Analysis of 3D pathology samples using weakly supervised AI.

Human tissue, which is inherently three-dimensional (3D), is traditionally examined through standard-of-care histopathology as limited two-dimensional (2D) cross-sections that can insufficiently represent the tissue due to sampling bias. To holistically characterize histomorphology, 3D imaging modalities have been developed, but clinical translation is hampered by complex manual evaluation and lack of computational platforms to distill clinical insights from large, high-resolution datasets. We present TriPath, a deep-learning platform for processing tissue volumes and efficiently predicting clinical outcomes based on 3D morphological features. Recurrence risk-stratification models were trained on prostate cancer specimens imaged with open-top light-sheet microscopy or microcomputed tomography. By comprehensively capturing 3D morphologies, 3D volume-based prognostication achieves superior performance to traditional 2D slice-based approaches, including clinical/histopathological baselines from six certified genitourinary pathologists. Incorporating greater tissue volume improves prognostic performance and mitigates risk prediction variability from sampling bias, further emphasizing the value of capturing larger extents of heterogeneous morphology.

Unconventional human CD61 pairing with CD103 promotes TCR signaling and antigen-specific T cell cytotoxicity.

Cancer remains one of the leading causes of mortality worldwide, leading to increased interest in utilizing immunotherapy strategies for better cancer treatments. In the past decade, CD103+ T cells have been associated with better clinical prognosis in patients with cancer. However, the specific immune mechanisms contributing toward CD103-mediated protective immunity remain unclear. Here, we show an unexpected and transient CD61 expression, which is paired with CD103 at the synaptic microclusters of T cells. CD61 colocalization with the T cell antigen receptor further modulates downstream T cell antigen receptor signaling, improving antitumor cytotoxicity and promoting physiological control of tumor growth. Clinically, the presence of CD61+ tumor-infiltrating T lymphocytes is associated with improved clinical outcomes, mediated through enhanced effector functions and phenotype with limited evidence of cellular exhaustion. In conclusion, this study identified an unconventional and transient CD61 expression and pairing with CD103 on human immune cells, which potentiates a new target for immune-based cellular therapies.

Molecular analysis of archival diagnostic prostate cancer biopsies identifies genomic similarities in cases with progression post-radiotherapy, and those with de novo metastatic disease.

BACKGROUND: It is important to identify molecular features that improve prostate cancer (PCa) risk stratification before radical treatment with curative intent. Molecular analysis of historical diagnostic formalin-fixed paraffin-embedded (FFPE) prostate biopsies from cohorts with post-radiotherapy (RT) long-term clinical follow-up has been limited. Utilizing parallel sequencing modalities, we performed a proof-of-principle sequencing analysis of historical diagnostic FFPE prostate biopsies. We compared patients with (i) stable PCa (sPCa) postprimary or salvage RT, (ii) progressing PCa (pPCa) post-RT, and (iii) de novo metastatic PCa (mPCa). METHODS: A cohort of 19 patients with diagnostic prostate biopsies (n = 6 sPCa, n = 5 pPCa, n = 8 mPCa) and mean 4 years 10 months follow-up (diagnosed 2009-2016) underwent nucleic acid extraction from demarcated malignancy. Samples underwent 3'RNA sequencing (3'RNAseq) (n = 19), nanoString analysis (n = 12), and Illumina 850k methylation (n = 8) sequencing. Bioinformatic analysis was performed to coherently identify differentially expressed genes and methylated genomic regions (MGRs). RESULTS: Eighteen of 19 samples provided useable 3'RNAseq data. Principal component analysis (PCA) demonstrated similar expression profiles between pPCa and mPCa cases, versus sPCa. Coherently differentially methylated probes between these groups identified ~600 differentially MGRs. The top 50 genes with increased expression in pPCa patients were associated with reduced progression-free survival post-RT (p < 0.0001) in an external cohort. CONCLUSIONS: 3'RNAseq, nanoString and 850k-methylation analyses are each achievable from historical FFPE diagnostic pretreatment prostate biopsies, unlocking the potential to utilize large cohorts of historic clinical samples. Profiling similarities between individuals with pPCa and mPCa suggests biological similarities and historical radiological staging limitations, which warrant further investigation.

First-in-man study of the PSMA Minibody IR800-IAB2M for molecularly targeted intraoperative fluorescence guidance during radical prostatectomy.

PURPOSE: Prostate-specific membrane antigen (PSMA) is increasingly used to image prostate cancer in clinical practice. We sought to develop and test a humanised PSMA minibody IAB2M conjugated to the fluorophore IRDye 800CW-NHS ester in men undergoing robot-assisted laparoscopic radical prostatectomy (RARP) to image prostate cancer cells during surgery. METHODS: The minibody was evaluated pre-clinically using PSMA positive/negative xenograft models, following which 23 men undergoing RARP between 2018 and 2020 received between 2.5 mg and 20 mg of IR800-IAB2M intravenously, at intervals between 24 h and 17 days prior to surgery. At every step of the procedure, the prostate, pelvic lymph node chains and extra-prostatic surrounding tissue were imaged with a dual Near-infrared (NIR) and white light optical platform for fluorescence in vivo and ex vivo. Histopathological evaluation of intraoperative and postoperative microscopic fluorescence imaging was undertaken for verification. RESULTS: Twenty-three patients were evaluated to optimise both the dose of the reagent and the interval between injection and surgery and secure the best possible specificity of fluorescence images. Six cases are presented in detail as exemplars. Overall sensitivity and specificity in detecting non-lymph-node extra-prostatic cancer tissue were 100% and 65%, and 64% and 64% respectively for lymph node positivity. There were no side-effects associated with administration of the reagent. CONCLUSION: Intraoperative imaging of prostate cancer tissue is feasible and safe using IR800-IAB2M. Further evaluation is underway to assess the benefit of using the technique in improving completion of surgical excision during RARP. REGISTRATION: ISCRCTN10046036: https://www.isrctn.com/ISRCTN10046036 .

Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures.

Genetic signatures have added a molecular dimension to prognostics and therapeutic decision-making. However, tumour heterogeneity in prostate cancer and current sampling methods could confound accurate assessment. Based on previously published spatial transcriptomic data from multifocal prostate cancer, we created virtual biopsy models that mimic conventional biopsy placement and core size. We then analysed the gene expression of different prognostic signatures (OncotypeDx®, Decipher®, Prostadiag®) using a step-wise approach with increasing resolution from pseudo-bulk analysis of the whole biopsy, to differentiation by tissue subtype (benign, stroma, tumour), followed by distinct tumour grade and finally clonal resolution. The gene expression profile of virtual tumour biopsies revealed clear differences between grade groups and tumour clones, compared to a benign control, which were not reflected in bulk analyses. This suggests that bulk analyses of whole biopsies or tumour-only areas, as used in clinical practice, may provide an inaccurate assessment of gene profiles. The type of tissue, the grade of the tumour and the clonal composition all influence the gene expression in a biopsy. Clinical decision making based on biopsy genomics should be made with caution while we await more precise targeting and cost-effective spatial analyses.

Protocol for the TRANSLATE prospective, multicentre, randomised clinical trial of prostate biopsy technique.

OBJECTIVES: Primary objectives: to determine whether local anaesthetic transperineal prostate (LATP) biopsy improves the detection of clinically significant prostate cancer (csPCa), defined as International Society of Urological Pathology (ISUP) Grade Group ≥2 disease (i.e., any Gleason pattern 4 disease), compared to transrectal ultrasound-guided (TRUS) prostate biopsy, in biopsy-naïve men undergoing biopsy based on suspicion of csPCa. SECONDARY OBJECTIVES: to compare (i) infection rates, (ii) health-related quality of life, (iii) patient-reported procedure tolerability, (iv) patient-reported biopsy-related complications (including bleeding, bruising, pain, loss of erectile function), (v) number of subsequent prostate biopsy procedures required, (vi) cost-effectiveness, (vii) other histological parameters, and (viii) burden and rate of detection of clinically insignificant PCa (ISUP Grade Group 1 disease) in men undergoing these two types of prostate biopsy. PATIENTS AND METHODS: The TRANSLATE trial is a UK-wide, multicentre, randomised clinical trial that meets the criteria for level-one evidence in diagnostic test evaluation. TRANSLATE is investigating whether LATP biopsy leads to a higher rate of detection of csPCa compared to TRUS prostate biopsy. Both biopsies are being performed with an average of 12 systematic cores in six sectors (depending on prostate size), plus three to five target cores per multiparametric/bi-parametric magnetic resonance imaging lesion. LATP biopsy is performed using an ultrasound probe-mounted needle-guidance device (either the 'Precision-Point' or BK UA1232 system). TRUS biopsy is performed according to each hospital's standard practice. The study is 90% powered to detect a 10% difference (LATP biopsy hypothesised at 55% detection rate for csPCa vs 45% for TRUS biopsy). A total of 1042 biopsy-naïve men referred with suspected PCa need to be recruited. CONCLUSIONS: This trial will provide robust prospective data to determine the diagnostic ability of LATP biopsy vs TRUS biopsy in the primary diagnostic setting.

Genomic Evolution and Transcriptional Changes in the Evolution of Prostate Cancer into Neuroendocrine and Ductal Carcinoma Types.

Prostate cancer is typically of acinar adenocarcinoma type but can occasionally present as neuroendocrine and/or ductal type carcinoma. These are associated with clinically aggressive disease, and the former often arises on a background of androgen deprivation therapy, although it can also arise de novo. Two prostate cancer cases were sequenced by exome capture from archival tissue. Case 1 was de novo small cell neuroendocrine carcinoma and ductal adenocarcinoma with three longitudinal samples over 5 years. Case 2 was a single time point after the development of treatment-related neuroendocrine prostate carcinoma. Case 1 showed whole genome doubling in all samples and focal amplification of AR in all samples except the first time point. Phylogenetic analysis revealed a common ancestry for ductal and small cell carcinoma. Case 2 showed 13q loss (involving RB1) in both adenocarcinoma and small cell carcinoma regions, and 3p gain, 4p loss, and 17p loss (involving TP53) in the latter. By using highly curated samples, we demonstrate for the first time that small-cell neuroendocrine and ductal prostatic carcinoma can have a common ancestry. We highlight whole genome doubling in a patient with prostate cancer relapse, reinforcing its poor prognostic nature.

TET2 Drives 5hmc Marking of GATA6 and Epigenetically Defines Pancreatic Ductal Adenocarcinoma Transcriptional Subtypes.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinoma (PDAC) is characterized by advanced disease stage at presentation, aggressive disease biology, and resistance to therapy, resulting in an extremely poor 5-year survival rate of <10%. PDAC is classified into transcriptional subtypes with distinct survival characteristics, although how these arise is not known. Epigenetic deregulation, rather than genetics, has been proposed to underpin progression, but exactly why is unclear and is hindered by the technical limitations of analyzing clinical samples. METHODS: We performed genome-wide epigenetic mapping of DNA modifications 5-methylcytosine and 5-hydroxymethylcytosine (5hmc) using oxidative bisulfite sequencing from formalin-embedded sections. We identified overlap with transcriptional signatures in formalin-fixed, paraffin-embedded tissue from resected patients, via bioinformatics using iCluster and mutational profiling and confirmed them in vivo. RESULTS: We found that aggressive squamous-like PDAC subtypes result from epigenetic inactivation of loci, including GATA6, which promote differentiated classical pancreatic subtypes. We showed that squamous-like PDAC transcriptional subtypes are associated with greater loss of 5hmc due to reduced expression of the 5-methylcytosine hydroxylase TET2. Furthermore, we found that SMAD4 directly supports TET2 levels in classical pancreatic tumors, and loss of SMAD4 expression was associated with reduced 5hmc, GATA6, and squamous-like tumors. Importantly, enhancing TET2 stability using metformin and vitamin C/ascorbic acid restores 5hmc and GATA6 levels, reverting squamous-like tumor phenotypes and WNT-dependence in vitro and in vivo. CONCLUSIONS: We identified epigenetic deregulation of pancreatic differentiation as an underpinning event behind the emergence of transcriptomic subtypes in PDAC. Our data showed that restoring epigenetic control increases biomarkers of classical pancreatic tumors that are associated with improved therapeutic responses and survival.

IFITM3-specific antibody reveals IFN preferences and slow IFN induction of the antiviral factor IFITM3 in humans.

Using a specific antibody, we found that expression of the viral restriction factor IFITM3 differs across cell types within the immune compartment with higher expression in myeloid rather than lymphoid cells. IFITM3 expression was increased following IFN stimulation, mostly type I, in immune cells, with the exception of T cells.

Potential quality pitfalls of digitalized whole slide image of breast pathology in routine practice.

Using digitalized whole slide images (WSI) in routine histopathology practice is a revolutionary technology. This study aims to assess the clinical impacts of WSI quality and representation of the corresponding glass slides. 40,160 breast WSIs were examined and compared with their corresponding glass slides. The presence, frequency, location, tissue type, and the clinical impacts of missing tissue were assessed. Scanning time, type of the specimens, time to WSIs implementation, and quality control (QC) measures were also considered. The frequency of missing tissue ranged from 2% to 19%. The area size of the missed tissue ranged from 1-70%. In most cases (>75%), the missing tissue area size was <10% and peripherally located. In all cases the missed tissue was fat with or without small entrapped normal breast parenchyma. No missing tissue was identified in WSIs of the core biopsy specimens. QC measures improved images quality and reduced WSI failure rates by seven-fold. A negative linear correlation between the frequency of missing tissue and both the scanning time and the image file size was observed (p < 0.05). None of the WSI with missing tissues resulted in a change in the final diagnosis. Missing tissue on breast WSI is observed but with variable frequency and little diagnostic consequence. Balancing between WSI quality and scanning time/image file size should be considered and pathology laboratories should undertake their own assessments of risk and provide the relevant mitigations with the appropriate level of caution.

Decoding germ cell tumours for clinicians.

PURPOSE OF REVIEW: Germ-cell tumours of the testis affect predominantly younger males aged between 15 and 40 years, with nearly 74,500 new cases estimated globally in 2020. Their rarity and the complex morphology, mean that, in nonexpert hands, there is a significant risk of misdiagnosis of both type and staging of these neoplasms. RECENT FINDINGS: There have been significant changes in the 2016 WHO classification of Testicular tumours that need to be understood by both pathologists and clinicians for streamlining management. Standardised structured reporting guidelines and discussion at the multidisciplinary-team meetings lead to subsequently better health outcomes and patient safety. SUMMARY: Therefore, communication with high-quality reports and understanding of clinicians of what constitutes an adequate report, is the key to ensure proper management of these patients. We attempt to discuss the key updates and pathological features that influence management and need to be communicated with clarity and precision.

Ethical issues in computational pathology.

This paper explores ethical issues raised by whole slide image-based computational pathology. After briefly giving examples drawn from some recent literature of advances in this field, we consider some ethical problems it might be thought to pose. These arise from (1) the tension between artificial intelligence (AI) research-with its hunger for more and more data-and the default preference in data ethics and data protection law for the minimisation of personal data collection and processing; (2) the fact that computational pathology lends itself to kinds of data fusion that go against data ethics norms and some norms of biobanking; (3) the fact that AI methods are esoteric and produce results that are sometimes unexplainable (the so-called 'black box'problem) and (4) the fact that computational pathology is particularly dependent on scanning technology manufacturers with interests of their own in profit-making from data collection. We shall suggest that most of these issues are resolvable.

Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning.

OBJECTIVE: Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), histological grading is a poor predictor of disease progression, and consensus molecular subtypes (CMSs) cannot be distinguished without gene expression profiling. We hypothesise that image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data and to resolve unclassifiable or heterogeneous cases. In this study, we present an image-based approach to predict CRC CMS from standard H&E sections using deep learning. DESIGN: Training and evaluation of a neural network were performed using a total of n=1206 tissue sections with comprehensive multi-omic data from three independent datasets (training on FOCUS trial, n=278 patients; test on rectal cancer biopsies, GRAMPIAN cohort, n=144 patients; and The Cancer Genome Atlas (TCGA), n=430 patients). Ground truth CMS calls were ascertained by matching random forest and single sample predictions from CMS classifier. RESULTS: Image-based CMS (imCMS) accurately classified slides in unseen datasets from TCGA (n=431 slides, AUC)=0.84) and rectal cancer biopsies (n=265 slides, AUC=0.85). imCMS spatially resolved intratumoural heterogeneity and provided secondary calls correlating with bioinformatic prediction from molecular data. imCMS classified samples previously unclassifiable by RNA expression profiling, reproduced the expected correlations with genomic and epigenetic alterations and showed similar prognostic associations as transcriptomic CMS. CONCLUSION: This study shows that a prediction of RNA expression classifiers can be made from H&E images, opening the door to simple, cheap and reliable biological stratification within routine workflows.

Artificial intelligence for advance requesting of immunohistochemistry in diagnostically uncertain prostate biopsies.

The use of immunohistochemistry in the reporting of prostate biopsies is an important adjunct when the diagnosis is not definite on haematoxylin and eosin (H&E) morphology alone. The process is however inherently inefficient with delays while waiting for pathologist review to make the request and duplicated effort reviewing a case more than once. In this study, we aimed to capture the workflow implications of immunohistochemistry requests and demonstrate a novel artificial intelligence tool to identify cases in which immunohistochemistry (IHC) is required and generate an automated request. We conducted audits of the workflow for prostate biopsies in order to understand the potential implications of automated immunohistochemistry requesting and collected prospective cases to train a deep neural network algorithm to detect tissue regions that presented ambiguous morphology on whole slide images. These ambiguous foci were selected on the basis of the pathologist requesting immunohistochemistry to aid diagnosis. A gradient boosted trees classifier was then used to make a slide-level prediction based on the outputs of the neural network prediction. The algorithm was trained on annotations of 219 immunohistochemistry-requested and 80 control images, and tested by threefold cross-validation. Validation was conducted on a separate validation dataset of 222 images. Non IHC-requested cases were diagnosed in 17.9 min on average, while IHC-requested cases took 33.4 min over multiple reporting sessions. We estimated 11 min could be saved on average per case by automated IHC requesting, by removing duplication of effort. The tool attained 99% accuracy and 0.99 Area Under the Curve (AUC) on the test data. In the validation, the average agreement with pathologists was 0.81, with a mean AUC of 0.80. We demonstrate the proof-of-principle that an AI tool making automated immunohistochemistry requests could create a significantly leaner workflow and result in pathologist time savings.

Deep learning based digital cell profiles for risk stratification of urine cytology images.

Urine cytology is a test for the detection of high-grade bladder cancer. In clinical practice, the pathologist would manually scan the sample under the microscope to locate atypical and malignant cells. They would assess the morphology of these cells to make a diagnosis. Accurate identification of atypical and malignant cells in urine cytology is a challenging task and is an essential part of identifying different diagnosis with low-risk and high-risk malignancy. Computer-assisted identification of malignancy in urine cytology can be complementary to the clinicians for treatment management and in providing advice for carrying out further tests. In this study, we presented a method for identifying atypical and malignant cells followed by their profiling to predict the risk of diagnosis automatically. For cell detection and classification, we employed two different deep learning-based approaches. Based on the best performing network predictions at the cell level, we identified low-risk and high-risk cases using the count of atypical cells and the total count of atypical and malignant cells. The area under the receiver operating characteristic (ROC) curve shows that a total count of atypical and malignant cells is comparably better at diagnosis as compared to the count of malignant cells only. We obtained area under the ROC curve with the count of malignant cells and the total count of atypical and malignant cells as 0.81 and 0.83, respectively. Our experiments also demonstrate that the digital risk could be a better predictor of the final histopathology-based diagnosis. We also analyzed the variability in annotations at both cell and whole slide image level and also explored the possible inherent rationales behind this variability.

Validation of grading of non-invasive urothelial carcinoma by digital pathology for routine diagnosis.

BACKGROUND: Pathological grading of non-invasive urothelial carcinoma has a direct impact upon management. This study evaluates the reproducibility of grading these tumours on glass slides and digital pathology. METHODS: Forty eight non-invasive urothelial bladder carcinomas were graded by three uropathologists on glass and on a digital platform using the 1973 WHO and 2004 ISUP/WHO systems. RESULTS: Consensus grades for glass and digital grading gave Cohen's kappa scores of 0.78 (2004) and 0.82 (1973). Of 142 decisions made on the key therapeutic borderline of low grade versus high grade urothelial carcinoma (2004) by the three pathologists, 85% were in agreement. For the 1973 grading system, agreement overall was 90%. CONCLUSIONS: Agreement on grading on glass slide and digital screen assessment is similar or in some cases improved, suggesting at least non-inferiority of DP for grading of non-invasive urothelial carcinoma.

Patient-derived malignant pleural mesothelioma cell cultures: a tool to advance biomarker-driven treatments.

Malignant pleural mesothelioma (MPM) is an aggressive cancer, associated with poor prognosis. We assessed the feasibility of patient-derived cell cultures to serve as an ex vivo model of MPM. Patient-derived MPM cell cultures (n=16) exhibited stemness features and reflected intratumour and interpatient heterogeneity. A subset of the cells were subjected to high-throughput drug screening and coculture assays with cancer-specific cytotoxic T cells and showed diverse responses. Some of the biphasic MPM cells were capable of processing and presenting the neoantigen SSX-2 endogenously. In conclusion, patient-derived MPM cell cultures are a promising and faithful ex vivo model of MPM.

Artificial intelligence in digital pathology: a roadmap to routine use in clinical practice.

The use of artificial intelligence will transform clinical practice over the next decade and the early impact of this will likely be the integration of image analysis and machine learning into routine histopathology. In the UK and around the world, a digital revolution is transforming the reporting practice of diagnostic histopathology and this has sparked a proliferation of image analysis software tools. While this is an exciting development that could discover novel predictive clinical information and potentially address international pathology workforce shortages, there is a clear need for a robust and evidence-based framework in which to develop these new tools in a collaborative manner that meets regulatory approval. With these issues in mind, the NCRI Cellular Molecular Pathology (CM-Path) initiative and the British In Vitro Diagnostics Association (BIVDA) have set out a roadmap to help academia, industry, and clinicians develop new software tools to the point of approved clinical use. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Appraising the relevance of DNA copy number loss and gain in prostate cancer using whole genome DNA sequence data.

A variety of models have been proposed to explain regions of recurrent somatic copy number alteration (SCNA) in human cancer. Our study employs Whole Genome DNA Sequence (WGS) data from tumor samples (n = 103) to comprehensively assess the role of the Knudson two hit genetic model in SCNA generation in prostate cancer. 64 recurrent regions of loss and gain were detected, of which 28 were novel, including regions of loss with more than 15% frequency at Chr4p15.2-p15.1 (15.53%), Chr6q27 (16.50%) and Chr18q12.3 (17.48%). Comprehensive mutation screens of genes, lincRNA encoding sequences, control regions and conserved domains within SCNAs demonstrated that a two-hit genetic model was supported in only a minor proportion of recurrent SCNA losses examined (15/40). We found that recurrent breakpoints and regions of inversion often occur within Knudson model SCNAs, leading to the identification of ZNF292 as a target gene for the deletion at 6q14.3-q15 and NKX3.1 as a two-hit target at 8p21.3-p21.2. The importance of alterations of lincRNA sequences was illustrated by the identification of a novel mutational hotspot at the KCCAT42, FENDRR, CAT1886 and STCAT2 loci at the 16q23.1-q24.3 loss. Our data confirm that the burden of SCNAs is predictive of biochemical recurrence, define nine individual regions that are associated with relapse, and highlight the possible importance of ion channel and G-protein coupled-receptor (GPCR) pathways in cancer development. We concluded that a two-hit genetic model accounts for about one third of SCNA indicating that mechanisms, such haploinsufficiency and epigenetic inactivation, account for the remaining SCNA losses.

Increased EZH2 expression in prostate cancer is associated with metastatic recurrence following external beam radiotherapy.

BACKGROUND: Enhancer of zeste 2 (EZH2) promotes prostate cancer progression. We hypothesized that increased EZH2 expression is associated with postradiotherapy metastatic disease recurrence, and may promote radioresistance. METHODS: EZH2 expression was investigated using immunohistochemistry in diagnostic prostate biopsies of 113 prostate cancer patients treated with radiotherapy with curative intent. Associations between EZH2 expression in malignant and benign tissue in prostate biopsy cores and outcomes were investigated using univariate and multivariate Cox regression analyses. LNCaP and PC3 cell radiosensitivity was investigated using colony formation and γH2AX assays following UNC1999 chemical probe-mediated EZH2 inhibition. RESULTS: While there was no significant association between EZH2 expression and biochemical recurrence following radiotherapy, univariate analysis revealed that prostate cancer cytoplasmic and total EZH2 expression were significantly associated with metastasis development postradiotherapy (P = 0.034 and P = 0.003, respectively). On multivariate analysis, the prostate cancer total EZH2 expression score remained statistically significant (P = 0.003), while cytoplasmic EZH2 expression did not reach statistical significance (P = 0.053). No association was observed between normal adjacent prostate EZH2 expression and biochemical recurrence or metastasis. LNCaP and PC3 cell treatment with UNC1999 reduced histone H3 lysine 27 tri-methylation levels. Irradiation of LNCaP or PC3 cells with a single 2 Gy fraction with UNC1999-mediated EZH2 inhibition resulted in a statistically significant, though modest, reduction in cell colony number for both cell lines. Increased γH2AX foci were observed 24 hours after ionizing irradiation in LNCaP cells, but not in PC3, following UNC1999-mediated EZH2 inhibition vs controls. CONCLUSIONS: Taken together, these results reveal that high pretreatment EZH2 expression in prostate cancer in diagnostic biopsies is associated with an increased risk of postradiotherapy metastatic disease recurrence, but EZH2 function may only at most play a modest role in promoting prostate cancer cell radioresistance.