HIV-PULSE: a long-read sequencing assay for high-throughput near full-length HIV-1 proviral genome characterization.

A deep understanding of the composition of the HIV-1 reservoir is necessary for the development of targeted therapies and the evaluation of curative efforts. However, current near full-length (NFL) HIV-1 proviral genome sequencing assays are based on labor-intensive and costly principles of repeated PCRs at limiting dilution, restricting their scalability. To address this, we developed a high-throughput, long-read sequencing assay called HIV-PULSE (HIV Proviral UMI-mediated Long-read Sequencing). This assay uses unique molecular identifiers (UMIs) to tag individual HIV-1 genomes, allowing for the omission of the limiting dilution step and enabling long-range PCR amplification of many NFL genomes in a single PCR reaction, while simultaneously overcoming poor single-read accuracy. We optimized the assay using HIV-infected cell lines and then applied it to blood samples from 18 individuals living with HIV on antiretroviral therapy, yielding a total of 1308 distinct HIV-1 genomes. Benchmarking against the widely applied Full-Length Individual Proviral Sequencing assay revealed similar sensitivity (11 vs 18%) and overall good concordance, although at a significantly higher throughput. In conclusion, HIV-PULSE is a cost-efficient and scalable assay that allows for the characterization of the HIV-1 proviral landscape, making it an attractive method to study the HIV-1 reservoir composition and dynamics.

The role of Helicobacter suis, Fusobacterium gastrosuis, and the pars oesophageal microbiota in gastric ulceration in slaughter pigs receiving meal or pelleted feed.

This study investigated the role of causative infectious agents in ulceration of the non-glandular part of the porcine stomach (pars oesophagea). In total, 150 stomachs from slaughter pigs were included, 75 from pigs that received a meal feed, 75 from pigs that received an equivalent pelleted feed with a smaller particle size. The pars oesophagea was macroscopically examined after slaughter. (q)PCR assays for H. suis, F. gastrosuis and H. pylori-like organisms were performed, as well as 16S rRNA sequencing for pars oesophagea microbiome analyses. All 150 pig stomachs showed lesions. F. gastrosuis was detected in 115 cases (77%) and H. suis in 117 cases (78%), with 92 cases (61%) of co-infection; H. pylori-like organisms were detected in one case. Higher infectious loads of H. suis increased the odds of severe gastric lesions (OR = 1.14, p = 0.038), while the presence of H. suis infection in the pyloric gland zone increased the probability of pars oesophageal erosions [16.4% (95% CI 0.6-32.2%)]. The causal effect of H. suis was mediated by decreased pars oesophageal microbiome diversity [-1.9% (95% CI - 5.0-1.2%)], increased abundances of Veillonella and Campylobacter spp., and decreased abundances of Lactobacillus, Escherichia-Shigella, and Enterobacteriaceae spp. Higher infectious loads of F. gastrosuis in the pars oesophagea decreased the odds of severe gastric lesions (OR = 0.8, p = 0.0014). Feed pelleting had no significant impact on the prevalence of severe gastric lesions (OR = 1.72, p = 0.28). H. suis infections are a risk factor for ulceration of the porcine pars oesophagea, probably mediated through alterations in pars oesophageal microbiome diversity and composition.

Cost-effectiveness of an urinary biomarker panel in combination with MRI for prostate cancer diagnosis.

PURPOSE: The health impact and cost-effectiveness of the biomarker test SelectMDx were evaluated when used in combination with MRI, in two US populations: biopsy naïve men and men with a previous negative biopsy. METHODS: Using a decision model, the current MRI strategy was compared with two SelectMDx strategies: SelectMDx used before MRI to select men for MRI and SelectMDx used after a negative MRI to select men for biopsy. Parameters were informed by the literature most relevant for both populations. Differences in quality-adjusted life years (QALYs) and costs between the current strategy and the SelectMDx strategies were calculated using two different assumptions regarding PCa-specific mortality (SPCG-4 and PIVOT). RESULTS: In biopsy naïve men, the use of SelectMDx before MRI results in a gain of 0.004 QALY per patient under the SPCG-4 scenario, and a gain of 0.030 QALY under the PIVOT scenario. The cost savings are $1650 per patient. When used after MRI, SelectMDx results in a QALY gain per patient of 0.004 (SPCG-4), and 0.006 (PIVOT) with $262 in cost savings. In the previous negative population, SelectMDx before MRI results in a QALY gain of 0.006 (SPCG-4) and 0.022 (PIVOT), with $1281 in cost savings per patient. SelectMDx after MRI results in a QALY gain of 0.003 (SPCG-4) and 0.004 (PIVOT) with $193 in cost savings. CONCLUSION: Application of SelectMDx results in better health outcomes and cost savings. The value of SelectMDx was highest when used before MRI to select patients for MRI and subsequent biopsy.

Spectral Prediction Features as a Solution for the Search Space Size Problem in Proteogenomics.

Proteogenomics approaches often struggle with the distinction between true and false peptide-to-spectrum matches as the database size enlarges. However, features extracted from tandem mass spectrometry intensity predictors can enhance the peptide identification rate and can provide extra confidence for peptide-to-spectrum matching in a proteogenomics context. To that end, features from the spectral intensity pattern predictors MS2PIP and Prosit were combined with the canonical scores from MaxQuant in the Percolator postprocessing tool for protein sequence databases constructed out of ribosome profiling and nanopore RNA-Seq analyses. The presented results provide evidence that this approach enhances both the identification rate as well as the validation stringency in a proteogenomic setting.

Single cell epigenetic visualization assay.

Characterization of the epigenetic status of individual cells remains a challenge. Current sequencing approaches have limited coverage, and it is difficult to assign an epigenetic status to the transcription state of individual gene alleles in the same cell. To address these limitations, a targeted microscopy-based epigenetic visualization assay (EVA) was developed for detection and quantification of epigenetic marks at genes of interest in single cells. The assay is based on an in situ biochemical reaction between an antibody-conjugated alkaline phosphatase bound to the epigenetic mark of interest, and a 5'-phosphorylated fluorophore-labeled DNA oligo tethered to a target gene by gene-specific oligonucleotides. When the epigenetic mark is present at the gene, phosphate group removal by the phosphatase protects the oligo from λ-exonuclease activity providing a quantitative fluorescent readout. We applied EVA to measure 5-methylcytosine (5mC) and H3K9Ac levels at different genes and the HIV-1 provirus in human cell lines. To link epigenetic marks to gene transcription, EVA was combined with RNA-FISH. Higher 5mC levels at the silenced compared to transcribed XIST gene alleles in female somatic cells validated this approach and demonstrated that EVA can be used to relate epigenetic marks to the transcription status of individual gene alleles.

Evaluation of the New American Urological Association Guidelines Risk Classification for Hematuria.

PURPOSE: Microhematuria is a prevalent condition and the American Urological Association has developed a new risk-stratified approach for the evaluation of patients with microhematuria. Our objective was to provide the first evaluation of this important guideline. MATERIALS AND METHODS: This multinational cohort study combines contemporary patients from 5 clinical trials and 2 prospective registries who underwent urological evaluation for hematuria. Patients were stratified into American Urological Association risk strata (low, intermediate or high risk) based on sex, age, degree of hematuria, and smoking history. The primary end point was the incidence of bladder cancer within each risk stratum. RESULTS: A total of 15,779 patients were included in the analysis. Overall, 727 patients (4.6%) were classified as low risk, 1,863 patients (11.8%) were classified as intermediate risk, and 13,189 patients (83.6%) were classified as high risk. The predominance of high risk patients was consistent across all cohorts. A total of 857 bladder cancers were diagnosed with a bladder cancer incidence of 5.4%. Bladder cancer was more prevalent in men, smokers, older patients and patients with gross hematuria. The cancer incidence for low, intermediate and high risk groups was 0.4% (3 patients), 1.0% (18 patients) and 6.3% (836 patients), respectively. CONCLUSIONS: The new risk stratification system separates hematuria patients into clinically meaningful categories with differing likelihoods of bladder cancer that would justify evaluating the low, intermediate and high risk groups with incremental intensity. Furthermore, it provides the relative incidence of bladder cancer in each risk group which should facilitate patient counseling regarding the risks and benefits of evaluation for bladder cancer.

PROTEOFORMER 2.0: Further Developments in the Ribosome Profiling-assisted Proteogenomic Hunt for New Proteoforms.

PROTEOFORMER is a pipeline that enables the automated processing of data derived from ribosome profiling (RIBO-seq, i.e. the sequencing of ribosome-protected mRNA fragments). As such, genome-wide ribosome occupancies lead to the delineation of data-specific translation product candidates and these can improve the mass spectrometry-based identification. Since its first publication, different upgrades, new features and extensions have been added to the PROTEOFORMER pipeline. Some of the most important upgrades include P-site offset calculation during mapping, comprehensive data pre-exploration, the introduction of two alternative proteoform calling strategies and extended pipeline output features. These novelties are illustrated by analyzing ribosome profiling data of human HCT116 and Jurkat data. The different proteoform calling strategies are used alongside one another and in the end combined together with reference sequences from UniProt. Matching mass spectrometry data are searched against this extended search space with MaxQuant. Overall, besides annotated proteoforms, this pipeline leads to the identification and validation of different categories of new proteoforms, including translation products of up- and downstream open reading frames, 5' and 3' extended and truncated proteoforms, single amino acid variants, splice variants and translation products of so-called noncoding regions. Further, proof-of-concept is reported for the improvement of spectrum matching by including Prosit, a deep neural network strategy that adds extra fragmentation spectrum intensity features to the analysis. In the light of ribosome profiling-driven proteogenomics, it is shown that this allows validating the spectrum matches of newly identified proteoforms with elevated stringency. These updates and novel conclusions provide new insights and lessons for the ribosome profiling-based proteogenomic research field. More practical information on the pipeline, raw code, the user manual (README) and explanations on the different modes of availability can be found at the GitHub repository of PROTEOFORMER: https://github.com/Biobix/proteoformer.

MEXPRESS update 2019.

The recent growth in the number of publicly available cancer omics databases has been accompanied by the development of various tools that allow researchers to visually explore these data. In 2015, we built MEXPRESS, an online tool for the integration and visualization of gene expression, DNA methylation and clinical data from The Cancer Genome Atlas (TCGA), a large collection of publicly available multi-omics cancer data. MEXPRESS addresses the need for an easy-to-use, interactive application that allows researchers to identify dysregulated genes and their clinical relevance in cancer. Furthermore, while other tools typically do not support integrated visualization of expression and DNA methylation data in combination with the precise genomic location of the methylation, MEXPRESS is unique in how it depicts these diverse data types together. Motivated by the large number of users MEXPRESS has managed to attract over the past 3 years and the recent migration of all TCGA data to a new data portal, we developed a new version of MEXPRESS (https://mexpress.be). It contains the latest TCGA data, additional types of omics and clinical data and extra functionality, allowing users to explore mechanisms of gene dysregulation beyond expression and DNA methylation.

Validation of a 2-gene mRNA urine test for the detection of ≥GG2 prostate cancer in an opportunistic screening population.

BACKGROUND: A 2-gene urine-based molecular test that targets messenger RNAs known to be overexpressed in aggressive prostate cancer (PCa) has been described as a helpful method for detecting clinically significant prostate cancer (grade group [GG] ≥2). We performed an external validation of this test in men undergoing initial prostate biopsy (Bx) within a Spanish opportunistic screening scenario. METHODS: We analyzed archived samples from 492 men who underwent prostate Bx in an opportunistic screening scenario, with prostate-specific antigen (PSA) 3 to 10 ng/mL and/or suspicious digital rectal exploration (DRE) and without previous multi-parametric magnetic resonance imaging (mpMRI). Urinary biomarker measurements were combined with clinical risk factors to determine a risk score, and accuracy for GG ≥ 2 PCa detection was compared with PCA3, European randomized screening in prostate cancer (ERSPC), and prostate biopsy collaborative group (PBCG) risk calculators in a validation workup that included calibration, discrimination, and clinical utility analysis. RESULTS: In our cohort, the detection rates for GG1 and GG ≥ 2 PCa were 20.3% and 14.0%, respectively. The median PSA level was 3.9 ng/mL and 13.4% of subjects had suspicious DRE findings. The median risk score for men with GG ≥ 2 PCa was 21 (interquartile range: 14-28), significantly higher than benign+GG1 PCa (10, 6-18), P < .001, achieving the highest area under the curve among the models tested, 0.749 (95% confidence interval: 0.690-0.807). The urine test was well-calibrated, while ERSPC showed a slight underestimation and PBCG a slight overestimation of risk. Assuming a GG2 non-detection rate of 11% without using mpMRI, use of the urinary biomarker-based clinical model could have helped avoid 37.2% of excess biopsies while delaying the diagnosis of eight patients (1.6% of the entire cohort) with GG ≥ 2 PCa. CONCLUSIONS: In this first evaluation in an opportunistic screening population, the urinary biomarker-based test improved the detection of clinically significant PCa. Facing men with elevated PSA and/or suspicious DRE, it could be a useful tool to help avoid excess initial Bx and to identify patients most likely to benefit from Bx.

A Urine Based Genomic Assay to Triage Patients with Hematuria for Cystoscopy.

PURPOSE: Current clinical guidelines recommend cystoscopy in patients who present with hematuria to rule out a bladder tumor. We evaluated whether our previously developed urine assay was able to triage patients with hematuria for cystoscopy in a large prospective cohort. MATERIALS AND METHODS: A urine sample was collected before cystoscopy and mutation/methylation status of 6 genes was determined on cellular DNA. The existing diagnostic model was validated on this cohort. Logistic regression was applied to investigate other potential variables. The primary end point was the model performance as indicated by the AUC. Secondary end points were sensitivity, specificity and negative predictive value. Clinical usefulness was determined by the net benefit approach. RESULTS: In 838 patients biomarker status could be determined for all genes. Urothelial cancer was observed in 112 patients (98 of 457 in the gross and 14 of 381 in the microscopic hematuria group). Validation of the existing model resulted in an AUC of 0.93. Logistic regression analysis identified type of hematuria as a significant additional variable. Adding type of hematuria resulted in an AUC of 0.95 (96% sensitivity, 73% specificity, 99% negative predictive value). The assay identified all upper tract tumors not visible by cystoscopy (in 6). Net benefit analysis showed that the urine assay should be preferred over current clinical practice. Implementing the urine assay as a triage tool could lead to a 53% reduction in cystoscopies. CONCLUSIONS: The urine assay detected urothelial cancer with a very high accuracy and can be used to triage patients presenting with hematuria for cystoscopy.

Stable Oxidative Cytosine Modifications Accumulate in Cardiac Mesenchymal Cells From Type2 Diabetes Patients: Rescue by α-Ketoglutarate and TET-TDG Functional Reactivation.

RATIONALE: Human cardiac mesenchymal cells (CMSCs) are a therapeutically relevant primary cell population. Diabetes mellitus compromises CMSC function as consequence of metabolic alterations and incorporation of stable epigenetic changes. OBJECTIVE: To investigate the role of α-ketoglutarate (αKG) in the epimetabolic control of DNA demethylation in CMSCs. METHODS AND RESULTS: Quantitative global analysis, methylated and hydroxymethylated DNA sequencing, and gene-specific GC methylation detection revealed an accumulation of 5-methylcytosine, 5-hydroxymethylcytosine, and 5-formylcytosine in the genomic DNA of human CMSCs isolated from diabetic donors. Whole heart genomic DNA analysis revealed iterative oxidative cytosine modification accumulation in mice exposed to high-fat diet (HFD), injected with streptozotocin, or both in combination (streptozotocin/HFD). In this context, untargeted and targeted metabolomics indicated an intracellular reduction of αKG synthesis in diabetic CMSCs and in the whole heart of HFD mice. This observation was paralleled by a compromised TDG (thymine DNA glycosylase) and TET1 (ten-eleven translocation protein 1) association and function with TET1 relocating out of the nucleus. Molecular dynamics and mutational analyses showed that αKG binds TDG on Arg275 providing an enzymatic allosteric activation. As a consequence, the enzyme significantly increased its capacity to remove G/T nucleotide mismatches or 5-formylcytosine. Accordingly, an exogenous source of αKG restored the DNA demethylation cycle by promoting TDG function, TET1 nuclear localization, and TET/TDG association. TDG inactivation by CRISPR/Cas9 knockout or TET/TDG siRNA knockdown induced 5-formylcytosine accumulation, thus partially mimicking the diabetic epigenetic landscape in cells of nondiabetic origin. The novel compound (S)-2-[(2,6-dichlorobenzoyl)amino]succinic acid (AA6), identified as an inhibitor of αKG dehydrogenase, increased the αKG level in diabetic CMSCs and in the heart of HFD and streptozotocin mice eliciting, in HFD, DNA demethylation, glucose uptake, and insulin response. CONCLUSIONS: Restoring the epimetabolic control of DNA demethylation cycle promises beneficial effects on cells compromised by environmental metabolic changes.

An update on sORFs.org: a repository of small ORFs identified by ribosome profiling.

sORFs.org (http://www.sorfs.org) is a public repository of small open reading frames (sORFs) identified by ribosome profiling (RIBO-seq). This update elaborates on the major improvements implemented since its initial release. sORFs.org now additionally supports three more species (zebrafish, rat and Caenorhabditis elegans) and currently includes 78 RIBO-seq datasets, a vast increase compared to the three that were processed in the initial release. Therefore, a novel pipeline was constructed that also enables sORF detection in RIBO-seq datasets comprising solely elongating RIBO-seq data while previously, matching initiating RIBO-seq data was necessary to delineate the sORFs. Furthermore, a novel noise filtering algorithm was designed, able to distinguish sORFs with true ribosomal activity from simulated noise, consequently reducing the false positive identification rate. The inclusion of other species also led to the development of an inner BLAST pipeline, assessing sequence similarity between sORFs in the repository. Building on the proof of concept model in the initial release of sORFs.org, a full PRIDE-ReSpin pipeline was now released, reprocessing publicly available MS-based proteomics PRIDE datasets, reporting on true translation events. Next to reporting those identified peptides, sORFs.org allows visual inspection of the annotated spectra within the Lorikeet MS/MS viewer, thus enabling detailed manual inspection and interpretation.

Multicenter Optimization and Validation of a 2-Gene mRNA Urine Test for Detection of Clinically Significant Prostate Cancer before Initial Prostate Biopsy.

PURPOSE: A 2-gene, urine based molecular test that combines mRNA biomarkers with clinical factors can risk stratify patients for clinically significant prostate cancer. To ensure the generalizability of assay results we optimized and validated the clinical model for men with serum prostate specific antigen less than 10 ng/ml who were undergoing initial prostate biopsy. MATERIALS AND METHODS: Urine samples were collected from 1,955 men from The Netherlands, France and Germany prior to an initial prostate biopsy and study subjects were divided into training and validation cohorts. Urinary HOXC6 and DLX1 mRNA levels were quantified and RNA results were then combined with other risk factors in a clinical model optimized to detect ISUP (International Society of Urological Pathology) Grade Group 2 or greater prostate cancer in men with prostate specific antigen less than 10 ng/ml. Results in the validation cohort were compared with the PCPTRC (Prostate Cancer Prevention Trial Risk Calculator), version 2.0. RESULTS: The optimal clinical model included urinary HOXC6 and DLX1 mRNA levels, patient age, digital rectal examination and prostate specific antigen density (serum prostate specific antigen/prostate volume). In the 715 validation cohort subjects with prostate specific antigen less than 10 ng/ml the AUC was 0.82 with 89% sensitivity, 53% specificity and 95% negative predictive value. The PCPTRC AUC was 0.70. The full validation cohort of 916 men including all prostate specific antigen levels yielded an AUC of 0.85 with 93% sensitivity, 47% specificity and 95% negative predictive value. The PCPTRC AUC was 0.76. CONCLUSIONS: The 2-gene based urine assay, which is optimized for biopsy naïve patients with serum prostate specific antigen less than 10 ng/ml, demonstrated high sensitivity and negative predictive value to detect clinically significant prostate cancer. These data support using the test to help guide initial prostate biopsy decisions.

Clinically significant Prostate Cancer diagnosed using a urinary molecular biomarker-based risk score: two case reports.

BACKGROUND: Identifying men for a repeat prostate biopsy is a conundrum to urologists. Risk calculators (RCs) such as the European Randomized Study of Screening for Prostate Cancer (ERSPC) RCs have been developed to predict the outcome of prostate biopsies and have been shown to improve diagnostic accuracy compared to PSA alone. However, it was recently shown that the outcome for high-grade prostate cancer (PCa) upon biopsy tended to be underestimated in men with previous negative biopsies using ERSPC RC model 4. For these men, an individualized approach combining the clinical information with the outcome of biomarker-related urine tests may help to make a more informed decision. CASE PRESENTATION: Two men, aged 66 and 69 respectively when presented in the clinic, show the typical dilemma of urologist and patient for electing repeat prostate biopsy. Both men had normal DRE findings, did not have a family history of PCa, presented with serum PSA values between 3 and 10 ng/ml and the first biopsies were negative for disease. The ERSPC RC4 did not indicate a biopsy in these men. The urinary molecular biomarker-based test for HOXC6 and DLX1, combining biomarker-expression profiling with clinical risk factors, resulted in SelectMDx Risk scores for these men that were higher than the cut-off of the test. Based on this outcome, mpMRI was performed with an outcome of PI-RADS ≥4 in both men. Histopathological evaluation of TRUS-guided biopsies confirmed high-grade PCa. CONCLUSIONS: The urinary molecular biomarker-based risk score played a pivotal role in the diagnosis of clinically significant PCa whereas ERSPC RC4 outcome would not have indicated further diagnostic follow-up in these two cases. The timely diagnosis was shown to be crucial for the curative treatment by radical retropubic prostatectomy and the potential life-years gained for these two vital males.

Epigenetic markers in circulating cell-free DNA as prognostic markers for survival of castration-resistant prostate cancer patients.

BACKGROUND: Noninvasive biomarkers to guide personalized treatment for castration-resistant prostate cancer (CRPC) are needed. In this study, we analyzed hypermethylation patterns of two genes (GSTP1 and APC) in plasma cell-free DNA (cfDNA) of CRPC patients. The aim of this study was to analyze the cfDNA concentrations and levels of the epigenetic markers and to assess the value of these biomarkers for prognosis. METHODS: In this prospective study, patients were included before starting new treatment after developing CRPC. The blood samples were collected prior to start of the treatment and at three time points thereafter. cfDNA was extracted from 1.5 mL of plasma and before performing a methylation-specific PCR, bisulfate modification was carried out. RESULTS: The median levels of cfDNA, GSTP1, and APC copies in the baseline samples of CRPC patients (n = 47) were higher than in controls (n = 30). In the survival analysis, the group with baseline marker levels below median had significant less PCa-related deaths (P-values <0.02) and did not reach the median survival point. The survival distributions for the groups were statistically significant for the cfDNA concentration, GSTP1 and APC copies, as well as PSA combined with GSTP1 + APC (P-values <0.03). Furthermore, there were strong positive correlations between PSA and marker response after starting treatment (P-values <0.04). CONCLUSIONS: In conclusion, this study showed the kinetics of methylated cfDNA (GSTP1 and APC) in plasma of CRPC patients after starting treatment. Furthermore, the value of the markers before treatment is prognostic for overall survival. These results are promising for developing a test to guide treatment-decision-making for CRPC patients.

Novel Stool-Based Protein Biomarkers for Improved Colorectal Cancer Screening: A Case-Control Study.

BACKGROUND: The fecal immunochemical test (FIT) for detecting hemoglobin is used widely for noninvasive colorectal cancer (CRC) screening, but its sensitivity leaves room for improvement. OBJECTIVE: To identify novel protein biomarkers in stool that outperform or complement hemoglobin in detecting CRC and advanced adenomas. DESIGN: Case-control study. SETTING: Colonoscopy-controlled referral population from several centers. PARTICIPANTS: 315 stool samples from one series of 12 patients with CRC and 10 persons without colorectal neoplasia (control samples) and a second series of 81 patients with CRC, 40 with advanced adenomas, and 43 with nonadvanced adenomas, as well as 129 persons without colorectal neoplasia (control samples); 72 FIT samples from a third independent series of 14 patients with CRC, 16 with advanced adenomas, and 18 with nonadvanced adenomas, as well as 24 persons without colorectal neoplasia (control samples). MEASUREMENTS: Stool samples were analyzed by mass spectrometry. Classification and regression tree (CART) analysis and logistic regression analyses were performed to identify protein combinations that differentiated CRC or advanced adenoma from control samples. Antibody-based assays for 4 selected proteins were done on FIT samples. RESULTS: In total, 834 human proteins were identified, 29 of which were statistically significantly enriched in CRC versus control stool samples in both series. Combinations of 4 proteins reached sensitivities of 80% and 45% for detecting CRC and advanced adenomas, respectively, at 95% specificity, which was higher than that of hemoglobin alone (P < 0.001 and P = 0.003, respectively). Selected proteins could be measured in small sample volumes used in FIT-based screening programs and discriminated between CRC and control samples (P < 0.001). LIMITATION: Lack of availability of antibodies prohibited validation of the top protein combinations in FIT samples. CONCLUSION: Mass spectrometry of stool samples identified novel candidate protein biomarkers for CRC screening. Several protein combinations outperformed hemoglobin in discriminating CRC or advanced adenoma from control samples. Proof of concept that such proteins can be detected with antibody-based assays in small sample volumes indicates the potential of these biomarkers to be applied in population screening. PRIMARY FUNDING SOURCE: Center for Translational Molecular Medicine, International Translational Cancer Research Dream Team, Stand Up to Cancer (American Association for Cancer Research and the Dutch Cancer Society), Dutch Digestive Foundation, and VU University Medical Center.

Epigenetic risk score improves prostate cancer risk assessment.

BACKGROUND: Early detection of aggressive prostate cancer (PCa) remains crucial for effective treatment of patients. However, PCa screening remains controversial due to a high rate of overdiagnosis and overtreatment. To better reconcile both objectives, more effective methods for assessing disease severity at the time of diagnosis are needed. METHODS: The relationship between DNA-methylation and high-grade PCa was examined in a cohort of 102 prospectively enrolled men who received standard 12-core prostate biopsies. EpiScore, an algorithm that quantifies the relative DNA methylation intensities of GSTP1, RASSF1, and APC in prostate biopsy tissue, was evaluated as a method to compensate for biopsy under-sampling and improve risk stratification at the time of diagnosis. RESULTS: DNA-methylation intensities of GSTP1, RASSF1, and APC were higher in biopsy cores from men diagnosed with GS ≥ 7 cancer compared to men with diagnosed GS 6 disease. This was confirmed by EpiScore, which was significantly higher for subjects with high-grade biopsies and higher NCCN risk categories (both P < 0.001). In patients diagnosed with GS ≥ 7, increased levels of DNA-methylation were present, not only in the high-grade biopsy cores, but also in other cores with no or low-grade disease (P < 0.001). By combining EpiScore with traditional clinical risk factors into a logistic regression model, the prediction of high GS reached an AUC of 0.82 (95%CI: 0.73-0.91) with EpiScore, DRE, and atypical histological findings as most important contributors. CONCLUSIONS: In men diagnosed with PCa, DNA-methylation profiling can detect under-sampled high-risk PCa in prostate biopsy specimens through a field effect. Predictive accuracy increased when EpiScore was combined with other clinical risk factors. These results suggest that EpiScore could aid in the detection of occult high-grade disease at the time of diagnosis, thereby improving the selection of candidates for Active Surveillance.

A urinary biomarker-based risk score correlates with multiparametric MRI for prostate cancer detection.

BACKGROUND: Prostate cancer (PCa) diagnostics would greatly benefit from more accurate, non-invasive techniques for the detection of clinically significant disease, leading to a reduction of over-diagnosis and over-treatment. The aim of this study was to determine the association between a novel urinary biomarker-based risk score (SelectMDx), multiparametric MRI (mpMRI) outcomes, and biopsy results for PCa detection. METHODS: This retrospective observational study used data from the validation study of the SelectMDx score, in which urine was collected after digital rectal examination from men undergoing prostate biopsies. A subset of these patients also underwent a mpMRI scan of the prostate. The indications for performing mpMRI were based on persistent clinical suspicion of PCa or local staging after PCa was found upon biopsy. All mpMRI images were centrally reviewed in 2016 by an experienced radiologist blinded for the urine test results and biopsy outcome. The PI-RADS version 2 was used. RESULTS: In total, 172 patients were included for analysis. Hundred (58%) patients had PCa detected upon prostate biopsy, of which 52 (52%) had high-grade disease correlated with a significantly higher SelectMDx score (P < 0.01). The median SelectMDx score was significantly higher in patients with a suspicious significant lesion on mpMRI compared to no suspicion of significant PCa (P < 0.01). For the prediction of mpMRI outcome, the area-under-the-curve of SelectMDx was 0.83 compared to 0.66 for PSA and 0.65 for PCA3. There was a positive association between SelectMDx score and the final PI-RADS grade. There was a statistically significant difference in SelectMDx score between PI-RADS 3 and 4 (P < 0.01) and between PI-RADS 4 and 5 (P < 0.01). CONCLUSIONS: The novel urinary biomarker-based SelectMDx score is a promising tool in PCa detection. This study showed promising results regarding the correlation between the SelectMDx score and mpMRI outcomes, outperforming PCA3. Our results suggest that this risk score could guide clinicians in identifying patients at risk for significant PCa and selecting patients for further radiological diagnostics to reduce unnecessary procedures.

Methylome analysis of extreme chemoresponsive patients identifies novel markers of platinum sensitivity in high-grade serous ovarian cancer.

BACKGROUND: Despite an early response to platinum-based chemotherapy in advanced stage high-grade serous ovarian cancer (HGSOC), the majority of patients will relapse with drug-resistant disease. Aberrant epigenetic alterations like DNA methylation are common in HGSOC. Differences in DNA methylation are associated with chemoresponse in these patients. The objective of this study was to identify and validate novel epigenetic markers of chemoresponse using genome-wide analysis of DNA methylation in extreme chemoresponsive HGSOC patients. METHODS: Genome-wide next-generation sequencing was performed on methylation-enriched tumor DNA of two HGSOC patient groups with residual disease, extreme responders (≥18 months progression-free survival (PFS), n = 8) and non-responders (≤6 months PFS, n = 10) to platinum-based chemotherapy. DNA methylation and expression data of the same patients were integrated to create a gene list. Genes were validated on an independent cohort of extreme responders (n = 21) and non-responders (n = 31) using pyrosequencing and qRT-PCR. In silico validation was performed using publicly available DNA methylation (n = 91) and expression (n = 208) datasets of unselected advanced stage HGSOC patients. Functional validation of FZD10 on chemosensitivity was carried out in ovarian cancer cell lines using siRNA-mediated silencing. RESULTS: Integrated genome-wide methylome and expression analysis identified 45 significantly differentially methylated and expressed genes between two chemoresponse groups. Four genes FZD10, FAM83A, MYO18B, and MKX were successfully validated in an external set of extreme chemoresponsive HGSOC patients. High FZD10 and MKX methylation were related with extreme responders and high FAM83A and MYO18B methylation with non-responders. In publicly available advanced stage HGSOC datasets, FZD10 and MKX methylation levels were associated with PFS. High FZD10 methylation was strongly associated with improved PFS in univariate analysis (hazard ratio (HR) = 0.43; 95% CI, 0.27-0.71; P = 0.001) and multivariate analysis (HR = 0.39; 95% CI, 0.23-0.65; P = 0.003). Consistently, low FZD10 expression was associated with improved PFS (HR = 1.36; 95% CI, 0.99-1.88; P = 0.058). FZD10 silencing caused significant sensitization towards cisplatin treatment in survival assays and apoptosis assays. CONCLUSIONS: By applying genome-wide integrated methylome analysis on extreme chemoresponsive HGSOC patients, we identified novel clinically relevant, epigenetically-regulated markers of platinum-sensitivity in HGSOC patients. The clinical potential of these markers in predictive and therapeutic approaches has to be further validated in prospective studies.

Validation of a DNA Methylation-Mutation Urine Assay to Select Patients with Hematuria for Cystoscopy.

PURPOSE: Only 3% to 28% of patients referred to the urology clinic for hematuria are diagnosed with bladder cancer. Cystoscopy leads to high diagnostic costs and a high patient burden. Therefore, to improve the selection of patients for cystoscopy and reduce costs and over testing we aimed to validate a recently developed diagnostic urine assay. MATERIALS AND METHODS: Included in study were 200 patients from a total of 3 European countries who underwent cystoscopy for hematuria, including 97 with bladder cancer and 103 with nonmalignant findings. Voided urine samples were collected prior to cystoscopy. DNA was extracted and analyzed for mutations in FGFR3, TERT and HRAS, and methylation of OTX1, ONECUT2 and TWIST1. Logistic regression was used to analyze the association between predictor variables and bladder cancer. RESULTS: Combining the methylation and mutation markers with age led to an AUC of 0.96 (95% CI 0.92-0.99) with 93% sensitivity and 86% specificity, and an optimism corrected AUC of 0.95. The AUC was higher for T1 or greater tumors compared to Ta tumors (0.99 vs 0.93). The AUC was also higher for high grade tumors compared to low grade tumors (1.00 vs 0.93). Overall negative predictive value was 99% based on the 5% to 10% prevalence of bladder cancer in patients with hematuria. This would lead to a 77% reduction in diagnostic cystoscopy. CONCLUSIONS: Analyzing hematuria patients for the risk of bladder cancer using novel molecular markers may lead to a reduction in diagnostic cystoscopy. Combining methylation analysis (OTX1, ONECUT2 and TWIST1) with mutation analysis (FGFR3, TERT and HRAS) and patient age resulted in a validated accurate prediction model.