Prostate cancer Ki-67 (MIB-1) expression, perineural invasion, and gleason score as biopsy-based predictors of prostate cancer mortality: the Mayo model

Development and Validation of a Biparametric MRI Deep Learning Radiomics Model with Clinical Characteristics for Predicting Perineural Invasion in Patients with Prostate Cancer

RATIONALE AND OBJECTIVES

Perineural invasion (PNI) is an important prognostic biomarker for prostate cancer (PCa). This study aimed to develop and validate a predictive model integrating biparametric MRI-based deep learning radiomics and clinical characteristics for the non-invasive prediction of PNI in patients with PCa.

MATERIALS AND METHODS

In this prospective study, 557 PCa patients who underwent preoperative MRI and radical prostatectomy were recruited and randomly divided into the training and the validation cohorts at a ratio of 7:3. Clinical model for predicting PNI was constructed by univariate and multivariate regression analyses on various clinical indicators, followed by logistic regression. Radiomics and deep learning methods were used to develop different MRI-based radiomics and deep learning models. Subsequently, the clinical, radiomics, and deep learning signatures were combined to develop the integrated deep learning-radiomics-clinical model (DLRC). The performance of the models was assessed by plotting the receiver operating characteristic (ROC) curves and precision-recall (PR) curves, as well as calculating the area under the ROC and PR curves (ROC-AUC and PR-AUC). The calibration curve and decision curve were used to evaluate the model's goodness of fit and clinical benefit.

RESULTS

The DLRC model demonstrated the highest performance in both the training and the validation cohorts, with ROC-AUCs of 0.914 and 0.848, respectively, and PR-AUCs of 0.948 and 0.926, respectively. The DLRC model showed good calibration and clinical benefit in both cohorts.

CONCLUSION

The DLRC model, which integrated clinical, radiomics, and deep learning signatures, can serve as a robust tool for predicting PNI in patients with PCa, thus aiding in developing effective treatment strategies.

Nerve-tumor crosstalk in tumor microenvironment: From tumor initiation and progression to clinical implications

The autonomic nerve system (ANS) innervates organs and tissues throughout the body and maintains functional balance among various systems. Further investigations have shown that excessive activation of ANS not only causes disruption of homeostasis, but also may promote tumor formation. In addition, the dynamic interaction between nerve and tumor cells in the tumor microenvironment also regulate tumor progression. On the one hand, nerves are passively invaded by tumor cells, that is, perineural invasion (PNI). On the other hand, compared with normal tissues, tumor tissues are subject to more abundant innervation, and nerves can influence tumor progression through regulating tumor proliferation, metastasis and drug resistance. A large number of studies have shown that nerve-tumor crosstalk, including PNI and innervation, is closely related to the prognosis of patients, and contributes to the formation of cancer pain, which significantly deteriorates the quality of life for patients. These findings suggest that nerve-tumor crosstalk represents a potential target for anti-tumor therapies and the management of cancer pain in the future. In this review, we systematically describe the mechanism by which nerve-tumor crosstalk regulates tumorigenesis and progression.

Revolutionizing Pathology with Artificial Intelligence: Innovations in Immunohistochemistry

Artificial intelligence (AI) is a reality of our times, and it has been successfully implemented in all fields, including medicine. As a relatively new domain, all efforts are directed towards creating algorithms applicable in most medical specialties. Pathology, as one of the most important areas of interest for precision medicine, has received significant attention in the development and implementation of AI algorithms. This focus is especially important for achieving accurate diagnoses. Moreover, immunohistochemistry (IHC) serves as a complementary diagnostic tool in pathology. It can be further augmented through the application of deep learning (DL) and machine learning (ML) algorithms for assessing and analyzing immunohistochemical markers. Such advancements can aid in delineating targeted therapeutic approaches and prognostic stratification. This article explores the applications and integration of various AI software programs and platforms used in immunohistochemical analysis. It concludes by highlighting the application of these technologies to pathologies such as breast, prostate, lung, melanocytic proliferations, and hematologic conditions. Additionally, it underscores the necessity for further innovative diagnostic algorithms to assist physicians in the diagnostic process.

A Study of Ki-67 Immunostaining in Prostate Carcinomas and Its Correlation with Gleason's Score and Prognosis: An Experience at a Tertiary Centre in the Himalayan Foothills

Prostate cancer is a significant cause of cancer-related mortality among men worldwide, necessitating the exploration of prognostic biomarkers to aid in accurate risk assessment and treatment decision-making. This cross-sectional study aimed to comprehensively evaluate the role of Ki-67 as a prognostic marker in prostate cancer by examining its association with clinicopathological parameters. A total of 102 archived cases of prostate core biopsy specimens, histopathologically reported as prostate carcinoma, were included in this study. Histopathological grading was conducted using Gleason's scoring and grading system based on morphology. The statistical software "R" was utilized for data analysis. Kruskal-Wallis test and Fisher's exact test were employed to analyze the association between Ki-67 expression and clinicopathological parameters. The study revealed significant correlations between Ki-67 expression and various clinicopathological parameters in prostate cancer cases. High Ki-67 expression levels were associated with higher Gleason scores, increased incidence of perineural invasion, advanced T stages, lymph node metastasis, presence of distant metastasis, and higher prognostic stage groups. The findings of this cross-sectional study support the potential of Ki-67 as a prognostic marker in prostate cancer. The significant associations observed between Ki-67 expression and clinicopathological parameters indicate its usefulness in risk stratification and treatment decision-making. The incorporation of histopathological grading, including Gleason scoring, and analysis of perineural invasion strengthens the validity of the study. Ki-67, in combination with morphological assessments, provides valuable prognostic information for prostate cancer patients.

MRI Radiomics-Based Machine Learning Models for Ki67 Expression and Gleason Grade Group Prediction in Prostate Cancer

PURPOSE

The Ki67 index and the Gleason grade group (GGG) are vital prognostic indicators of prostate cancer (PCa). This study investigated the value of biparametric magnetic resonance imaging (bpMRI) radiomics feature-based machine learning (ML) models in predicting the Ki67 index and GGG of PCa.

METHODS

A total of 122 patients with pathologically proven PCa who had undergone preoperative MRI were retrospectively included. Radiomics features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) maps. Then, recursive feature elimination (RFE) was applied to remove redundant features. ML models for predicting Ki67 expression and GGG were constructed based on bpMRI and different algorithms, including logistic regression (LR), support vector machine (SVM), random forest (RF), and K-nearest neighbor (KNN). The performances of different models were evaluated with receiver operating characteristic (ROC) analysis. In addition, a joint analysis of Ki67 expression and GGG was performed by assessing their Spearman correlation and calculating the diagnostic accuracy for both indices.

RESULTS

The ML model based on LR and ADC + T2 (LR_ADC + T2, AUC = 0.8882) performed best in predicting Ki67 expression, and ADC_wavelet-LHH_firstorder_Maximum had the highest feature weighting. The SVM_DWI + T2 (AUC = 0.9248) performed best in predicting GGG, and DWI_wavelet HLL_glcm_SumAverage had the highest feature weighting. The Ki67 and GGG exhibited a weak positive correlation (r = 0.382, p < 0.001), and LR_ADC + DWI had the highest diagnostic accuracy in predicting both (0.6230).

CONCLUSION

The proposed ML models are suitable for predicting both Ki67 expression and GGG in PCa. This algorithm could be used to identify indolent or invasive PCa with a noninvasive, repeatable, and accurate diagnostic method.

Multiparametric MRI radiomics in prostate cancer for predicting Ki-67 expression and Gleason score: a multicenter retrospective study

PURPOSE

Prostate cancer (PCa) with high Ki-67 expression and high Gleason Scores (GS) tends to have aggressive clinicopathological characteristics and a dismal prognosis. In order to predict the Ki-67 expression status and the GS in PCa, we sought to construct and verify MRI-based radiomics signatures.

METHODS AND MATERIALS

We collected T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) images from 170 PCa patients at three institutions and extracted 321 original radiomic features from each image modality. We used support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO) logistic regression to select the most informative radiomic features and built predictive models using up sampling and feature selection techniques. Using receiver operating characteristic (ROC) analysis, the discriminating power of this feature was determined. Subsequent decision curve analysis (DCA) assessed the clinical utility of the radiomic features. The Kaplan-Meier (KM) test revealed that the radiomics-predicted Ki-67 expression status and GS were prognostic factors for PCa survival.

RESULT

The hypothesized radiomics signature, which included 15 and 9 selected radiomics features, respectively, was significantly correlated with pathological Ki-67 and GS outcomes in both the training and validation datasets. Areas under the curve (AUC) for the developed model were 0.813 (95% CI 0.681,0.930) and 0.793 (95% CI 0.621, 0.929) for the training and validation datasets, respectively, demonstrating discrimination and calibration performance. The model's clinical usefulness was verified using DCA. In both the training and validation sets, high Ki-67 expression and high GS predicted by radiomics using SVM models were substantially linked with poor overall survival (OS).

CONCLUSIONS

Both Ki-67 expression status and high GS correlate with PCa patient survival outcomes; therefore, the ability of the SVM classifier-based model to estimate Ki-67 expression status and the Lasso classifier-based model to assess high GS may enhance clinical decision-making.

Neurons as stromal drivers of nervous system cancer formation and progression

Similar to their pivotal roles in nervous system development, neurons have emerged as critical regulators of cancer initiation, maintenance, and progression. Focusing on nervous system tumors, we describe the normal relationships between neurons and other cell types relevant to normal nerve function, and discuss how disruptions of these interactions promote tumor evolution, focusing on electrical (gap junctions) and chemical (synaptic) coupling, as well as the establishment of new paracrine relationships. We also review how neuron-tumor communication contributes to some of the complications of cancer, including neuropathy, chemobrain, seizures, and pain. Finally, we consider the implications of cancer neuroscience in establishing risk for tumor penetrance and in the design of future anti-tumoral treatments.

The Role of Perineural Invasion in Prostate Cancer and Its Prognostic Significance

Simple Summary

Prostate cancer is one of the most frequently diagnosed cancers in men worldwide. Perineural invasion (PNI), the movement of cancer cells along nerves, is a commonly observed approach to tumor spread and is important in both research and clinical practice of prostate cancer. However, despite many studies reporting on molecules and pathways involved in PNI, understanding its clinical relevance remains insufficient. In this review, we aim to summarize the current knowledge of mechanisms and prognostic significance of PNI in prostate cancer, which may provide new perspectives for future studies and improved treatment.

Abstract

Perineural invasion (PNI) is a common indication of tumor metastasis that can be detected in multiple malignancies, including prostate cancer. In the development of PNI, tumor cells closely interact with the nerve components in the tumor microenvironment and create the perineural niche, which provides a supportive surrounding for their survival and invasion and benefits the nerve cells. Various transcription factors, cytokines, chemokines, and their related signaling pathways have been reported to be important in the progress of PNI. Nevertheless, the current understanding of the molecular mechanism of PNI is still very limited. Clinically, PNI is commonly associated with adverse clinicopathological parameters and poor outcomes for prostate cancer patients. However, whether PNI could act as an independent prognostic predictor remains controversial among studies due to inconsistent research aim and endpoint, sample type, statistical methods, and, most importantly, the definition and inclusion criteria. In this review, we provide a summary and comparison of the prognostic significance of PNI in prostate cancer based on existing literature and propose that a more standardized description of PNI would be helpful for a better understanding of its clinical relevance.

Detection of perineural invasion in prostate needle biopsies with deep neural networks

The presence of perineural invasion (PNI) by carcinoma in prostate biopsies has been shown to be associated with poor prognosis. The assessment and quantification of PNI are, however, labor intensive. To aid pathologists in this task, we developed an artificial intelligence (AI) algorithm based on deep neural networks. We collected, digitized, and pixel-wise annotated the PNI findings in each of the approximately 80,000 biopsy cores from the 7406 men who underwent biopsy in a screening trial between 2012 and 2014. In total, 485 biopsy cores showed PNI. We also digitized more than 10% (n = 8318) of the PNI negative biopsy cores. Digitized biopsies from a random selection of 80% of the men were used to build the AI algorithm, while 20% were used to evaluate its performance. For detecting PNI in prostate biopsy cores, the AI had an estimated area under the receiver operating characteristics curve of 0.98 (95% CI 0.97-0.99) based on 106 PNI positive cores and 1652 PNI negative cores in the independent test set. For a pre-specified operating point, this translates to sensitivity of 0.87 and specificity of 0.97. The corresponding positive and negative predictive values were 0.67 and 0.99, respectively. The concordance of the AI with pathologists, measured by mean pairwise Cohen's kappa (0.74), was comparable to inter-pathologist concordance (0.68 to 0.75). The proposed algorithm detects PNI in prostate biopsies with acceptable performance. This could aid pathologists by reducing the number of biopsies that need to be assessed for PNI and by highlighting regions of diagnostic interest.

Multiparametric MRI and Machine Learning Based Radiomic Models for Preoperative Prediction of Multiple Biological Characteristics in Prostate Cancer

Objectives

This study aims to develop and evaluate multiparametric MRI (MP-MRI)-based radiomic models as a noninvasive diagnostic method to predict several biological characteristics of prostate cancer.

Methods

A total of 252 patients were retrospectively included who underwent radical prostatectomy and MP-MRI examinations. The prediction characteristics of this study were as follows: Ki67, S100, extracapsular extension (ECE), perineural invasion (PNI), and surgical margin (SM). Patients were divided into training cohorts and validation cohorts in the ratio of 4:1 for each group. After lesion segmentation manually, radiomic features were extracted from MP-MRI images and some clinical factors were also included. Max relevance min redundancy (mRMR) and recursive feature elimination (RFE) based on random forest (RF) were adopted to select features. Six classifiers were included (SVM, KNN, RF, decision tree, logistic regression, XGBOOST) to find the best diagnostic performance among them. The diagnostic efficiency of the construction models was evaluated by ROC curves and quantified by AUC.

Results

RF performed best among the six classifiers for the four groups according to AUC values (Ki67 = 0.87, S100 = 0.80, ECE = 0.85, PNI = 0.82). The performance of SVM was relatively the best for SM (AUC = 0.77). The number and importance of DCE features ranked first in the models of each group. The combined models of MP-MRI and clinical characteristics showed no significant difference compared with MP-MRI models according to Delong’s tests.

Conclusions

Radiomics models based on MP-MRI have the potential to predict biological characteristics and are expected to be a noninvasive method to evaluate the risk stratification of prostate cancer.

Transperineal multiparametric magnetic resonance imaging-ultrasound fusion-targeted prostate biopsy combined with standard template improves perineural invasion detection

Perineural invasion (PNI) on biopsy is associated with adverse features in prostate cancer (PCa). Transrectal multiparametric magnetic resonance imaging (MRI)-targeted biopsy (TBx) has shown to detect higher presence of PNI than standard template biopsy (SBx). Transperineal biopsy provides effective cancer detection with lower complications than the transrectal approach. We compared PNI detection efficiency between SBx and TBx through transperineal approach. We identified patients with PCa who underwent transperineal TBx and concomitant standard 20-core template SBx from September 2019 to February 2021. Clinical, MRI imaging and biopsy characteristics were evaluated and compared between TBx and SBx. Two hundred thirty-eight patients with PCa underwent concomitant transperineal SBx and TBx procedures. Combined PNI+ (SBxPNI+ and/or TBxPNI+) was identified in 77 of 238 (32.4%) patients. SBx detected 23.9% PNI-positive patients and TBx detected 19.3% PNI-positive patients of all patients with PCa. Patients with PNI were with significantly different clinicopathological characteristics than patients without PNI. Although significantly more positive PCa cores and higher positive PCa core rate were found in the SBx method, patients with SBxPNI+ only shared similar features as TBxPNI+only patients. Of 176 cases with both SBxPCa and TBxPCa, TBx could detect 19 (15.1%) more PNI cases than SBx while SBx could detect 24 (18.3%) more PNI cases than TBx. Multiparametric MRI fusion-targeted biopsy in combination with template biopsy through transperineal approach achieved PNI detection rate over 30% of PCa cases. The increased PNI detection may improve the model to select active surveillance candidates in clinical practice.

The 2019 Genitourinary Pathology Society (GUPS) White Paper on Contemporary Grading of Prostate Cancer

CONTEXT.—

Controversies and uncertainty persist in prostate cancer grading.

OBJECTIVE.—

To update grading recommendations.

DATA SOURCES.—

Critical review of the literature along with pathology and clinician surveys.

CONCLUSIONS.—

Percent Gleason pattern 4 (%GP4) is as follows: (1) report %GP4 in needle biopsy with Grade Groups (GrGp) 2 and 3, and in needle biopsy on other parts (jars) of lower grade in cases with at least 1 part showing Gleason score (GS) 4 + 4 = 8; and (2) report %GP4: less than 5% or less than 10% and 10% increments thereafter. Tertiary grade patterns are as follows: (1) replace "tertiary grade pattern" in radical prostatectomy (RP) with "minor tertiary pattern 5 (TP5)," and only use in RP with GrGp 2 or 3 with less than 5% Gleason pattern 5; and (2) minor TP5 is noted along with the GS, with the GrGp based on the GS. Global score and magnetic resonance imaging (MRI)-targeted biopsies are as follows: (1) when multiple undesignated cores are taken from a single MRI-targeted lesion, an overall grade for that lesion is given as if all the involved cores were one long core; and (2) if providing a global score, when different scores are found in the standard and the MRI-targeted biopsy, give a single global score (factoring both the systematic standard and the MRI-targeted positive cores). Grade Groups are as follows: (1) Grade Groups (GrGp) is the terminology adopted by major world organizations; and (2) retain GS 3 + 5 = 8 in GrGp 4. Cribriform carcinoma is as follows: (1) report the presence or absence of cribriform glands in biopsy and RP with Gleason pattern 4 carcinoma. Intraductal carcinoma (IDC-P) is as follows: (1) report IDC-P in biopsy and RP; (2) use criteria based on dense cribriform glands (>50% of the gland is composed of epithelium relative to luminal spaces) and/or solid nests and/or marked pleomorphism/necrosis; (3) it is not necessary to perform basal cell immunostains on biopsy and RP to identify IDC-P if the results would not change the overall (highest) GS/GrGp part per case; (4) do not include IDC-P in determining the final GS/GrGp on biopsy and/or RP; and (5) "atypical intraductal proliferation (AIP)" is preferred for an intraductal proliferation of prostatic secretory cells which shows a greater degree of architectural complexity and/or cytological atypia than typical high-grade prostatic intraepithelial neoplasia, yet falling short of the strict diagnostic threshold for IDC-P. Molecular testing is as follows: (1) Ki67 is not ready for routine clinical use; (2) additional studies of active surveillance cohorts are needed to establish the utility of PTEN in this setting; and (3) dedicated studies of RNA-based assays in active surveillance populations are needed to substantiate the utility of these expensive tests in this setting. Artificial intelligence and novel grading schema are as follows: (1) incorporating reactive stromal grade, percent GP4, minor tertiary GP5, and cribriform/intraductal carcinoma are not ready for adoption in current practice.

Grading Evolution and Contemporary Prognostic Biomarkers of Clinically Significant Prostate Cancer

Simple Summary

Prostate cancer treatment decisions are based on clinical stage and histological diagnosis, including Gleason grading assessed by a pathologist, in biopsies. Prior to staging and grading, serum or blood prostate-specific antigen (PSA) levels are measured and often trigger diagnostic examinations. However, PSA is best suited as a marker of cancer relapse after initial treatment. In this review, we first narratively describe the evolution of histological grading, the current status of Gleason pattern-based diagnostics and glance into future methodology of risk assessment by histological examination. In the second part, we systematically review the biomarkers that have been shown, independent from clinical characteristics, to correlate with clinically relevant end-points, i.e., occurrence of metastases, disease-specific mortality and overall survival after initial treatment of localized prostate cancer.

Abstract

Gleason grading remains the strongest prognostic parameter in localized prostate adenocarcinoma. We have here outlined the evolution and contemporary practices in pathological evaluation of prostate tissue samples for Gleason score and Grade group. The state of more observer-independent grading methods with the aid of artificial intelligence is also reviewed. Additionally, we conducted a systematic review of biomarkers that hold promise in adding independent prognostic or predictive value on top of clinical parameters, Grade group and PSA. We especially focused on hard end points during the follow-up, i.e., occurrence of metastasis, disease-specific mortality and overall mortality. In peripheral blood, biopsy-detected prostate cancer or in surgical specimens, we can conclude that there are more than sixty biomarkers that have been shown to have independent prognostic significance when adjusted to conventional risk assessment or grouping. Our search brought up some known putative markers and panels, as expected. Also, the synthesis in the systematic review indicated markers that ought to be further studied as part of prospective trials and in well characterized patient cohorts in order to increase the resolution of the current clinico-pathological prognostic factors.

Interobserver reproducibility of perineural invasion of prostatic adenocarcinoma in needle biopsies

Numerous studies have shown a correlation between perineural invasion (PNI) in prostate biopsies and outcome. The reporting of PNI varies widely in the literature. While the interobserver variability of prostate cancer grading has been studied extensively, less is known regarding the reproducibility of PNI. A total of 212 biopsy cores from a population-based screening trial were included in this study (106 with and 106 without PNI according to the original pathology reports). The glass slides were scanned and circulated among four pathologists with a special interest in urological pathology for assessment of PNI. Discordant cases were stained by immunohistochemistry for S-100 protein. PNI was diagnosed by all four observers in 34.0% of cases, while 41.5% were considered to be negative for PNI. In 24.5% of cases, there was a disagreement between the observers. The kappa for interobserver variability was 0.67–0.75 (mean 0.73). The observations from one participant were compared with data from the original reports, and a kappa for intraobserver variability of 0.87 was achieved. Based on immunohistochemical findings among discordant cases, 88.6% had PNI while 11.4% did not. The most common diagnostic pitfall was the presence of bundles of stroma or smooth muscle. It was noted in a few cases that collagenous micronodules could be mistaken for a nerve. The distance between cancer and nerve was another cause of disagreement. Although the results suggest that the reproducibility of PNI may be greater than that of prostate cancer grading, there is still a need for improvement and standardization.

Clinical significance of EPHX2 deregulation in prostate cancer

The arachidonic acid (AA) metabolic pathway participates in various physiological processes as well as in the development of malignancies. We analyzed genomic alterations in AA metabolic enzymes in the Cancer Genome Atlas (TCGA) prostate cancer (PCa) dataset and found that the gene encoding soluble epoxide hydrolase (EPHX2) is frequently deleted in PCa. EPHX2 mRNA and protein expression in PCa was examined in multiple datasets by differential gene expression analysis and in a tissue microarray by immunohistochemistry. The expression data were analyzed in conjunction with clinicopathological variables. Both the mRNA and protein expression levels of EPHX2 were significantly decreased in tumors compared with normal prostate tissues and were inversely correlated with the Gleason grade and disease-free survival time. Furthermore, EPHX2 mRNA expression was significantly decreased in metastatic and recurrent PCa compared with localized and primary PCa, respectively. In addition, EPHX2 protein expression correlated negatively with Ki67 expression. In conclusion, EPHX2 deregulation is significantly correlated with the clinical characteristics of PCa progression and may serve as a prognostic marker for PCa.

Perineural invasion by prostate adenocarcinoma in needle biopsies predicts bone metastasis: Ten year data from the TROG 03.04 RADAR Trial

AIMS

Perineural invasion (PNI) by prostatic adenocarcinoma is debated as a prognostic parameter. This study investigates the prognostic predictive value of PNI in a series of patients with locally advanced prostate cancer treated with radiotherapy and androgen deprivation using 10 years outcome data from the TROG 03.04 RADAR trial.

METHODS

Diagnostic prostate biopsies from 976 patients were reviewed and the presence of PNI noted. Patients were followed for 10 years according to the trial protocol or until death. The primary endpoint for the study was time to bone metastasis. Secondary endpoints included time to soft tissue metastasis, transition to castration resistance, prostate cancer-specific mortality and all-cause mortality.

RESULTS

PNI was detected in 449 cases (46%), with 234 cases (24%) having PNI in more than one core. The presence of PNI was significantly associated with higher ISUP grade, clinical T staging category, National Comprehensive Cancer Network risk group, and percent positive biopsy cores. The cumulative probability of bone metastases according to PNI status was significant over the 10 years follow-up interval of the study (log-rank test P < 0.0001). PNI was associated with all endpoints on univariable analysis. After adjusting for baseline clinicopathological and treatment factors, bone metastasis was the only endpoint in which PNI retained its prognostic significance (hazard ratio 1.42, 95% confidence interval 1.05-1.92, P = 0.021).

CONCLUSIONS

The association between PNI and the development of bone metastases supports the inclusion of this parameter as a component of the routine histology report. Further this association suggests that evaluation of PNI may assist in selecting those patients who should be monitored more closely during follow-up.

Complexity of Neural Component of Tumor Microenvironment in Prostate Cancer

The tumor microenvironment (TME) plays an essential role in the development and progression of neoplasms. TME consists of the extracellular matrix and numerous specialized cells interacting with cancer cells by paracrine and autocrine mechanisms. Tumor axonogenesis and neoneurogenesis constitute a developing area of investigation. Prostate cancer (PC) is one of the most common malignancies in men worldwide. During the past years, more and more studies have shown that mechanisms leading to the development of PC are not confined only to the epithelial cancer cell, but also involve the tumor stroma. Different nerve types and neurotransmitters present within the TME are thought to be important factors in PC biology. Moreover, perineural invasion, which is a common way of PC spreading, in parallel creates the neural niche for malignant cells. Cancer neurobiology seems to have become a new discipline to explore the contribution of neoplastic cell interactions with the nervous system and the neural TME component, also to search for potential therapeutic targets in malignant tumors such as PC.

Molecular Biomarkers in Localized Prostate Cancer: ASCO Guideline

PURPOSE

This guideline provides recommendations for available tissue-based prostate cancer biomarkers geared toward patient selection for active surveillance, identification of clinically significant disease, choice of postprostatectomy adjuvant versus salvage radiotherapy, and to address emerging questions such as the relative value of tissue biomarkers compared with magnetic resonance imaging.

METHODS

An ASCO multidisciplinary Expert Panel, with representatives from the European Association of Urology, American Urological Association, and the College of American Pathologists, conducted a systematic literature review of localized prostate cancer biomarker studies between January 2013 and January 2019. Numerous tissue-based molecular biomarkers were evaluated for their prognostic capabilities and potential for improving management decisions. Here, the Panel makes recommendations regarding the clinical use and indications of these biomarkers.

RESULTS

Of 555 studies identified, 77 were selected for inclusion plus 32 additional references selected by the Expert Panel. Few biomarkers had rigorous testing involving multiple cohorts and only 5 of these tests are commercially available currently: Oncotype Dx Prostate, Prolaris, Decipher, Decipher PORTOS, and ProMark. With various degrees of value and validation, multiple biomarkers have been shown to refine risk stratification and can be considered for select men to improve management decisions. There is a paucity of prospective studies assessing short- and long-term outcomes of patients when these markers are integrated into clinical decision making.

RECOMMENDATIONS

Tissue-based molecular biomarkers (evaluating the sample with the highest volume of the highest Gleason pattern) may improve risk stratification when added to standard clinical parameters, but the Expert Panel endorses their use only in situations in which the assay results, when considered as a whole with routine clinical factors, are likely to affect a clinical decision. These assays are not recommended for routine use as they have not been prospectively tested or shown to improve long-term outcomes-for example, quality of life, need for treatment, or survival. Additional information is available at www.asco.org/genitourinary-cancer-guidelines.

Anticancer effect of icaritin on prostate cancer via regulating miR-381-3p and its target gene UBE2C

Prostate cancer (PCa) is one of the most common health-related issues in the male individuals of western countries. Icaritin (ICT) is a traditional Chinese herbal medicine that exhibits antitumor efficacy in variety of cancers including PCa. However, the precise function and detailed molecular mechanism of ICT in the regression of PCa remain unclear. Ubiquitin-conjugating enzyme E2C (UBE2C) is an anaphase-promoting complex/cyclosome (APC/C)-specific ubiquitin conjugating enzyme, which acts as an oncogene in PCa progression. The function of ICT in PCa was investigated in transgenic adenocarcinoma mouse prostate (TRAMP) mice using survival analysis, hematoxylin and eosin (HE) staining, TUNEL assay, and immunohistochemistry and in human PCa cell lines using various molecular techniques and functional assays including plasmid construction and transfection. Bioinformatic analyses were performed to identify the interaction between miRNA and UBE2C via the TargetScan algorithm. We demonstrated that ICT inhibited the development and progression of PCa in TRAMP mice by improving the survival rate and tumor differentiation. Furthermore, we found that ICT could significantly inhibit cell proliferation and invasion and induce apoptosis in PCa cells. Consistently, downregulation of UBE2C suppressed the proliferation and invasion of PCa cells. Moreover, a luciferase reporter assay confirmed that UBE2C was a direct target of miR-381-3p. Meanwhile, ICT simultaneously downregulated UBE2C expression and upregulated miR-381-3p levels in human PCa cells. Altogether, our findings provide a strong rationale for the clinical application of ICT as a potential oncotherapeutic agent against PCa via a novel molecular mechanism of regulating the miR-381-3p/UBE2C pathway.

Ki-67 is an independent predictor of prostate cancer death in routine needle biopsy samples: proving utility for routine assessments

Standard clinical parameters fail to accurately differentiate indolent from aggressive prostate cancer. Our previous studies showed that immunohistochemical testing for Ki-67 improved prediction of prostate cancer death in a previous cohort of conservatively treated clinically localized prostate cancer. However there is a need for validation of usage with whole biopsy sections rather than tissue micro-arrays for use in routine diagnostics. Prostate cancer biopsy cases were identified in the UK, between 1990 and 2003, treated conservatively. Tumor extent and prostate-specific antigen (PSA) serum measurements were available. Biopsy cases were centrally reviewed by three uropathologists and Gleason conformed to contemporary ISUP 2014 criteria. Follow-up was through cancer registries up until 2012. Deaths were divided into those from prostate cancer and those from other causes. The percentage of Ki-67 in tumor cells was evaluated by immunohistochemistry on whole biopsy sections and was available for 756 patients. This percentage was used in analysis of cancer specific survival using a Cox proportional hazards model. In univariate analysis, the interquartile hazard ratio (HR) (95% confidence intervals) for continuous Ki-67 was 1.68 (1.49, 1.89), χ₁² = 47.975, P < 0.001. In grade groups 1 and 2, continuous Ki-67 was a statistically significant predictor of time to death from prostate cancer, HR (95% CI) = 1.97 (1.34, 2.88), χ₁² = 9.017, p = 0.003. In multivariate analysis, continuous Ki-67 added significant predictive information to that provided by grade groups, extent of disease and serum PSA, HR (95% CI) = 1.34 (1.16, 1.54), Δχ₁² = 13.703, P < 0.001. We now advocate the introduction of Ki-67 as a viable and practicable prognostic biomarker in clinical practice. The association of Ki-67 with mortality was highest in grade groups 1 and 2, showing that Ki-67 can be used as a routine biomarker in patients being considered for active surveillance.

Impact of biopsy perineural invasion on the outcomes of patients who underwent radical prostatectomy: a systematic review and meta-analysis

Objectives: To investigate the association between biopsy perineural invasion (PNI) and oncological outcomes of prostate cancer (PCa) after radical prostatectomy (RP).Materials and methods: A systematic literature search was performed using PubMed, EMBASE and Web of Science up to December 2018 to identify the eligible studies that included localized PCa patients who underwent biopsy and subsequently RP as well as follow-up information. Meta-analyses were conducted using available hazard ratios (HRs) of biopsy PNI from both univariate and multivariate analyses.Results: Eighteen studies including 14,855 patients with treatment follow-up information were included in the current systematic review. The rate of biopsy PNI varied between 7.0% and 33.0%. Seven out of the 18 studies that demonstrated biopsy PNI were associated with adverse pathologic features. Thirteen out of the 18 studies showed biopsy PNI correlated significantly with higher rates of biochemical recurrence (BCR)/cancer progression status or worse prognostic outcomes. With pooled data based on four studies with available univariate analysis results and four studies with multivariate analysis, statistically significant associations were found between biopsy PNI and BCR with univariate analysis (HR = 2.05; 95% CI = 1.57-2.68; p < 0.001) and with multivariate analysis (HR = 1.57; 95% CI = 1.28-1.93; p < 0.001).Conclusion: Evidence from the included observational studies indicated that biopsy PNI was not only correlated with adverse pathologic characteristics but also with worse BCR prognosis of local PCa after RP. The status of biopsy PNI could serve as a promising risk-stratification factor to help the decision-making process, considering active surveillance (AS) or further treatment for PCa patients.

Aneuploidy drives lethal progression in prostate cancer

Aneuploidy, defined as chromosome gains and losses, is a hallmark of cancer. However, compared with other tumor types, extensive aneuploidy is relatively rare in prostate cancer. Thus, whether numerical chromosome aberrations dictate disease progression in prostate cancer patients is not known. Here, we report the development of a method based on whole-transcriptome profiling that allowed us to identify chromosome-arm gains and losses in 333 primary prostate tumors. In two independent cohorts (n = 404) followed prospectively for metastases and prostate cancer-specific death for a median of 15 years, increasing extent of tumor aneuploidy as predicted from the tumor transcriptome was strongly associated with higher risk of lethal disease. The 23% of patients whose tumors had five or more predicted chromosome-arm alterations had 5.3 times higher odds of lethal cancer (95% confidence interval, 2.2 to 13.1) than those with the same Gleason score and no predicted aneuploidy. Aneuploidy was associated with lethality even among men with high-risk Gleason score 8-to-10 tumors. These results point to a key role of aneuploidy in driving aggressive disease in primary prostate cancer.

The clinical significance of perineural invasion in patients with de novo metastatic prostate cancer

BACKGROUND

The clinical value of perineural invasion (PNI) in patients with localized prostate cancer (PCa) is widely explored. However, its role in metastatic PCa (mPCa) remains unknown.

OBJECTIVES

We aim to investigate the clinical significance of PNI in patients with mPCa.

MATERIALS AND METHODS

Data of 515 mPCa patients between 2012 and 2018 were retrospectively studied. PNI and its intensity were identified by prostate biopsy. The prognostic value of PNI was evaluated by Kaplan-Meier curves and Cox proportional-hazards model.

RESULTS

Perineural invasion was detected in 170/515 (33.0%) cases. Among them 73/170 (42.9%) and 97/170 (57.1%) harbored unifocal PNI (uni-PNI) and multifocal PNI (multi-PNI), respectively. Compared to patients without PNI, those with PNI had statistically shorter castration-resistant PCa-free survival (CFS) and numerically shorter overall survival (OS) (mCFS: 15.4- vs. 18.5-Mo, p = 0.015; mOS: 63.8- vs. 71.4-Mo, p = 0.108). Patients harboring multi-PNI were associated with poorer clinical outcomes than those with uni-PNI (mCFS: 12.4- vs. 18.0-Mo, p = 0.040; mOS: 39.7-Mo vs. NR, p = 0.018) or those without PNI (mCFS: 12.4- vs. 18.5-Mo, p = 0.002; mOS: 39.7- vs. 71.4-Mo, p = 0.002). Totally, neither uni-PNI nor multi-PNI was an independent risk factor impacting survival outcomes in multivariate analyses. While remarkably, for patients with favorable/intermediate-risk mPCa, multi-PNI was an independent adverse prognosticator for both CFS and OS (CFS: HR: 1.705, 95% CI: 1.029-2.825, p = 0.038; OS: HR: 3.294, 95% CI: 1.464-7.413, p = 0.004).

DISCUSSION AND CONCLUSION

This study filled the blank of the clinical significance of PNI in mPCa. We found that multi-PNI could distinguish men with relatively poor prognosis from patients initially regarded as with favorable survival outcomes by other prognosticators, and thus, avoid disease underestimation in this group of patients. Our finding would help physicians have a deeper understanding of the heterogeneity of mPCa and make better individualized therapeutic strategy.

Association between decreased expression of estrogen receptor alpha, androgen receptor and phosphatase and tensin homolog immunoexpression in the canine prostate

ABSTRACT: Canine prostate gland is a hormonal dependent organ and its imbalance of estrogen and androgen receptor expressions are directly associated with the development of different diseases. Due to the lack of information regarding the behavior of the aforementioned receptors in canine prostate cancer (PC), this study aimed to identify estrogen receptor alpha (ERα), androgen receptor (AR), Ki67 and phosphatase and tensin homolog (PTEN) protein expressions in canine PC by immunohistochemistry. We found nuclear expression of ERα and AR in the epithelial cells of normal canine samples and a loss of protein expression in PC samples. Normal samples showed Ki67 expression in a few basal cells and the PC samples showed the highest mean of positive cells (253.1). Canine prostate cancer showed a high proliferative index, which was associated with independence of hormonal actuation. PTEN showed positive nuclear and cytoplasmic expression in normal canine samples and a loss in PC. Loss of ERα, AR and PTEN indicated that canine PC exhibits the same immunohistochemical phenotype as in human patients with PC resistant to hormonal therapy. Therefore, canine PC should be considered as a model to study human PC resistant to hormonal therapy.

Life History Trade-Offs in Tumors

Purpose

In this paper, we provide an overview of a life history theory and how it applies to cancer evolution.

Recent Findings

We review the literature on trade-offs in tumors, focusing on the trade-offs among cellular proliferation, survival, and motility. Trade-offs are critical natural constraints for almost all evolutionary processes. Many ecological studies show that trade-offs among these cellular functions maintain a genetic diversity. In addition, these trade-offs are not fixed, but rather can shift depending on the ecological circumstances in the microenvironment. This can lead to selection for the cellular capacity to respond to these differing microenvironments in ways that promote the fitness of the cancer cell. We relate these life history trade-offs to the recently developed Evo-Eco indexes and discuss how life history theory can help refine our measures of tumor evolution and ecology.

Summary

Life history theory provides a framework for understanding how the spatial and temporal variability in the tumor microenvironment—in particular resources and threats—affect trade-offs among cell survival, cell proliferation, and cell migration. We discuss how these trade-offs can potentially be leveraged in cancer therapy to increase the effectiveness of treatment.

Should reporting of peri-neural invasion and extra prostatic extension be mandatory in prostate cancer biopsies? correlation with outcome in biopsy cases treated conservatively

The identification of perineural invasion (PNI) and extraprostatic extension (ECE) in prostate cancer (PC) biopsies is time consuming and can be difficult. Although this is required information in many datasets, there is little evidence on their effect on outcome in patients treated conservatively. Cases of PC were identified from three cancer registries in the UK from men with clinically localized prostate cancer diagnosed by needle biopsy from 1990-2003. The endpoint was prostate cancer death (DOD). Patients treated radically within 6 months, those with objective evidence of metastases or who had prior hormone therapy were excluded. Follow-up was through cancer registries up until 2012. Deaths were divided into those from PC and those from other causes, according to WHO criteria. 988 biopsy cases (6522 biopsy cores) were centrally reviewed by three uropathologists and assigned a Gleason score and Grade Group (GG). The presence of both PNI and ECE was recorded. Of 988 patients, PNI was present in 288 (DOD = 75) and ECE in 23 (DOD = 5). On univariable analysis PNI was highly significantly associated with DOD (hazard ratio [HR] 2.28, 95% CI: 1.68, 3.1, log-rank test p-value = 4.8 × 10-8), but ECE was not (log-rank test p-value = 0.334). On multivariable analysis with GG, serum PSA (per 10%), clinical stage and extent of disease (per 10%), PNI lost significance (HR 1.16, 95% CI: 0.83, 1.63, likelihood ratio test p-value = 0.371). The utility of routinely examining prostate biopsies for ECE and PNI is doubtful as it is not independently associated with higher grade, stage or prognosis.

Ki-67 expression predicts biochemical recurrence after radical prostatectomy in the setting of positive surgical margins

Background

Positive surgical margin (PSM) is a predictor of biochemical recurrence (BCR) following radical prostatectomy (RP). Attempts to stratify PSM based on linear length, Gleason score, location and number have failed to add to predictive models using margin status alone. We evaluated the prognostic significance of Ki-67 expression in this setting.

Methods

Immunohistochemical staining for Ki-67 was done on prostatectomy specimens from 117 patients who had a PSM. Ki67 expression was measured at the margin and in the index lesion. Patients were dichotomized based on Ki-67 expression into three groups. Group 1 with no Ki-67 expression, Group 2 with Ki-67 ≤ 2%, and Group 3 with Ki-67 ≥ 3%.

To eliminate the impact of the adjuvant treatment (AT) on the outcome, data were analyzed by the Cox proportional hazards in which AT was Considered as a time-dependent covariate.

Results

The discordance rate of Ki-67 expression between matched index lesion and margin specimens was 44/117 (37.6%). There was a trend for higher risk of BCR (HR:2.06, (0.97–4.43), P = 0.06) in patients expressing high Ki67 at the surgical margin although this was not statistically significant. However High Ki-67 expression in the index lesion was an independent predictive factor for BCR in this subset of patients. (HR:4, (1.64–9.80), P = 0.002).

Conclusion

High Ki67 expression in the index prostate cancer lesion is an independent predictor of BCR in patients with positive surgical margin following radical prostatectomy. Our findings need to be validated in a larger cohort.

Prognostic value of MIB-1 proliferation index in solitary fibrous tumors of the pleura implemented in a new score - a multicenter study

Background

Although the majority of solitary fibrous tumors of the pleura (SFTP) follow a benign course, 10–25% of patients suffer from recurrence or metastatic disease. Several scoring models have been proposed to predict the outcome. However, none of these included immunohistochemical (IHC) markers as possible prognosticators.

Methods

In this multicenter study, we collected clinical data and formalin-fixed and paraffin-embedded (FFPE) tissue blocks of patients with histologically proven SFTP which had been surgically resected between 2000 und 2015. After systematic and extensive IHC staining on tissue microarrays, the results were analyzed and compared to histomorphological and clinical data for their possible prognostic value.

Results

In total, 78 patients (mean age 61 ± 11 years) were included. Of these, 9 patients (11%) had an adverse outcome including SFTP recurrence (n = 6) or SFTP-related death (n = 3). Mean overall survival was 172 ± 13 months. 1 and 10-year event-free survival rates were 99% and 93%. In the multivariable analysis only MIB-1 proliferation index (Ki-67) ≥10% (HR 12.3, CI 1.1–139.5, p = 0.043), ≥4 mitoses per 10 high power fields (HR 36.5, CI 1.2–1103.7, p = 0.039) and tumor size larger than 10 cm (HR 81.8, CI 1.7–4016.8, p = 0.027) were independently associated with adverse outcome.

Conclusion

A high proliferation rate by MIB-1 IHC was associated with impaired outcome. Upon this, we established a new score using mitosis, necrosis, size of the tumor and MIB-1, which performed better than the traditional scores in our data set. This prognostic score could help to better evaluate outcome of SFTP, but requires external validation.

Evaluation of the proliferation marker Ki-67 in a large prostatectomy cohort

The tumor proliferation index marker Ki-67 is strongly associated with tumor cell proliferation, growth and progression, and is widely used in routine clinicopathological investigation. Prostate cancer is a complex multifaceted and biologically heterogeneous disease, and overtreatment of localized, low volume indolent tumors, is evident. Here, we aimed to assess Ki-67 expression and related outcomes of 535 patients treated with radical prostatectomy. The percentage of tumor epithelial cells expressing Ki-67 was determined by immunohistochemical assay, both digital image analysis and visual scoring by light microscope were used for quantification. The association of Ki-67 and prostate cancer was evaluated, as well as its prognostic value. There was a positive correlation between high expression of Ki-67 and Gleason score > 7 (p < 0.001) as well as tumor size (≥ 20 mm, p = 0.03). In univariate analyses, a high expression of Ki-67 in tumor epithelium was significantly associated with biochemical failure (BF) (digital scoring, p = 0.014) and (visual scoring, p = 0.004). In the multivariate analyses, a high level of Ki-67 was an independent poor prognostic factor for biochemical failure-free survival (BFFS) (Visual scoring, Ki67, p = 0.012, HR:1.50, CI95% 1.10–2.06). In conclusion, high Ki-67 expression is an independent negative prognostic marker for biochemical failure. Our findings support the role of Ki-67 as a significant, poor prognostic factor for in prostate cancer outcome.

Biomarkers in prostate cancer - Current clinical utility and future perspectives

Current tendencies in the treatment course of prostate cancer patients increase the need for reliable biomarkers that help in decision-making in a challenging clinical setting. Within the last decade, several novel biomarkers have been introduced. In the following comprehensive review article, we focus on diagnostic (PHI^®, 4K score, SelectMDx^®, ConfirmMDx^®, PCA3, MiPS, ExoDX^®, mpMRI) and prognostic (OncotypeDX GPS^®, Prolaris^®, ProMark^®, DNA-ploidy, Decipher^®) biomarkers that are in widespread clinical use and are supported by evidence. Hereby, we focus on multiple clinical situations in which innovative biomarkers may guide decision-making in prostate cancer therapy. In addition, we describe novel liquid biopsy approaches (circulating tumor cells, cell-free DNA) that have been described as predictive biomarkers in metastatic castration-resistant prostate cancer and might support an individual patient-centred oncological approach in the nearer future.

Prognostic role of Ki-67 score in localized prostate cancer: A systematic review and meta-analysis

BACKGROUND

Ki-67 for quantifying tumor proliferation is widely used. In localized prostate cancer (PCa), despite a suggested predictive role of Ki-67 for outcomes after therapies, it has not been incorporated into clinical practice. Herein, we conduct a systematic review and meta-analysis of the literature reporting the association of Ki-67 and disease outcomes in PCa treated radically.

METHODS

Medline and EMBASE databases were searched without date or language restrictions, using "KI67" and "prostate cancer" MeSH terms. Studies reporting Ki-67 association with clinical outcomes (disease-free survival [DFS], biochemical failure-free survival, rate of distant metastases [DM], disease-specific survival [DSS], or overall survival [OS], or all of these) in patients with PCa managed actively were included, and relevant data extracted by 2 independent reviewers. Odds ratios (OR) were weighted and pooled in a meta-analysis using Mantel-Haenszel random-effect modeling.

RESULTS

Twenty-one studies comprising 5,419 patients met eligibility for analysis, and 67.6% of patients had low Ki-67. Mean Ki-67 was 6.14%. High Ki-67 was strongly associated with worse clinical outcomes. DFS was better in those patients with low Ki-67 at 5 and 10 years (OR = 0.32, 95% CI: 0.23-0.44, P<0.00001; OR = 0.31, 95% CI: 0.20-0.48, P<0.00001). Similarly, low Ki-67 was related to improved DSS at 5 and 10 years (OR = 0.15, 95% CI: 0.10-0.21, P<0.00001; OR = 0.16, 95% CI: 0.06-0.40, P<0.00001). Association between low Ki-67 scores with improved OS (OR = 0.47; 95% CI: 0.37-0.61; P<0.00001) and high Ki-67 scores with DM at 5 years (OR = 4.07; 95% CI: 2.52-6.58; P<0.00001) was consistently observed.

CONCLUSIONS

High Ki-67 expression in localized PCa is a factor of poor prognosis for DSS, biochemical failure-free survival, DFS, DM, and OS after curative-intent treatments. Incorporation into clinical routine of this widely available and standardized biomarker should be strongly considered.

Myosin regulatory light chain phosphorylation is associated with leiomyosarcoma development

Leiomyosarcoma is a rare malignant smooth muscle tumor which can be very unpredictable. Myosin II is involved in many functions, including cell contraction, migration, and adhesion. The phosphorylation of myosin regulatory light chain (MLC) by myosin light chain kinase (MLCK) determines the activity of Myosin II. However, it is still unclear whether MLC phosphorylation is involved in cell proliferation in leiomyosarcoma. In this study, we aimed to explore the role of MLCK-dependent MLC phosphorylation in leiomyosarcoma development. We found that the expression of MLCK, phosphorylated MLC, and Ki67 in leiomyosarcoma was significantly higher than in leiomyoma and adjacent normal smooth muscle cells. MLCK expression was significantly correlated with phosphorylated MLC level. Kaplan-Meier survival analysis revealed that patients with high expression of MLCK or phosphorylated MLC had shorter overall survival times compared with the patients with low expression of MLCK or phosphorylated MLC. In vitro studies revealed a causative link between MLC phosphorylation and cellular proliferation as expression of phosphomimetic MLC (T19D, S20D) increased cellular proliferation as assessed by Ki67 staining. In contrast, MLCK specific inhibitor reduced cellular proliferation. We concluded that MLCK, phosphorylated MLC and Ki67 were overexpressed in leiomyosarcoma. MLCK dependent MLC phosphorylation might be responsible for the high proliferative state in leiomyosarcoma. MLCK and phosphorylated MLC are potential prognostic indicators of leiomyosarcoma.

Associations of Prostate-Specific Antigen, Prostate Carcinoma Tissue Gleason Score, and Androgen Receptor Expression with Bone Metastasis in Patients with Prostate Carcinoma

Background

Prostate carcinoma (PCa) is often not diagnosed until advanced disease with bone metastasis. Predictive factors for bone metastasis are required to improve patient outcomes. The study aimed to analyze the factors associated with bone metastases in newly diagnosed patients with PCa.

Material/Methods

This was a retrospective study of 80 patients newly diagnosed with PCa by pathological examination between January 2012 and December 2014. Bone metastases were diagnosed by positron emission computed tomography. Clinical data, serological laboratory results, and pathological examination results were collected.

Results

Among the 80 patients, 45 (56%) had bone metastases. Age, serum alkaline phosphatase, prostate-specific antigen (PSA), erythrocyte sedimentation rate, PCa tissue Gleason score, androgen receptor (AR) expression, and Ki-67 expression were higher in patients with bone metastasis compared with those without (all P<0.05). Multivariate logistic regression showed that PSA (OR: 1.005; 95%CI: 1.001–1.010; P=0.016), Gleason score (OR: 4.095; 95%CI: 1.592–10.529; P=0.003), and AR expression (OR: 14.023; 95%CI: 3.531–55.6981; P=0.005) were independently associated with bone metastases. Cut-off values for PSA, Gleason score, and AR expression were 67.1 ng/ml (sensitivity: 55.6%; specificity: 97.1%), 7.5 (sensitivity: 75.6%; specificity: 82.9%), and 2.5 (sensitivity: 84.0%; specificity: 91.4%), respectively.

Conclusions

PSA, Gleason score, and AR expression in PCa tissues were independently associated with PCa bone metastases. These results could help identifying patients with PCa at high risk of bone metastases.

Genomic tests to guide prostate cancer management following diagnosis

INTRODUCTION

Prostate cancer (PCa) is a common cancer in men, but variable clinical behaviors make its management challenging. Risk stratification is a key issue in disease management. Patient-tailored strategies are strongly advocated to reduce unnecessary treatment while maximizing the oncological outcomes of patient who need active treatment in the primary, adjuvant or salvage setting. Recently, tissue-based biomarkers or genomic tests have become available to improve the clinical decision-making. Areas covered: In this review, the authors present recent evidence about these tissue-based biomarkers, discussing the application of each of them in the clinical setting, focusing on the tests aimed to provide a better risk stratification and to guide decision-making after the diagnosis of PCa (i.e. OncotypeDX^Ⓡ, Prolaris^Ⓡ, ProMark^Ⓡ, Ki-67, Decipher^Ⓡ, PTEN, PORTOS, AR-V7 and DNA repair gene mutations). Expert commentary: Even if the clinicopathologic features are still the most frequently-used predictors of disease progression, these tools can be helpful in decision-making at every stage of the PCa management. Actually, OncotypeDX^Ⓡ, Prolaris^Ⓡ and Decipher^Ⓡ are recommended in the clinical setting by guidelines at different steps of PCa management. Consequently, further studies are indispensable to better tailor the right therapy for the right patient and at the right time.

Perineural Invasion and Risk of Lethal Prostate Cancer

Background: Prostate cancer has a propensity to invade and grow along nerves, a phenomenon called perineural invasion (PNI). Recent studies suggest that the presence of PNI in prostate cancer has been associated with cancer aggressiveness.Methods: We investigated the association between PNI and lethal prostate cancer in untreated and treated prostate cancer cohorts: the Swedish Watchful Waiting Cohort of 615 men who underwent watchful waiting, and the U.S. Health Professionals Follow-Up Study of 849 men treated with radical prostatectomy. One pathologist performed a standardized histopathologic review assessing PNI and Gleason grade. Patients were followed from diagnosis until metastasis or death.Results: The prevalence of PNI was 7% and 44% in the untreated and treated cohorts, respectively. PNI was more common in high Gleason grade tumors in both cohorts. PNI was associated with enhanced tumor angiogenesis, but not tumor proliferation or apoptosis. In the Swedish study, PNI was associated with lethal prostate cancer [OR 7.4; 95% confidence interval (CI), 3.6-16.6; P < 0.001]. A positive, although not statistically significant, association persisted after adjustment for age, Gleason grade, and tumor volume (OR 1.9; 95% CI, 0.8-5.1; P = 0.17). In the U.S. study, PNI predicted lethal prostate cancer independent of clinical factors (HR 1.8; 95% CI, 1.0, 3.3; P =0.04).Conclusions: These data support the hypothesis that perineural invasion creates a microenvironment that promotes cancer aggressiveness.Impact: Our findings suggest that PNI should be a standardized component of histopathologic review, and highlights a mechanism underlying prostate cancer metastasis. Cancer Epidemiol Biomarkers Prev; 26(5); 719-26. ©2017 AACR.

Novel concepts for risk stratification in prostate cancer

Since Partin introduced the analysis of prostate-specific antigen, clinical T-stage and Gleason scores to estimate the risk of progression in men with localised prostate cancer, our understanding of factors that modify this risk has changed drastically. There are now multiple risk stratification tools available, including look-up tables, risk stratification/classification analyses, regression-tree analyses, nomograms and artificial neural networks. Concurrently, descriptions of novel biopsy strategies, imaging modalities and biomarkers are frequently published with the aim of improving risk stratification. With an abundance of new information available, incorporating advances into clinical practice can be confusing. This article aims to outline the major novel concepts in prostate cancer risk stratification for men with biopsy confirmed prostate cancer. We will detail which of these novel techniques and tools are likely to be adopted to aid treatment decisions and enable more accurate post-diagnosis, pretreatment risk stratification.

Activin A regulates microRNAs and gene expression in LNCaP cells

BACKGROUND

Prostate cancer (PCa) is an increasing health issue worldwide. For patients with advanced castration-resistant PCa (CRPC) treatment options are limited and overall survival is relatively short. Paired with this, non-invasive diagnostic options are yet to be established. Activins are members of the TGF-β superfamily and have been linked to prostate physiology. For instance, activin A is an inhibitor of growth in the prostate. A novel class of non-coding RNA, microRNAs (miRNAs) have been intrinsically linked to a range of cellular processes and carcinogenesis. No studies have investigated the impact of activin A on miRNA expression in PCa cell lines. Hence, the objective of this study was to determine the effect of activin A on miRNA expression and downstream target genes in PCa.

METHODS

Activin-sensitive (LNCaP) and insensitive (PC3) prostate cells were treated with 50 ng/ml of activin A for 72 hr. To examine miRNA expression following treatment, SYBR RT-qPCR miRNA arrays were used in conjunction with TaqMan RT-qPCR. MiRPath-TarBase analysis was conducted using the miRNAs that were significantly altered following activin A treatment of LNCaP cells to highlight enriched target genes within biological pathways. Highlighted target genes were assessed using pathway-focused TGF-β and cell cycle SYBR RT-qPCR arrays.

RESULTS

Activin A treatment altered nine miRNAs in LNCaP cells: miR-222-3p, miR-15b-5p, miR-93-5p, miR-18a-5p, and let-7i-5p were significantly decreased, while miR-30a/30d-5p, let-7c, and miR-196b-5p were significantly increased versus media control. In PC3 cells five miRNAs were altered: miR-130a-3p, miR-7-5p, and miR-140-3p were significantly decreased while miR-191-5p and miR-26a-5p were significantly increased versus media control. MiRPath-TarBase analysis highlighted that the miRNAs significantly altered in LNCaP cells targeted genes contained in activin A-related KEGG pathways. Furthermore, when LNCaP cells were treated with activin A the expression of the targeted genes was the inverse of the expression of activin A-mediated miRNAs.

CONCLUSIONS

This study demonstrated the ability of activin A to modulate miRNA expression in PCa cell lines and suggests a correlative relationship between miRNA expression and downstream target genes in LNCaP cells. This study provides impetus for further studies into activin A and miRNAs in PCa. Prostate 76:951-963, 2016. © 2016 Wiley Periodicals, Inc.

Survival predictors in patients with prostate adenocarcinoma with hormonal blockade

Ki-67 index and clinical-pathological factors such as the Gleason score and the presence of neuroendocrine differentiation have been used for predicting survival in patients with prostate cancer. We examined prostate tissue from 45 patients with advanced prostate cancer who were treated with maximal androgen blockade and analysed their cancer-specific survival (CSS). We assessed the Gleason index, performed an immunohistochemical analysis of Ki-67 (MIB-1) and determined the presence of neuroendocrine differentiation (chromogranin A). A survival study was conducted using Kaplan-Meier curves (log-rank test) and a Cox regression analysis. Twenty-four patients (53.3%) died from the disease, with a mean follow-up of 68.7±7.7 months (56.6% CSS at 5 years and 31.8% at 10 years). In the univariate analysis, survival was associated with an interquartile distribution of Ki-67 (0-5, 6-12%, 13-25%, >25%; log-rank, p=0.01), Gleason 5 (total index 9-10; log-rank, p=0.002) and the presence of metastases during the diagnosis (M1; log-rank, p=0.004) but not to cT category (T3-T4; log-rank, p=0.26) or neuroendocrine differentiation (immunohistochemically positive tumour cell nests; log-rank, p=0.46). The multivariate analysis revealed that a Ki-67 index ≤12% (HR, 0.22; p=0.0009) and the absence of metastases (M0) during diagnosis (HR, 0.17; p=0.0002) were protective factors in this population. In conclusion, Ki-67 proliferation index and the lack of metastases at diagnosis predict CSS in patients with advanced prostate cancer who undergo hormonal blockade. Neuroendocrine differentiation in tumour tissue had no prognostic value in this study.

Incorporation of tissue-based genomic biomarkers into localized prostate cancer clinics

Localized prostate cancer (PCa) is a clinically heterogeneous disease, which presents with variability in patient outcomes within the same risk stratification (low, intermediate or high) and even within the same Gleason scores. Genomic tools have been developed with the purpose of stratifying patients affected by this disease to help physicians personalize therapies and follow-up schemes. This review focuses on these tissue-based tools. At present, four genomic tools are commercially available: Decipher™, Oncotype DX®, Prolaris® and ProMark®. Decipher™ is a tool based on 22 genes and evaluates the risk of adverse outcomes (metastasis) after radical prostatectomy (RP). Oncotype DX® is based on 17 genes and focuses on the ability to predict outcomes (adverse pathology) in very low-low and low-intermediate PCa patients, while Prolaris® is built on a panel of 46 genes and is validated to evaluate outcomes for patients at low risk as well as patients who are affected by high risk PCa and post-RP. Finally, ProMark® is based on a multiplexed proteomics assay and predicts PCa aggressiveness in patients found with similar features to Oncotype DX®. These biomarkers can be helpful for post-biopsy decision-making in low risk patients and post-radical prostatectomy in selected risk groups. Further studies are needed to investigate the clinical benefit of these new technologies, the financial ramifications and how they should be utilized in clinics.

Vimentin and Ki67 expression in circulating tumour cells derived from castrate-resistant prostate cancer

BACKGROUND

High circulating tumor cell (CTC) counts are associated with poor prognosis in advanced prostate cancer, and recently CTC number was suggested to be a surrogate for survival in metastatic castrate-resistant prostate cancer (mCRPC). Ki67 and vimentin are well-characterised markers of tumour cell proliferation and the epithelial-mesenchymal transition (EMT), respectively. Here we asked if the expression of vimentin and Ki67 in CTCs offered prognostic or predictive information in mCRPC.

METHODS

In two separate patient cohorts, anti-vimentin or anti-Ki67 antibodies were added to the free channel in the CellSearch® system for analysis of peripheral blood samples. For each cohort, association of CTC number with clinical characteristics were assessed using Fisher's exact, Mann-Whitney and chi-squared tests. Kaplan-Meier method and log-rank tests were used to analyse overall survival (OS) of vimentin-expressing and Ki67-expressing CTC patient cohorts.

RESULTS

In this retrospective analysis, CTC vimentin expression was analysed in 142 blood samples from 93 patients, and CTC Ki67 expression was analysed in 90 blood samples from 51 patients. In the vimentin cohort, 80/93 (86 %) of baseline samples from patients were CTC-positive overall (≥1 total CTC per 7.5 mls blood), and 30/93 (32.3 %) vimentin CTC-positive (≥1 vimentin-positive CTC per 7.5 mls blood). 41/51 (80.4 %) of baseline samples from patients in the Ki67 cohort were CTC-positive overall, and 23/51 (45.1 %) Ki67 CTC-positive (≥1 Ki67-positive CTC per 7.5 mls blood). There was no significant difference in baseline PSA in patients with vimentin-positive CTC at baseline versus those with no vimentin-positive CTC at baseline (p = 0.33). A significant reduction in OS was shown in patients with vimentin-positive CTC compared to those without vimentin-positive CTC (median 305 days vs 453 days, p = 0.0293). There was no significant difference in baseline PSA in patients with Ki67-positive CTC at baseline versus those without Ki67-positive CTC (p = 0.228), but OS was significantly reduced in the Ki67-positive CTC group (median 512 days vs 751 days, p = 0.0091). No changes in relative proportion of vimentin- or Ki67-positive CTCs were observed in post-treatment samples compared to baseline.

CONCLUSIONS

Analysis of vimentin and Ki67 expression can straightforwardly be assessed in CTCs from patients with mCRPC. Poorer survival outcomes were observed in vimentin- and Ki67-positive CTC patients.

TRANSLATIONAL STUDY PROTOCOLS

CEC-CTC (IDRCB2008-AOO585-50) and Petrus ( NCT01786031 ).

The relationship between perineural invasion, tumor grade, reactive stroma and prostate cancer-specific mortality: A clinicopathologic study on a population-based cohort

BACKGROUND

In vitro and in vivo studies have shown that nerves, tumor epithelium, and stroma interact and promote prostate cancer (PC) progression. Perineural invasion (PNI) is established amidst these interactions and may therefore indicate an aggressive PC phenotype. The purpose of the present study was to determine the relationship between PNI, tumor grade, reactive stroma, and PC-specific mortality.

METHODS

A population-based study on 318 patients, encompassing all cases of PC diagnosed by needle biopsies and without evidence of systemic metastasis at the time of diagnosis in Aust-Agder County in the period of 1991-1999. Patients were identified by cross-referencing the Cancer Registry of Norway. Clinical data were obtained by review of medical charts. Diagnostic prostate needle biopsies were reviewed with respect to presence of PNI, percentage of biopsy cores with PNI, Gleason score (GS), and reactive stromal grade (RSG). The endpoint was PC-specific mortality.

RESULTS

The presence of PNI was significantly associated with high tumor grade and abundant reactive stroma. The 10-year PC-specific survival for patients with and without PNI was 72% and 91%, respectively (P = 0.001, log rank). PNI predicted PC-specific mortality independently of clinical factors, though the effect of PNI was attenuated when adjusting for GS and RSG. However, a percentage of biopsy cores with PNI >50% was found to predict PC-specific mortality independently of other clinicopathologic parameters.

CONCLUSIONS

The present population-based study shows that PNI on diagnostic prostate needle biopsy is associated with increased risk of PC-specific mortality. Our findings demonstrate that the prognostic effect of PNI is dependent on an association with high grade carcinoma and reactive stroma. However; the impact of PNI on clinical outcome becomes stronger and independent of other clinicopathologic factors upon increased percentage of PNI positive biopsy cores. Thus, our study highlights the importance of PNI and microenvironmental interactions for the long-term outcome of PC.

Revisiting tumour aneuploidy - the place of ploidy assessment in the molecular era

Chromosome instability (CIN) is gaining increasing interest as a central process in cancer. CIN, either past or present, is indicated whenever tumour cells harbour an abnormal quantity of DNA, termed 'aneuploidy'. At present, the most widely used approach to detecting aneuploidy is DNA cytometry - a well-known research assay that involves staining of DNA in the nuclei of cells from a tissue sample, followed by analysis using quantitative flow cytometry or microscopic imaging. Aneuploidy in cancer tissue has been implicated as a predictor of a poor prognosis. In this Review, we have explored this hypothesis by surveying the current landscape of peer-reviewed research in which DNA cytometry has been applied in studies with disease-appropriate clinical follow up. This area of research is broad, however, and we restricted our survey to results published since 2000 relating to seven common epithelial cancers (those of the breast; endometrium, ovary, and uterine cervix; oesophagus; colon and rectum; lung; prostate; and bladder). We placed particular emphasis on results from multivariate analyses to pinpoint situations in which the prognostic value of aneuploidy as a biomarker is strong compared with that of existing indicators, such as clinical stage, histological grade, and specific molecular markers. We summarize the implications of our findings for the prognostic use of ploidy analysis in the clinic and for the theoretical understanding of the role of CIN in carcinogenesis.

Clinical features and prognosis of prostate cancer with high-grade prostatic intraepithelial neoplasia

Purpose

To evaluate the clinical features and biochemical recurrence (BCR) in prostate cancer (PCa) with high-grade prostatic intraepithelial neoplasia (HGPIN).

Materials and Methods

We retrospectively analyzed the medical records of 893 patients who underwent a radical prostatectomy for PCa between 2011 and 2012 at Asan Medical Center; 752 of these patients who did not receive neoadjuvant or adjuvant therapy and were followed up for more than 1 year were included. The cohort was divided into two groups-patients with and without HGPIN-and their characteristics were compared. The Cox proportional hazards model was used to analyze factors affecting BCR.

Results

In total, 652 study patients (86.7%) had HGPIN. There were no significant differences in preoperative factors between the two groups, including age (p=0.369) and preoperative prostate-specific antigen concentration (p=0.234). Patients with HGPIN had a higher Gleason score (p=0.012), more frequent multiple tumor (p=0.013), and more perineural invasion (p=0.012), but no other postoperative pathologic characteristics were significantly different between the two groups. There were no significant differences in BCR (13.0% vs. 11.5%, p=0.665) and HGPIN was not associated with BCR (p=0.745). In multivariate analysis, only the T stage (p<0.001) was associated with BCR.

Conclusions

PCa patients with HGPIN have a higher Gleason score, more frequent multiple tumors, and more perineural invasion than those without HGPIN. The presence of HGPIN is not an independent predictor of BCR.

Comparison of digital image analysis and visual scoring of KI-67 in prostate cancer prognosis after prostatectomy

Background

The tumor proliferative index marker Ki-67 was shown to be associated with clinically significant outcomes in prostate cancer, but its clinical application has limitations due to lack of uniformity and consistency in quantification. Our objective was to compare the measurements obtained with digital image analysis (DIA) versus virtual microscopy (visual scoring (VS)).

Methods

To do so, we compared the measurement distributions of each technique and their ability to predict clinically useful endpoints. A tissue microarray series from a cohort of 225 men who underwent radical prostatectomy was immunostained for Ki-67. The percentage of Ki-67 positive nuclei in malignant cells was assessed both by VS and DIA, and a H–score was calculated. The distribution and predictive ability of these scoring methods to predict biochemical recurrence (BCR) and death from prostate cancer (DPCa) were compared using Mann–Whitney test and C-index.

Results

The measurements obtained with VS were similar to the DIA measurements (p = 0.73) but dissimilar to the H-score (p < 0.001). Cox regression models showed that Ki-67 was associated with BCR (HR 1.46, 95 % CI 1.10-1.94) and DPCa (HR 1.26, 95 % CI 1.06-1.50). C-indexes revealed that Ki-67 was a better predictor of DPCa (0.803, 0.8059 and 0.789; VS, DIA and H-score, respectively) than of BCR (0.625, 0.632 and 0.604; VS, DIA and H-score, respectively).

Conclusion

The measurement distributions and the predictive abilities of VS and DIA were similar and presented the same predictive behaviour in our cohort, supporting the role of Ki-67 proliferative index as an important prognostic factor of BCR and DPCa in prostate cancer post RP.

Virtual Slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/6656878501536663

Electronic supplementary material

The online version of this article (doi:10.1186/s13000-015-0294-0) contains supplementary material, which is available to authorized users.