71 research outputs found
Development of a multivariable risk model integrating urinary cell DNA methylation and cell-free RNA data for the detection of significant prostate cancer
Background: Prostate cancer exhibits severe clinical heterogeneity and there is a critical need for clinically implementable tools able to precisely and noninvasively identify patients that can either be safely removed from treatment pathways or those requiring further follow up. Our objectives were to develop a multivariable risk prediction model through the integration of clinical, urine-derived cell-free messenger RNA (cf-RNA) and urine cell DNA methylation data capable of noninvasively detecting significant prostate cancer in biopsy naïve patients. Methods: Post-digital rectal examination urine samples previously analyzed separately for both cellular methylation and cf-RNA expression within the Movember GAP1 urine biomarker cohort were selected for a fully integrated analysis (n = 207). A robust feature selection framework, based on bootstrap resampling and permutation, was utilized to find the optimal combination of clinical and urinary markers in a random forest model, deemed ExoMeth. Out-of-bag predictions from ExoMeth were used for diagnostic evaluation in men with a clinical suspicion of prostate cancer (PSA ≥ 4 ng/mL, adverse digital rectal examination, age, or lower urinary tract symptoms). Results: As ExoMeth risk score (range, 0-1) increased, the likelihood of high-grade disease being detected on biopsy was significantly greater (odds ratio = 2.04 per 0.1 ExoMeth increase, 95% confidence interval [CI]: 1.78-2.35). On an initial TRUS biopsy, ExoMeth accurately predicted the presence of Gleason score ≥3 + 4, area under the receiver-operator characteristic curve (AUC) = 0.89 (95% CI: 0.84-0.93) and was additionally capable of detecting any cancer on biopsy, AUC = 0.91 (95% CI: 0.87-0.95). Application of ExoMeth provided a net benefit over current standards of care and has the potential to reduce unnecessary biopsies by 66% when a risk threshold of 0.25 is accepted. Conclusion: Integration of urinary biomarkers across multiple assay methods has greater diagnostic ability than either method in isolation, providing superior predictive ability of biopsy outcomes. ExoMeth represents a more holistic view of urinary biomarkers and has the potential to result in substantial changes to how patients suspected of harboring prostate cancer are diagnosed
Metabolic Fingerprinting Links Oncogenic PIK3CA with Enhanced Arachidonic Acid-Derived Eicosanoids.
Oncogenic transformation is associated with profound changes in cellular metabolism, but whether tracking these can improve disease stratification or influence therapy decision-making is largely unknown. Using the iKnife to sample the aerosol of cauterized specimens, we demonstrate a new mode of real-time diagnosis, coupling metabolic phenotype to mutant PIK3CA genotype. Oncogenic PIK3CA results in an increase in arachidonic acid and a concomitant overproduction of eicosanoids, acting to promote cell proliferation beyond a cell-autonomous manner. Mechanistically, mutant PIK3CA drives a multimodal signaling network involving mTORC2-PKCζ-mediated activation of the calcium-dependent phospholipase A2 (cPLA2). Notably, inhibiting cPLA2 synergizes with fatty acid-free diet to restore immunogenicity and selectively reduce mutant PIK3CA-induced tumorigenicity. Besides highlighting the potential for metabolic phenotyping in stratified medicine, this study reveals an important role for activated PI3K signaling in regulating arachidonic acid metabolism, uncovering a targetable metabolic vulnerability that largely depends on dietary fat restriction. VIDEO ABSTRACT
epiCaPture: a urine DNA methylation test for early detection of aggressive prostate cancer
Purpose Liquid biopsies that noninvasively detect molecular correlates of aggressive prostate cancer (PCa) could be used to triage patients, reducing the burdens of unnecessary invasive prostate biopsy and enabling early detection of high-risk disease. DNA hypermethylation is among the earliest and most frequent aberrations in PCa. We investigated the accuracy of a six-gene DNA methylation panel (Epigenetic Cancer of the Prostate Test in Urine [epiCaPture]) at detecting PCa, high-grade (Gleason score greater than or equal to 8) and high-risk (D'Amico and Cancer of the Prostate Risk Assessment] PCa from urine. Patients and Methods Prognostic utility of epiCaPture genes was first validated in two independent prostate tissue cohorts. epiCaPture was assessed in a multicenter prospective study of 463 men undergoing prostate biopsy. epiCaPture was performed by quantitative methylation-specific polymerase chain reaction in DNA isolated from prebiopsy urine sediments and evaluated by receiver operating characteristic and decision curves (clinical benefit). The epiCaPture score was developed and validated on a two thirds training set to one third test set. Results Higher methylation of epiCaPture genes was significantly associated with increasing aggressiveness in PCa tissues. In urine, area under the receiver operating characteristic curve was 0.64, 0.86, and 0.83 for detecting PCa, high-grade PCa, and highrisk PCa, respectively. Decision curves revealed a net benefit across relevant threshold probabilities. Independent analysis of two epiCaPture genes in the same clinical cohort provided analytical validation. Parallel epiCaPture analysis in urine and matched biopsy cores showed added value of a liquid biopsy. Conclusion epiCaPture is a urine DNA methylation test for high-risk PCa. Its tumor specificity out-performs that of prostate-specific antigen (greater than 3 ng/mL). Used as an adjunct to prostate-specific antigen, epiCaPture could aid patient stratification to determine need for biopsy
Reasons for Discontinuing Active Surveillance : Assessment of 21 Centres in 12 Countries in the Movember GAP3 Consortium
Background: Careful assessment of the reasons for discontinuation of active surveillance (AS) is required for men with prostate cancer (PCa). Objective: Using Movember's Global Action Plan Prostate Cancer Active Surveillance initiative (GAP3) database, we report on reasons for AS discontinuation. Design, setting, and participants: We compared data from 10 296 men on AS from 21 centres across 12 countries. Outcome measurements and statistical analysis: Cumulative incidence methods were used to estimate the cumulative incidence rates of AS discontinuation. Results and limitations: During 5-yr follow-up, 27.5% (95% confidence interval [CI]: 26.4-28.6%) men showed signs of disease progression, 12.8% (95% CI: 12.0-13.6%) converted to active treatment without evidence of progression, 1.7% (95% CI: 1.5-2.0%) continued to watchful waiting, and 1.7% (95% CI: 1.4-2.1%) died from other causes. Of the 7049 men who remained on AS, 2339 had follow-up for >5 yr, 4561 had follow-up for Conclusions: Our descriptive analyses of current AS practices worldwide showed that 43.6% of men drop out of AS during 5-yr follow-up, mainly due to signs of disease progression. Improvements in selection tools for AS are thus needed to correctly allocate men with PCa to AS, which will also reduce discontinuation due to conversion to active treatment without evidence of disease progression. Patient summary: Our assessment of a worldwide database of men with prostate cancer (PCa) on active surveillance (AS) shows that 43.6% drop out of AS within 5 yr, mainly due to signs of disease progression. Better tools are needed to select and monitor men with PCa as part of AS. (C) 2018 European Association of Urology. Published by Elsevier B.V. All rights reserved.Peer reviewe
Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170.
We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.352
Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel
Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562 WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants
Nucleotide Substitution Rates in Legume Chloroplast DNA Depend on the Presence of the Inverted Repeat
Novel Strategies for Cancer Treatment: Highlights from the 55th IACR Annual Conference
While conventional cancer treatments, such as surgery, radiotherapy and chemotherapy, have been combined for decades in an effort to treat cancer patients, the emergence of novel fields of cancer research have led to a renewed interest in combining conventional treatments with more innovative approaches. The realisation that cancer progression is not exclusively due to changes in the cancer epithelial cells, but also involves changes in the tumour microenvironment, has opened new avenues for combination treatments. Here we discuss the use of combination therapies presented at the 55th Irish Association for Cancer Research (IACR) Annual Conference, highlighting examples of novel therapeutic strategies which, combined with conventional therapies, may greatly enhance not only the overall outcome for patients, but also the quality of life for cancer survivors. Among the novel treatment strategies, immune metabolism, epigenetic therapies and physical exercise are presented. In addition, novel technologies in the field of precision medicine, which will be useful to discover new therapeutics and to stratify patients for combination treatments, are also discussed
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