Evaluation of an epigenetic assay for predicting repeat prostate biopsy outcome in African American men

OBJECTIVE: To evaluate an epigenetic assay performed on tissue from negative prostate biopsies in a group of African American (AA) men undergoing repeat biopsy, and to compare accuracy for predicting repeat biopsy outcome to prior studies conducted in predominantly Caucasian populations. MATERIALS AND METHODS: The study population consisted of 211 AA men from 7 urology centers across the United States; all of whom were undergoing 12-core transrectal ultrasound-guided repeat biopsy within 30 months from a negative index biopsy. All biopsy cores from the negative index biopsy were profiled for the epigenetic biomarkers GSTP1, APC, and RASSF1 using ConfirmMDx for Prostate Cancer (MDxHealth, Irvine, CA). RESULTS: Upon repeat biopsy, 130 of 211 subjects (62%) had no prostate cancer (PCa) detected and 81 of 211 (38%) were diagnosed with PCa. Of the subjects with PCa, 54 (67%) were diagnosed with Gleason score (GS) = 7 disease. For detection of PCa at repeat biopsy, ConfirmMDx sensitivity was 74.1% and specificity was 60.0%, equivalent to prior studies (P = .235 and .697, respectively). For detection of GS >= 7 PCa, sensitivity was 78% and specificity was 53%. The negative predictive values for detection of all PCa and GS >= 7 PCa were 78.8% and 94.2%, respectively. CONCLUSION: In this group of AA men, we successfully validated an epigenetic assay to assess the need for repeat biopsy. Results were consistent with previous studies from predominantly Caucasian populations. Therefore, the ConfirmMDx assay is a useful tool for risk stratification of AA men who had an initial negative biopsy

Stellar Diameters and Temperatures II. Main Sequence K & M Stars

We present interferometric diameter measurements of 21 K- and M- dwarfs made with the CHARA Array. This sample is enhanced by literature radii measurements to form a data set of 33 K-M dwarfs with diameters measured to better than 5%. For all 33 stars, we compute absolute luminosities, linear radii, and effective temperatures (Teff). We develop empirical relations for \simK0 to M4 main- sequence stars between the stellar Teff, radius, and luminosity to broad-band color indices and metallicity. These relations are valid for metallicities between [Fe/H] = -0.5 and +0.1 dex, and are accurate to ~2%, ~5%, and ~4% for Teff, radius, and luminosity, respectively. Our results show that it is necessary to use metallicity dependent transformations to convert colors into stellar Teffs, radii, and luminosities. We find no sensitivity to metallicity on relations between global stellar properties, e.g., Teff-radius and Teff-luminosity. Robust examinations of single star Teffs and radii compared to evolutionary model predictions on the luminosity-Teff and luminosity-radius planes reveals that models overestimate the Teffs of stars with Teff < 5000 K by ~3%, and underestimate the radii of stars with radii < 0.7 R\odot by ~5%. These conclusions additionally suggest that the models overestimate the effects that the stellar metallicity may have on the astrophysical properties of an object. By comparing the interferometrically measured radii for single stars to those of eclipsing binaries, we find that single and binary star radii are consistent. However, the literature Teffs for binary stars are systematically lower compared to Teffs of single stars by ~ 200 to 300 K. Lastly, we present a empirically determined HR diagram for a total of 74 nearby, main-sequence, A- to M-type stars, and define regions of habitability for the potential existence of sub-stellar mass companions in each system. [abridged]Comment: 73 pages, 12 Tables, 18 Figures. Accepted for publication in The Astrophysical Journa

Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities

The hERG (human ether-a-go-go-related gene) encoded potassium ion (K+) channel plays a major role in cardiac repolarization. Drug-induced blockade of hERG has been a major cause of potentially lethal ventricular tachycardia termed Torsades de Pointes (TdPs). Therefore, we presented a pharmacoinformatics strategy using combined ligand and structure based models for the prediction of hERG inhibition potential (IC50) of new chemical entities (NCEs) during early stages of drug design and development. Integrated GRid-INdependent Descriptor (GRIND) models, and lipophilic efficiency (LipE), ligand efficiency (LE) guided template selection for the structure based pharmacophore models have been used for virtual screening and subsequent hERG activity (pIC50) prediction of identified hits. Finally selected two hits were experimentally evaluated for hERG inhibition potential (pIC50) using whole cell patch clamp assay. Overall, our results demonstrate a difference of less than ±1.6 log unit between experimentally determined and predicted hERG inhibition potential (IC50) of the selected hits. This revealed predictive ability and robustness of our models and could help in correctly rank the potency order (lower μM to higher nM range) against hERG

Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities

The hERG (human ether-a-go-go-related gene) encoded potassium ion (K+) channel plays a major role in cardiac repolarization. Drug-induced blockade of hERG has been a major cause of potentially lethal ventricular tachycardia termed Torsades de Pointes (TdPs). Therefore, we presented a pharmacoinformatics strategy using combined ligand and structure based models for the prediction of hERG inhibition potential (IC50) of new chemical entities (NCEs) during early stages of drug design and development. Integrated GRid-INdependent Descriptor (GRIND) models, and lipophilic efficiency (LipE), ligand efficiency (LE) guided template selection for the structure based pharmacophore models have been used for virtual screening and subsequent hERG activity (pIC50) prediction of identified hits. Finally selected two hits were experimentally evaluated for hERG inhibition potential (pIC50) using whole cell patch clamp assay. Overall, our results demonstrate a difference of less than ±1.6 log unit between experimentally determined and predicted hERG inhibition potential (IC50) of the selected hits. This revealed predictive ability and robustness of our models and could help in correctly rank the potency order (lower μM to higher nM range) against hERG

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Constitutivism

A brief explanation and overview of constitutivism

The twilight of the Liberal Social Contract? On the Reception of Rawlsian Political Liberalism

This chapter discusses the Rawlsian project of public reason, or public justification-based 'political' liberalism, and its reception. After a brief philosophical rather than philological reconstruction of the project, the chapter revolves around a distinction between idealist and realist responses to it. Focusing on political liberalism’s critical reception illuminates an overarching question: was Rawls’s revival of a contractualist approach to liberal legitimacy a fruitful move for liberalism and/or the social contract tradition? The last section contains a largely negative answer to that question. Nonetheless the chapter's conclusion shows that the research programme of political liberalism provided and continues to provide illuminating insights into the limitations of liberal contractualism, especially under conditions of persistent and radical diversity. The programme is, however, less receptive to challenges to do with the relative decline of the power of modern states

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment