ssVERDICT: Self-supervised VERDICT-MRI for enhanced prostate tumor characterization.

PURPOSE: Demonstrating and assessing self-supervised machine-learning fitting of the VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumors) model for prostate cancer. METHODS: We derive a self-supervised neural network for fitting VERDICT (ssVERDICT) that estimates parameter maps without training data. We compare the performance of ssVERDICT to two established baseline methods for fitting diffusion MRI models: conventional nonlinear least squares and supervised deep learning. We do this quantitatively on simulated data by comparing the Pearson's correlation coefficient, mean-squared error, bias, and variance with respect to the simulated ground truth. We also calculate in vivo parameter maps on a cohort of 20 prostate cancer patients and compare the methods' performance in discriminating benign from cancerous tissue via Wilcoxon's signed-rank test. RESULTS: In simulations, ssVERDICT outperforms the baseline methods (nonlinear least squares and supervised deep learning) in estimating all the parameters from the VERDICT prostate model in terms of Pearson's correlation coefficient, bias, and mean-squared error. In vivo, ssVERDICT shows stronger lesion conspicuity across all parameter maps, and improves discrimination between benign and cancerous tissue over the baseline methods. CONCLUSION: ssVERDICT significantly outperforms state-of-the-art methods for VERDICT model fitting and shows, for the first time, fitting of a detailed multicompartment biophysical diffusion MRI model with machine learning without the requirement of explicit training labels.

ST6GAL1-mediated aberrant sialylation promotes prostate cancer progression.

Aberrant glycosylation is a universal feature of cancer cells, and cancer-associated glycans have been detected in virtually every cancer type. A common change in tumour cell glycosylation is an increase in α2,6 sialylation of N-glycans, a modification driven by the sialyltransferase ST6GAL1. ST6GAL1 is overexpressed in numerous cancer types, and sialylated glycans are fundamental for tumour growth, metastasis, immune evasion, and drug resistance, but the role of ST6GAL1 in prostate cancer is poorly understood. Here, we analyse matched cancer and normal tissue samples from 200 patients and verify that ST6GAL1 is upregulated in prostate cancer tissue. Using MALDI imaging mass spectrometry (MALDI-IMS), we identify larger branched α2,6 sialylated N-glycans that show specificity to prostate tumour tissue. We also monitored ST6GAL1 in plasma samples from >400 patients and reveal ST6GAL1 levels are significantly increased in the blood of men with prostate cancer. Using both in vitro and in vivo studies, we demonstrate that ST6GAL1 promotes prostate tumour growth and invasion. Our findings show ST6GAL1 introduces α2,6 sialylated N-glycans on prostate cancer cells and raise the possibility that prostate cancer cells can secrete active ST6GAL1 enzyme capable of remodelling glycans on the surface of other cells. Furthermore, we find α2,6 sialylated N-glycans expressed by prostate cancer cells can be targeted using the sialyltransferase inhibitor P-3FAX -Neu5Ac. Our study identifies an important role for ST6GAL1 and α2,6 sialylated N-glycans in prostate cancer progression and highlights the opportunity to inhibit abnormal sialylation for the development of new prostate cancer therapeutics. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Accurate diagnosis of prostate cancer by combining Proclarix with magnetic resonance imaging.

OBJECTIVES: To assess of the clinical performance of Proclarix® (a novel Conformité Européenne [CE]-marked biomarker test aiding in the identification of clinically significant prostate cancer [csPCa]) alone or in combination with multiparametric magnetic resonance imaging (mpMRI) to predict csPCa (International Society of Urological Pathology Grade Group ≥2). PATIENTS AND METHODS: The study included blood samples from 721 men undergoing mpMRI followed by biopsy at University College London, London, and Vall d'Hebron University Hospital, Barcelona. Samples were tested blindly. The Proclarix-MRI model combining prostate volume, Proclarix and mpMRI results was trained using the UCL cohort (n = 159) and validated in the Vall d'Hebron cohort (n = 562). Its diagnostic performance was established in correlation to biopsy outcome and compared to available clinical parameters and risk calculators. RESULTS: Clinical performance of the Proclarix-MRI model in the validation cohort did not significantly differ from the training cohort and resulted in a sensitivity for csPCa of 90%, 90% negative predictive value and 66% positive predictive value. The Proclarix-MRI score's specificity (68%) was significantly (P < 0.001) better than the MRI-European Randomized study of Screening for Prostate Cancer risk score (51%), Proclarix (27%) or mpMRI (28%) alone. In addition, Proclarix by itself was found to be useful in the MRI Prostate Imaging-Reporting and Data System (PI-RADS) score 3 subgroup by outperforming prostate-specific antigen density in terms of specificity (25% vs 13%, P = 0.004) at 100% sensitivity. CONCLUSION: When combined with mpMRI and prostate volume, Proclarix reliably predicted csPCa and ruled out men with no or indolent cancer. A large reduction of two thirds of unneeded biopsies was achieved. Proclarix can further be used with high confidence to reliably detect csPCa in men with an indeterminate PI-RADS score 3 mpMRI. Despite these encouraging results, further validation is needed.

Avoiding Unnecessary Biopsy after Multiparametric Prostate MRI with VERDICT Analysis: The INNOVATE Study.

Background In men suspected of having prostate cancer (PCa), up to 50% of men with positive multiparametric MRI (mpMRI) findings (Prostate Imaging Reporting and Data System [PI-RADS] or Likert score of 3 or higher) have no clinically significant (Gleason score ≤3+3, benign) biopsy findings. Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumor (VERDICT) MRI analysis could improve the stratification of positive mpMRI findings. Purpose To evaluate VERDICT MRI, mpMRI-derived apparent diffusion coefficient (ADC), and prostate-specific antigen density (PSAD) as determinants of clinically significant PCa (csPCa). Materials and Methods Between April 2016 and December 2019, men suspected of having PCa were prospectively recruited from two centers and underwent VERDICT MRI and mpMRI at one center before undergoing targeted biopsy. Biopsied lesion ADC, lesion-derived fractional intracellular volume (FIC), and PSAD were compared between men with csPCa and those without csPCa, using nonparametric tests subdivided by Likert scores. Area under the receiver operating characteristic curve (AUC) was calculated to test diagnostic performance. Results Among 303 biopsy-naive men, 165 study participants (mean age, 65 years ± 7 [SD]) underwent targeted biopsy; of these, 73 had csPCa. Median lesion FIC was higher in men with csPCa (FIC, 0.53) than in those without csPCa (FIC, 0.18) for Likert 3 (P = .002) and Likert 4 (0.60 vs 0.28, P < .001) lesions. Median lesion ADC was lower for Likert 4 lesions with csPCa (0.86 × 10-3 mm2/sec) compared with lesions without csPCa (1.12 × 10-3 mm2/sec, P = .03), but there was no evidence of a difference for Likert 3 lesions (0.97 × 10-3 mm2/sec vs 1.20 × 10-3 mm2/sec, P = .09). PSAD also showed no difference for Likert 3 (0.17 ng/mL2 vs 0.12 ng/mL2, P = .07) or Likert 4 (0.14 ng/mL2 vs 0.12 ng/mL2, P = .47) lesions. The diagnostic performance of FIC (AUC, 0.96; 95% CI: 0.93, 1.00) was higher (P = .02) than that of ADC (AUC, 0.85; 95% CI: 0.79, 0.91) and PSAD (AUC, 0.74; 95% CI: 0.66, 0.82) for the presence of csPCa in biopsied lesions. Conclusion Lesion fractional intracellular volume enabled better classification of clinically significant prostate cancer than did apparent diffusion coefficient and prostate-specific antigen density. Clinical trial registration no. NCT02689271 © RSNA, 2022 Online supplemental material is available for this article.

PEOPLE: PatiEnt prOstate samPLes for rEsearch, a tissue collection pathway utilizing magnetic resonance imaging data to target tumor and benign tissue in fresh radical prostatectomy specimens.

BACKGROUND: Over 1 million men are diagnosed with prostate cancer each year worldwide, with a wide range of research programs requiring access to patient tissue samples for development of improved diagnoses and treatments. A random sampling of prostate tissue is sufficient for certain research studies; however, there is growing research need to target areas of the aggressive tumor as fresh tissue. Here we set out to develop a new pathway "PEOPLE: PatiEnt prOstate samPLes for rEsearch" to collect high-quality fresh tissue for research use, using magnetic resonance imaging (MRI) to target areas of tumor and benign tissue. METHODS: Prostate tissue was sampled following robotic radical prostatectomy, using MRI data to target areas of benign and tumor tissue. Initially, 25 cases were sampled using MRI information from clinical notes. A further 59 cases were sampled using an optimized method that included specific MRI measurements of tumor location along with additional exclusion criteria. All cases were reviewed in batches with detailed clinical and histopathological data recorded. For one subset of samples, DNA was extracted and underwent quality control. Ex vivo culture was carried out using the gelatin sponge method for an additional subset. RESULTS: Tumor was successfully fully or partially targeted in 64% of the initial cohort and 70% of the optimized cohort. DNA of high quality and concentration was isolated from 39 tumor samples, and ex vivo culture was successfully carried out in three cases with tissue morphology, proliferation, and apoptosis remaining comparable before and after 72 hours culture. CONCLUSION: Here we report initial data from the PEOPLE pathway; using a method for targeting areas of tumor within prostate samples using MRI. This method operates alongside the standard clinical pathway and minimizes additional input from surgical, radiological, and pathological teams, while preserving surgical margins and diagnostic tissue.

VERDICT MRI for Prostate Cancer: Intracellular Volume Fraction versus Apparent Diffusion Coefficient.

Background Biologic specificity of diffusion MRI in relation to prostate cancer aggressiveness may improve by examining separate components of the diffusion MRI signal. The Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumors (VERDICT) model estimates three distinct signal components and associates them to (a) intracellular water, (b) water in the extracellular extravascular space, and (c) water in the microvasculature. Purpose To evaluate the repeatability, image quality, and diagnostic utility of intracellular volume fraction (FIC) maps obtained with VERDICT prostate MRI and to compare those maps with apparent diffusion coefficient (ADC) maps for Gleason grade differentiation. Materials and Methods Seventy men (median age, 62.2 years; range, 49.5-82.0 years) suspected of having prostate cancer or undergoing active surveillance were recruited to a prospective study between April 2016 and October 2017. All men underwent multiparametric prostate and VERDICT MRI. Forty-two of the 70 men (median age, 67.7 years; range, 50.0-82.0 years) underwent two VERDICT MRI acquisitions to assess repeatability of FIC measurements obtained with VERDICT MRI. Repeatability was measured with use of intraclass correlation coefficients (ICCs). The image quality of FIC and ADC maps was independently evaluated by two board-certified radiologists. Forty-two men (median age, 64.8 years; range, 49.5-79.6 years) underwent targeted biopsy, which enabled comparison of FIC and ADC metrics in the differentiation between Gleason grades. Results VERDICT MRI FIC demonstrated ICCs of 0.87-0.95. There was no significant difference between image quality of ADC and FIC maps (score, 3.1 vs 3.3, respectively; P = .90). FIC was higher in lesions with a Gleason grade of at least 3+4 compared with benign and/or Gleason grade 3+3 lesions (mean, 0.49 ± 0.17 vs 0.31 ± 0.12, respectively; P = .002). The difference in ADC between these groups did not reach statistical significance (mean, 1.42 vs 1.16 × 10-3 mm2/sec; P = .26). Conclusion Fractional intracellular volume demonstrates high repeatability and image quality and enables better differentiation of a Gleason 4 component cancer from benign and/or Gleason 3+3 histology than apparent diffusion coefficient. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Sigmund and Rosenkrantz in this issue.

VERDICT MRI validation in fresh and fixed prostate specimens using patient-specific moulds for histological and MR alignment.

The VERDICT framework for modelling diffusion MRI data aims to relate parameters from a biophysical model to histological features used for tumour grading in prostate cancer. Validation of the VERDICT model is necessary for clinical use. This study compared VERDICT parameters obtained ex vivo with histology in five specimens from radical prostatectomy. A patient-specific 3D-printed mould was used to investigate the effects of fixation on VERDICT parameters and to aid registration to histology. A rich diffusion data set was acquired in each ex vivo prostate before and after fixation. At both time points, data were best described by a two-compartment model: the model assumes that an anisotropic tensor compartment represents the extracellular space and a restricted sphere compartment models the intracellular space. The effect of fixation on model parameters associated with tissue microstructure was small. The patient-specific mould minimized tissue deformations and co-localized slices, so that rigid registration of MRI to histology images allowed region-based comparison with histology. The VERDICT estimate of the intracellular volume fraction corresponded to histological indicators of cellular fraction, including high values in tumour regions. The average sphere radius from VERDICT, representing the average cell size, was relatively uniform across samples. The primary diffusion direction from the extracellular compartment of the VERDICT model aligned with collagen fibre patterns in the stroma obtained by structure tensor analysis. This confirmed the biophysical relationship between ex vivo VERDICT parameters and tissue microstructure from histology.

Immunohistochemical biomarker validation in highly selective needle biopsy microarrays derived from mpMRI-characterized prostates.

INTRODUCTION: Diagnosing prostate cancer routinely involves tissue biopsy and increasingly image guided biopsy using multiparametric MRI (mpMRI). Excess tissue after diagnosis can be used for research to improve the diagnostic pathway and the vertical assembly of prostate needle biopsy cores into tissue microarrays (TMAs) allows the parallel immunohistochemical (IHC) validation of cancer biomarkers in routine diagnostic specimens. However, tissue within a biopsy core is often heterogeneous and cancer is not uniformly present, resulting in needle biopsy TMAs that suffer from highly variable cancer detection rates that complicate parallel biomarker validation. MATERIALS AND METHODS: The prostate cores with the highest tumor burden (in terms of Gleason score and/or maximum cancer core length) were obtained from 249 patients in the PICTURE trial who underwent transperineal template prostate mapping (TPM) biopsy at 5 mm intervals preceded by mpMRI. From each core, 2 mm segments containing tumor or benign tissue (as assessed on H&E pathology) were selected, excised and embedded vertically into a new TMA block. TMA sections were then IHC-stained for the routinely used prostate cancer biomarkers PSA, PSMA, AMACR, p63, and MSMB and assessed using the h-score method. H-scores in patient matched malignant and benign tissue were correlated with the Gleason grade of the original core and the MRI Likert score for the sampled prostate area. RESULTS: A total of 2240 TMA cores were stained and IHC h-scores were assigned to 1790. There was a statistically significant difference in h-scores between patient matched malignant and adjacent benign tissue that is independent of Likert score. There was no association between the h-scores and Gleason grade or Likert score within each of the benign or malignant groups. CONCLUSION: The construction of highly selective TMAs from prostate needle biopsy cores is possible. IHC data obtained through this method are highly reliable and can be correlated with imaging. IHC expression patterns for PSA, PSMA, AMACR, p63, and MSMB are distinct in malignant and adjacent benign tissue but did not correlate with mpMRI Likert score.

Cathepsin B-degradable, NIR-responsive nanoparticulate platform for target-specific cancer therapy.

Stimuli-responsive anticancer formulations can promote drug release and activation within the target tumour, facilitate cellular uptake, as well as improve the therapeutic efficacy of drugs and reduce off-target effects. In the present work, indocyanine green (ICG)-containing polyglutamate (PGA) nanoparticles were developed and characterized. Digestion of nanoparticles with cathepsin B, a matrix metalloproteinase overexpressed in the microenvironment of advanced tumours, decreased particle size and increased ICG cellular uptake. Incorporation of ICG in PGA nanoparticles provided the NIR-absorbing agent with time-dependent altered optical properties in the presence of cathepsin B. Having minimal dark toxicity, the formulation exhibited significant cytotoxicity upon NIR exposure. Combined use of the formulation with saporin, a ribosome-inactivating protein, resulted in synergistically enhanced cytotoxicity attributed to the photo-induced release of saporin from endo/lysosomes. The results suggest that this therapeutic approach can offer significant therapeutic benefit in the treatment of superficial malignancies, such as head and neck tumours.

INNOVATE: A prospective cohort study combining serum and urinary biomarkers with novel diffusion-weighted magnetic resonance imaging for the prediction and characterization of prostate cancer.

BACKGROUND: Whilst multi-parametric magnetic resonance imaging (mp-MRI) has been a significant advance in the diagnosis of prostate cancer, scanning all patients with elevated prostate specific antigen (PSA) levels is considered too costly for widespread National Health Service (NHS) use, as the predictive value of PSA levels for significant disease is poor. Despite the fact that novel blood and urine tests are available which may predict aggressive disease better than PSA, they are not routinely employed due to a lack of clinical validity studies. Furthermore approximately 40 % of mp-MRI studies are reported as indeterminate, which can lead to repeat examinations or unnecessary biopsy with associated patient anxiety, discomfort, risk and additional costs. METHODS/DESIGN: We aim to clinically validate a panel of minimally invasive promising blood and urine biomarkers, to better select patients that will benefit from a multiparametric prostate MRI. We will then test whether the performance of the mp-MRI can be improved by the addition of an advanced diffusion-weighted MRI technique, which uses a biophysical model to characterise tissue microstructure called VERDICT; Vascular and Extracellular Restricted Diffusion for Cytometry in Tumours. INNOVATE is a prospective single centre cohort study in 365 patients. mp-MRI will act as the reference standard for the biomarker panel. A clinical outcome based reference standard based on biopsy, mp-MRI and follow-up will be used for VERDICT MRI. DISCUSSION: We expect the combined effect of biomarkers and VERDICT MRI will improve care by better detecting aggressive prostate cancer early and make mp-MRI before biopsy economically viable for universal NHS adoption. TRIAL REGISTRATION: INNOVATE is registered on ClinicalTrials.gov, with reference NCT02689271 .

Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRI.

This work presents a biophysical model of diffusion and relaxation MRI for prostate called relaxation vascular, extracellular and restricted diffusion for cytometry in tumours (rVERDICT). The model includes compartment-specific relaxation effects providing T1/T2 estimates and microstructural parameters unbiased by relaxation properties of the tissue. 44 men with suspected prostate cancer (PCa) underwent multiparametric MRI (mp-MRI) and VERDICT-MRI followed by targeted biopsy. We estimate joint diffusion and relaxation prostate tissue parameters with rVERDICT using deep neural networks for fast fitting. We tested the feasibility of rVERDICT estimates for Gleason grade discrimination and compared with classic VERDICT and the apparent diffusion coefficient (ADC) from mp-MRI. The rVERDICT intracellular volume fraction fic discriminated between Gleason 3 + 3 and 3 + 4 (p = 0.003) and Gleason 3 + 4 and ≥ 4 + 3 (p = 0.040), outperforming classic VERDICT and the ADC from mp-MRI. To evaluate the relaxation estimates we compare against independent multi-TE acquisitions, showing that the rVERDICT T2 values are not significantly different from those estimated with the independent multi-TE acquisition (p > 0.05). Also, rVERDICT parameters exhibited high repeatability when rescanning five patients (R2 = 0.79-0.98; CV = 1-7%; ICC = 92-98%). The rVERDICT model allows for accurate, fast and repeatable estimation of diffusion and relaxation properties of PCa sensitive enough to discriminate Gleason grades 3 + 3, 3 + 4 and ≥ 4 + 3.

Prostate MR image quality of apparent diffusion coefficient maps versus fractional intracellular volume maps from VERDICT MRI using the PI-QUAL score and a dedicated Likert scale for artefacts.

PURPOSE: This study aimed to assess the image quality of apparent diffusion coefficient (ADC) maps derived from conventional diffusion-weighted MRI and fractional intracellular volume maps (FIC) from VERDICT MRI (Vascular, Extracellular, Restricted Diffusion for Cytometry in Tumours) in patients from the INNOVATE trial. The inter-reader agreement was also assessed. METHODS: Two readers analysed both ADC and FIC maps from 57 patients enrolled in the INNOVATE prospective trial. Image quality was assessed using the Prostate Imaging Quality (PI-QUAL) score and a subjective image quality Likert score (Likert-IQ). The image quality of FIC and ADC were compared using a Wilcoxon Signed Ranks test. The inter-reader agreement was assessed with Cohen's kappa. RESULTS: There was no statistically significant difference between the PI-QUAL score for FIC datasets compared to ADC datasets for either reader (p = 0.240 and p = 0.614). Using the Likert-IQ score, FIC image quality was higher compared to ADC (p = 0.021) as assessed by reader-1 but not for reader-2 (p = 0.663). The inter-reader agreement was 'fair' for PI-QUAL scoring of datasets with FIC maps at 0.27 (95% confidence interval; 0.08-0.46) and ADC datasets at 0.39 (95% confidence interval 0.22-0.57). For Likert scoring, the inter-reader agreement was also 'fair' for FIC maps at 0.38 (95% confidence interval; 0.10-0.65) and substantial for ADC maps at 0.62 (95% confidence interval; 0.39-0.86). CONCLUSION: Image quality was comparable for FIC and ADC. The inter-reader agreement was similar when using PIQUAL for both FIC and ADC datasets but higher for ADC maps compared to FIC maps using the image quality Likert score.

Upregulation of GALNT7 in prostate cancer modifies O-glycosylation and promotes tumour growth.

Prostate cancer is the most common cancer in men and it is estimated that over 350,000 men worldwide die of prostate cancer every year. There remains an unmet clinical need to improve how clinically significant prostate cancer is diagnosed and develop new treatments for advanced disease. Aberrant glycosylation is a hallmark of cancer implicated in tumour growth, metastasis, and immune evasion. One of the key drivers of aberrant glycosylation is the dysregulated expression of glycosylation enzymes within the cancer cell. Here, we demonstrate using multiple independent clinical cohorts that the glycosyltransferase enzyme GALNT7 is upregulated in prostate cancer tissue. We show GALNT7 can identify men with prostate cancer, using urine and blood samples, with improved diagnostic accuracy than serum PSA alone. We also show that GALNT7 levels remain high in progression to castrate-resistant disease, and using in vitro and in vivo models, reveal that GALNT7 promotes prostate tumour growth. Mechanistically, GALNT7 can modify O-glycosylation in prostate cancer cells and correlates with cell cycle and immune signalling pathways. Our study provides a new biomarker to aid the diagnosis of clinically significant disease and cements GALNT7-mediated O-glycosylation as an important driver of prostate cancer progression.

Risk Assessment for Activity Regulated Under the Human Tissue Act: A Single Institution Experience.

Risk assessment represents one of the requirements for all activities involving human tissues within the premises. Although a variety of procedures are available to prepare risk assessments in general, there are no published examples of risks associated with the use of human samples in research. To cover this gap and to give an overview of the evaluation performed in our institution, we summarized the potential risks for the use of human samples in research identified in the projects under the remit of the UCL/UCLH Biobank. The procedures of acquisition, transportation, storage, use, and disposal of human samples, and security of the premises were analyzed. From our experience, there are governance-related risks associated with the process of consenting the patients, with the donor confidentiality, with mislabeling of samples and with the ethical approval associated with the project, and they generally do not compromise the integrity of the samples. On the other hand, samples' integrity is more at risk during collection, storage, transport, and use of the sample. Adequate training and having appropriate standard procedures in place and available for all staff seem to be the most effective control measures to prevent any issue. In addition, appropriate equipment maintenance, contingency plans, and strict regulation and monitoring of the facility security should always be in place. In summary, an appropriate evaluation of the risks associated with the use of human samples in research is one of the requirements for the use of human samples in research and it is fundamental for the protection of staff, students, the institution itself, and the patients. Supporting biobanking, implementing a culture of biosafety in the life sciences, and raising awareness in the scientific and regulatory communities are key ways to anticipate future problems associated with biological and governance risks.

Differentiating False Positive Lesions from Clinically Significant Cancer and Normal Prostate Tissue Using VERDICT MRI and Other Diffusion Models.

False positives on multiparametric MRIs (mp-MRIs) result in many unnecessary invasive biopsies in men with clinically insignificant diseases. This study investigated whether quantitative diffusion MRI could differentiate between false positives, true positives and normal tissue non-invasively. Thirty-eight patients underwent mp-MRI and Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors (VERDICT) MRI, followed by transperineal biopsy. The patients were categorized into two groups following biopsy: (1) significant cancer­true positive, 19 patients; (2) atrophy/inflammation/high-grade prostatic intraepithelial neoplasia (PIN)­false positive, 19 patients. The clinical apparent diffusion coefficient (ADC) values were obtained, and the intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) and VERDICT models were fitted via deep learning. Significant differences (p < 0.05) between true positive and false positive lesions were found in ADC, IVIM perfusion fraction (f) and diffusivity (D), DKI diffusivity (DK) (p < 0.0001) and kurtosis (K) and VERDICT intracellular volume fraction (fIC), extracellular−extravascular volume fraction (fEES) and diffusivity (dEES) values. Significant differences between false positives and normal tissue were found for the VERDICT fIC (p = 0.004) and IVIM D. These results demonstrate that model-based diffusion MRI could reduce unnecessary biopsies occurring due to false positive prostate lesions and shows promising sensitivity to benign diseases.

The oncological relevance of fragile sites in cancer.

Recent developments in sequencing the cancer genome have provided the first in-depth mapping of structural variants (SV) across 38 tumour types. Sixteen signatures of structural variants have been proposed which broadly characterise the variation seen across cancer types. One signature shows increased duplications and deletions at fragile sites, with little association with the typical DNA repair defects. We discuss how, for many of these fragile sites, the clinical impacts are yet to be explored. One example is NAALADL2, one of the most frequently altered fragile sites in the cancer genome. The copy-number variations (CNVs) which occur at fragile sites, such as NAALADL2, may span many genes without typical DNA repair defects and could have a large impact on cell signalling.

Evaluation of PSA and PSA Density in a Multiparametric Magnetic Resonance Imaging-Directed Diagnostic Pathway for Suspected Prostate Cancer: The INNOVATE Trial.

Objectives: To assess the clinical outcomes of mpMRI before biopsy and evaluate the space remaining for novel biomarkers. Methods: The INNOVATE study was set up to evaluate the validity of novel fluidic biomarkers in men with suspected prostate cancer who undergo pre-biopsy mpMRI. We report the characteristics of this clinical cohort, the distribution of clinical serum biomarkers, PSA and PSA density (PSAD), and compare the mpMRI Likert scoring system to the Prostate Imaging-Reporting and Data System v2.1 (PI-RADS) in men undergoing biopsy. Results: 340 men underwent mpMRI to evaluate suspected prostate cancer. 193/340 (57%) men had subsequent MRI-targeted prostate biopsy. Clinically significant prostate cancer (csigPCa), i.e., overall Gleason ≥ 3 + 4 of any length OR maximum cancer core length (MCCL) ≥4 mm of any grade including any 3 + 3, was found in 96/195 (49%) of biopsied patients. Median PSA (and PSAD) was 4.7 (0.20), 8.0 (0.17), and 9.7 (0.31) ng/mL (ng/mL/mL) in mpMRI scored Likert 3,4,5 respectively for men with csigPCa on biopsy. The space for novel biomarkers was shown to be within the group of men with mpMRI scored Likert3 (178/340) and 4 (70/350), in whom an additional of 40% (70/178) men with mpMRI-scored Likert3, and 37% (26/70) Likert4 could have been spared biopsy. PSAD is already considered clinically in this cohort to risk stratify patients for biopsy, despite this 67% (55/82) of men with mpMRI-scored Likert3, and 55% (36/65) Likert4, who underwent prostate biopsy had a PSAD below a clinical threshold of 0.15 (or 0.12 for men aged <50 years). Different thresholds of PSA and PSAD were assessed in mpMRI-scored Likert4 to predict csigPCa on biopsy, to achieve false negative levels of ≤5% the proportion of patients whom who test as above the threshold were unsuitably high at 86 and 92% of patients for PSAD and PSA respectively. When PSA was re tested in a sub cohort of men repeated PSAD showed its poor reproducibility with 43% (41/95) of patients being reclassified. After PI-RADS rescoring of the biopsied lesions, 66% (54/82) of the Likert3 lesions received a different PI-RADS score. Conclusions: The addition of simple biochemical and radiological markers (Likert and PSAD) facilitate the streamlining of the mpMRI-diagnostic pathway for suspected prostate cancer but there remains scope for improvement, in the introduction of novel biomarkers for risk assessment in Likert3 and 4 patients, future application of novel biomarkers tested in a Likert cohort would also require re-optimization around Likert3/PI-RADS2, as well as reproducibility testing.

Author Correction: Genetic alterations in the 3q26.31-32 locus confer an aggressive prostate cancer phenotype.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genetic alterations in the 3q26.31-32 locus confer an aggressive prostate cancer phenotype.

Large-scale genetic aberrations that underpin prostate cancer development and progression, such as copy-number alterations (CNAs), have been described but the consequences of specific changes in many identified loci is limited. Germline SNPs in the 3q26.31 locus are associated with aggressive prostate cancer, and is the location of NAALADL2, a gene overexpressed in aggressive disease. The closest gene to NAALADL2 is TBL1XR1, which is implicated in tumour development and progression. Using publicly-available cancer genomic data we report that NAALADL2 and TBL1XR1 gains/amplifications are more prevalent in aggressive sub-types of prostate cancer when compared to primary cohorts. In primary disease, gains/amplifications occurred in 15.99% (95% CI: 13.02-18.95) and 14.96% (95% CI: 12.08-17.84%) for NAALADL2 and TBL1XR1 respectively, increasing in frequency in higher Gleason grade and stage tumours. Gains/amplifications result in transcriptional changes and the development of a pro-proliferative and aggressive phenotype. These results support a pivotal role for copy-number gains in this genetic region.

An optimised saliva collection method to produce high-yield, high-quality RNA for translational research.

Saliva represents an ideal matrix for diagnostic biomarker development as it is readily available and requires no invasive collection procedures. However, salivary RNA is labile and rapidly degrades. Previous attempts to isolate RNA from saliva have yielded poor quality and low concentrations. Here we compare collection and processing methods and propose an approach for future studies. The effects of RNA stabilisers, storage temperatures, length of storage and fasting windows were investigated on pooled saliva samples from healthy volunteers. Isolated RNA was assessed for concentration and quality. Bacterial growth was investigated through RT-PCR using bacterial and human primers. Optimal conditions were implemented and quality controlled in a clinical setting. The addition of RNAlater increased mean RNA yield from 4912 ng/µl to 15,473 ng and RNA Integrity Number (RIN) from 4.5 to 7.0. No significant changes to RNA yield were observed for storage at room temperature beyond 1 day or at -80 °C. Bacterial growth did not occur in samples stored at ambient temperature for up to a week. There was a trend towards higher RNA concentration when saliva was collected after overnight fasting but no effect on RIN. In the clinic, RNA yields of 6307 ng and RINs of 3.9 were achieved, improving on previous reports. The method we describe here is a robust, clinically feasible saliva collection method using preservative that gives high concentrations and improved RINs compared to saliva collected without preservative.