Diffusion tensor MRI is sensitive to fibrotic injury in a mouse model of oxalate-induced chronic kidney disease.

Chronic kidney disease (CKD) is characterized by inflammation and fibrosis in the kidney. Renal biopsies and estimated glomerular filtration rate (eGFR) remain the standard of care, but these endpoints have limitations in detecting the stage, progression, and spatial distribution of fibrotic pathology in the kidney. MRI diffusion tensor imaging (DTI) has emerged as a promising noninvasive technology to evaluate renal fibrosis in vivo both in clinical and preclinical studies. However, these imaging studies have not systematically identified fibrosis particularly deeper in the kidney where biopsy sampling is limited, or completed an extensive analysis of whole organ histology, blood biomarkers, and gene expression to evaluate the relative strengths and weaknesses of MRI for evaluating renal fibrosis. In this study, we performed DTI in the sodium oxalate mouse model of CKD. The DTI parameters fractional anisotropy, apparent diffusion coefficient, and axial diffusivity were compared between the control and oxalate groups with region of interest (ROI) analysis to determine changes in the cortex and medulla. In addition, voxel-based analysis (VBA) was implemented to systematically identify local regions of injury over the whole kidney. DTI parameters were found to be significantly different in the medulla by both ROI analysis and VBA, which also spatially matched with collagen III immunohistochemistry (IHC). The DTI parameters in this medullary region exhibited moderate to strong correlations with histology, blood biomarkers, hydroxyproline, and gene expression. Our results thus highlight the sensitivity of DTI to the heterogeneity of renal fibrosis and importance of whole kidney noninvasive imaging.NEW & NOTEWORTHY Chronic kidney disease (CKD) can be characterized by inflammation and fibrosis of the kidney. Although standard of care methods have been limited in scope, safety, and spatial distribution, MRI diffusion tensor imaging (DTI) has emerged as a promising noninvasive technology to evaluate renal fibrosis in vivo. In this study, we performed DTI in an oxalate mouse model of CKD to systematically identify local kidney injury. DTI parameters strongly correlated with histology, blood biomarkers, hydroxyproline, and gene expression.

Quantifying KRAS G12C Covalent Drug Inhibitor Activity in Mouse Tumors Using Mass Spectrometry.

The growing opportunities recognized for covalent drug inhibitors, like KRAS G12C inhibitors, are driving the need for mass spectrometry methods that can quickly and robustly measure therapeutic drug activity in vivo for drug discovery research and development. Effective front-end sample preparation is critical for proteins extracted from tumors but is generally labor intensive and impractical for large sample numbers typical in pharmacodynamic (PD) studies. Herein, we describe an automated and integrated sample preparation method for the measurement of activity levels of KRAS G12C drug inhibitor alkylation from complex tumor samples involving high throughput detergent removal and preconcentration followed by quantitation using mass spectrometry. We introduce a robust assay with an average intra-assay coefficient of variation (CV) of 4% and an interassay CV of 6% obtained from seven studies, enabling us to understand the relationship between KRAS G12C target occupancy and the therapeutic PD effect from mouse tumor samples. Further, the data demonstrated that the drug candidate GDC-6036, a KRAS G12C covalent inhibitor, shows dose-dependent target inhibition (KRAS G12C alkylation) and MAPK pathway inhibition, which correlate with high antitumor potency in the MIA PaCa-2 pancreatic xenograft model.

A whole genome sequencing study of moderate to severe asthma identifies a lung function locus associated with asthma risk.

Genome-wide association studies (GWAS) have identified many common variant loci associated with asthma susceptibility, but few studies investigate the genetics underlying moderate-to-severe asthma risk. Here, we present a whole-genome sequencing study comparing 3181 moderate-to-severe asthma patients to 3590 non-asthma controls. We demonstrate that asthma risk is genetically correlated with lung function measures and that this component of asthma risk is orthogonal to the eosinophil genetics that also contribute to disease susceptibility. We find that polygenic scores for reduced lung function are associated with younger asthma age of onset. Genome-wide, seven previously reported common asthma variant loci and one previously reported lung function locus, near THSD4, reach significance. We replicate association of the lung function locus in a recently published GWAS of moderate-to-severe asthma patients. We additionally replicate the association of a previously reported rare (minor allele frequency < 1%) coding variant in IL33 and show significant enrichment of rare variant burden in genes from common variant allergic disease loci. Our findings highlight the contribution of lung function genetics to moderate-to-severe asthma risk, and provide initial rare variant support for associations with moderate-to-severe asthma risk at several candidate genes from common variant loci.

RTK-Dependent Inducible Degradation of Mutant PI3Kα Drives GDC-0077 (Inavolisib) Efficacy.

PIK3CA is one of the most frequently mutated oncogenes; the p110a protein it encodes plays a central role in tumor cell proliferation. Small-molecule inhibitors targeting the PI3K p110a catalytic subunit have entered clinical trials, with early-phase GDC-0077 studies showing antitumor activity and a manageable safety profile in patients with PIK3CA-mutant breast cancer. However, preclinical studies have shown that PI3K pathway inhibition releases negative feedback and activates receptor tyrosine kinase signaling, reengaging the pathway and attenuating drug activity. Here we discover that GDC-0077 and taselisib more potently inhibit mutant PI3K pathway signaling and cell viability through unique HER2-dependent mutant p110a degradation. Both are more effective than other PI3K inhibitors at maintaining prolonged pathway suppression. This study establishes a new strategy for identifying inhibitors that specifically target mutant tumors by selective degradation of the mutant oncoprotein and provide a strong rationale for pursuing PI3Kα degraders in patients with HER2-positive breast cancer. SIGNIFICANCE: The PI3K inhibitors GDC-0077 and taselisib have a unique mechanism of action; both inhibitors lead to degradation of mutant p110a protein. The inhibitors that have the ability to trigger specific degradation of mutant p110a without significant change in wild-type p110a protein may result in improved therapeutic index in PIK3CA-mutant tumors.See related commentary by Vanhaesebroeck et al., p. 20.This article is highlighted in the In This Issue feature, p. 1.

MiDAS-Meaningful Immunogenetic Data at Scale.

Human immunogenetic variation in the form of HLA and KIR types has been shown to be strongly associated with a multitude of immune-related phenotypes. However, association studies involving immunogenetic loci most commonly involve simple analyses of classical HLA allelic diversity, resulting in limitations regarding the interpretability and reproducibility of results. We here present MiDAS, a comprehensive R package for immunogenetic data transformation and statistical analysis. MiDAS recodes input data in the form of HLA alleles and KIR types into biologically meaningful variables, allowing HLA amino acid fine mapping, analyses of HLA evolutionary divergence as well as experimentally validated HLA-KIR interactions. Further, MiDAS enables comprehensive statistical association analysis workflows with phenotypes of diverse measurement scales. MiDAS thus closes the gap between the inference of immunogenetic variation and its efficient utilization to make relevant discoveries related to immune and disease biology. It is freely available under a MIT license.

Characterization of Hepatic UDP-Glucuronosyltransferase Enzyme Abundance-Activity Correlations and Population Variability Using a Proteomics Approach and Comparison with Cytochrome P450 Enzymes.

The expression of ten major drug-metabolizing UDP-glucuronosyltransferase (UGT) enzymes in a panel of 130 human hepatic microsomal samples was measured using a liquid chromatography-tandem mass spectrometry-based approach. Simultaneously, ten cytochromes P450 and P450 reductase were also measured, and activity-expression relationships were assessed for comparison. The resulting data sets demonstrated that, with the exception of UGT2B17, 10th to 90th percentiles of UGT expression spanned 3- to 8-fold ranges. These ranges were small relative to ranges of reported mean UGT enzyme expression across different laboratories. We tested correlation of UGT expression with enzymatic activities using selective probe substrates. A high degree of abundance-activity correlation (Spearman's rank correlation coefficient > 0.6) was observed for UGT1As (1A1, 3, 4, 6) and cytochromes P450. In contrast, protein abundance and activity did not correlate strongly for UGT1A9 and UGT2B enzymes (2B4, 7, 10, 15, and 17). Protein abundance was strongly correlated for UGTs 2B7, 2B10, and 2B15. We suggest a number of factors may contribute to these differences including incomplete selectivity of probe substrates, correlated expression of these UGT2B isoforms, and the impact of splice and polymorphic variants on the peptides used in proteomics analysis, and exemplify this in the case of UGT2B10. Extensive correlation analyses identified important criteria for validating the fidelity of proteomics and enzymatic activity approaches for assessing UGT variability, population differences, and ontogenetic changes. SIGNIFICANCE STATEMENT: Protein expression data allow detailed assessment of interindividual variability and enzyme ontogeny. This study has observed that expression and enzyme activity are well correlated for hepatic UGT1A enzymes and cytochromes P450. However, for the UGT2B family, caution is advised when assuming correlation of expression and activity as is often done in physiologically based pharmacokinetic modeling. This can be due to incomplete probe substrate specificities, but may also be related to presence of inactive UGT protein materials and the effect of splicing variations.

Ocular phenotypes in a mouse model of impaired glucocerebrosidase activity.

Mutations in the GBA1 gene encoding glucocerebrosidase (GCase) are linked to Gaucher (GD) and Parkinson's Disease (PD). Since some GD and PD patients develop ocular phenotypes, we determined whether ocular phenotypes might result from impaired GCase activity and the corresponding accumulation of glucosylceramide (GluCer) and glucosylsphingosine (GluSph) in the Gba1D409V/D409V knock-in (Gba KI/KI; "KI") mouse. Gba KI mice developed age-dependent pupil dilation deficits to an anti-muscarinic agent; histologically, the iris covered the anterior part of the lens with adhesions between the iris and the anterior surface of the lens (posterior synechia). This may prevent pupil dilation in general, beyond an un-responsiveness of the iris to anti-muscarinics. Gba KI mice displayed atrophy and pigment dispersion of the iris, and occlusion of the iridocorneal angle by pigment-laden cells, reminiscent of secondary open angle glaucoma. Gba KI mice showed progressive thinning of the retina consistent with retinal degeneration. GluSph levels were increased in the anterior and posterior segments of the eye, suggesting that accumulation of lipids in the eye may contribute to degeneration in this compartment. We conclude that the Gba KI model provides robust and reproducible eye phenotypes which may be used to test for efficacy and establish biomarkers for GBA1-related therapies.

Generalized Additive Mixed Modeling of Longitudinal Tumor Growth Reduces Bias and Improves Decision Making in Translational Oncology.

Scientists working in translational oncology regularly conduct multigroup studies of mice with serially measured tumors. Longitudinal data collected can feature mid-study dropouts and complex nonlinear temporal response patterns. Parametric statistical models such as ones assuming exponential growth are useful for summarizing tumor volume over ranges for which the growth model holds, with the advantage that the model's parameter estimates can be used to summarize between-group differences in tumor volume growth with statistical measures of uncertainty. However, these same assumed growth models are too rigid to recapitulate patterns observed in many experiments, which in turn diminishes the effectiveness of their parameter estimates as summary statistics. To address this problem, we generalized such models by adopting a nonparametric approach in which group-level response trends for logarithmically scaled tumor volume are estimated as regression splines in a generalized additive mixed model. We also describe a novel summary statistic for group level splines over user-defined, experimentally relevant time ranges. This statistic reduces to the log-linear growth rate for data well described by exponential growth and also has a sampling distribution across groups that is well approximated by a multivariate Gaussian, thus facilitating downstream analysis. Real-data examples show that this nonparametric approach not only enhances fidelity in describing nonlinear growth scenarios but also improves statistical power to detect interregimen differences when compared with the simple exponential model so that it generalizes the linear mixed effects paradigm for analysis of log-linear growth to nonlinear scenarios in a useful way. SIGNIFICANCE: This work generalizes the statistical linear mixed modeling paradigm for summarizing longitudinally measured preclinical tumor volume studies to encompass studies with nonlinear and nonmonotonic group response patterns in a statistically rigorous manner.

Characterizing and Quantitating Therapeutic Tethered Multimeric Antibody Degradation Using Affinity Capture Mass Spectrometry.

There are many pharmacokinetic challenges associated with administering protein therapeutics, including biotransformation via clipping, deamidation, isomerization, oxidation, etc. In the case of engineered multivalent tethered antibody formats, proteolysis or deconjugation at the fusion or conjugation site present further issues. Unlike degradations associated with antibody drug conjugates, such biotransformations of tethered antibody formats usually result in degraded products with large mass differences. These large differences can result in processing or mass spectrometry response bias among the resulting product species that can lead to inaccurate stability quantitation. Herein, we describe an assay strategy for characterizing and quantitating degradations accurately for multivalent antibodies by incorporating response bias corrections. For the multivalent tethered antibody molecules selected, an ∼30-80% difference in response, compared to the cleaved product, was observed. To correct for the response bias, selected tethered multivalent antibodies and an IgG antibody (representing the stable intact and the degraded product species, respectively) were spiked in serum at known ratios for analysis. Following affinity capture, we generated calibration curves (five-parameter logistic fit p < 0.05) by plotting the measured ratios of the MS ion responses against the known spiked-in ratios (CVs < 8% for calibration standards). The qualified calibration curve (accuracy within 8% and 2% for measuring degradations of 5% and 15% product, respectively) was then used, through interpolation, to determine stability profiles for the same multivalent tethered antibody formats from both in vitro serum and pharmacokinetic study samples.

Characterization of the Ontogeny of Hepatic UDP-Glucuronosyltransferase Enzymes Based on Glucuronidation Activity Measured in Human Liver Microsomes.

An understanding of the postnatal development of hepatic UDP-glucuronosyltransferase (UGT) enzymes is required for accurate prediction of the age-dependent changes in pharmacokinetics of many drugs used in children. However, the maturation rate of hepatic UGT isoforms remains a major knowledge gap. This study aimed to establish the age-associated changes in glucuronidation activity of 10 major hepatic UGT isoforms in humans, namely, UGT1A1, UGT1A3, UGT1A4, UGT1A6, UGT1A9, UGT2B4, UGT2B7, UGT2B10, UGT2B15, and UGT2B17. Human liver microsomes from pediatric and adult donors were incubated under optimized incubation conditions to assess the activity rates of hepatic UGT isoforms using a panel of 19 in vitro UGT probe substrates and clinically used drugs. Statistically strong correlations of glucuronidation activities allowed the ontogeny of UGT1A1, UGT1A4, UGT2B7, UGT2B10, and UGT2B15 to be established using multiple selective UGT substrates and matched human liver microsome samples. The postnatal development of hepatic UGTs is isoform-dependent using either individual or cross-correlated selective isoform substrates. Maximal adult activity was reached at different times ranging from within a month (UGT1A1, UGT2B4, UGT2B7, UGT2B10, and UGT2B15), during infancy (UGT1A3, UGT1A4, and UGT1A9), to adolescence (UGT1A6 and UGT2B17). This study provides an extensive characterization of the postnatal ontogeny profiles of hepatic UGT enzymes that are instrumental for predicting drug disposition via in vitro-in vivo extrapolation algorithms and verifying pharmacokinetic predictions against in vivo observations via pediatric physiologically based pharmacokinetic modeling in pediatric patients.

Multiple-gene targeting and mismatch tolerance can confound analysis of genome-wide pooled CRISPR screens.

BACKGROUND: Genome-wide loss-of-function screens using the CRISPR/Cas9 system allow the efficient discovery of cancer cell vulnerabilities. While several studies have focused on correcting for DNA cleavage toxicity biases associated with copy number alterations, the effects of sgRNAs co-targeting multiple genomic loci in CRISPR screens have not been discussed. RESULTS: In this work, we analyze CRISPR essentiality screen data from 391 cancer cell lines to characterize biases induced by multi-target sgRNAs. We investigate two types of multi-targets: on-targets predicted through perfect sequence complementarity and off-targets predicted through sequence complementarity with up to two nucleotide mismatches. We find that the number of on-targets and off-targets both increase sgRNA activity in a cell line-specific manner and that existing additive models of gene knockout effects fail at capturing genetic interactions that may occur between co-targeted genes. We use synthetic lethality between paralog genes to show that genetic interactions can introduce biases in essentiality scores estimated from multi-target sgRNAs. We further show that single-mismatch tolerant sgRNAs can confound the analysis of gene essentiality and lead to incorrect co-essentiality functional networks. Lastly, we also find that single nucleotide polymorphisms located in protospacer regions can impair on-target activity as a result of mismatch tolerance. CONCLUSION: We show the impact of multi-target effects on estimating cancer cell dependencies and the impact of off-target effects caused by mismatch tolerance in sgRNA-DNA binding.

Previously reported placebo-response-associated variants do not predict patient outcomes in inflammatory disease Phase III trial placebo arms.

In clinical trials, a placebo response refers to improvement in disease symptoms arising from the psychological effect of receiving a treatment rather than the actual treatment under investigation. Previous research has reported genomic variation associated with the likelihood of observing a placebo response, but these studies have been limited in scope and have not been validated. Here, we analyzed whole-genome sequencing data from 784 patients undergoing placebo treatment in Phase III Asthma or Rheumatoid Arthritis trials to assess the impact of previously reported variation on patient outcomes in the placebo arms and to identify novel variants associated with the placebo response. Contrary to expectations based on previous reports, we did not observe any statistically significant associations between genomic variants and placebo treatment outcome. Our findings suggest that the biological origin of the placebo response is complex and likely to be variable between disease areas.

Germline genetic polymorphisms influence tumor gene expression and immune cell infiltration.

Cancer immunotherapy has emerged as an effective therapy in a variety of cancers. However, a key challenge in the field is that only a subset of patients who receive immunotherapy exhibit durable response. It has been hypothesized that host genetics influences the inherent immune profiles of patients and may underlie their differential response to immunotherapy. Herein, we systematically determined the association of common germline genetic variants with gene expression and immune cell infiltration of the tumor. We identified 64,094 expression quantitative trait loci (eQTLs) that associated with 18,210 genes (eGenes) across 24 human cancers. Overall, eGenes were enriched for their being involved in immune processes, suggesting that expression of immune genes can be shaped by hereditary genetic variants. We identified the endoplasmic reticulum aminopeptidase 2 (ERAP2) gene as a pan-cancer type eGene whose expression levels stratified overall survival in a subset of patients with bladder cancer receiving anti-PD-L1 (atezolizumab) therapy. Finally, we identified 103 gene signature QTLs (gsQTLs) that were associated with predicted immune cell abundance within the tumor microenvironment. Our findings highlight the impact of germline SNPs on cancer-immune phenotypes and response to therapy; and these analyses provide a resource for integration of germline genetics as a component of personalized cancer immunotherapy.

Analysis of protein-altering variants in telomerase genes and their association with MUC5B common variant status in patients with idiopathic pulmonary fibrosis: a candidate gene sequencing study.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) risk has a strong genetic component. Studies have implicated variations at several loci, including TERT, surfactant genes, and a single nucleotide polymorphism at chr11p15 (rs35705950) in the intergenic region between TOLLIP and MUC5B. Patients with IPF who have risk alleles at rs35705950 have longer survival from the time of IPF diagnosis than do patients homozygous for the non-risk allele, whereas patients with shorter telomeres have shorter survival times. We aimed to assess whether rare protein-altering variants in genes regulating telomere length are enriched in patients with IPF homozygous for the non-risk alleles at rs35705950. METHODS: Between Nov 1, 2014, and Nov 1, 2016, we assessed blood samples from patients aged 40 years or older and of European ancestry with sporadic IPF from three international phase 3 clinical trials (INSPIRE, CAPACITY, ASCEND), one phase 2 study (RIFF), and US-based observational studies (Vanderbilt Clinical Interstitial Lung Disease Registry and the UCSF Interstitial Lung Disease Clinic registry cohorts) at the Broad Institute (Cambridge, MA, USA) and Human Longevity (San Diego, CA, USA). We also assessed blood samples from non-IPF controls in several clinical trials. We did whole-genome sequencing to assess telomere length and identify rare protein-altering variants, stratified by rs35705950 genotype. We also assessed rare functional variation in TERT exons and compared telomere length and disease progression across genotypes. FINDINGS: We assessed samples from 1510 patients with IPF and 1874 non-IPF controls. 30 (3%) of 1046 patients with an rs35705950 risk allele had a rare protein-altering variant in TERT compared with 34 (7%) of 464 non-risk allele carriers (odds ratio 0·40 [95% CI 0·24-0·66], p=0·00039). Subsequent analyses identified enrichment of rare protein-altering variants in PARN and RTEL1, and rare variation in TERC in patients with IPF compared with controls. We expanded our study population to provide a more accurate estimation of rare variant frequency in these four loci, and to calculate telomere length. The proportion of patients with at least one rare variant in TERT, PARN, TERC, or RTEL1 was higher in patients with IPF than in controls (149 [9%] of 1739 patients vs 205 [2%] of 8645 controls, p=2·44 × 10-8). Patients with IPF who had a variant in any of the four identified telomerase component genes had telomeres that were 3·69-16·10% shorter than patients without a variant in any of the four genes and had an earlier mean age of disease onset than patients without one or more variants (65·1 years [SD 7·8] vs 67·1 years [7·9], p=0·004). In the placebo arms of clinical trials, shorter telomeres were significantly associated with faster disease progression (1·7% predicted forced vital capacity per kb per year, p=0·002). Pirfenidone had treatment benefit regardless of telomere length (p=4·24 × 10-8 for telomere length lower than the median, p=0·0044 for telomere length greater than the median). INTERPRETATION: Rare protein-altering variants in TERT, PARN, TERC, and RTEL1 are enriched in patients with IPF compared with controls, and, in the case of TERT, particularly in individuals without a risk allele at the rs35705950 locus. This suggests that multiple genetic factors contribute to sporadic IPF, which might implicate distinct mechanisms of pathogenesis and disease progression. FUNDING: Genentech, National Institutes of Health, Francis Family Foundation, Pulmonary Fibrosis Foundation, Nina Ireland Program for Lung Health, US Department of Veterans Affairs.

Dual functionality of ß-tryptase protomers as both proteases and cofactors in the active tetramer.

Human ß-tryptase, a tetrameric trypsin-like serine protease, is an important mediator of the allergic inflammatory responses in asthma. During acute hypersensitivity reactions, mast cells degranulate, releasing active tetramer as a complex with proteoglycans. Extensive efforts have focused on developing therapeutic ß-tryptase inhibitors, but its unique activation mechanism is less well-explored. Tryptase is active only after proteolytic removal of the pro-domain followed by tetramer formation via two distinct symmetry-related interfaces. We show that the cleaved I16G mutant cannot tetramerize, likely due to impaired insertion of its N terminus into its "activation pocket," indicating allosteric linkage at multiple sites on each protomer. We engineered cysteines into each of the two distinct interfaces (Y75C for small or I99C for large) to assess the activity of each tetramer and disulfide-locked dimer. Using size-exclusion chromatography and enzymatic assays, we demonstrate that the two large tetramer interfaces regulate enzymatic activity, elucidating the importance of this protein-protein interaction for allosteric regulation. Notably, the I99C large interface dimer is active, even in the absence of heparin. We show that a monomeric ß-tryptase mutant (I99C*/Y75A/Y37bA, where C* is cysteinylated Cys-99) cannot form a dimer or tetramer, yet it is active but only in the presence of heparin. Thus heparin both stabilizes the tetramer and allosterically conditions the active site. We hypothesize that each ß-tryptase protomer in the tetramer has two distinct roles, acting both as a protease and as a cofactor for its neighboring protomer, to allosterically regulate enzymatic activity, providing a rationale for direct correlation of tetramer stability with proteolytic activity.

Reactive-site-centric chemoproteomics identifies a distinct class of deubiquitinase enzymes.

Activity-based probes (ABPs) are widely used to monitor the activity of enzyme families in biological systems. Inferring enzyme activity from probe reactivity requires that the probe reacts with the enzyme at its active site; however, probe-labeling sites are rarely verified. Here we present an enhanced chemoproteomic approach to evaluate the activity and probe reactivity of deubiquitinase enzymes, using bioorthogonally tagged ABPs and a sequential on-bead digestion protocol to enhance the identification of probe-labeling sites. We confirm probe labeling of deubiquitinase catalytic Cys residues and reveal unexpected labeling of deubiquitinases on non-catalytic Cys residues and of non-deubiquitinase proteins. In doing so, we identify ZUFSP (ZUP1) as a previously unannotated deubiquitinase with high selectivity toward cleaving K63-linked chains. ZUFSP interacts with and modulates ubiquitination of the replication protein A (RPA) complex. Our reactive-site-centric chemoproteomics method is broadly applicable for identifying the reaction sites of covalent molecules, which may expand our understanding of enzymatic mechanisms.

USP7 small-molecule inhibitors interfere with ubiquitin binding.

The ubiquitin system regulates essential cellular processes in eukaryotes. Ubiquitin is ligated to substrate proteins as monomers or chains and the topology of ubiquitin modifications regulates substrate interactions with specific proteins. Thus ubiquitination directs a variety of substrate fates including proteasomal degradation. Deubiquitinase enzymes cleave ubiquitin from substrates and are implicated in disease; for example, ubiquitin-specific protease-7 (USP7) regulates stability of the p53 tumour suppressor and other proteins critical for tumour cell survival. However, developing selective deubiquitinase inhibitors has been challenging and no co-crystal structures have been solved with small-molecule inhibitors. Here, using nuclear magnetic resonance-based screening and structure-based design, we describe the development of selective USP7 inhibitors GNE-6640 and GNE-6776. These compounds induce tumour cell death and enhance cytotoxicity with chemotherapeutic agents and targeted compounds, including PIM kinase inhibitors. Structural studies reveal that GNE-6640 and GNE-6776 non-covalently target USP7 12 Å distant from the catalytic cysteine. The compounds attenuate ubiquitin binding and thus inhibit USP7 deubiquitinase activity. GNE-6640 and GNE-6776 interact with acidic residues that mediate hydrogen-bond interactions with the ubiquitin Lys48 side chain, suggesting that USP7 preferentially interacts with and cleaves ubiquitin moieties that have free Lys48 side chains. We investigated this idea by engineering di-ubiquitin chains containing differential proximal and distal isotopic labels and measuring USP7 binding by nuclear magnetic resonance. This preferential binding protracted the depolymerization kinetics of Lys48-linked ubiquitin chains relative to Lys63-linked chains. In summary, engineering compounds that inhibit USP7 activity by attenuating ubiquitin binding suggests opportunities for developing other deubiquitinase inhibitors and may be a strategy more broadly applicable to inhibiting proteins that require ubiquitin binding for full functional activity.

Identifying and mitigating batch effects in whole genome sequencing data.

BACKGROUND: Large sample sets of whole genome sequencing with deep coverage are being generated, however assembling datasets from different sources inevitably introduces batch effects. These batch effects are not well understood and can be due to changes in the sequencing protocol or bioinformatics tools used to process the data. No systematic algorithms or heuristics exist to detect and filter batch effects or remove associations impacted by batch effects in whole genome sequencing data. RESULTS: We describe key quality metrics, provide a freely available software package to compute them, and demonstrate that identification of batch effects is aided by principal components analysis of these metrics. To mitigate batch effects, we developed new site-specific filters that identified and removed variants that falsely associated with the phenotype due to batch effect. These include filtering based on: a haplotype based genotype correction, a differential genotype quality test, and removing sites with missing genotype rate greater than 30% after setting genotypes with quality scores less than 20 to missing. This method removed 96.1% of unconfirmed genome-wide significant SNP associations and 97.6% of unconfirmed genome-wide significant indel associations. We performed analyses to demonstrate that: 1) These filters impacted variants known to be disease associated as 2 out of 16 confirmed associations in an AMD candidate SNP analysis were filtered, representing a reduction in power of 12.5%, 2) In the absence of batch effects, these filters removed only a small proportion of variants across the genome (type I error rate of 3%), and 3) in an independent dataset, the method removed 90.2% of unconfirmed genome-wide SNP associations and 89.8% of unconfirmed genome-wide indel associations. CONCLUSIONS: Researchers currently do not have effective tools to identify and mitigate batch effects in whole genome sequencing data. We developed and validated methods and filters to address this deficiency.

BACE1 across species: a comparison of the in vivo consequences of BACE1 deletion in mice and rats.

Assessing BACE1 (ß-site APP cleaving enzyme 1) knockout mice for general health and neurological function may be useful in predicting risks associated with prolonged pharmacological BACE1 inhibition, a treatment approach currently being developed for Alzheimer's disease. To determine whether BACE1 deletion-associated effects in mice generalize to another species, we developed a novel Bace1-/- rat line using zinc-finger nuclease technology and compared Bace1-/- mice and rats with their Bace1+/+ counterparts. Lack of BACE1 was confirmed in Bace1-/- animals from both species. Removal of BACE1 affected startle magnitude, balance beam performance, pain response, and nerve myelination in both species. While both mice and rats lacking BACE1 have shown increased mortality, the increase was smaller and restricted to early developmental stages for rats. Bace1-/- mice and rats further differed in body weight, spontaneous locomotor activity, and prepulse inhibition of startle. While the effects of species and genetic background on these phenotypes remain difficult to distinguish, our findings suggest that BACE1's role in myelination and some sensorimotor functions is consistent between mice and rats and may be conserved in other species. Other phenotypes differ between these models, suggesting that some effects of BACE1 inhibition vary with the biological context (e.g. species or background strain).

The molecular landscape of high-risk early breast cancer: comprehensive biomarker analysis of a phase III adjuvant population.

Breast cancer is a heterogeneous disease and patients are managed clinically based on ER, PR, HER2 expression, and key risk factors. We sought to characterize the molecular landscape of high-risk breast cancer patients enrolled onto an adjuvant chemotherapy study to understand how disease subsets and tumor immune status impact survival. DNA and RNA were extracted from 861 breast cancer samples from patients enrolled onto the United States Oncology trial 01062. Samples were characterized using multiplex gene expression, copy number, and qPCR mutation assays. HR+ patients with a PIK3CA mutant tumor had a favorable disease-free survival (DFS; HR 0.66, P=0.05), however, the prognostic effect was specific to luminal A patients (Luminal A: HR 0.67, P=0.1; Luminal B: HR 1.01, P=0.98). Molecular subtyping of triple-negative breast cancers (TNBCs) suggested that the mesenchymal subtype had the worst DFS, whereas the immunomodulatory subtype had the best DFS. Profiling of immunologic genes revealed that TNBC tumors (n=280) displaying an activated T-cell signature had a longer DFS following adjuvant chemotherapy (HR 0.59, P=0.04), while a distinct set of immune genes was associated with DFS in HR+ cancers. Utilizing a discovery approach, we identified genes associated with a high risk of recurrence in HR+ patients, which were validated in an independent data set. Molecular classification based on PAM50 and TNBC subtyping stratified clinical high-risk patients into distinct prognostic subsets. Patients with high expression of immune-related genes showed superior DFS in both HR+ and TNBC. These results may inform patient management and drug development in early breast cancer.