 000 prostate cancers. Normal prostatic glands were largely B7-H3 negative, while membranous B7-H3 immunostaining was seen in 47.0% of analyzed cancers. B7-H3 immunostaining was weak in 12.3%, moderate in 21.1% and strong in 13.5% of cases. High B7-H3 expression was associated with pT, Gleason score, lymph node metastasis, high Ki67 labeling index and early prostate-specific antigen recurrence (P < 0.0001 each). High B7-H3 expression was also linked to high androgen receptor expression and TMPRSS2:V-ets avian erythroblastosis virus E26 oncogene homolog (ERG) fusions (P < 0.0001 each). Multivariate analyses showed a strong independent prognostic impact of high B7-H3 expression in all cancers and in the ERG negative subgroup. Comparison with previously analyzed frequent chromosomal deletions revealed a close association with Phosphatase and Tensin Homolog deletions. Analysis of B7-H3, alone or in combination with other markers, might be of clinical utility, especially in the subgroup of ERG negative prostate cancers.

The 2019 International Society of Urological Pathology (ISUP) Consensus Conference on Grading of Prostatic Carcinoma

Five years after the last prostatic carcinoma grading consensus conference of the International Society of Urological Pathology (ISUP), accrual of new data and modification of clinical practice require an update of current pathologic grading guidelines. This manuscript summarizes the proceedings of the ISUP consensus meeting for grading of prostatic carcinoma held in September 2019, in Nice, France. Topics brought to consensus included the following: (1) approaches to reporting of Gleason patterns 4 and 5 quantities, and minor/tertiary patterns, (2) an agreement to report the presence of invasive cribriform carcinoma, (3) an agreement to incorporate intraductal carcinoma into grading, and (4) individual versus aggregate grading of systematic and multiparametric magnetic resonance imaging-targeted biopsies. Finally, developments in the field of artificial intelligence in the grading of prostatic carcinoma and future research perspectives were discussed.

Upregulation of Phosphatase 1 Nuclear-Targeting Subunit (PNUTS) Is an Independent Predictor of Poor Prognosis in Prostate Cancer

Protein phosphatase 1 nuclear-targeting subunit (PNUTS) is ubiquitously expressed and associates with PTEN and protein phosphatase 1 (PP1) to control its activity. The role of PNUTS overexpression has hardly been studied in cancer. In this study, we used immunohistochemistry to quantitate PNUTS expression on a tissue microarray containing 17,747 clinical prostate cancer specimens. As compared to normal prostate epithelium, PNUTS expression was often higher in cancer. Among 12,235 interpretable tumors, PNUTS staining was negative in 21%, weak in 34%, moderate in 35%, and strong in 10% of cases. High PNUTS expression was associated with higher tumor stage, classical and quantitative Gleason grade, nodal stage, surgical margin, Ki67 labeling index, and early biochemical recurrence (p < 0.0001 each). PNUTS expression proved to be a moderate prognostic parameter with a maximal univariable Cox proportional hazard for PSA recurrence-free survival of 2.21 compared with 5.91 for Gleason grading. It was independent from established prognostic parameters in multivariable analysis. Comparison with molecular data available from earlier studies using the same TMA identified associations between high PNUTS expression and elevated androgen receptor expression (p < 0.0001), presence of TMPRSS2:ERG fusion (p < 0.0001), and 8 of 11 chromosomal deletions (3p13, 5q21, 8p21, 10q23, 12p13, 13q14, 16q24, and 17p13; p < 0.05 each). Particularly strong associations with PTEN and 12p13 deletions (p < 0.0001 each) may indicate a functional relationship, which has already been established for PNUTS and PTEN. PNUTS had no additional role on outcome in PTEN-deleted cancers. In conclusion, the results of our study identify high PNUTS protein levels as a predictor of poor prognosis possibly linked to increased levels of genomic instability. PNUTS measurement, either alone or in combination, might be of clinical utility in prostate cancers.

High-level expression of protein tyrosine phosphatase non-receptor 12 is a strong and independent predictor of poor prognosis in prostate cancer

BACKGROUND

Protein tyrosine phosphatase non-receptor 12 (PTPN12) is ubiquitously tyrosine phosphatase with tumor suppressive properties.

METHODS

PTPN12 expression was analyzed by immunohistochemistry on a tissue microarray with 13,660 clinical prostate cancer specimens.

RESULTS

PTPN12 staining was typically absent or weak in normal prostatic epithelium but seen in the majority of cancers, where staining was considered weak in 26.5%, moderate in 39.9%, and strong in 4.7%. High PTPN12 staining was associated with high pT category, high classical and quantitative Gleason grade, lymph node metastasis, positive surgical margin, high Ki67 labeling index and early prostate specific antigen recurrence (p < 0.0001 each). PTPN12 staining was seen in 86.4% of TMPRSS2:ERG fusion positive but in only 58.4% of ERG negative cancers. Subset analyses discovered that all associations with unfavorable phenotype and prognosis were markedly stronger in ERG positive than in ERG negative cancers but still retained in the latter group. Multivariate analyses revealed an independent prognostic impact of high PTPN12 expression in all cancers and in the ERG negative subgroup and to a lesser extent also in ERG positive cancers. Comparison with 12 previously analyzed chromosomal deletions revealed that high PTPN12 expression was significantly associated with 10 of 12 deletions in ERG negative and with 7 of 12 deletions in ERG positive cancers (p < 0.05 each) indicating that PTPN12 overexpression parallels increased genomic instability in prostate cancer.

CONCLUSIONS

These data identify PTPN12 as an independent prognostic marker in prostate cancer. PTPN12 analysis, either alone or in combination with other biomarkers might be of clinical utility in assessing prostate cancer aggressiveness.

Expression of the TPα and TPβ isoforms of the thromboxane prostanoid receptor (TP) in prostate cancer: clinical significance and diagnostic potential

The prostanoid thromboxane (TX) A₂ plays a central role in haemostasis and is increasingly implicated in cancer progression. TXA₂ signals through two T Prostanoid receptor (TP) isoforms termed TPα and TPβ, with both encoded by the TBXA2R gene. Despite exhibiting several functional and regulatory differences, the role of the individual TP isoforms in neoplastic diseases is largely unknown.

This study evaluated expression of the TPα and TPβ isoforms in tumour microarrays of the benign prostate and different pathological (Gleason) grades of prostate cancer (PCa). Expression of TPβ was significantly increased in PCa relative to benign tissue and strongly correlated with increasing Gleason grade. Furthermore, higher TPβ expression was associated with increased risk of biochemical recurrence (BCR) and significantly shorter disease-free survival time in patients post-surgery. While TPα was more variably expressed than TPβ in PCa, increased/high TPα expression within the tumour also trended toward increased BCR and shorter disease-free survival time. Comparative genomic CpG DNA methylation analysis revealed substantial differences in the extent of methylation of the promoter regions of the TBXA2R that specifically regulate expression of TPα and TPβ, respectively, both in benign prostate and in clinically-derived tissue representative of precursor lesions and progressive stages of PCa. Collectively, TPα and TPβ expression is differentially regulated both in the benign and tumourigenic prostate, and coincides with clinical pathology and altered CpG methylation of the TBXA2R gene. Analysis of TPβ, or a combination of TPα/TPβ, expression levels may have significant clinical potential as a diagnostic biomarker and predictor of PCa disease recurrence.

Optimized b-value selection for the discrimination of prostate cancer grades, including the cribriform pattern, using diffusion weighted imaging

Multiparametric magnetic resonance imaging (MP-MRI), including diffusion-weighted imaging, is commonly used to diagnose prostate cancer. This radiology–pathology study correlates prostate cancer grade and morphology with common b-value combinations for calculating apparent diffusion coefficient (ADC). Thirty-nine patients undergoing radical prostatectomy were recruited for MP-MRI prior to surgery. Diffusion imaging was collected with seven b-values, and ADC was calculated. Excised prostates were sliced in the same orientation as the MRI using 3-D printed slicing jigs. Whole-mount slides were digitized and annotated by a pathologist. Annotated samples were aligned to the MRI, and ADC values were extracted from annotated peripheral zone (PZ) regions. A receiver operating characteristic (ROC) analysis was performed to determine accuracy of tissue type discrimination and optimal ADC b-value combination. ADC significantly discriminates Gleason (G) G4-5 cancer from G3 and other prostate tissue types. The optimal b-values for discriminating high from low-grade and noncancerous tissue in the PZ are 50 and 2000, followed closely by 100 to 2000 and 0 to 2000. Optimal ADC cut-offs are presented for dichotomized discrimination of tissue types according to each b-value combination. Selection of b-values affects the sensitivity and specificity of ADC for discrimination of prostate cancer.

Pathology-Driven Comprehensive Proteomic Profiling of the Prostate Cancer Tumor Microenvironment

Prostate cancer is the second most common cancer in men worldwide. Gleason grading is an important predictor of prostate cancer outcomes and is influential in determining patient treatment options. Clinical decisions based on a Gleason score of 7 are difficult as the prognosis for individuals diagnosed with Gleason 4+3 cancer is much worse than for those diagnosed with Gleason 3+4 cancer. Laser capture microdissection (LCM) is a highly precise method to isolate specific cell populations or discrete microregions from tissues. This report undertook a detailed molecular characterization of the tumor microenvironment in prostate cancer to define the proteome in the epithelial and stromal regions from tumor foci of Gleason grades 3 and 4. Tissue regions of interest were isolated from several Gleason 3+3 and Gleason 4+4 tumors using telepathology to leverage specialized pathology expertise to support LCM. Over 2,000 proteins were identified following liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of all regions of interest. Statistical analysis revealed significant differences in protein expression (>100 proteins) between Gleason 3 and Gleason 4 regions-in both stromal and epithelial compartments. A subset of these proteins has had prior strong association with prostate cancer, thereby providing evidence for the authenticity of the approach. Finally, validation of these proteins by immunohistochemistry has been obtained using an independent cohort of prostate cancer tumor specimens.Implications: This unbiased strategy provides a strong foundation for the development of biomarker protein panels with significant diagnostic and prognostic potential. Mol Cancer Res; 15(3); 281-93. ©2017 AACR.

The Impact of Downgrading from Biopsy Gleason 7 to Prostatectomy Gleason 6 on Biochemical Recurrence and Prostate Cancer Specific Mortality

PURPOSE

Gleason score is one of the most important prognostic indicators for prostate cancer. Downgrading from biopsy Gleason score 7 to radical prostatectomy Gleason score 6 occurs commonly and yet to our knowledge the impact on survival outcomes is unknown. We examined biochemical recurrence and prostate cancer specific mortality risk in a large cohort evaluated by a single group of expert urological pathologists.

MATERIALS AND METHODS

Of 23,918 men who underwent radical prostatectomy at our institution between 1984 and 2014, 10,236 with biopsy and radical prostatectomy Gleason score 6 or 7 without upgrading were included in analysis. The cohort was divided into 3 groups, including group 1-biopsy and radical prostatectomy Gleason score 6 in 6,923 patients (67.6%), group 2-Gleason score 7 downgraded to radical prostatectomy Gleason score 6 in 648 (6.3%) and group 3-biopsy and radical prostatectomy Gleason score 7 in 2,665 (26.0%). Biochemical recurrence and prostate cancer specific mortality risks were compared using Cox regression and competing risk analyses adjusting for clinicopathological variables.

RESULTS

At a median followup of 5 years (range 1 to 29), 992 men experienced biochemical recurrence and 95 had died of prostate cancer. Biochemical recurrence-free survival in downgraded cases (group 2) was better than in group 3 cases, which had Gleason score 7 on biopsy and radical prostatectomy (p <0.001), but worse than group 1 cases, which had Gleason score 6 on biopsy and radical prostatectomy (p <0.001). Downgrading was independently associated with biochemical recurrence (adjusted HR 1.87, p <0.0001) but not with prostate cancer specific mortality (adjusted HR 1.65, p = 0.636).

CONCLUSIONS

Downgrading from biopsy Gleason score 7 to radical prostatectomy Gleason score 6 was an independent predictor of biochemical recurrence but not prostate cancer specific mortality, likely due to the presence of minor amounts of Gleason pattern 4.

Automated prostate tissue referencing for cancer detection and diagnosis

Background

The current practice of histopathology review is limited in speed and accuracy. The current diagnostic paradigm does not fully describe the complex and complicated patterns of cancer. To address these needs, we develop an automated and objective system that facilitates a comprehensive and easy information management and decision-making. We also develop a tissue similarity measure scheme to broaden our understanding of tissue characteristics.

Results

The system includes a database of previously evaluated prostate tissue images, clinical information and a tissue retrieval process. In the system, a tissue is characterized by its morphology. The retrieval process seeks to find the closest matching cases with the tissue of interest. Moreover, we define 9 morphologic criteria by which a pathologist arrives at a histomorphologic diagnosis. Based on the 9 criteria, true tissue similarity is determined and serves as the gold standard of tissue retrieval. Here, we found a minimum of 4 and 3 matching cases, out of 5, for ~80 % and ~60 % of the queries when a match was defined as the tissue similarity score ≥5 and ≥6, respectively. We were also able to examine the relationship between tissues beyond the Gleason grading system due to the tissue similarity scoring system.

Conclusions

Providing the closest matching cases and their clinical information with pathologists will help to conduct consistent and reliable diagnoses. Thus, we expect the system to facilitate quality maintenance and quality improvement of cancer pathology.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1086-6) contains supplementary material, which is available to authorized users.

Feature-based analysis of mouse prostatic intraepithelial neoplasia in histological tissue sections

This paper describes work presented at the Nordic Symposium on Digital Pathology 2015, in Linköping, Sweden. Prostatic intraepithelial neoplasia (PIN) represents premalignant tissue involving epithelial growth confined in the lumen of prostatic acini. In the attempts to understand oncogenesis in the human prostate, early neoplastic changes can be modeled in the mouse with genetic manipulation of certain tumor suppressor genes or oncogenes. As with many early pathological changes, the PIN lesions in the mouse prostate are macroscopically small, but microscopically spanning areas often larger than single high magnification focus fields in microscopy. This poses a challenge to utilize full potential of the data acquired in histological specimens. We use whole prostates fixed in molecular fixative PAXgene™, embedded in paraffin, sectioned through and stained with H&E. To visualize and analyze the microscopic information spanning whole mouse PIN (mPIN) lesions, we utilize automated whole slide scanning and stacked sections through the tissue. The region of interests is masked, and the masked areas are processed using a cascade of automated image analysis steps. The images are normalized in color space, after which exclusion of secretion areas and feature extraction is performed. Machine learning is utilized to build a model of early PIN lesions for determining the probability for histological changes based on the calculated features. We performed a feature-based analysis to mPIN lesions. First, a quantitative representation of over 100 features was built, including several features representing pathological changes in PIN, especially describing the spatial growth pattern of lesions in the prostate tissue. Furthermore, we built a classification model, which is able to align PIN lesions corresponding to grading by visual inspection to more advanced and mild lesions. The classifier allowed both determining the probability of early histological changes for uncategorized tissue samples and interpretation of the model parameters. Here, we develop quantitative image analysis pipeline to describe morphological changes in histological images. Even subtle changes in mPIN lesion characteristics can be described with feature analysis and machine learning. Constructing and using multidimensional feature data to represent histological changes enables richer analysis and interpretation of early pathological lesions.

Does active surveillance lead to anxiety and stress?

For men with prostate cancer (PC), patient care and treatment recommendations should not focus solely on the disease but should also take into account the views of the patient. The diagnosis and consequences of monitoring or treatment should be fully explained. Recommending Active Surveillance (AS) for the monitoring of a proven low-risk, low-volume prostate cancer should ensure that the psychological impact of AS is taken into account and included in a holistic approach to patient and disease management. This article is a rapid literature search relating to AS, and how the psychological impact of a cancer diagnosis may influence patient choice.

Increased aPKC Expression Correlates with Prostatic Adenocarcinoma Gleason Score and Tumor Stage in the Japanese Population

Background. Levels of the protein kinase aPKC have been previously correlated with prostate cancer prognosis in a British cohort. However, prostate cancer incidence and progression rates, as well as genetic changes in this disease, show strong ethnic variance, particularly in Asian populations. Objective. The aim of this study was to validate association of aPKC expression with prostatic adenocarcinoma stages in a Japanese cohort. Methods. Tissue microarrays consisting of 142 malignant prostate cancer cases and 21 benign prostate tissues were subject to immunohistological staining for aPKC. aPKC staining intensity was scored by three independent pathologists and categorized as absent (0), dim (1+), intermediate (2+), and bright (3+). aPKC staining intensities were correlated with Gleason score and tumor stage. Results. Increased aPKC staining was observed in malignant prostate cancer, in comparison to benign tissue. Additionally, aPKC staining levels correlated with Gleason score and tumor stage. Our results extend the association of aPKC with prostate cancer to a Japanese population and establish the suitability of aPKC as a universal prostate cancer biomarker that performs consistently across ethnicities.

Comparison of Classic and International Society of Urological Pathology 2005 Modified Gleason Grading Using Needle Biopsies From the Reduction by Dutasteride of Prostate Cancer Events (REDUCE) Trial

Context.—Use of the International Society of Urological Pathology (ISUP) 2005 modified Gleason score may result in higher scores compared with the classic Gleason scoring system.

Objective.—To compare scores derived using the 2 scoring systems.

Design.—On-study and for-cause biopsies were centrally reviewed and assigned a classic Gleason score in the Reduction by Dutasteride of prostate Cancer Events trial. Positive biopsies were reviewed by an independent pathologist in a secondary review using the ISUP 2005 modified Gleason score. The independent pathologist also recorded a classic Gleason score.

Results.—In total, 1482/1507 (98%) positive biopsy results were independently reviewed. Scores assigned by the 2 pathologists (classic versus modified) agreed in 83% (1230 of 1481) of cases; 99% (1471 of 1481) of cancers were within ±1 of their previous score. Of discordant cases, similar numbers of biopsies were upgraded and downgraded in the secondary review, with minor differences in the score distributions. Interobserver agreement was good, with κ values ranging from 0.62 (95% confidence interval [CI], 0.56–0.67) to 0.70 (95% CI, 0.65–0.76). The overall number of high-grade tumors (Gleason score 8–10; n = 48) remained constant between reviews, with 3 fewer cases in the placebo group (n = 16) and 3 more in the dutasteride group (n = 32) in the secondary review. When comparing the independent pathologist's modified scores versus the classic, 17 of 1481 cancers (1.1%) were upgraded (including 9 of 17 upgrades [53%] to high-grade tumors).

Conclusions.—This analysis showed similar score distributions between the classic and modified Gleason scoring systems. The differences seen between the 2 pathologists' scores likely reflect differences in interpretation rather than the scoring system chosen.

Increased bisecting N-acetylglucosamine and decreased branched chain glycans of N-linked glycoproteins in expressed prostatic secretions associated with prostate cancer progression

PURPOSE

Using prostatic fluids rich in glycoproteins like prostate-specific antigen and prostatic acid phosphatase (PAP), the goal of this study was to identify the structural types and relative abundance of glycans associated with prostate cancer status for subsequent use in emerging MS-based glycopeptide analysis platforms.

EXPERIMENTAL DESIGN

A series of pooled samples of expressed prostatic secretions (EPS) and exosomes reflecting different stages of prostate cancer disease were used for N-linked glycan profiling by three complementary methods, MALDI-TOF profiling, normal-phase HPLC separation, and triple quadropole MS analysis of PAP glycopeptides.

RESULTS

Glycan profiling of N-linked glycans from different EPS fluids indicated a global decrease in larger branched tri- and tetra-antennary glycans. Differential exoglycosidase treatments indicated a substantial increase in bisecting N-acetylglucosamines correlated with disease severity. A triple quadrupole MS analysis of the N-linked glycopeptides sites from PAP in aggressive prostate cancer pools was done to cross-reference with the glycan profiling data.

CONCLUSION AND CLINICAL RELEVANCE

Changes in glycosylation as detected in EPS fluids reflect the clinical status of prostate cancer. Defining these molecular signatures at the glycopeptide level in individual samples could improve current approaches of diagnosis and prognosis.

Markers of field cancerization: proposed clinical applications in prostate biopsies

Field cancerization denotes the occurrence of genetic, epigenetic, and biochemical aberrations in structurally intact cells in histologically normal tissues adjacent to cancerous lesions. This paper tabulates markers of prostate field cancerization known to date and discusses their potential clinical value in the analysis of prostate biopsies, including diagnosis, monitoring progression during active surveillance, and assessing efficacy of presurgical neoadjuvant and focal therapeutic interventions.

Cancer detection and biopsy classification using concurrent histopathological and metabolomic analysis of core biopsies

Background

Metabolomics, the non-targeted interrogation of small molecules in a biological sample, is an ideal technology for identifying diagnostic biomarkers. Current tissue extraction protocols involve sample destruction, precluding additional uses of the tissue. This is particularly problematic for high value samples with limited availability, such as clinical tumor biopsies that require structural preservation to histologically diagnose and gauge cancer aggressiveness. To overcome this limitation and increase the amount of information obtained from patient biopsies, we developed and characterized a workflow to perform metabolomic analysis and histological evaluation on the same biopsy sample.

Methods

Biopsies of ten human tissues (muscle, adrenal gland, colon, lung, pancreas, small intestine, spleen, stomach, prostate, kidney) were placed directly in a methanol solution to recover metabolites, precipitate proteins, and fix tissue. Following incubation, biopsies were removed from the solution and processed for histology. Kidney and prostate cancer tumor and benign biopsies were stained with hemotoxylin and eosin and prostate biopsies were subjected to PIN-4 immunohistochemistry. The methanolic extracts were analyzed for metabolites on GC/MS and LC/MS platforms. Raw mass spectrometry data files were automatically extracted using an informatics system that includes peak identification and metabolite identification software.

Results

Metabolites across all major biochemical classes (amino acids, peptides, carbohydrates, lipids, nucleotides, cofactors, xenobiotics) were measured. The number (ranging from 260 in prostate to 340 in colon) and identity of metabolites were comparable to results obtained with the current method requiring 30 mg ground tissue. Comparing relative levels of metabolites, cancer tumor from benign kidney and prostate biopsies could be distinguished. Successful histopathological analysis of biopsies by chemical staining (hematoxylin, eosin) and antibody binding (PIN-4, in prostate) showed cellular architecture and immunoreactivity were retained.

Conclusions

Concurrent metabolite extraction and histological analysis of intact biopsies is amenable to the clinical workflow. Methanol fixation effectively preserves a wide range of tissues and is compatible with chemical staining and immunohistochemistry. The method offers an opportunity to augment histopathological diagnosis and tumor classification with quantitative measures of biochemicals in the same tissue sample. Since certain biochemicals have been shown to correlate with disease aggressiveness, this method should prove valuable as an adjunct to differentiate cancer aggressiveness.

Adult murine prostate basal and luminal cells are self-sustained lineages that can both serve as targets for prostate cancer initiation

The prostate epithelial lineage hierarchy and the cellular origin for prostate cancer remain inadequately defined. Using a lineage-tracing approach, we show that adult rodent prostate basal and luminal cells are independently self-sustained in vivo. Disrupting the tumor suppressor Pten in either lineage led to prostate cancer initiation. However, the cellular composition and onset dynamics of the resulting tumors are distinctive. Prostate luminal cells are more responsive to Pten null-induced mitogenic signaling. In contrast, basal cells are resistant to direct transformation. Instead, loss of Pten activity induces the capability of basal cells to differentiate into transformation-competent luminal cells. Our study suggests that deregulation of epithelial differentiation is a critical step for the initiation of prostate cancers of basal cell origin.