A Multipathway Phosphopeptide Standard for Rapid Phosphoproteomics Assay Development.

Recent advances in methodology have made phosphopeptide analysis a tractable problem for many proteomics researchers. There are now a wide variety of robust and accessible enrichment strategies to generate phosphoproteomes while free or inexpensive software tools for quantitation and site localization have simplified phosphoproteome analysis workflow tremendously. As a research group under the Association for Biomolecular Resource Facilities umbrella, the Proteomics Standards Research Group has worked to develop a multipathway phosphopeptide standard based on a mixture of heavy-labeled phosphopeptides designed to enable researchers to rapidly develop assays. This mixture contains 131 mass spectrometry vetted phosphopeptides specifically chosen to cover as many known biologically interesting phosphosites as possible from seven different signaling networks: AMPK signaling, death and apoptosis signaling, ErbB signaling, insulin/insulin-like growth factor-1 signaling, mTOR signaling, PI3K/AKT signaling, and stress (p38/SAPK/JNK) signaling. Here, we describe a characterization of this mixture spiked into a HeLa tryptic digest stimulated with both epidermal growth factor and insulin-like growth factor-1 to activate the MAPK and PI3K/AKT/mTOR pathways. We further demonstrate a comparison of phosphoproteomic profiling of HeLa performed independently in five labs using this phosphopeptide mixture with data-independent acquisition. Despite different experimental and instrumentation processes, we found that labs could produce reproducible, harmonized datasets by reporting measurements as ratios to the standard, while intensity measurements showed lower consistency between labs even after normalization. Our results suggest that widely available, biologically relevant phosphopeptide standards can act as a quantitative "yardstick" across laboratories and sample preparations enabling experimental designs larger than a single laboratory can perform. Raw data files are publicly available in the MassIVE dataset MSV000090564.

ProteomicsML: An Online Platform for Community-Curated Data sets and Tutorials for Machine Learning in Proteomics.

Data set acquisition and curation are often the most difficult and time-consuming parts of a machine learning endeavor. This is especially true for proteomics-based liquid chromatography (LC) coupled to mass spectrometry (MS) data sets, due to the high levels of data reduction that occur between raw data and machine learning-ready data. Since predictive proteomics is an emerging field, when predicting peptide behavior in LC-MS setups, each lab often uses unique and complex data processing pipelines in order to maximize performance, at the cost of accessibility and reproducibility. For this reason we introduce ProteomicsML, an online resource for proteomics-based data sets and tutorials across most of the currently explored physicochemical peptide properties. This community-driven resource makes it simple to access data in easy-to-process formats, and contains easy-to-follow tutorials that allow new users to interact with even the most advanced algorithms in the field. ProteomicsML provides data sets that are useful for comparing state-of-the-art machine learning algorithms, as well as providing introductory material for teachers and newcomers to the field alike. The platform is freely available at https://www.proteomicsml.org/, and we welcome the entire proteomics community to contribute to the project at https://github.com/ProteomicsML/ProteomicsML.

Design and Evaluation of a Computational Phenotype to Identify Patients With Metastatic Breast Cancer Within the Electronic Health Record.

PURPOSE: Outcomes for patients with metastatic breast cancer (MBC) are continually improving as more effective treatments become available. Granular data sets of this unique population are lacking, and the standard method for data collection relies largely on chart review. Therefore, using electronic health records (EHR) collected at a tertiary hospital system, we developed and evaluated a computational phenotype designed to identify all patients with MBC, and we compared the effectiveness of this algorithm against the gold standard, clinical chart review. METHODS: A cohort of patients with breast cancer were identified according to International Classification of Diseases codes, the institutional tumor registry, and SNOMED codes. Chart review was performed to determine whether distant metastases had occurred. We developed a computational phenotype, on the basis of SNOMED concept IDs, which was applied to the EHR to identify patients with MBC. Contingency tables were used to aggregate and compare results. RESULTS: A total of 1,741 patients with breast cancer were identified using data from International Classification of Diseases codes, the tumor registry, and/or SNOMED concept identifiers. Chart review of all patients classified each patient as having MBC (n = 416; 23.9%) versus not (n = 1,325; 75.9%). The final computational phenotype successfully classified 1,646 patients (95% accuracy; 82% sensitivity; 99% specificity). CONCLUSION: Hospital systems with robust EHRs and reliable mapping to SNOMED have the ability to use standard codes to derive computational phenotypes. These algorithms perform reasonably well and have the added ability to be run at disparate health care facilities. Better tooling to navigate the polyhierarchical structure of SNOMED ontology could yield better-performing computational phenotypes.

Low-touch, team-based care for co-morbidity management in cancer patients: the ONE TEAM randomized controlled trial.

BACKGROUND: As treatments for cancer have improved, more people are surviving cancer. However, compared to people without a history of cancer, cancer survivors are more likely to die of cardiovascular disease (CVD). Increased risk for CVD-related mortality among cancer survivors is partially due to lack of medication adherence and problems that exist in care coordination between cancer specialists, primary care physicians, and cardiologists. METHODS/DESIGN: The Onco-primary care networking to support TEAM-based care (ONE TEAM) study is an 18-month cluster-randomized controlled trial with clustering at the primary care clinic level. ONE TEAM compares the provision of the iGuide intervention to patients and primary care providers versus an education-only control. For phase 1, at the patient level, the intervention includes video vignettes and a live webinar; provider-level interventions include electronic health records-based communication and case-based webinars. Participants will be enrolled from across North Carolina one of their first visits with a cancer specialist (e.g., surgeon, radiation or medical oncologist). We use a sequential multiple assignment randomized trial (SMART) design. Outcomes (measured at the patient level) will include Healthcare Effectiveness Data and Information Set (HEDIS) quality measures of management of three CVD comorbidities using laboratory testing (glycated hemoglobin [A1c], lipid profile) and blood pressure measurements; (2) medication adherence assessed pharmacy refill data using Proportion of Days Covered (PDC); and (3) patient-provider communication (Patient-Centered Communication in Cancer Care, PCC-Ca-36). Primary care clinics in the intervention arm will be considered non-responders if 90% or more of their participating patients do not meet the modified HEDIS quality metrics at the 6-month measurement, assessed once the first enrollee from each practice reaches the 12-month mark. Non-responders will be re-randomized to either continue to receive the iGuide 1 intervention, or to receive the iGuide 2 intervention, which includes tailored videos for participants and specialist consults with primary care providers. DISCUSSION: As the population of cancer survivors grows, ONE TEAM will contribute to closing the CVD outcomes gap among cancer survivors by optimizing and integrating cancer care and primary care teams. ONE TEAM is designed so that it will be possible for others to emulate and implement at scale. TRIAL REGISTRATION: This study (NCT04258813) was registered in clinicaltrals.gov on February 6, 2020.

Rewinding the Molecular Clock: Looking at Pioneering Molecular Phylogenetics Experiments in the Light of Proteomics.

Science is full of overlooked and undervalued research waiting to be rediscovered. Proteomics is no exception. In this perspective, we follow the ripples from a 1960 study of Zuckerkandl, Jones, and Pauling comparing tryptic peptides across animal species. This pioneering work directly led to the molecular clock hypothesis and the ensuing explosion in molecular phylogenetics. In the decades following, proteins continued to provide essential clues on evolutionary history. While technology has continued to improve, contemporary proteomics has strayed from this larger biological context, rarely comparing species or asking how protein structure, function, and interactions have evolved. Here we recombine proteomics with molecular phylogenetics, highlighting the value of framing proteomic results in a larger biological context and how almost forgotten research, though technologically surpassed, can still generate new ideas and illuminate our work from a different perspective. Though it is infeasible to read all research published on a large topic, looking up older papers can be surprisingly rewarding when rediscovering a "gem" at the end of a long citation chain, aided by digital collections and perpetually helpful librarians. Proper literature study reduces unnecessary repetition and allows research to be more insightful and impactful by truly standing on the shoulders of giants. All data was uploaded to MassIVE (https://massive.ucsd.edu/) as dataset MSV000087993.

Hi-C scaffolded short- and long-read genome assemblies of the California sea lion are broadly consistent for syntenic inference across 45 million years of evolution.

With the advent of chromatin-interaction maps, chromosome-level genome assemblies have become a reality for a wide range of organisms. Scaffolding quality is, however, difficult to judge. To explore this gap, we generated multiple chromosome-scale genome assemblies of an emerging wild animal model for carcinogenesis, the California sea lion (Zalophus californianus). Short-read assemblies were scaffolded with two independent chromatin interaction mapping data sets (Hi-C and Chicago), and long-read assemblies with three data types (Hi-C, optical maps and 10X linked reads) following the "Vertebrate Genomes Project (VGP)" pipeline. In both approaches, 18 major scaffolds recovered the karyotype (2n = 36), with scaffold N50s of 138 and 147 Mb, respectively. Synteny relationships at the chromosome level with other pinniped genomes (2n = 32-36), ferret (2n = 34), red panda (2n = 36) and domestic dog (2n = 78) were consistent across approaches and recovered known fissions and fusions. Comparative chromosome painting and multicolour chromosome tiling with a panel of 264 genome-integrated single-locus canine bacterial artificial chromosome probes provided independent evaluation of genome organization. Broad-scale discrepancies between the approaches were observed within chromosomes, most commonly in translocations centred around centromeres and telomeres, which were better resolved in the VGP assembly. Genomic and cytological approaches agreed on near-perfect synteny of the X chromosome, and in combination allowed detailed investigation of autosomal rearrangements between dog and sea lion. This study presents high-quality genomes of an emerging cancer model and highlights that even highly fragmented short-read assemblies scaffolded with Hi-C can yield reliable chromosome-level scaffolds suitable for comparative genomic analyses.

Proteogenomic Assessment of Intraspecific Venom Variability: Molecular Adaptations in the Venom Arsenal of Conus purpurascens.

Cone snails produce venom that contains diverse groups of peptides (conopeptides/conotoxins) and display a wide mass range, high rate of posttranslational modifications, and many potential pharmacological targets. Here we employ a proteogenomic approach to maximize conopeptide identification from the injected venom of Conus purpurascens. mRNA sequences from C. purpurascens venom ducts were assembled into a search database and complemented with known sequences and de novo approaches. We used a top-down peptidomic approach and tandem mass spectrometry identification to compare injected venom samples of 27 specimens. This intraspecific analysis yielded 543 unique conopeptide identifications, which included 33 base conopeptides and their toxiforms, 21 of which are novel. The results reveal two distinct venom profiles with different synergistic interactions to effectively target neural pathways aimed to immobilize prey. These venom expression patterns will aid target prediction, a significant step toward developing conotoxins into valuable drugs or neural probes.

Cloudy with a Chance of Peptides: Accessibility, Scalability, and Reproducibility with Cloud-Hosted Environments.

Cloud-hosted environments offer known benefits when computational needs outstrip affordable local workstations, enabling high-performance computation without a physical cluster. What has been less apparent, especially to novice users, is the transformative potential for cloud-hosted environments to bridge the digital divide that exists between poorly funded and well-resourced laboratories, and to empower modern research groups with remote personnel and trainees. Using cloud-based proteomic bioinformatic pipelines is not predicated on analyzing thousands of files, but instead can be used to improve accessibility during remote work, extreme weather, or working with under-resourced remote trainees. The general benefits of cloud-hosted environments also allow for scalability and encourage reproducibility. Since one possible hurdle to adoption is awareness, this paper is written with the nonexpert in mind. The benefits and possibilities of using a cloud-hosted environment are emphasized by describing how to setup an example workflow to analyze a previously published label-free data-dependent acquisition mass spectrometry data set of mammalian urine. Cost and time of analysis are compared using different computational tiers, and important practical considerations are described. Overall, cloud-hosted environments offer the potential to solve large computational problems, but more importantly can enable and accelerate research in smaller research groups with inadequate infrastructure and suboptimal local computational resources.

Mixed-Methods Study to Predict Upstaging of DCIS to Invasive Disease on Mammography.

BACKGROUND. The incidence of ductal carcinoma in situ (DCIS) has steadily increased, as have concerns regarding overtreatment. Active surveillance is a novel treatment strategy that avoids surgical excision, but identifying patients with occult invasive disease who should be excluded from active surveillance is challenging. Radiologists are not typically expected to predict the upstaging of DCIS to invasive disease, though they might be trained to perform this task. OBJECTIVE. The purpose of this study was to determine whether a mixed-methods two-stage observer study can improve radiologists' ability to predict upstaging of DCIS to invasive disease on mammography. METHODS. All cases of DCIS calcifications that underwent stereotactic biopsy between 2010 and 2015 were identified. Two cohorts were randomly generated, each containing 150 cases (120 pure DCIS cases and 30 DCIS cases upstaged to invasive disease at surgery). Nine breast radiologists reviewed the mammograms in the first cohort in a blinded fashion and scored the probability of upstaging to invasive disease. The radiologists then reviewed the cases and results collectively in a focus group to develop consensus criteria that could improve their ability to predict upstaging. The radiologists reviewed the mammograms from the second cohort in a blinded fashion and again scored the probability of upstaging. Statistical analysis compared the performances between rounds 1 and 2. RESULTS. The mean AUC for reader performance in predicting upstaging in round 1 was 0.623 (range, 0.514-0.684). In the focus group, radiologists agreed that upstaging was better predicted when an associated mass, asymmetry, or architectural distortion was present; when densely packed calcifications extended over a larger area; and when the most suspicious features were focused on rather than the most common features. Additionally, radiologists agreed that BI-RADS descriptors do not adequately characterize risk of invasion, and that microinvasive disease and smaller areas of DCIS will have poor prediction estimates. Reader performance significantly improved in round 2 (mean AUC, 0.765; range, 0.617-0.852; p = .045). CONCLUSION. A mixed-methods two-stage observer study identified factors that helped radiologists significantly improve their ability to predict upstaging of DCIS to invasive disease. CLINICAL IMPACT. Breast radiologists can be trained to better predict upstaging of DCIS to invasive disease, which may facilitate discussions with patients and referring providers.

Proteomic Analysis of Urine from California Sea Lions ( Zalophus californianus): A Resource for Urinary Biomarker Discovery.

Urinary markers for the assessment of kidney diseases in wild animals are limited, in part, due to the lack of urinary proteome data, especially for marine mammals. One of the most prevalent kidney diseases in marine mammals is caused by Leptospira interrogans, which is the second most common etiology linked to stranding of California sea lions ( Zalophus californianus). Urine proteins from 11 sea lions with leptospirosis kidney disease and eight sea lions without leptospirosis or kidney disease were analyzed using shotgun proteomics. In total, 2694 protein groups were identified, and 316 were differentially abundant between groups. Major urine proteins in sea lions were similar to major urine proteins in dogs and humans except for the preponderance of resistin, lysozyme C, and PDZ domain containing 1, which appear to be over-represented. Previously reported urine protein markers of kidney injury in humans and animals were also identified. Notably, neutrophil gelatinase-associated lipocalin, osteopontin, and epidermal fatty acid binding protein were elevated over 20-fold in the leptospirosis-infected sea lions. Consistent with leptospirosis infection in rodents, urinary proteins associated with the renin-angiotensin system were depressed, including neprilysin. This study represents a foundation from which to explore the clinical use of urinary protein markers in California sea lions.

C3a receptor antagonism as a novel therapeutic target for chronic rhinosinusitis.

Chronic rhinosinusitis with nasal polyps (CRSwNP) is an inflammatory disease with an unknown etiology. Recent studies have implicated the complement system as a potential modulator of disease immunopathology. We performed proteomic pathway enrichment analysis of differentially increased proteins, and found an enrichment of complement cascade pathways in the nasal mucus of individuals with CRSwNP as compared to control subjects. Sinonasal mucus levels of complement 3 (C3) correlated with worse subjective disease severity, whereas no significant difference in systemic C3 levels could be determined in plasma samples. Given that human sinonasal epithelial cells were the predominate sinonasal source of C3 and complement anaphylatoxin 3a (C3a) staining, we focused on their role in in vitro studies. Baseline intracellular C3 levels were higher in CRSwNP cells, and following exposure to Aspergillus fumigatus (Af) extract, they released significantly more C3 and C3a. Inhibition of complement 3a receptor (C3aR) signaling led to a decrease in Af-induced C3 and C3a release, both in vitro and in vivo. Finally, we found in vivo that C3aR deficiency or inhibition significantly reduced inflammation and CRS development in a mouse model of Af-induced CRS. These findings demonstrate that local sinonasal complement activation correlates with subjective disease severity, and that local C3aR antagonism significantly ameliorates Af-induced CRS in a rodent model.

One Size Does Not Fit All: Disease Profiles of Serious Illness Patients Receiving Specialty Palliative Care.

INTRODUCTION: Understanding the symptom profiles of seriously ill patients who receive palliative care, especially noncancer diagnoses where the data are sparse and are critical to better targeting our resources to the needs of patients. METHODS: We performed a retrospective, multicohort study of patients evaluated during their first consultative palliative care visit in a community-based palliative care registry. We placed into one of seven major disease categories based on clinician-reported primary diagnosis for consultation. Our primary aim of this analysis was to determine the univariate association between several patient-specific characteristics (e.g., demographics, care of setting, initial screening score) and the primary diagnosis. RESULTS: We evaluated the first visit consultation records of 1615 patients. Most prevalent diagnosis was Neurologic (564; 35%), followed by Cardiovascular (266; 16%), Pulmonary (229; 14%), and Cancer (208; 13%). Patients in the study with the highest symptom burden were those diagnosed with cancer or pulmonary disease, with 45% and 37% of cancer and pulmonary patients, respectively, having two or more moderate-to-severe symptoms; 26% of cardiovascular disease patients reported two or more moderate-to-severe symptoms, whereas 11% reported three or more. Patients with a neurologic or infectious diagnosis had less symptom burden, but a large percentage of neurologic patients were unable to respond. DISCUSSION: This study is one of the first to describe symptom burden and functional scores by diagnostic categories and care settings across a community-based interdisciplinary specialty palliative care program. Results demonstrated statistically significant and clinically relevant differences among settings of care, functional status, and symptom profiles between patients with various serious illnesses.

Predicting the risk of bleeding during dual antiplatelet therapy after acute coronary syndromes.

OBJECTIVES: Dual antiplatelet therapy (DAPT) with aspirin + a P2Y12 inhibitor is recommended for at least 12 months for patients with acute coronary syndrome (ACS), with shorter durations considered for patients with increased bleeding risk. However, there are no decision support tools available to predict an individual patient's bleeding risk during DAPT treatment in the post-ACS setting. METHODS: To develop a longitudinal bleeding risk prediction model, we analy sed 9240 patients with unstable angina/non-ST segment elevation myocardial infarction (NSTEMI) from the Targeted Platelet Inhibition to Clarify the Optimal Strategy to Medically Manage Acute Coronary Syndromes (TRILOGY ACS) trial, who were managed without revasculari sation and treated with DAPT for a median of 14.8 months. RESULTS: We identified 10 significant baseline predictors of non-coronary artery bypass grafting (CABG)-related Global Use of Strategies to Open Occluded Arteries (GUSTO) severe/life-threatening/moderate bleeding: age, sex, weight, NSTEMI (vs unstable angina), angiography performed before randomi sation, prior peptic ulcer disease, creatinine, systolic blood pressure, haemoglobin and treatment with beta-blocker. The five significant baseline predictors of Thrombolysis In Myocardial Infarction (TIMI) major or minor bleeding included age, sex, angiography performed before randomi sation, creatinine and haemoglobin. The models showed good predictive accuracy with Therneau's C-indices: 0.78 (SE = 0.024) for the GUSTO model and 0.67 (SE = 0.023) for the TIMI model. Internal validation with bootstrapping gave similar C-indices of 0.77 and 0.65, respectively. External validation demonstrated an attenuated C-index for the GUSTO model (0.69) but not the TIMI model (0.68). CONCLUSIONS: Longitudinal bleeding risks during treatment with DAPT in patients with ACS can be reliably predicted using selected baseline characteristics. The TRILOGY ACS bleeding models can inform risk -benefit considerations regarding the duration of DAPT following ACS. TRIAL REGISTRATION: ClinicalTrials.gov identifier: https://clinicaltrials.gov/ct2/show/NCT00699998.

Hormonally up-regulated neu-associated kinase: A novel target for breast cancer progression.

Hormonally up-regulated neu-associated Kinase (Hunk) is a protein kinase that was originally identified in the murine mammary gland and has been shown to be highly expressed in Human Epidermal Growth Factor Receptor 2 positive (HER2+/ErbB2+) breast cancer cell lines as well as MMTV-neu derived mammary tumor cell lines. However, the physiological role of Hunk has been largely elusive since its identification. Though Hunk is predicted to be a Serine/Threonine (Ser/Thr) protein kinase with homology to the SNF1/AMPK family of protein kinases, there are no known Hunk substrates that have been identified to date. Recent work demonstrates a role for Hunk in HER2+/ErbB2+ breast cancer progression, including drug resistance to HER2/ErbB2 inhibitors, with Hunk potentially acting downstream of HER2/ErbB2 and the PI3K/Akt pathway. These studies have collectively shown that Hunk plays a vital role in promoting mammary tumorigenesis, as Hunk knockdown via shRNA in xenograft tumor models or crossing MMTV-neu or Pten-deficient genetically engineered mouse models into a Hunk knockout (Hunk-/-) background impairs mammary tumor growth in vivo. Because the majority of HER2+/ErbB2+ breast cancer patients acquire drug resistance to HER2/ErbB2 inhibitors, the characterization of novel drug targets like Hunk that have the potential to simultaneously suppress tumorigenesis and potentially enhance efficacy of current therapeutics is an important facet of drug development. Therefore, work aimed at uncovering specific regulatory functions for Hunk that could contribute to this protein kinase's role in both tumorigenesis and drug resistance will be informative. This review focuses on what is currently known about this under-studied protein kinase, and how targeting Hunk may prove to be a potential therapeutic target for the treatment of breast cancer.

Proteomic Profiling of Serial Prediagnostic Serum Samples for Early Detection of Colon Cancer in the U.S. Military.

Background: Serum proteomic biomarkers offer a promising approach for early detection of cancer. In this study, we aimed to identify proteomic profiles that could distinguish colon cancer cases from controls using serial prediagnostic serum samples.Methods: This was a nested case-control study of active duty military members. Cases consisted of 264 patients diagnosed with colon cancer between 2001 and 2009. Controls were matched to cases on age, gender, race, serum sample count, and collection date. We identified peaks that discriminated cases from controls using random forest data analysis with a 2/3 training and 1/3 validation dataset. We then included epidemiologic data to see whether further improvement of model performance was obtainable. Proteins that corresponded to discriminatory peaks were identified.Results: Peaks with m/z values of 3,119.32, 2,886.67, 2,939.23, and 5,078.81 were found to discriminate cases from controls with a sensitivity of 69% and a specificity of 67% in the year before diagnosis. When smoking status was included, sensitivity increased to 76% while histories of other cancer and tonsillectomy raised specificity to 76%. Peaks at 2,886.67 and 3,119.32 m/z were identified as histone acetyltransferases while 2,939.24 m/z was a transporting ATPase subunit.Conclusions: Proteomic profiles in the year before cancer diagnosis have the potential to discriminate colon cancer patients from controls, and the addition of epidemiologic information may increase the sensitivity and specificity of discrimination.Impact: Our findings indicate the potential value of using serum prediagnostic proteomic biomarkers in combination with epidemiologic data for early detection of colon cancer. Cancer Epidemiol Biomarkers Prev; 26(5); 711-8. ©2016 AACR.

Impact of glycoprotein IIb/IIIa inhibitors on the efficacy and safety of ticagrelor compared with clopidogrel in patients with acute coronary syndromes: Analysis from the Platelet Inhibition and Patient Outcomes (PLATO) Trial.

BACKGROUND: Ticagrelor reduced cardiovascular events compared with clopidogrel in PLATO without increasing overall major bleeding. We evaluated whether the use of glycoprotein IIb/IIIa inhibitor (GPI) impacts the relative efficacy and safety of ticagrelor compared with clopidogrel. METHODS: PLATO randomized 18,624 subjects with acute coronary syndrome to ticagrelor versus clopidogrel. The primary efficacy end point was cardiovascular death/myocardial infarction/stroke, and the primary safety end point was major bleeding. The use of GPI was at the physician's discretion and open-label. We evaluated outcomes at 30 days stratified by GPI use in the subgroup of 9,983 patients who underwent percutaneous coronary intervention (PCI) within 72 hours. RESULTS: A total of 4,020 (40%) received a GPI. Those receiving a GPI were more likely to be younger, be male, and undergo multivessel PCI. There was no interaction between treatment and GPI use for the primary efficacy and safety end points. Patients treated without GPI had a lower rate of definite stent thrombosis and higher rate of minor/major bleeding with ticagrelor compared with clopidogrel (P < .05), whereas there was no such difference with GPI (P interaction < .05). CONCLUSIONS: In patients with acute coronary syndrome undergoing early PCI, the efficacy and safety of ticagrelor as compared with clopidogrel were not modified by GPI use according to the primary efficacy and safety end point of the trial, although there were indications of greater benefit on definite stent thrombosis and more major or minor bleeding with ticagrelor in patients without (vs with) GPI treatment.

Proteotranscriptomic Analysis Reveals Stage Specific Changes in the Molecular Landscape of Clear-Cell Renal Cell Carcinoma.

Renal cell carcinoma comprises 2 to 3% of malignancies in adults with the most prevalent subtype being clear-cell RCC (ccRCC). This type of cancer is well characterized at the genomic and transcriptomic level and is associated with a loss of VHL that results in stabilization of HIF1. The current study focused on evaluating ccRCC stage dependent changes at the proteome level to provide insight into the molecular pathogenesis of ccRCC progression. To accomplish this, label-free proteomics was used to characterize matched tumor and normal-adjacent tissues from 84 patients with stage I to IV ccRCC. Using pooled samples 1551 proteins were identified, of which 290 were differentially abundant, while 783 proteins were identified using individual samples, with 344 being differentially abundant. These 344 differentially abundant proteins were enriched in metabolic pathways and further examination revealed metabolic dysfunction consistent with the Warburg effect. Additionally, the protein data indicated activation of ESRRA and ESRRG, and HIF1A, as well as inhibition of FOXA1, MAPK1 and WISP2. A subset analysis of complementary gene expression array data on 47 pairs of these same tissues indicated similar upstream changes, such as increased HIF1A activation with stage, though ESRRA and ESRRG activation and FOXA1 inhibition were not predicted from the transcriptomic data. The activation of ESRRA and ESRRG implied that HIF2A may also be activated during later stages of ccRCC, which was confirmed in the transcriptional analysis. This combined analysis highlights the importance of HIF1A and HIF2A in developing the ccRCC molecular phenotype as well as the potential involvement of ESRRA and ESRRG in driving these changes. In addition, cofilin-1, profilin-1, nicotinamide N-methyltransferase, and fructose-bisphosphate aldolase A were identified as candidate markers of late stage ccRCC. Utilization of data collected from heterogeneous biological domains strengthened the findings from each domain, demonstrating the complementary nature of such an analysis. Together these results highlight the importance of the VHL/HIF1A/HIF2A axis and provide a foundation and therapeutic targets for future studies. (Data are available via ProteomeXchange with identifier PXD003271 and MassIVE with identifier MSV000079511.).

Time-Varying Effects of Prasugrel Versus Clopidogrel on the Long-Term Risks of Stroke After Acute Coronary Syndromes: Results From the TRILOGY ACS Trial.

BACKGROUND AND PURPOSE: The role of more intense, sustained platelet inhibition in preventing stroke after acute coronary syndrome (ACS) is unclear. We observed a signal for reduced stroke risk in the Targeted Platelet Inhibition to Clarify the Optimal Strategy to Medically Manage Acute Coronary Syndromes (TRILOGY ACS) trial after 12 months of treatment with prasugrel versus clopidogrel in medically managed patients with ACS. METHODS: We examined 7243 patients with ACS, aged <75 years and without prior stroke, analyzing differences in baseline characteristics between patients with and without a stroke event through 30 months with a Cox proportional hazards model. We also assessed the effect of prasugrel versus clopidogrel (plus aspirin) on risk of all stroke events and ischemic stroke over time with an extended Cox proportional hazards model. RESULTS: Stroke events were infrequent through 30 months (ischemic stroke=62; hemorrhagic stroke=15). Patients with stroke were older, had more comorbidities, and had a higher Global Registry of Acute Coronary Events (GRACE) risk score. There was a trend for a lower unadjusted frequency of all stroke events through 30 months for prasugrel versus clopidogrel: 31 (1.5%) versus 46 (2.2%); P=0.08. There was a significant treatment-by-time interaction for those with ischemic stroke (P=0.03), consistent with the 12-month landmarked Kaplan-Meier log-rank test showing a reduced hazard of ischemic stroke after 12 months with prasugrel (P=0.04). No significant interactions between treatment effect of prasugrel versus clopidogrel and time were observed for all stroke events. CONCLUSIONS: We observed a potential late treatment effect for prasugrel versus clopidogrel for a reduced risk of ischemic stroke in medically managed patients with ACS aged <75 years. These hypothesis-generating findings suggest that longer duration and more potent platelet inhibition with prasugrel may be associated with lower risk of ischemic stroke after 12 months. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00699998.

Changes in Protein Expression and Lysine Acetylation Induced by Decreased Glutathione Levels in Astrocytes.

Astrocytes and neurons form a highly specialized functional unit, and the loss or gain of astrocytic functions can influence the initiation and progression of different neurodegenerative diseases. Neurons depend on the antioxidant protection provided by neighboring astrocytes. Glutathione (γ-l-glutamyl-l-cysteinyl-glycine) is a major component of the antioxidant system that defends cells against the toxic effects of reactive oxygen/nitrogen species. A decline in glutathione levels has been observed in aging and neurodegenerative diseases, and it aggravates the pathology in an amyotrophic lateral sclerosis-mouse model. Using a SILAC-based quantitative proteomic approach, we analyzed changes in global protein expression and lysine acetylation in primary astrocyte cultures obtained from wild-type mice or those deficient in the glutamate-cysteine ligase modifier subunit (GCLM). GCLM knockout astrocytes display an ∼80% reduction in total glutathione levels. We identified potential molecular targets and novel sites of acetylation that are affected by the chronic decrease in glutathione levels and observed a response mediated by Nrf2 activation. In addition, sequence analysis of peptides displaying increased acetylation in GCLM knockout astrocytes revealed an enrichment of cysteine residues in the vicinity of the acetylation site, which suggests potential crosstalk between lysine-acetylation and cysteine modification. Regulation of several metabolic and antioxidant pathways was observed at the level of protein expression and lysine acetylation, revealing a coordinated response involving transcriptional and posttranslational regulation.

Concomitant proton-pump inhibitor use, platelet activity, and clinical outcomes in patients with acute coronary syndromes treated with prasugrel versus clopidogrel and managed without revascularization: insights from the Targeted Platelet Inhibition to Clarify the Optimal Strategy to Medically Manage Acute Coronary Syndromes trial.

UNLABELLED: Concomitant use of proton-pump inhibitors (PPIs) has been implicated in diminished antiplatelet response to clopidogrel and an increased risk of ischemic events, but primarily among patients undergoing percutaneous coronary intervention. We sought to examine the potential influence of interactions between PPIs and clopidogrel versus prasugrel on platelet reactivity and clinical outcomes after acute coronary syndromes (ACS) in patients managed medically without revascularization. METHODS: This analysis from the TRILOGY ACS trial focused upon the 7,243 ACS patients aged <75 years who were managed without revascularization, randomized to clopidogrel or prasugrel, and followed for a median of 17 months. Proton-pump inhibitor type and use were assessed at each study visit, and 2,049 of the patients in this cohort underwent serial platelet reactivity assessments. RESULTS: Proton-pump inhibitor use (23%) was similar between the clopidogrel and prasugrel groups at baseline and throughout the study. Median on-treatment platelet reactivity values were consistently lower with prasugrel versus clopidogrel irrespective of PPI use. For the primary end point (composite of cardiovascular death, myocardial infarction [MI], or stroke), PPI use modified the unadjusted treatment effect of prasugrel versus clopidogrel (interaction P = .02). After adjusting for differences in baseline characteristics, this treatment effect modification was attenuated for the composite end point (interaction P = .06) but was significant for the MI component end point (interaction P = .01). Similarly, among patients on a PPI, the frequency of MI was significantly lower with prasugrel versus clopidogrel (hazard ratio = 0.61; 95% CI 0.42-0.88). These findings were similar by PPI type (omeprazole and pantoprazole). CONCLUSIONS: Among ACS patients managed without revascularization, use of PPIs did not result in a differential antiplatelet response between prasugrel versus clopidogrel but was associated with a lower incidence of MI with prasugrel. These hypothesis-generating findings suggest that factors besides platelet reactivity may underlie the differential risk of MI observed by treatment assignment with PPI use.