Citations

ObjectiveEpalrestat, an aldose reductase inhibitor increases phosphomannomutase (PMM) enzyme activity in a PMM2‐congenital disorders of glycosylation (CDG) worm model. Epalrestat also decreases sorbitol level in diabetic neuropathy. We evaluated the genetic, biochemical, and clinical characteristics, including the Nijmegen Progression CDG Rating Scale (NPCRS), urine polyol levels and fibroblast glycoproteomics in patients with PMM2‐CDG.MethodsWe performed PMM enzyme measurements, multiplexed proteomics, and glycoproteomics in PMM2‐deficient fibroblasts before and after epalrestat treatment. Safety and efficacy of 0.8 mg/kg/day oral epalrestat were studied in a child with PMM2‐CDG for 12 months.ResultsPMM enzyme activity increased post‐epalrestat treatment. Compared with controls, 24% of glycopeptides had reduced abundance in PMM2‐deficient fibroblasts, 46% of which improved upon treatment. Total protein N‐glycosylation improved upon epalrestat treatment bringing overall glycosylation toward the control fibroblasts’ glycosylation profile. Sorbitol levels were increased in the urine of 74% of patients with PMM2‐CDG and correlated with the presence of peripheral neuropathy, and CDG severity rating scale. In the child with PMM2‐CDG on epalrestat treatment, ataxia scores improved together with significant growth improvement. Urinary sorbitol levels nearly normalized in 3 months and blood transferrin glycosylation normalized in 6 months.InterpretationEpalrestat improved PMM enzyme activity, N‐glycosylation, and glycosylation biomarkers in vitro. Leveraging cellular glycoproteome assessment, we provided a systems‐level view of treatment efficacy and discovered potential novel biosignatures of therapy response. Epalrestat was well‐tolerated and led to significant clinical improvements in the first pediatric patient with PMM2‐CDG treated with epalrestat. We also propose urinary sorbitol as a novel biomarker for disease severity and treatment response in future clinical trials in PMM2‐CDG. ANN NEUROL 20219999:n/a–n/a

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has provided some of the most in-depth analyses of the phenotypes of human tumors ever constructed. Today, the majority of proteomic data analysis is still performed using software housed on desktop computers which limits the number of sequence variants and post-translational modifications that can be considered. The original CPTAC studies limited the search for PTMs to only samples that were chemically enriched for those modified peptides. Similarly, the only sequence variants considered were those with strong evidence at the exon or transcript level. In this multi-institutional collaborative reanalysis, we utilized unbiased protein databases containing millions of human sequence variants in conjunction with hundreds of common post-translational modifications. Using these tools, we identified tens of thousands of high-confidence PTMs and sequence variants. We identified 4132 phosphorylated peptides in nonenriched samples, 93% of which were confirmed in the samples which were chemically enriched for phosphopeptides. In addition, our results also cover 90% of the high-confidence variants reported by the original proteogenomics study, without the need for sample specific next-generation sequencing. Finally, we report fivefold more somatic and germline variants that have an independent evidence at the peptide level, including mutations in ERRB2 and BCAS1. In this reanalysis of CPTAC proteomic data with cloud computing, we present an openly available and searchable web resource of the highest-coverage proteomic profiling of human tumors described to date.

Abstract To discover lipidomic alterations during pregnancy in mothers who subsequently delivered small for gestational age (SGA) neonates and identify predictive lipid markers that can help recognize and manage these mothers, we carried out untargeted lipidomics on maternal serum samples collected between 24–28 weeks of gestation. We used a nested case-control study design and serum from mothers who delivered SGA and appropriate for gestational age babies. We applied untargeted lipidomics using mass spectrometry to characterize lipids and discover changes associated with SGA births during pregnancy. Multivariate pattern recognition software Collaborative Laboratory Integrated Reports (CLIR) was used for the post-analytical recognition of range differences in lipid ratios that could differentiate between SGA and control mothers and their integration for complete separation between the two groups. Here, we report changes in lipids from serum collected during pregnancy in mothers who delivered SGA neonates. In contrast to normal pregnancies where lysophosphatidic acid increased over the course of the pregnancy owing to increased activity of lysophospholipase D, we observed a decrease (32%; P = 0.05) of 20:4-lysophosphatidic acid in SGA mothers, which could potentially compromise fetal growth and development. Integration of lipid ratios in an interpretive tool (CLIR) could completely separate SGA mothers from controls demonstrating the power of untargeted lipidomic analyses for identifying novel predictive biomarkers. Additional studies are required for further assessment of the lipid biomarkers identified in this report.

Overexpression and amplification of AXL receptor tyrosine kinase (RTK) has been found in several hematologic and solid malignancies. Activation of AXL can enhance tumor-promoting processes such as cancer cell proliferation, migration, invasion and survival. Despite the important role of AXL in cancer development, a deep and quantitative mapping of its temporal dynamic signaling transduction has not yet been reported. Here, we used a TMT labeling-based quantitative proteomics approach to characterize the temporal dynamics of the phosphotyrosine proteome induced by AXL activation. We identified >1100 phosphotyrosine sites and observed a widespread upregulation of tyrosine phosphorylation induced by GAS6 stimulation. We also detected several tyrosine sites whose phosphorylation levels were reduced upon AXL activation. Gene set enrichment-based pathway analysis indicated the activation of several cancer-promoting and cell migration/invasion-related signaling pathways, including RAS, EGFR, focal adhesion, VEGFR and cytoskeletal rearrangement pathways. We also observed a rapid induction of phosphorylation of protein tyrosine phosphatases, including PTPN11 and PTPRA, upon GAS6 stimulation. The novel molecules downstream of AXL identified in this study along with the detailed global quantitative map elucidating the temporal dynamics of AXL activation should not only help understand the oncogenic role of AXL, but also aid in developing therapeutic options to effectively target AXL.

Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the worldwide COVID-19 pandemic which began in 2019. It has a high transmission rate and pathogenicity leading to health emergencies and economic crisis. Recent studies pertaining to the understanding of the molecular pathogenesis of SARS-CoV-2 infection exhibited the indispensable role of ion channels in viral infection inside the host. Moreover, machine learning (ML)-based algorithms are providing higher accuracy for host-SARS-CoV-2 protein-protein interactions (PPIs). In this study, predictions of PPIs of SARS-CoV-2 proteins with human ion channels (HICs) were performed using PPI-MetaGO algorithm. The PPIs were predicted with 82.71% accuracy, 84.09% precision, 84.09% sensitivity, 0.89 AUC-ROC, 65.17% Matthews correlation coefficient (MCC) score and 84.09% F1 score. Thereafter, PPI networks of SARSCoV-2 proteins with HICs were generated. Furthermore, biological pathway analysis of HICs interacting with SARS-CoV-2 proteins showed the involvement of six pathways, namely inflammatory mediator regulation of transient receptor potential (TRP) channels, insulin secretion, renin secretion, gap junction, taste transduction and apelin signaling pathway. Our analysis suggests that transient receptor potential cation channel subfamily M member 4 (TRPM4), transient receptor potential cation channel subfamily A member 1 (TRPA1), gap junction protein alpha 1 (GJA1), potassium calcium-activated channel subfamily N member 4 (KCNN4), acid sensing ion channel subunit 1 (ASIC1) and inositol 1,4,5-trisphosphate receptor type 1 (ITPR1) could serve as an initial set to the experimentalists for further validation. Additionally, various US food and drug administration (FDA) approved drugs interacting with the potential HICs were also identified. The study also reinforcesthe drug repurposing approach for the development of host directed antiviral drugs.

Abstract Several plasma glycoproteins are clinically useful as biomarkers in a variety of diseases. Although thousands of proteins are present in plasma, >95% of the plasma proteome by mass is represented by only 22 proteins. This necessitates strategies to deplete the abundant proteins and enrich other subsets of proteins. Although glycoproteins are abundant in plasma, in routine proteomic analyses, glycopeptides are not often investigated. Traditional methods such as lectin-based enrichment of glycopeptides followed by deglycosylation have helped understand the glycoproteome, but they lack any information about the attached glycans. Here, we apply size-exclusion chromatography (SEC) as a simple strategy to enrich intact N-glycopeptides based on their larger size which achieves broad selectivity regardless of the nature of attached glycans. Using this approach, we identified 1317 N-glycopeptides derived from 266 glycosylation sites on 154 plasma glycoproteins. The deep coverage achieved by this approach was evidenced by extensive heterogeneity that was observed. For instance, 20–100 glycopeptides were observed per protein for the 15 most-glycosylated glycoproteins. Notably, we discovered 615 novel glycopeptides of which 39 glycosylation sites (from 38 glycoproteins) were not included in protein databases such as Uniprot and GlyConnectDB. Finally, we also identified 12 novel glycopeptides containing di-sialic acid, which is a rare glycan epitope. Our results demonstrate the utility of SEC for efficient LC-MS/MS-based deep glycoproteomics analysis of human plasma. Overall, the SEC-based method described here is a simple, rapid and high-throughput strategy for characterization of any glycoproteome.

Pancreatic ductal adenocarcinoma is a recalcitrant tumor with minimal response to conventional chemotherapeutic approaches. Oncogenic signaling by activated tyrosine kinases has been implicated in cancers resulting in activation of diverse effector signaling pathways. Thus, the discovery of aberrantly activated tyrosine kinases is of great interest in developing novel therapeutic strategies in the treatment and management of pancreatic cancer. Patient-derived tumor xenografts (PDXs) in mice serve as potentially valuable preclinical models as they maintain the histological and molecular heterogeneity of the original human tumor. Here, we employed high-resolution mass spectrometry combined with immunoaffinity purification using anti-phosphotyrosine antibodies to profile tyrosine phosphoproteome across 13 pancreatic ductal adenocarcinoma PDX models. This analysis resulted in the identification of 1199 tyrosine-phosphorylated sites mapping to 704 proteins. The mass spectrometric analysis revealed widespread and heterogeneous activation of both receptor and non-receptor tyrosine kinases. Preclinical studies confirmed ephrin type-B receptor 4 (EphB4) as a potential therapeutic target based on the efficacy of human serum albumin-conjugated soluble EphB4 in mice bearing orthotopic xenografts. Immunohistochemistry-based validation using tissue microarrays from 346 patients with PDAC showed significant expression of EphB4 in >70% of patients. In summary, we present a comprehensive landscape of tyrosine phosphoproteome with EphB4 as a promising therapeutic target in pancreatic ductal adenocarcinoma.

Abstract Background We evaluated the analytical sensitivity and specificity of 4 rapid antigen diagnostic tests (Ag RDTs) for severe acute respiratory syndrome coronavirus 2, using reverse transcription quantitative PCR (RT-qPCR) as the reference method and further characterizing samples using droplet digital quantitative PCR (ddPCR) and a mass spectrometric antigen test. Methods Three hundred fifty (150 negative and 200 RT-qPCR positive) residual PBS samples were tested for antigen using the BD Veritor lateral flow (LF), ACON LF, ACON fluorescence immunoassay (FIA), and LumiraDx FIA. ddPCR was performed on RT-qPCR–positive samples to quantitate the viral load in copies/mL applied to each Ag RDT. Mass spectrometric antigen testing was performed on PBS samples to obtain a set of RT-qPCR–positive, antigen-positive samples for further analysis. Results All Ag RDTs had nearly 100% specificity compared to RT-qPCR. Overall analytical sensitivity varied from 66.5% to 88.3%. All methods detected antigen in samples with viral load >1 500 000 copies/mL RNA, and detected ≥75% of samples with viral load of 500 000 to 1 500 000 copies/mL. The BD Veritor LF detected only 25% of samples with viral load between 50 000 to 500 000 copies/mL, compared to 75% for the ACON LF device and >80% for LumiraDx and ACON FIA. The ACON FIA detected significantly more samples with viral load <50 000 copies/mL compared to the BD Veritor. Among samples with detectable antigen and viral load <50 000 copies/mL, sensitivity of the Ag RDT varied between 13.0% (BD Veritor) and 78.3% (ACON FIA). Conclusions Ag RDTs differ significantly in analytical sensitivity, particularly at viral load <500 000 copies/mL.