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 non-invasive 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. Additionally, 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 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 non-invasive imaging.

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.

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.

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.

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.

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.

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.

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.

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.

Hominoid-specific enzyme GLUD2 promotes growth of IDH1R132H glioma.

Somatic mutation of isocitrate dehydrogenase 1 (IDH1) is now recognized as the most common initiating event for secondary glioblastoma, a brain tumor type arising with high frequency in the frontal lobe. A puzzling feature of IDH1 mutation is the selective manifestation of glioma as the only neoplasm frequently associated with early postzygotic occurrence of this genomic alteration. We report here that IDH1(R132H) exhibits a growth-inhibitory effect that is abrogated in the presence of glutamate dehydrogenase 2 (GLUD2), a hominoid-specific enzyme purportedly optimized to facilitate glutamate turnover in human forebrain. Using murine glioma progenitor cells, we demonstrate that IDH1(R132H) exerts a growth-inhibitory effect that is paralleled by deficiency in metabolic flux from glucose and glutamine to lipids. Examining human gliomas, we find that glutamate dehydrogenase 1 (GLUD1) and GLUD2 are overexpressed in IDH1-mutant tumors and that orthotopic growth of an IDH1-mutant glioma line is inhibited by knockdown of GLUD1/2. Strikingly, introduction of GLUD2 into murine glioma progenitor cells reverses deleterious effects of IDH1 mutation on metabolic flux and tumor growth. Further, we report that glutamate, a substrate of GLUD2 and a neurotransmitter abundant in mammalian neocortex, can support growth of glioma progenitor cells irrespective of IDH1 mutation status. These findings suggest that specialization of human neocortex for high glutamate neurotransmitter flux creates a metabolic niche conducive to growth of IDH1 mutant tumors.

Conformational dynamics control ubiquitin-deubiquitinase interactions and influence in vivo signaling.

Ubiquitin is a highly conserved eukaryotic protein that interacts with a diverse set of partners to act as a cellular signaling hub. Ubiquitin's conformational flexibility has been postulated to underlie its multifaceted recognition. Here we use computational and library-based means to interrogate core mutations that modulate the conformational dynamics of human ubiquitin. These ubiquitin variants exhibit increased affinity for the USP14 deubiquitinase, with concomitantly reduced affinity for other deubiquitinases. Strikingly, the kinetics of conformational motion are dramatically slowed in these variants without a detectable change in either the ground state fold or excited state population. These variants can be ligated into substrate-linked chains in vitro and in vivo but cannot solely support growth in eukaryotic cells. Proteomic analyses reveal nearly identical interaction profiles between WT ubiquitin and the variants but identify a small subset of altered interactions. Taken together, these results show that conformational dynamics are critical for ubiquitin-deubiquitinase interactions and imply that the fine tuning of motion has played a key role in the evolution of ubiquitin as a signaling hub.

Small molecule inhibition of group I p21-activated kinases in breast cancer induces apoptosis and potentiates the activity of microtubule stabilizing agents.

INTRODUCTION: Breast cancer, the most common cause of cancer-related deaths worldwide among women, is a molecularly and clinically heterogeneous disease. Extensive genetic and epigenetic profiling of breast tumors has recently revealed novel putative driver genes, including p21-activated kinase (PAK)1. PAK1 is a serine/threonine kinase downstream of small GTP-binding proteins, Rac1 and Cdc42, and is an integral component of growth factor signaling networks and cellular functions fundamental to tumorigenesis. METHODS: PAK1 dysregulation (copy number gain, mRNA and protein expression) was evaluated in two cohorts of breast cancer tissues (n=980 and 1,108). A novel small molecule inhibitor, FRAX1036, and RNA interference were used to examine PAK1 loss of function and combination with docetaxel in vitro. Mechanism of action for the therapeutic combination, both cellular and molecular, was assessed via time-lapse microscopy and immunoblotting. RESULTS: We demonstrate that focal genomic amplification and overexpression of PAK1 are associated with poor clinical outcome in the luminal subtype of breast cancer (P=1.29×10(-4) and P=0.015, respectively). Given the role for PAK1 in regulating cytoskeletal organization, we hypothesized that combination of PAK1 inhibition with taxane treatment could be combined to further interfere with microtubule dynamics and cell survival. Consistent with this, administration of docetaxel with either a novel small molecule inhibitor of group I PAKs, FRAX1036, or PAK1 small interfering RNA oligonucleotides dramatically altered signaling to cytoskeletal-associated proteins, such as stathmin, and induced microtubule disorganization and cellular apoptosis. Live-cell imaging revealed that the duration of mitotic arrest mediated by docetaxel was significantly reduced in the presence of FRAX1036, and this was associated with increased kinetics of apoptosis. CONCLUSIONS: Taken together, these findings further support PAK1 as a potential target in breast cancer and suggest combination with taxanes as a viable strategy to increase anti-tumor efficacy.

PAK1 mediates pancreatic cancer cell migration and resistance to MET inhibition.

Pancreatic adenocarcinoma (PDAC) is a major unmet medical need and a deeper understanding of molecular drivers is needed to advance therapeutic options for patients. We report here that p21-activated kinase 1 (PAK1) is a central node in PDAC cells downstream of multiple growth factor signalling pathways, including hepatocyte growth factor (HGF) and MET receptor tyrosine kinase. PAK1 inhibition blocks signalling to cytoskeletal effectors and tumour cell motility driven by HGF/MET. MET antagonists, such as onartuzumab and crizotinib, are currently in clinical development. Given that even highly effective therapies have resistance mechanisms, we show that combination with PAK1 inhibition overcomes potential resistance mechanisms mediated either by activation of parallel growth factor pathways or by direct amplification of PAK1. Inhibition of PAK1 attenuated in vivo tumour growth and metastasis in a model of pancreatic adenocarcinoma. In human tissues, PAK1 is highly expressed in a proportion of PDACs (33% IHC score 2 or 3; n = 304) and its expression is significantly associated with MET positivity (p < 0.0001) and linked to a widespread metastatic pattern in patients (p = 0.067). Taken together, our results provide evidence for a functional role of MET/PAK1 signalling in pancreatic adenocarcinoma and support further characterization of therapeutic inhibitors in this indication.

Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis.

Previously undescribed prognostic subclasses of high-grade astrocytoma are identified and discovered to resemble stages in neurogenesis. One tumor class displaying neuronal lineage markers shows longer survival, while two tumor classes enriched for neural stem cell markers display equally short survival. Poor prognosis subclasses exhibit markers either of proliferation or of angiogenesis and mesenchyme. Upon recurrence, tumors frequently shift toward the mesenchymal subclass. Chromosomal locations of genes distinguishing tumor subclass parallel DNA copy number differences between subclasses. Functional relevance of tumor subtype molecular signatures is suggested by the ability of cell line signatures to predict neurosphere growth. A robust two-gene prognostic model utilizing PTEN and DLL3 expression suggests that Akt and Notch signaling are hallmarks of poor prognosis versus better prognosis gliomas, respectively.

In situ validation of an intestinal stem cell signature in colorectal cancer.

OBJECTIVE: Wnt/Tcf, Lgr5, Ascl2 and/or Bmi1 signalling is believed to define the mouse intestinal stem cell niche(s) from which adenomas arise. The aim of this study was to determine the relevance of these putative intestinal stem cell markers to human colorectal cancer. DESIGN: 19 putative intestinal stem cell markers, including Ascl2 and Lgr5, were identified from published data and an evaluation of a human colorectal gene expression database. Associations between these genes were assessed by isotopic in situ hybridisation (ISH) in 57 colorectal adenocarcinomas. Multiplex fluorescent ISH and chromogenic non-isotopic ISH were performed to confirm expression patterns. The prognostic significance of Lgr5 was assessed in 891 colorectal adenocarcinomas. RESULTS: Ascl2 and Lgr5 were expressed in 85% and 74% of cancers respectively, and expression was positively correlated (p=0.003). Expression of Bmi1 was observed in 47% of cancers but was very weak in 98% of cases with expression. Both Ascl2 and/or Lgr5 were positively correlated with the majority of genes in the signature but neither was correlated with Cdk6, Gpx2, Olfm4 or Tnfrsf19. Lgr5 did not have prognostic significance. CONCLUSION: These data suggest that 74-85% of colorectal cancers express a Lgr5/Ascl2 associated signature and support the hypothesis that they derive from Lgr5(+)/Ascl2(+) crypt stem cells, not Bmi1(+) stem cells. However, Olfm4 was not found to be a useful marker of Lgr5(+) cells in normal colon or tumours. In this large series, Lgr5 expression is not associated with increased tumour aggressiveness, as might be expected from a cancer stem cell marker.

Anti-VEGF antibody therapy does not promote metastasis in genetically engineered mouse tumour models.

Resistance to anti-angiogenic therapy can occur via several potential mechanisms. Unexpectedly, recent studies showed that short-term inhibition of either VEGF or VEGFR enhanced tumour invasiveness and metastatic spread in preclinical models. In an effort to evaluate the translational relevance of these findings, we examined the consequences of long-term anti-VEGF monoclonal antibody therapy in several well-validated genetically engineered mouse tumour models of either neuroendocrine or epithelial origin. Anti-VEGF therapy decreased tumour burden and increased overall survival, either as a single agent or in combination with chemotherapy, in all four models examined. Importantly, neither short- nor long-term exposure to anti-VEGF therapy altered the incidence of metastasis in any of these autochthonous models, consistent with retrospective analyses of clinical trials. In contrast, we observed that sunitinib treatment recapitulated previously reported effects on tumour invasiveness and metastasis in a pancreatic neuroendocrine tumour (PNET) model. Consistent with these results, sunitinib treatment resulted in an up-regulation of the hypoxia marker GLUT1 in PNETs, whereas anti-VEGF did not. These results indicate that anti-VEGF mediates anti-tumour effects and therapeutic benefits without a paradoxical increase in metastasis. Moreover, these data underscore the concept that drugs targeting VEGF ligands and receptors may affect tumour metastasis in a context-dependent manner and are mechanistically distinct from one another.

Complementary proteomic tools for the dissection of apoptotic proteolysis events.

Proteolysis is a key regulatory event that controls intracellular and extracellular signaling through irreversible changes in a protein's structure that greatly alters its function. Here we describe a platform for profiling caspase substrates which encompasses two highly complementary proteomic techniques--the first is a differential gel based approach termed Global Analyzer of SILAC-derived Substrates of Proteolysis (GASSP) and the second involves affinity enrichment of peptides containing a C-terminal aspartic acid residue. In combination, these techniques have enabled the profiling of a large cellular pool of apoptotic-mediated proteolytic events across a wide dynamic range. By applying this integrated proteomic work flow to analyze proteolytic events resulting from the induction of intrinsic apoptosis in Jurkat cells via etoposide treatment, 3346 proteins were quantified, of which 360 proteins were identified as etoposide-induced proteolytic substrates, including 160 previously assigned caspase substrates. In addition to global profiling, a targeted approach using BAX HCT116 isogenic cell lines was utilized to dissect pre- and post-mitochondrial extrinsic apoptotic cleavage events. By employing apoptotic activation with a pro-apoptotic receptor agonist (PARA), a limited set of apoptotic substrates including known caspase substrates such as BH3 interacting-domain death agonist (BID) and Poly (ADP-ribose) polymerase (PARP)-1, and novel substrates such as Basic Transcription Factor 3, TRK-fused gene protein (TFG), and p62/Sequestosome were also identified.

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.