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Lipids are highly structurally diverse molecules involved in a wide variety of biological processes. Here, we use high precision ion mobility-mass spectrometry to compile a structural database of 456 mass-resolved collision cross sections (CCS) of sphingolipid and glycerophospholipid species. Our CCS database comprises sphingomyelin, cerebroside, ceramide, phosphatidylethanolamine, phosphatidylcholine, phosphatidylserine, and phosphatidic acid classes. Primary differences observed are between lipid categories, with sphingolipids exhibiting 2-6% larger CCSs than glycerophospholipids of similar mass, likely a result of the sphingosine backbone's restriction of the sn1 tail length, limiting gas-phase packing efficiency. Acyl tail length and degree of unsaturation are found to be the primary structural descriptors determining CCS magnitude, with degree of unsaturation being four times as influential per mass unit. The empirical CCS values and previously unmapped quantitative structural trends detailed in this work are expected to facilitate prediction of CCS in broadscale lipidomics research.
BACKGROUND - Immune checkpoint inhibitors (ICIs) have substantially improved clinical outcomes in multiple cancer types and are increasingly being used in early disease settings and in combinations of different immunotherapies. However, ICIs can also cause severe or fatal immune-related adverse-events (irAEs). We aimed to identify and characterise cardiovascular irAEs that are significantly associated with ICIs.
METHODS - In this observational, retrospective, pharmacovigilance study, we used VigiBase, WHO's global database of individual case safety reports, to compare cardiovascular adverse event reporting in patients who received ICIs (ICI subgroup) with this reporting in the full database. This study included all cardiovascular irAEs classified by group queries according to the Medical Dictionary for Regulatory Activities, between inception on Nov 14, 1967, and Jan 2, 2018. We evaluated the association between ICIs and cardiovascular adverse events using the reporting odds ratio (ROR) and the information component (IC). IC is an indicator value for disproportionate Bayesian reporting that compares observed and expected values to find associations between drugs and adverse events. IC is the lower end of the IC 95% credibility interval, and an IC value of more than zero is deemed significant. This study is registered with ClinicalTrials.gov, number NCT03387540.
FINDINGS - We identified 31 321 adverse events reported in patients who received ICIs and 16 343 451 adverse events reported in patients treated with any drugs (full database) in VigiBase. Compared with the full database, ICI treatment was associated with higher reporting of myocarditis (5515 reports for the full database vs 122 for ICIs, ROR 11·21 [95% CI 9·36-13·43]; IC 3·20), pericardial diseases (12 800 vs 95, 3·80 [3·08-4·62]; IC 1·63), and vasculitis (33 289 vs 82, 1·56 [1·25-1·94]; IC 0·03), including temporal arteritis (696 vs 18, 12·99 [8·12-20·77]; IC 2·59) and polymyalgia rheumatica (1709 vs 16, 5·13 [3·13-8·40]; IC 1·33). Pericardial diseases were reported more often in patients with lung cancer (49 [56%] of 87 patients), whereas myocarditis (42 [41%] of 103 patients) and vasculitis (42 [60%] of 70 patients) were more commonly reported in patients with melanoma (χ test for overall subgroup comparison, p<0·0001). Vision was impaired in five (28%) of 18 patients with temporal arteritis. Cardiovascular irAEs were severe in the majority of cases (>80%), with death occurring in 61 (50%) of 122 myocarditis cases, 20 (21%) of 95 pericardial disease cases, and five (6%) of 82 vasculitis cases (χ test for overall comparison between pericardial diseases, myocarditis, and vasculitis, p<0·0001).
INTERPRETATION - Treatment with ICIs can lead to severe and disabling inflammatory cardiovascular irAEs soon after commencement of therapy. In addition to life-threatening myocarditis, these toxicities include pericardial diseases and temporal arteritis with a risk of blindness. These events should be considered in patient care and in combination clinical trial designs (ie, combinations of different immunotherapies as well as immunotherapies and chemotherapy).
FUNDING - The Cancer Institut Thématique Multi-Organisme of the French National Alliance for Life and Health Sciences (AVIESAN) Plan Cancer 2014-2019; US National Cancer Institute, National Institutes of Health; the James C. Bradford Jr. Melanoma Fund; and the Melanoma Research Foundation.
Copyright © 2018 Elsevier Ltd. All rights reserved.
Renal medullary carcinoma (RMC) is one of the most aggressive renal cell carcinomas. It predominantly afflicts young adults and adolescents with sickle cell trait and other sickle hemoglobinopathies, and is refractory to targeted and antiangiogenic therapies used in patients with clear-cell renal cell carcinoma. Platinum-based cytotoxic chemotherapy is the mainstay for RMC treatment. On the basis of recent advances in the diagnosis, management, and clinical trial development for RMC, a panel of experts met in October 2017 and developed updated consensus recommendations to inform clinicians, researchers, and patients. Because RMC often aggressively recurs while patients are still recovering from nephrectomy, upfront chemotherapy should be considered for most patients, including those with localized disease. After safety and dosing information has been established in adults, phase II and III trials enrolling patients with RMC should allow patients aged 12 years and older to be accrued. Patients with the very rare unclassified renal cell carcinoma with medullary phenotype variant should be included in RMC trials. Medical providers should be aware that RMC can afflict subjects of all races, and not only those of African descent, and that the presence of sickle cell trait, or of other sickle hemoglobinopathies, can affect drug responses and toxicity.
Copyright © 2018 Elsevier Inc. All rights reserved.
Importance - Immune checkpoint inhibitors (ICIs) are now a mainstay of cancer treatment. Although rare, fulminant and fatal toxic effects may complicate these otherwise transformative therapies; characterizing these events requires integration of global data.
Objective - To determine the spectrum, timing, and clinical features of fatal ICI-associated toxic effects.
Design, Setting, and Participants - We retrospectively queried a World Health Organization (WHO) pharmacovigilance database (Vigilyze) comprising more than 16 000 000 adverse drug reactions, and records from 7 academic centers. We performed a meta-analysis of published trials of anti-programmed death-1/ligand-1 (PD-1/PD-L1) and anti-cytotoxic T lymphocyte antigen-4 (CTLA-4) to evaluate their incidence using data from large academic medical centers, global WHO pharmacovigilance data, and all published ICI clinical trials of patients with cancer treated with ICIs internationally.
Exposures - Anti-CTLA-4 (ipilimumab or tremelimumab), anti-PD-1 (nivolumab, pembrolizumab), or anti-PD-L1 (atezolizumab, avelumab, durvalumab).
Main Outcomes and Measures - Timing, spectrum, outcomes, and incidence of ICI-associated toxic effects.
Results - Internationally, 613 fatal ICI toxic events were reported from 2009 through January 2018 in Vigilyze. The spectrum differed widely between regimens: in a total of 193 anti-CTLA-4 deaths, most were usually from colitis (135 [70%]), whereas anti-PD-1/PD-L1-related fatalities were often from pneumonitis (333 [35%]), hepatitis (115 [22%]), and neurotoxic effects (50 [15%]). Combination PD-1/CTLA-4 deaths were frequently from colitis (32 [37%]) and myocarditis (22 [25%]). Fatal toxic effects typically occurred early after therapy initiation for combination therapy, anti-PD-1, and ipilimumab monotherapy (median 14.5, 40, and 40 days, respectively). Myocarditis had the highest fatality rate (52 [39.7%] of 131 reported cases), whereas endocrine events and colitis had only 2% to 5% reported fatalities; 10% to 17% of other organ-system toxic effects reported had fatal outcomes. Retrospective review of 3545 patients treated with ICIs from 7 academic centers revealed 0.6% fatality rates; cardiac and neurologic events were especially prominent (43%). Median time from symptom onset to death was 32 days. A meta-analysis of 112 trials involving 19 217 patients showed toxicity-related fatality rates of 0.36% (anti-PD-1), 0.38% (anti-PD-L1), 1.08% (anti-CTLA-4), and 1.23% (PD-1/PD-L1 plus CTLA-4).
Conclusions and Relevance - In the largest evaluation of fatal ICI-associated toxic effects published to date to our knowledge, we observed early onset of death with varied causes and frequencies depending on therapeutic regimen. Clinicians across disciplines should be aware of these uncommon lethal complications.
Although a subset of clear cell renal cell carcinoma (ccRCC) patients respond to immune checkpoint blockade (ICB), predictors of response remain uncertain. We investigated whether abnormal expression of endogenous retroviruses (ERVs) in tumors is associated with local immune checkpoint activation (ICA) and response to ICB. Twenty potentially immunogenic ERVs (πERVs) were identified in ccRCC in The Cancer Genome Atlas data set, and tumors were stratified into 3 groups based on their expression levels. πERV-high ccRCC tumors showed increased immune infiltration, checkpoint pathway upregulation, and higher CD8+ T cell fraction in infiltrating leukocytes compared with πERV-low ccRCC tumors. Similar results were observed in ER+/HER2- breast, colon, and head and neck squamous cell cancers. ERV expression correlated with expression of genes associated with histone methylation and chromatin regulation, and πERV-high ccRCC was enriched in BAP1 mutant tumors. ERV3-2 expression correlated with ICA in 11 solid cancers, including the 4 named above. In a small retrospective cohort of 24 metastatic ccRCC patients treated with single-agent PD-1/PD-L1 blockade, ERV3-2 expression in tumors was significantly higher in responders compared with nonresponders. Thus, abnormal expression of πERVs is associated with ICA in several solid cancers, including ccRCC, and ERV3-2 expression is associated with response to ICB in ccRCC.
We report a web-based tool for analysis of experiments using indirect calorimetry to measure physiological energy balance. CalR simplifies the process to import raw data files, generate plots, and determine the most appropriate statistical tests for interpretation. Analysis using the generalized linear model (which includes ANOVA and ANCOVA) allows for flexibility in interpreting diverse experimental designs, including those of obesity and thermogenesis. Users also may produce standardized output files for an experiment that can be shared and subsequently re-evaluated using CalR. This framework will provide the transparency necessary to enhance consistency, rigor, and reproducibility. The CalR analysis software will greatly increase the speed and efficiency with which metabolic experiments can be organized, analyzed per accepted norms, and reproduced and will likely become a standard tool for the field. CalR is accessible at https://CalRapp.org/.
Copyright © 2018 Elsevier Inc. All rights reserved.
State-of-the-art strategies for proteomics are not able to rapidly interrogate complex peptide mixtures in an untargeted manner with sensitive peptide and protein identification rates. We describe a data-independent acquisition (DIA) approach, microDIA (μDIA), that applies a novel tandem mass spectrometry (MS/MS) mass spectral deconvolution method to increase the specificity of tandem mass spectra acquired during proteomics experiments. Using the μDIA approach with a 10 min liquid chromatography gradient allowed detection of 3.1-fold more HeLa proteins than the results obtained from data-dependent acquisition (DDA) of the same samples. Additionally, we found the μDIA MS/MS deconvolution procedure is critical for resolving modified peptides with relatively small precursor mass shifts that cause the same peptide sequence in modified and unmodified forms to theoretically cofragment in the same raw MS/MS spectra. The μDIA workflow is implemented in the PROTALIZER software tool which fully automates tandem mass spectral deconvolution, queries every peptide with a library-free search algorithm against a user-defined protein database, and confidently identifies multiple peptides in a single tandem mass spectrum. We also benchmarked μDIA against DDA using a 90 min gradient analysis of HeLa and Escherichia coli peptides that were mixed in predefined quantitative ratios, and our results showed μDIA provided 24% more true positives at the same false positive rate.
The latent structure of schizotypy and psychosis-spectrum symptoms remains poorly understood. Furthermore, molecular genetic substrates are poorly defined, largely due to the substantial resources required to collect rich phenotypic data across diverse populations. Sample sizes of phenotypic studies are often insufficient for advanced structural equation modeling approaches. In the last 50 years, efforts in both psychiatry and psychological science have moved toward (1) a dimensional model of psychopathology (eg, the current Hierarchical Taxonomy of Psychopathology [HiTOP] initiative), (2) an integration of methods and measures across traits and units of analysis (eg, the RDoC initiative), and (3) powerful, impactful study designs maximizing sample size to detect subtle genomic variation relating to complex traits (the Psychiatric Genomics Consortium [PGC]). These movements are important to the future study of the psychosis spectrum, and to resolving heterogeneity with respect to instrument and population. The International Consortium of Schizotypy Research is composed of over 40 laboratories in 12 countries, and to date, members have compiled a body of schizotypy- and psychosis-related phenotype data from more than 30000 individuals. It has become apparent that compiling data into a protected, relational database and crowdsourcing analytic and data science expertise will result in significant enhancement of current research on the structure and biological substrates of the psychosis spectrum. The authors present a data-sharing infrastructure similar to that of the PGC, and a resource-sharing infrastructure similar to that of HiTOP. This report details the rationale and benefits of the phenotypic data collective and presents an open invitation for participation.