Stat5 induces androgen receptor (AR) gene transcription in prostate cancer and offers a druggable pathway to target AR signaling.

Androgen receptor (AR) drives prostate cancer (PC) growth and progression, and targeting AR signaling is the mainstay of pharmacological therapies for PC. Resistance develops relatively fast as a result of refueled AR activity. A major gap in the field is the lack of understanding of targetable mechanisms that induce persistent AR expression in castrate-resistant PC (CRPC). This study uncovers an unexpected function of active Stat5 signaling, a known promoter of PC growth and clinical progression, as a potent inducer of AR gene transcription. Stat5 suppression inhibited AR gene transcription in preclinical PC models and reduced the levels of wild-type, mutated, and truncated AR proteins. Pharmacological Stat5 inhibition by a specific small-molecule Stat5 inhibitor down-regulated Stat5-inducible genes as well as AR and AR-regulated genes and suppressed PC growth. This work introduces the concept of Stat5 as an inducer of AR gene transcription in PC. Pharmacological Stat5 inhibitors may represent a new strategy for suppressing AR and CRPC growth.

High PD-L2 Predicts Early Recurrence of ER-Positive Breast Cancer.

PURPOSE: T-cell-mediated cytotoxicity is suppressed when programmed cell death-1 (PD-1) is bound by PD-1 ligand-1 (PD-L1) or PD-L2. Although PD-1 inhibitors have been approved for triple-negative breast cancer, the lower response rates of 25%-30% in estrogen receptor-positive (ER+) breast cancer will require markers to identify likely responders. The focus of this study was to evaluate whether PD-L2, which has higher affinity than PD-L1 for PD-1, is a predictor of early recurrence in ER+ breast cancer. METHODS: PD-L2 protein levels in cancer cells and stromal cells of therapy-naive, localized or locoregional ER+ breast cancers were measured retrospectively by quantitative immunofluorescence histocytometry and correlated with progression-free survival (PFS) in the main study cohort (n = 684) and in an independent validation cohort (n = 273). All patients subsequently received standard-of-care adjuvant therapy without immune checkpoint inhibitors. RESULTS: Univariate analysis of the main cohort revealed that high PD-L2 expression in cancer cells was associated with shorter PFS (hazard ratio [HR], 1.8; 95% CI, 1.3 to 2.6; P = .001), which was validated in an independent cohort (HR, 2.3; 95% CI, 1.1 to 4.8; P = .026) and remained independently predictive after multivariable adjustment for common clinicopathological variables (HR, 2.0; 95% CI, 1.4 to 2.9; P < .001). Subanalysis of the ER+ breast cancer patients treated with adjuvant chemotherapy (n = 197) revealed that high PD-L2 levels in cancer cells associated with short PFS in univariate (HR, 2.5; 95% CI, 1.4 to 4.4; P = .003) and multivariable analyses (HR, 3.4; 95% CI, 1.9 to 6.2; P < .001). CONCLUSION: Up to one third of treatment-naive ER+ breast tumors expressed high PD-L2 levels, which independently predicted poor clinical outcome, with evidence of further elevated risk of progression in patients who received adjuvant chemotherapy. Collectively, these data warrant studies to gain a deeper understanding of PD-L2 in the progression of ER+ breast cancer and may provide rationale for immune checkpoint blockade for this patient group.

Spatial Metrics of Interaction between CD163-Positive Macrophages and Cancer Cells and Progression-Free Survival in Chemo-Treated Breast Cancer.

Tumor-associated macrophages (TAMs) promote progression of breast cancer and other solid malignancies via immunosuppressive, pro-angiogenic and pro-metastatic effects. Tumor-promoting TAMs tend to express M2-like macrophage markers, including CD163. Histopathological assessments suggest that the density of CD163-positive TAMs within the tumor microenvironment is associated with reduced efficacy of chemotherapy and unfavorable prognosis. However, previous analyses have required research-oriented pathologists to visually enumerate CD163+ TAMs, which is both laborious and subjective and hampers clinical implementation. Objective, operator-independent image analysis methods to quantify TAM-associated information are needed. In addition, since M2-like TAMs exert local effects on cancer cells through direct juxtacrine cell-to-cell interactions, paracrine signaling, and metabolic factors, we hypothesized that spatial metrics of adjacency of M2-like TAMs to breast cancer cells will have further information value. Immunofluorescence histo-cytometry of CD163+ TAMs was performed retrospectively on tumor microarrays of 443 cases of invasive breast cancer from patients who subsequently received adjuvant chemotherapy. An objective and automated algorithm was developed to phenotype CD163+ TAMs and calculate their density within the tumor stroma and derive several spatial metrics of interaction with cancer cells. Shorter progression-free survival was associated with a high density of CD163+ TAMs, shorter median cancer-to-CD163+ nearest neighbor distance, and a high number of either directly adjacent CD163+ TAMs (within juxtacrine proximity <12 µm to cancer cells) or communicating CD163+ TAMs (within paracrine communication distance <250 µm to cancer cells) after multivariable adjustment for clinical and pathological risk factors and correction for optimistic bias due to dichotomization.

Multi-Site Concordance of Diffusion-Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness.

BACKGROUND: Diffusion-weighted imaging (DWI) is commonly used to detect prostate cancer, and a major clinical challenge is differentiating aggressive from indolent disease. PURPOSE: To compare 14 site-specific parametric fitting implementations applied to the same dataset of whole-mount pathologically validated DWI to test the hypothesis that cancer differentiation varies with different fitting algorithms. STUDY TYPE: Prospective. POPULATION: Thirty-three patients prospectively imaged prior to prostatectomy. FIELD STRENGTH/SEQUENCE: 3 T, field-of-view optimized and constrained undistorted single-shot DWI sequence. ASSESSMENT: Datasets, including a noise-free digital reference object (DRO), were distributed to the 14 teams, where locally implemented DWI parameter maps were calculated, including mono-exponential apparent diffusion coefficient (MEADC), kurtosis (K), diffusion kurtosis (DK), bi-exponential diffusion (BID), pseudo-diffusion (BID*), and perfusion fraction (F). The resulting parametric maps were centrally analyzed, where differentiation of benign from cancerous tissue was compared between DWI parameters and the fitting algorithms with a receiver operating characteristic area under the curve (ROC AUC). STATISTICAL TEST: Levene's test, P < 0.05 corrected for multiple comparisons was considered statistically significant. RESULTS: The DRO results indicated minimal discordance between sites. Comparison across sites indicated that K, DK, and MEADC had significantly higher prostate cancer detection capability (AUC range = 0.72-0.76, 0.76-0.81, and 0.76-0.80 respectively) as compared to bi-exponential parameters (BID, BID*, F) which had lower AUC and greater between site variation (AUC range = 0.53-0.80, 0.51-0.81, and 0.52-0.80 respectively). Post-processing parameters also affected the resulting AUC, moving from, for example, 0.75 to 0.87 for MEADC varying cluster size. DATA CONCLUSION: We found that conventional diffusion models had consistent performance at differentiating prostate cancer from benign tissue. Our results also indicated that post-processing decisions on DWI data can affect sensitivity and specificity when applied to radiological-pathological studies in prostate cancer. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.

Updates and new directions in the use of radiation therapy for the treatment of pancreatic adenocarcinoma: dose, sensitization, and novel technology.

Panc reatic ductal adenocarcinoma (PDAC) is a devastating malignancy. There have been few advances that have substantially improved overall survival in the past several years. On its current trajectory, the deaths from PDAC are expected to cross that from all gastrointestinal cancers combined by 2030. Radiation therapy is a technically very complex modality that bridges multiple different treatment strategies. It represents a hybrid among advanced diagnostic imaging, local (often ablative) intervention, and heterogeneous biological mechanisms contributing to normal and oncologic cell kill. In this article, we bring an overview of the several promising strategies that are currently being investigated to improve outcomes using radiation therapy for patients with PDAC.

Second-Generation Jak2 Inhibitors for Advanced Prostate Cancer: Are We Ready for Clinical Development?

Androgen deprivation therapy (ADT) for metastatic and high-risk prostate cancer (PC) inhibits growth pathways driven by the androgen receptor (AR). Over time, ADT leads to the emergence of lethal castrate-resistant PC (CRPC), which is consistently caused by an acquired ability of tumors to re-activate AR. This has led to the development of second-generation anti-androgens that more effectively antagonize AR, such as enzalutamide (ENZ). However, the resistance of CRPC to ENZ develops rapidly. Studies utilizing preclinical models of PC have established that inhibition of the Jak2-Stat5 signaling leads to extensive PC cell apoptosis and decreased tumor growth. In large clinical cohorts, Jak2-Stat5 activity predicts PC progression and recurrence. Recently, Jak2-Stat5 signaling was demonstrated to induce ENZ-resistant PC growth in preclinical PC models, further emphasizing the importance of Jak2-Stat5 for therapeutic targeting for advanced PC. The discovery of the Jak2V617F somatic mutation in myeloproliferative disorders triggered the rapid development of Jak1/2-specific inhibitors for a variety of myeloproliferative and auto-immune disorders as well as hematological malignancies. Here, we review Jak2 inhibitors targeting the mutated Jak2V617F vs. wild type (WT)-Jak2 that are currently in the development pipeline. Among these 35 compounds with documented Jak2 inhibitory activity, those with potency against WT-Jak2 hold strong potential for advanced PC therapy.

NSG-Pro mouse model for uncovering resistance mechanisms and unique vulnerabilities in human luminal breast cancers.

Most breast cancer deaths are caused by estrogen receptor-α­positive (ER+) disease. Preclinical progress is hampered by a shortage of therapy-naïve ER+ tumor models that recapitulate metastatic progression and clinically relevant therapy resistance. Human prolactin (hPRL) is a risk factor for primary and metastatic ER+ breast cancer. Because mouse prolactin fails to activate hPRL receptors, we developed a prolactin-humanized Nod-SCID-IL2Rγ (NSG) mouse (NSG-Pro) with physiological hPRL levels. Here, we show that NSG-Pro mice facilitate establishment of therapy-naïve, estrogen-dependent PDX tumors that progress to lethal metastatic disease. Preclinical trials provide first-in-mouse efficacy of pharmacological hPRL suppression on residual ER+ human breast cancer metastases and document divergent biology and drug responsiveness of tumors grown in NSG-Pro versus NSG mice. Oncogenomic analyses of PDX lines in NSG-Pro mice revealed clinically relevant therapy-resistance mechanisms and unexpected, potently actionable vulnerabilities such as DNA-repair aberrations. The NSG-Pro mouse unlocks previously inaccessible precision medicine approaches for ER+ breast cancers.

Prospects for Clinical Development of Stat5 Inhibitor IST5-002: High Transcriptomic Specificity in Prostate Cancer and Low Toxicity In Vivo.

Stat5 is of significant interest in the search for new therapeutics for prostate cancer (PC) and hematopoietic disorders. We evaluated the transcriptomic specificity of the Stat5a/b inhibitor IST5-002 (IST5) in PC, defined more closely its mechanisms of action, and investigated the in vivo toxicity of IST5 for further optimization for clinical development. The transcriptomic specificity of IST5 vs. genetic Stat5 knockdown was evaluated by RNA-seq analysis, which showed high similarity with the Pearson correlation coefficient ranging from 0.98-0.99. The potency of IST5 vs. its derivative lacking the phosphate group in suppressing Stat5 was evaluated in two separate but complementary assays. The inhibitory activity of IST5 against kinases was investigated in cell-free assays followed by more focused evaluation in a cell-based assay. IST5 has no specific inhibitory activity against 54 kinases, while suppressing Stat5 phosphorylation and subsequent dimerization in PC cells. The phosphate group was not critical for the biological activity of IST5 in cells. The acute, sub-chronic and chronic toxicity studies of IST5 were carried out in mice. IST5 did not cause any significant toxic effects or changes in the blood profiles. The present work supports further optimization of IST5 for oral bioavailability for clinical development for therapies for solid tumors, hematological and myeloproliferative disorders.

Accurate segmentation of prostate cancer histomorphometric features using a weakly supervised convolutional neural network.

Purpose: Prostate cancer primarily arises from the glandular epithelium. Histomophometric techniques have been used to assess the glandular epithelium in automated detection and classification pipelines; however, they are often rigid in their implementation, and their performance suffers on large datasets where variation in staining, imaging, and preparation is difficult to control. The purpose of this study is to quantify performance of a pixelwise segmentation algorithm that was trained using different combinations of weak and strong stroma, epithelium, and lumen labels in a prostate histology dataset. Approach: We have combined weakly labeled datasets generated using simple morphometric techniques and high-quality labeled datasets from human observers in prostate biopsy cores to train a convolutional neural network for use in whole mount prostate labeling pipelines. With trained networks, we characterize pixelwise segmentation of stromal, epithelium, and lumen (SEL) regions on both biopsy core and whole-mount H&E-stained tissue. Results: We provide evidence that by simply training a deep learning algorithm on weakly labeled data generated from rigid morphometric methods, we can improve the robustness of classification over the morphometric methods used to train the classifier. Conclusions: We show that not only does our approach of combining weak and strong labels for training the CNN improve qualitative SEL labeling within tissue but also the deep learning generated labels are superior for cancer classification in a higher-order algorithm over the morphometrically derived labels it was trained on.

Cytokines, JAK-STAT Signaling and Radiation-Induced DNA Repair in Solid Tumors: Novel Opportunities for Radiation Therapy.

A number of solid tumors are treated with radiation therapy (RT) as a curative modality. At the same time, for certain types of cancers the applicable doses of RT are not high enough to result in a successful eradication of cancer cells. This is often caused by limited pharmacological tools and strategies to selectively sensitize tumors to RT while simultaneously sparing normal tissues from RT. We present an outline of a novel strategy for RT sensitization of solid tumors utilizing Jak inhibitors. Here, recently published pre-clinical data are reviewed which demonstrate the promising role of Jak inhibition in sensitization of tumors to RT. A wide number of currently approved Jak inhibitors for non-malignant conditions are summarized including Jak inhibitors currently in clinical development. Finally, intersection between Jak/Stat and the levels of serum cytokines are presented and discussed as they relate to susceptibility to RT.

Enzalutamide-Induced Feed-Forward Signaling Loop Promotes Therapy-Resistant Prostate Cancer Growth Providing an Exploitable Molecular Target for Jak2 Inhibitors.

The second-generation antiandrogen, enzalutamide, is approved for castrate-resistant prostate cancer (CRPC) and targets androgen receptor (AR) activity in CRPC. Despite initial clinical activity, acquired resistance to enzalutamide arises rapidly and most patients develop terminal disease. Previous work has established Stat5 as a potent inducer of prostate cancer growth. Here, we investigated the significance of Jak2-Stat5 signaling in resistance of prostate cancer to enzalutamide. The levels of Jak2 and Stat5 mRNA, proteins and activation were evaluated in prostate cancer cells, xenograft tumors, and clinical prostate cancers before and after enzalutamide therapy. Jak2 and Stat5 were suppressed by genetic knockdown using lentiviral shRNA or pharmacologic inhibitors. Responsiveness of primary and enzalutamide-resistant prostate cancer to pharmacologic inhibitors of Jak2-Stat5 signaling was assessed in vivo in mice bearing prostate cancer xenograft tumors. Patient-derived prostate cancers were tested for responsiveness to Stat5 blockade as second-line treatment after enzalutamide ex vivo in tumor explant cultures. Enzalutamide-liganded AR induces sustained Jak2-Stat5 phosphorylation in prostate cancer leading to the formation of a positive feed-forward loop, where activated Stat5, in turn, induces Jak2 mRNA and protein levels contributing to further Jak2 activation. Mechanistically, enzalutamide-liganded AR induced Jak2 phosphorylation through a process involving Jak2-specific phosphatases. Stat5 promoted prostate cancer growth during enzalutamide treatment. Jak2-Stat5 inhibition induced death of prostate cancer cells and patient-derived prostate cancers surviving enzalutamide treatment and blocked enzalutamide-resistant tumor growth in mice. This work introduces a novel concept of a pivotal role of hyperactivated Jak2-Stat5 signaling in enzalutamide-resistant prostate cancer, which is readily targetable by Jak2 inhibitors in clinical development.

Positive STAT5 Protein and Locus Amplification Status Predicts Recurrence after Radical Prostatectomy to Assist Clinical Precision Management of Prostate Cancer.

BACKGROUND: A significant fraction of prostate cancer patients experience post-radical prostatectomy (RP) biochemical recurrence (BCR). New predictive markers are needed for optimizing postoperative prostate cancer management. STAT5 is an oncogene in prostate cancer that undergoes amplification in 30% of prostate cancers during progression. METHODS: We evaluated the significance of a positive status for nuclear STAT5 protein expression versus STAT5 locus amplification versus combined positive status for both in predicting BCR after RP in 300 patients. RESULTS: Combined positive STAT5 status was associated with a 45% disadvantage in BCR in Kaplan-Meier survival analysis in all Gleason grade patients. Patients with Gleason grade group (GG) 2 and 3 prostate cancers and combined positive status for STAT5 had a more pronounced disadvantage of 55% to 60% at 7 years after RP in univariate analysis. In multivariate analysis, including the Cancer of the Prostate Risk Assessment Postsurgical nomogram (CAPRA-S) variables, combined positive STAT5 status was independently associated with a shorter BCR-free survival in all Gleason GG patients (HR, 2.34; P = 0.014) and in intermediate Gleason GG 2 or 3 patients (HR, 3.62; P = 0.021). The combined positive STAT5 status improved the predictive value of the CAPRA-S nomogram in both ROC-AUC analysis and in decision curve analysis for BCR. CONCLUSIONS: Combined positive status for STAT5 was independently associated with shorter disease-free survival in univariate analysis and was an independent predictor for BCR in multivariate analysis using the CAPRA-S variables in prostate cancer. IMPACT: Our results highlight potential for a novel precision medicine concept based on a pivotal role of STAT5 status in improving selection of prostate cancer patients who are candidates for early adjuvant interventions to reduce the risk of recurrence.

Gleason Probability Maps: A Radiomics Tool for Mapping Prostate Cancer Likelihood in MRI Space.

Prostate cancer is the most common noncutaneous cancer in men in the United States. The current paradigm for screening and diagnosis is imperfect, with relatively low specificity, high cost, and high morbidity. This study aims to generate new image contrasts by learning a distribution of unique image signatures associated with prostate cancer. In total, 48 patients were prospectively recruited for this institutional review board-approved study. Patients underwent multiparametric magnetic resonance imaging 2 weeks before surgery. Postsurgical tissues were annotated by a pathologist and aligned to the in vivo imaging. Radiomic profiles were generated by linearly combining 4 image contrasts (T2, apparent diffusion coefficient [ADC] 0-1000, ADC 50-2000, and dynamic contrast-enhanced) segmented using global thresholds. The distribution of radiomic profiles in high-grade cancer, low-grade cancer, and normal tissues was recorded, and the generated probability values were applied to a naive test set. The resulting Gleason probability maps were stable regardless of training cohort, functioned independent of prostate zone, and outperformed conventional clinical imaging (area under the curve [AUC] = 0.79). Extensive overlap was seen in the most common image signatures associated with high- and low-grade cancer, indicating that low- and high-grade tumors present similarly on conventional imaging.

Targeting STAT5 or STAT5-Regulated Pathways Suppresses Leukemogenesis of Ph+ Acute Lymphoblastic Leukemia.

Combining standard cytotoxic chemotherapy with BCR-ABL1 tyrosine kinase inhibitors (TKI) has greatly improved the upfront treatment of patients with Philadelphia chromosome-positive (Ph+) acute lymphoblastic leukemia (ALL). However, due to the development of drug resistance through both BCR-ABL1-dependent and -independent mechanisms, prognosis remains poor. The STAT5 transcription factor is activated by BCR-ABL1 and by JAK2-dependent cytokine signaling; therefore, inhibiting its activity could address both mechanisms of resistance in Ph+ ALL. We show here that genetic and pharmacologic inhibition of STAT5 activity suppresses cell growth, induces apoptosis, and inhibits leukemogenesis of Ph+ cell lines and patient-derived newly diagnosed and relapsed/TKI-resistant Ph+ ALL cells ex vivo and in mouse models. STAT5 silencing decreased expression of the growth-promoting PIM-1 kinase, the apoptosis inhibitors MCL1 and BCL2, and increased expression of proapoptotic BIM protein. The resulting apoptosis of STAT5-silenced Ph+ BV173 cells was rescued by silencing of BIM or restoration of BCL2 expression. Treatment of Ph+ ALL cells, including samples from relapsed/refractory patients, with the PIM kinase inhibitor AZD1208 and/or the BCL2 family antagonist Sabutoclax markedly suppressed cell growth and leukemogenesis ex vivo and in mice. Together, these studies indicate that targeting STAT5 or STAT5-regulated pathways may provide a new approach for therapy development in Ph+ ALL, especially the relapsed/TKI-resistant disease.Significance: Suppression of STAT5 by BCL2 and PIM kinase inhibitors reduces leukemia burden in mice and constitutes a new potential therapeutic approach against Ph+ ALL, especially in tyrosine kinase inhibitor-resistant disease. Cancer Res; 78(20); 5793-807. ©2018 AACR.

Radio-pathomic Maps of Epithelium and Lumen Density Predict the Location of High-Grade Prostate Cancer.

PURPOSE: This study aims to combine multiparametric magnetic resonance imaging (MRI) and digitized pathology with machine learning to generate predictive maps of histologic features for prostate cancer localization. METHODS AND MATERIALS: Thirty-nine patients underwent MRI prior to prostatectomy. After surgery, tissue was sliced according to MRI orientation using patient-specific 3-dimensionally printed slicing jigs. Whole-mount sections were annotated by our pathologist and digitally contoured to differentiate the lumen and epithelium. Slides were co-registered to the T2-weighted MRI scan. A learning curve was generated to determine the number of patients required for a stable machine-learning model. Patients were randomly stratified into 2 training sets and 1 test set. Two partial least-squares regression models were trained, each capable of predicting lumen and epithelium density. Predicted density values were calculated for each patient in the test dataset, mapped into the MRI space, and compared between regions confirmed as high-grade prostate cancer. RESULTS: The learning-curve analysis showed that a stable fit was achieved with data from 10 patients. Maps indicated that regions of increased epithelium and decreased lumen density, generated from each independent model, corresponded with pathologist-annotated regions of high-grade cancer. CONCLUSIONS: We present a radio-pathomic approach to mapping prostate cancer. We find that the maps are useful for highlighting high-grade tumors. This technique may be relevant for dose-painting strategies in prostate radiation therapy.

STAT5A/B Blockade Sensitizes Prostate Cancer to Radiation through Inhibition of RAD51 and DNA Repair.

Purpose: The standard treatment for organ-confined prostate cancer is surgery or radiation, and locally advanced prostate cancer is typically treated with radiotherapy alone or in combination with androgen deprivation therapy. Here, we investigated whether Stat5a/b participates in regulation of double-strand DNA break repair in prostate cancer, and whether Stat5 inhibition may provide a novel strategy to sensitize prostate cancer to radiotherapy.Experimental Design: Stat5a/b regulation of DNA repair in prostate cancer was evaluated by comet and clonogenic survival assays, followed by assays specific to homologous recombination (HR) DNA repair and nonhomologous end joining (NHEJ) DNA repair. For HR DNA repair, Stat5a/b regulation of Rad51 and the mechanisms underlying the regulation were investigated in prostate cancer cells, xenograft tumors, and patient-derived prostate cancers ex vivo in 3D explant cultures. Stat5a/b induction of Rad51 and HR DNA repair and responsiveness to radiation were evaluated in vivo in mice bearing prostate cancer xenograft tumors.Results: Stat5a/b is critical for Rad51 expression in prostate cancer via Jak2-dependent mechanisms by inducing Rad51 mRNA levels. Consistent with this, genetic knockdown of Stat5a/b suppressed HR DNA repair while not affecting NHEJ DNA repair. Pharmacologic Stat5a/b inhibition potently sensitized prostate cancer cell lines and prostate cancer tumors to radiation, while not inducing radiation sensitivity in the neighboring tissues.Conclusions: This work introduces a novel concept of a pivotal role of Jak2-Stat5a/b signaling for Rad51 expression and HR DNA repair in prostate cancer. Inhibition of Jak2-Stat5a/b signaling sensitizes prostate cancer to radiation and, therefore, may provide an adjuvant therapy for radiation to reduce radiation-induced damage to the neighboring tissues. Clin Cancer Res; 24(8); 1917-31. ©2018 AACR.

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.

Work-based learning in health care organisations experienced by nursing staff: A systematic review of qualitative studies.

The aim of this review is to systematically summarise qualitative evidence about work-based learning in health care organisations as experienced by nursing staff. Work-based learning is understood as informal learning that occurs inside the work community in the interaction between employees. Studies for this review were searched for in the CINAHL, PubMed, Scopus and ABI Inform ProQuest databases for the period 2000-2015. Nine original studies met the inclusion criteria. After the critical appraisal by two researchers, all nine studies were selected for the review. The findings of the original studies were aggregated, and four statements were prepared, to be utilised in clinical work and decision-making. The statements concerned the following issues: (1) the culture of the work community; (2) the physical structures, spaces and duties of the work unit; (3) management; and (4) interpersonal relations. Understanding the nurses' experiences of work-based learning and factors behind these experiences provides an opportunity to influence the challenges of learning in the demanding context of health care organisations.

Erratum: ETS Related Gene mediated Androgen Receptor Aggregation and Endoplasmic Reticulum Stress in Prostate Cancer Development.

A correction to this article has been published and is linked from the HTML version of this paper. The error has not been fixed in the paper.