Absolute Quantification of Apolipoproteins Following Treatment with Omega-3 Carboxylic Acids and Fenofibrate Using a High Precision Stable Isotope-labeled Recombinant Protein Fragments Based SRM Assay.

Stable isotope-labeled standard (SIS) peptides are used as internal standards in targeted proteomics to provide robust protein quantification, which is required in clinical settings. However, SIS peptides are typically added post trypsin digestion and, as the digestion efficiency can vary significantly between peptides within a protein, the accuracy and precision of the assay may be compromised. These drawbacks can be remedied by a new class of internal standards introduced by the Human Protein Atlas project, which are based on SIS recombinant protein fragments called SIS PrESTs. SIS PrESTs are added initially to the sample and SIS peptides are released on trypsin digestion. The SIS PrEST technology is promising for absolute quantification of protein biomarkers but has not previously been evaluated in a clinical setting. An automated and scalable solid phase extraction workflow for desalting and enrichment of plasma digests was established enabling simultaneous preparation of up to 96 samples. Robust high-precision quantification of 13 apolipoproteins was achieved using a novel multiplex SIS PrEST-based LC-SRM/MS Tier 2 assay in non-depleted human plasma. The assay exhibited inter-day coefficients of variation between 1.5% and 14.5% (median = 3.5%) and was subsequently used to investigate the effects of omega-3 carboxylic acids (OM3-CA) and fenofibrate on these 13 apolipoproteins in human plasma samples from a randomized placebo-controlled trial, EFFECT I (NCT02354976). No significant changes were observed in the OM3-CA arm, whereas treatment with fenofibrate significantly increased apoAII and reduced apoB, apoCI, apoE and apoCIV levels. The reduction in apoCIV following fenofibrate treatment is a novel finding. The study demonstrates that SIS PrESTs can facilitate the generation of robust multiplexed biomarker Tier 2 assays for absolute quantification of proteins in clinical studies.

Novel functional proteins coded by the human genome discovered in metastases of melanoma patients.

In the advanced stages, malignant melanoma (MM) has a very poor prognosis. Due to tremendous efforts in cancer research over the last 10 years, and the introduction of novel therapies such as targeted therapies and immunomodulators, the rather dark horizon of the median survival has dramatically changed from under 1 year to several years. With the advent of proteomics, deep-mining studies can reach low-abundant expression levels. The complexity of the proteome, however, still surpasses the dynamic range capabilities of current analytical techniques. Consequently, many predicted protein products with potential biological functions have not yet been verified in experimental proteomic data. This category of 'missing proteins' (MP) is comprised of all proteins that have been predicted but are currently unverified. As part of the initiative launched in 2016 in the USA, the European Cancer Moonshot Center has performed numerous deep proteomics analyses on samples from MM patients. In this study, nine MPs were clearly identified by mass spectrometry in MM metastases. Some MPs significantly correlated with proteins that possess identical PFAM structural domains; and other MPs were significantly associated with cancer-related proteins. This is the first study to our knowledge, where unknown and novel proteins have been annotated in metastatic melanoma tumour tissue.

Assessing Automated Sample Preparation Technologies for High-Throughput Proteomics of Frozen Well Characterized Tissues from Swedish Biobanks.

Large cohorts of carefully collected clinical tissue materials play a central role in acquiring sufficient depth and statistical power to discover disease-related mechanisms and biomarkers of clinical significance. Manual preparation of such large sample cohorts requires experienced laboratory personnel. This carries other possible downsides such as low throughput, high risk of errors, and low reproducibility. In this work, three automated technologies for high-throughput proteomics of frozen sectioned tissues were compared. The instruments evaluated included the Bioruptor for tissue disruption and protein extraction; the Barocycler, which is able to disrupt tissues and digest the proteins; and the AssayMAP Bravo, a microchromatography platform for protein digestion, peptide desalting, and fractionation. Wide varieties of tissue samples from rat spleen, malignant melanoma, and pancreatic tumors were used for the assessment. The three instruments displayed reproducible and consistent results, as was proven by high correlations and low coefficients of variation between technical replicates and even more importantly, between replicates that were processed in different batches or at different time points. The results from this study allowed us to integrate these technologies into an automated sample preparation workflow for large-scale proteomic studies that are currently ongoing. Data are available via ProteomeXchange with identifiers PXD010296 and PXD011295.

SGLT2 inhibition with empagliflozin improves coronary microvascular function and cardiac contractility in prediabetic ob/ob-/- mice.

BACKGROUND: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) is the first class of anti-diabetes treatment that reduces mortality and risk for hospitalization due to heart failure. In clinical studies it has been shown that SGLT2i's promote a general shift to fasting state metabolism characterized by reduced body weight and blood glucose, increase in glucagon/insulin ratio and modest increase in blood ketone levels. Therefore, we investigated the connection between metabolic changes and cardiovascular function in the ob/ob-/- mice; a rodent model of early diabetes with specific focus on coronary microvascular function. Due to leptin deficiency these mice develop metabolic syndrome/diabetes and hepatic steatosis. They also develop cardiac contractile and microvascular dysfunction and are thus a promising model for translational studies of cardiometabolic diseases. We investigated whether this mouse model responded in a human-like manner to empagliflozin treatment in terms of metabolic parameters and tested the hypothesis that it could exert direct effects on coronary microvascular function and contractile performance. METHODS: Lean, ob/ob-/- untreated and ob/ob-/- treated with SGLT2i were followed for 10 weeks. Coronary flow velocity reserve (CFVR) and fractional area change (FAC) were monitored with non-invasive Doppler ultrasound imaging. Food intake, urinary glucose excursion and glucose control via HbA1c measurements were followed throughout the study. Liver steatosis was assessed by histology and metabolic parameters determined at the end of the study. RESULTS: Sodium-glucose cotransporter 2 inhibitors treatment of ob/ob-/- animals resulted in a switch to a more catabolic state as observed in clinical studies: blood cholesterol and HbA1c were decreased whereas glucagon/insulin ratio and ketone levels were increased. SGLT2i treatment reduced liver triglyceride, steatosis and alanine aminotransferase, an indicator for liver dysfunction. L-Arginine/ADMA ratio, a marker for endothelial function was increased. SGLT2i treatment improved both cardiac contractile function and coronary microvascular function as indicated by improvement of FAC and CFVR, respectively. CONCLUSIONS: Sodium-glucose cotransporter 2 inhibitors treatment of ob/ob-/- mice mimics major clinical findings regarding metabolism and cardiovascular improvements and is thus a useful translational model. We demonstrate that SGLT2 inhibition improves coronary microvascular function and contractile performance, two measures with strong predictive values in humans for CV outcome, alongside with the known metabolic changes in a preclinical model for prediabetes and heart failure.

Clinical protein science in translational medicine targeting malignant melanoma.

Melanoma of the skin is the sixth most common type of cancer in Europe and accounts for 3.4% of all diagnosed cancers. More alarming is the degree of recurrence that occurs with approximately 20% of patients lethally relapsing following treatment. Malignant melanoma is a highly aggressive skin cancer and metastases rapidly extend to the regional lymph nodes (stage 3) and to distal organs (stage 4). Targeted oncotherapy is one of the standard treatment for progressive stage 4 melanoma, and BRAF inhibitors (e.g. vemurafenib, dabrafenib) combined with MEK inhibitor (e.g. trametinib) can effectively counter BRAFV600E-mutated melanomas. Compared to conventional chemotherapy, targeted BRAFV600E inhibition achieves a significantly higher response rate. After a period of cancer control, however, most responsive patients develop resistance to the therapy and lethal progression. The many underlying factors potentially causing resistance to BRAF inhibitors have been extensively studied. Nevertheless, the remaining unsolved clinical questions necessitate alternative research approaches to address the molecular mechanisms underlying metastatic and treatment-resistant melanoma. In broader terms, proteomics can address clinical questions far beyond the reach of genomics, by measuring, i.e. the relative abundance of protein products, post-translational modifications (PTMs), protein localisation, turnover, protein interactions and protein function. More specifically, proteomic analysis of body fluids and tissues in a given medical and clinical setting can aid in the identification of cancer biomarkers and novel therapeutic targets. Achieving this goal requires the development of a robust and reproducible clinical proteomic platform that encompasses automated biobanking of patient samples, tissue sectioning and histological examination, efficient protein extraction, enzymatic digestion, mass spectrometry-based quantitative protein analysis by label-free or labelling technologies and/or enrichment of peptides with specific PTMs. By combining data from, e.g. phosphoproteomics and acetylomics, the protein expression profiles of different melanoma stages can provide a solid framework for understanding the biology and progression of the disease. When complemented by proteogenomics, customised protein sequence databases generated from patient-specific genomic and transcriptomic data aid in interpreting clinical proteomic biomarker data to provide a deeper and more comprehensive molecular characterisation of cellular functions underlying disease progression. In parallel to a streamlined, patient-centric, clinical proteomic pipeline, mass spectrometry-based imaging can aid in interrogating the spatial distribution of drugs and drug metabolites within tissues at single-cell resolution. These developments are an important advancement in studying drug action and efficacy in vivo and will aid in the development of more effective and safer strategies for the treatment of melanoma. A collaborative effort of gargantuan proportions between academia and healthcare professionals has led to the initiation, establishment and development of a cutting-edge cancer research centre with a specialisation in melanoma and lung cancer. The primary research focus of the European Cancer Moonshot Lund Center is to understand the impact that drugs have on cancer at an individualised and personalised level. Simultaneously, the centre increases awareness of the relentless battle against cancer and attracts global interest in the exceptional research performed at the centre.

Effects of dapagliflozin and n-3 carboxylic acids on non-alcoholic fatty liver disease in people with type 2 diabetes: a double-blind randomised placebo-controlled study.

AIMS/HYPOTHESIS: The EFFECT-II study aimed to investigate the effects of dapagliflozin and omega-3 (n-3) carboxylic acids (OM-3CA), individually or combined, on liver fat content in individuals with type 2 diabetes and non-alcoholic fatty liver disease (NAFLD). METHODS: This randomised placebo-controlled double-blind parallel-group study was performed at five clinical research centres at university hospitals in Sweden. 84 participants with type 2 diabetes and NAFLD were randomly assigned 1:1:1:1 to four treatments by a centralised randomisation system, and all participants as well as investigators and staff involved in the study conduct and analyses were blinded to treatments. Each group received oral doses of one of the following: 10 mg dapagliflozin (n = 21), 4 g OM-3CA (n = 20), a combination of both (n = 22) or placebo (n = 21). The primary endpoint was liver fat content assessed by MRI (proton density fat fraction [PDFF]) and, in addition, total liver volume and markers of glucose and lipid metabolism as well as of hepatocyte injury and oxidative stress were assessed at baseline and after 12 weeks of treatment (completion of the trial). RESULTS: Participants had a mean age of 65.5 years (SD 5.9), BMI 31.2 kg/m2 (3.5) and liver PDFF 18% (9.3). All active treatments significantly reduced liver PDFF from baseline, relative changes: OM-3CA, -15%; dapagliflozin, -13%; OM-3CA + dapagliflozin, -21%. Only the combination treatment reduced liver PDFF (p = 0.046) and total liver fat volume (relative change, -24%, p = 0.037) in comparison with placebo. There was an interaction between the PNPLA3 I148M polymorphism and change in liver PDFF in the active treatment groups (p = 0.03). Dapagliflozin monotherapy, but not the combination with OM-3CA, reduced the levels of hepatocyte injury biomarkers, including alanine aminotransferase, aspartate aminotransferase, γ-glutamyl transferase (γ-GT), cytokeratin (CK) 18-M30 and CK 18-M65 and plasma fibroblast growth factor 21 (FGF21). Changes in γ-GT correlated with changes in liver PDFF (ρ = 0.53, p = 0.02). Dapagliflozin alone and in combination with OM-3CA improved glucose control and reduced body weight and abdominal fat volumes. Fatty acid oxidative stress biomarkers were not affected by treatments. There were no new or unexpected adverse events compared with previous studies with these treatments. CONCLUSIONS/INTERPRETATION: Combined treatment with dapagliflozin and OM-3CA significantly reduced liver fat content. Dapagliflozin monotherapy reduced all measured hepatocyte injury biomarkers and FGF21, suggesting a disease-modifying effect in NAFLD. TRIAL REGISTRATION: ClinicalTrials.gov NCT02279407 FUNDING: The study was funded by AstraZeneca.

Protocol for Standardizing High-to-Moderate Abundance Protein Biomarker Assessments Through an MRM-with-Standard-Peptides Quantitative Approach.

Quantitative mass spectrometry (MS)-based approaches are emerging as a core technology for addressing health-related queries in systems biology and in the biomedical and clinical fields. In several 'omics disciplines (proteomics included), an approach centered on selected or multiple reaction monitoring (SRM or MRM)-MS with stable isotope-labeled standards (SIS), at the protein or peptide level, has emerged as the most precise technique for quantifying and screening putative analytes in biological samples. To enable the widespread use of MRM-based protein quantitation for disease biomarker assessment studies and its ultimate acceptance for clinical analysis, the technique must be standardized to facilitate precise and accurate protein quantitation. To that end, we have developed a number of kits for assessing method/platform performance, as well as for screening proposed candidate protein biomarkers in various human biofluids. Collectively, these kits utilize a bottom-up LC-MS methodology with SIS peptides as internal standards and quantify proteins using regression analysis of standard curves. This chapter details the methodology used to quantify 192 plasma proteins of high-to-moderate abundance (covers a 6 order of magnitude range from 31 mg/mL for albumin to 18 ng/mL for peroxidredoxin-2), and a 21-protein subset thereof. We also describe the application of this method to patient samples for biomarker discovery and verification studies. Additionally, we introduce our recently developed Qualis-SIS software, which is used to expedite the analysis and assessment of protein quantitation data in control and patient samples.

Patient-Centric Quantitative Microsampling for Accurate Determination of Urine Albumin to Creatinine Ratio (UACR) in a Clinical Setting.

BACKGROUND: Developing and implementing new patient-centric strategies for drug trials lowers the barrier to participation for some patients by reducing the need to travel to research sites. In early chronic kidney disease (CKD) trials, albuminuria is the key measure for determining treatment effect prior to pivotal kidney outcome trials. METHODS: To facilitate albuminuria sample collection outside of a clinical research site, we developed 2 quantitative microsampling methods to determine the urinary albumin to creatinine ratio (UACR). Readout was performed by LC-MS/MS. RESULTS: For the Mitra device the within-batch precision (CV%) was 2.8% to 4.6% and the between-batch precision was 5.3% to 6.1%. Corresponding data for the Capitainer device were 4.0% to 8.6% and 6.7% to 9.0%, respectively. The storage stability at room temperature for 3 weeks was 98% to 103% for both devices. The recovery for the Mitra and Capitainer devices was 104% (SD 7.0%) and 95 (SD 7.4%), respectively. The inter-assay comparison of UACR assessment generated results that were indistinguishable regardless of microsampling technique. The accuracy based on LC-MS/MS vs analysis of neat urine using a clinical chemistry analyzer was assessed in a clinical setting, resulting in 102 ± 8.0% for the Mitra device and 95 ± 10.0% for the Capitainer device. CONCLUSIONS: Both UACR microsampling measurements exhibit excellent accuracy and precision compared to a clinical chemistry analyzer using neat urine. We applied our patient-centric sampling strategy to subjects with heart failure in a clinical setting. Precise UACR measurements using quantitative microsampling at home would be beneficial in clinical drug development for kidney therapies.

Targeted proteomics using stable isotope labeled protein fragments enables precise and robust determination of total apolipoprotein(a) in human plasma.

Lipoprotein(a), also known as Lp(a), is an LDL-like particle composed of apolipoprotein(a) (apo(a)) bound covalently to apolipoprotein B100. Plasma concentrations of Lp(a) are highly heritable and vary widely between individuals. Elevated plasma concentration of Lp(a) is considered as an independent, causal risk factor of cardiovascular disease (CVD). Targeted mass spectrometry (LC-SRM/MS) combined with stable isotope-labeled recombinant proteins provides robust and precise quantification of proteins in the blood, making LC-SRM/MS assays appealing for monitoring plasma proteins for clinical implications. This study presents a novel quantitative approach, based on proteotypic peptides, to determine the absolute concentration of apo(a) from two microliters of plasma and qualified according to guideline requirements for targeted proteomics assays. After optimization, assay parameters such as linearity, lower limits of quantification (LLOQ), intra-assay variability (CV: 4.7%) and inter-assay repeatability (CV: 7.8%) were determined and the LC-SRM/MS results were benchmarked against a commercially available immunoassay. In summary, the measurements of an apo(a) single copy specific peptide and a kringle 4 specific peptide allow for the determination of molar concentration and relative size of apo(a) in individuals.

Age prediction from human blood plasma using proteomic and small RNA data: a comparative analysis.

Aging clocks, built from comprehensive molecular data, have emerged as promising tools in medicine, forensics, and ecological research. However, few studies have compared the suitability of different molecular data types to predict age in the same cohort and whether combining them would improve predictions. Here, we explored this at the level of proteins and small RNAs in 103 human blood plasma samples. First, we used a two-step mass spectrometry approach measuring 612 proteins to select and quantify 21 proteins that changed in abundance with age. Notably, proteins increasing with age were enriched for components of the complement system. Next, we used small RNA sequencing to select and quantify a set of 315 small RNAs that changed in abundance with age. Most of these were microRNAs (miRNAs), downregulated with age, and predicted to target genes related to growth, cancer, and senescence. Finally, we used the collected data to build age-predictive models. Among the different types of molecules, proteins yielded the most accurate model (R² = 0.59 ± 0.02), followed by miRNAs as the best-performing class of small RNAs (R² = 0.54 ± 0.02). Interestingly, the use of protein and miRNA data together improved predictions (R2 = 0.70 ± 0.01). Future work using larger sample sizes and a validation dataset will be necessary to confirm these results. Nevertheless, our study suggests that combining proteomic and miRNA data yields superior age predictions, possibly by capturing a broader range of age-related physiological changes. It will be interesting to determine if combining different molecular data types works as a general strategy to improve future aging clocks.

Multiomics analysis of naturally efficacious lipid nanoparticle coronas reveals high-density lipoprotein is necessary for their function.

In terms of lipid nanoparticle (LNP) engineering, the relationship between particle composition, delivery efficacy, and the composition of the biocoronas that form around LNPs, is poorly understood. To explore this we analyze naturally efficacious biocorona compositions using an unbiased screening workflow. First, LNPs are complexed with plasma samples, from individual lean or obese male rats, and then functionally evaluated in vitro. Then, a fast, automated, and miniaturized method retrieves the LNPs with intact biocoronas, and multiomics analysis of the LNP-corona complexes reveals the particle corona content arising from each individual plasma sample. We find that the most efficacious LNP-corona complexes were enriched with high-density lipoprotein (HDL) and, compared to the commonly used corona-biomarker Apolipoprotein E, corona HDL content was a superior predictor of in-vivo activity. Using technically challenging and clinically relevant lipid nanoparticles, these methods reveal a previously unreported role for HDL as a source of ApoE and, form a framework for improving LNP therapeutic efficacy by controlling corona composition.

Development of a highly sensitive method using liquid chromatography-multiple reaction monitoring to quantify membrane P-glycoprotein in biological matrices and relationship to transport function.

The quantification of P-glycoprotein [P-gp, ABCB1, multidrug resistance 1 (MDR1)] protein in biological matrices is considered a key factor missing for useful translation of in vitro functional data to the in vivo situation and for comparison of transporter data among different in vitro models. In the present study a liquid chromatography (LC)-mass spectrometry method was developed to quantify P-gp membrane protein levels in different biological matrices. The amount of P-gp transporter protein was measured in Caco-2 cell monolayers and in inside-out human embryonic kidney (HEK)-MDR1 vesicles. From both in vitro systems, two preparations with different functionality were used. Transporter function was determined as digoxin efflux in Caco-2 cell monolayers and N-methylquinidine (NMQ) uptake in membrane vesicles, and, in addition, mRNA expression in the Caco-2 monolayers was measured. The results showed an excellent relationship between NMQ uptake functionality in inside-out HEK-MDR1 vesicles and protein contents. Similar concordance between the digoxin efflux and P-gp content in different Caco-2 cell cultures was observed, whereas mRNA levels are indicative of increased P-gp content and activity in older Caco-2 cultures, however, not yielding the same quantitative relationship. The results from both Caco-2 and HEK-MDR1 membrane vesicles confirm that the protein content is directly related to the level of activity in the respective system. The method presented here to quantify P-gp protein by LC-multiple reaction monitoring will facilitate the development of future methodologies to bridge between expression systems and cell/tissue models and to scale from in vitro models to whole organs.

The Human Melanoma Proteome Atlas-Complementing the melanoma transcriptome.

The MM500 meta-study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. Somatic mutations and their effect on the transcriptome have been extensively characterized in melanoma. However, the effects of these genetic changes on the proteomic landscape and the impact on cellular processes in melanoma remain poorly understood. In this study, the quantitative mass-spectrometry-based proteomic analysis is interfaced with pathological tumor characterization, and associated with clinical data. The melanoma proteome landscape, obtained by the analysis of 505 well-annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. More than 50 million MS/MS spectra were analyzed, resulting in approximately 13,6 million peptide spectrum matches (PSMs). Altogether 13 176 protein-coding genes, represented by 366 172 peptides, in addition to 52 000 phosphorylation sites, and 4 400 acetylation sites were successfully annotated. This data covers 65% and 74% of the predicted and identified human proteome, respectively. A high degree of correlation (Pearson, up to 0.54) with the melanoma transcriptome of the TCGA repository, with an overlap of 12 751 gene products, was found. Mapping of the expressed proteins with quantitation, spatiotemporal localization, mutations, splice isoforms, and PTM variants was proven not to be predicted by genome sequencing alone. The melanoma tumor molecular map was complemented by analysis of blood protein expression, including data on proteins regulated after immunotherapy. By adding these key proteomic pillars, the MM500 study expands the knowledge on melanoma disease.

The human melanoma proteome atlas-Defining the molecular pathology.

The MM500 study is an initiative to map the protein levels in malignant melanoma tumor samples, focused on in-depth histopathology coupled to proteome characterization. The protein levels and localization were determined for a broad spectrum of diverse, surgically isolated melanoma tumors originating from multiple body locations. More than 15,500 proteoforms were identified by mass spectrometry, from which chromosomal and subcellular localization was annotated within both primary and metastatic melanoma. The data generated by global proteomic experiments covered 72% of the proteins identified in the recently reported high stringency blueprint of the human proteome. This study contributes to the NIH Cancer Moonshot initiative combining detailed histopathological presentation with the molecular characterization for 505 melanoma tumor samples, localized in 26 organs from 232 patients.

Identification of Proteins Associated with the Early Restoration of Insulin Sensitivity After Biliopancreatic Diversion.

CONTEXT: Insulin resistance (IR) is a risk factor for type 2 diabetes, diabetic kidney disease, cardiovascular disease and nonalcoholic steatohepatitis. Biliopancreatic diversion (BPD) is the most effective form of bariatric surgery for improving insulin sensitivity. OBJECTIVE: To identify plasma proteins correlating with the early restoration of insulin sensitivity after BPD. DESIGN: Prospective single-center study including 20 insulin-resistant men with morbid obesity scheduled for BPD. Patient characteristics and blood samples were repeatedly collected from baseline up to 4 weeks postsurgery. IR was assessed by homeostatic model assessment for insulin resistance (HOMA-IR), Matsuda Index, and by studying metabolic profiles during meal tolerance tests. Unbiased proteomic analysis was performed to identify plasma proteins altered by BPD. Detailed plasma profiles were made on a selected set of proteins by targeted multiple reaction monitoring mass spectrometry (MRM/MS). Changes in plasma proteome were evaluated in relation to metabolic and inflammatory changes. RESULTS: BPD resulted in improved insulin sensitivity and reduced body weight. Proteomic analysis identified 29 proteins that changed following BPD. Changes in plasma levels of afamin, apolipoprotein A-IV (ApoA4), and apolipoprotein A-II (ApoA2) correlated significantly with changes in IR. CONCLUSION: Circulating levels of afamin, ApoA4, and ApoA2 were associated with and may contribute to the rapid improvement in insulin sensitivity after BPD.

Myeloperoxidase and related biomarkers are suggestive footprints of endothelial microvascular inflammation in HFpEF patients.

AIMS: In heart failure (HF) with preserved ejection fraction (HFpEF), microvascular inflammation is proposed as an underlying mechanism. Myeloperoxidase (MPO) is associated with vascular dysfunction and prognosis in congestive HF. METHODS AND RESULTS: MPO, MPO-related biomarkers, and echocardiography were assessed in 86 patients, 4-8 weeks after presentation with acute HF (EF ≥ 45%), and in 46 healthy controls. Patients were followed up for median 579 days (Q1;Q3 276;1178) regarding the composite endpoint all-cause mortality or HF hospitalization. Patients were 73 years old, 51% were female, EF was 64% (Q1;Q3 58;68), E/e' was ratio 10.8 (8.3;14.0), and left atrial volume index (LAVI) was 43 mL/m2 (38;52). Controls were 60 (57;62) years old (vs. patients; P < 0.001), 24% were female (P = 0.005), and left ventricular EF was 63% (59;66; P = 0.790). MPO was increased in HFpEF compared with controls, 101 (81;132) vs. 86 (74;101 ng/mL, P = 0.015), as was uric acid 369 (314;439) vs. 289 (252;328 µmol/L, P < 0.001), calprotectin, asymmetric dimethyl arginine (ADMA), and symmetric dimethyl arginine (SDMA), while arginine was decreased. MPO correlated with uric acid (r = 0.26; P = 0.016). In patients with E/e' > 14, uric acid and SDMA were elevated (421 vs. 344 µM, P = 0.012; 0.54 vs. 0.47 µM, P = 0.039, respectively), and MPO was 121 vs. 98 ng/mL (P = 0.090). The ratios of arginine/ADMA (112 vs. 162; P < 0.001) and ADMA/SDMA (1.36 vs. 1.17; P = 0.002) were decreased in HFpEF patients, suggesting reduced NO availability and increased enzymatic clearance of ADMA, respectively. Uric acid independently predicted the endpoint [hazard ratio (HR) 3.76 (95% CI 1.19-11.85; P = 0.024)] but not MPO [HR 1.48 (95% CI 0.70-3.14; P = 0.304)] or the other biomarkers. CONCLUSIONS: In HFpEF, MPO-dependent oxidative stress reflected by uric acid and calprotectin is increased, and SDMA is associated with diastolic dysfunction and uric acid with outcome. This suggests microvascular neutrophil involvement mirroring endothelial dysfunction, a central component of the HFpEF syndrome and a potential treatment target.

Optimization of sample preparation for transporter protein quantification in tissues by LC-MS/MS.

BACKGROUND: Reproducible quantification of drug transporter protein expression in tissues is important for predicting transporter mediated drug disposition. Many mass-spectrometry based transporter protein quantification methods result in high variability of the estimated transporter quantities. Therefore, we aimed to evaluate and optimize mass spectrometry-based quantification method for drug transporter proteins in tissues. MATERIALS AND METHODS: Plasma membrane (PM) proteins from mouse tissues were isolated by applying three extraction protocols: commercial plasma membrane extraction kit, tissue homogenization by Potter-Elvehjem homogenizer in combination with sucrose-cushion ultracentrifugation, and PM enrichment with Tween 40. Moreover, five different protein digestion protocols were applied on the same PM fraction. PM isolation and digestion protocols were evaluated by measuring the amount of transporter proteins by liquid chromatography-tandem mass spectrometry in selected reaction monitoring mode. RESULTS: Mouse liver homogenization by Potter-Elvehjem homogenizer in combination with sucrose-cushion ultracentrifugation and PM enrichment with Tween 40 resulted in two times higher transporter protein quantity (Breast cancer resistance protein (Bcrp) 18.0 fmol/µg protein) in comparison with the PM samples isolated by extraction kit (Bcrp 9.8 fmol/µg protein). The evaluation of protein digestion protocols revealed that the most optimal protocol for PM protein digestion is with Lys-C and trypsin, in combination with trypsin enhancer and heat denaturation. Overall, quantities of Bcrp and Na+/K + ATPase proteins evaluated in mouse liver and kidney cortex by using our optimized PM isolation method, as well as, established digestion protocol were two to three times higher than previously reported and coefficient of variation (CV) for technical replicates was below 10%. CONCLUSION: We have established an improved transporter protein quantification methodology by optimizing PM isolation and protein digestion procedures. The optimized procedure resulted in a higher transporter protein yield and improved precision.

The Hidden Story of Heterogeneous B-raf V600E Mutation Quantitative Protein Expression in Metastatic Melanoma-Association with Clinical Outcome and Tumor Phenotypes.

In comparison to other human cancer types, malignant melanoma exhibits the greatest amount of heterogeneity. After DNA-based detection of the BRAF V600E mutation in melanoma patients, targeted inhibitor treatment is the current recommendation. This approach, however, does not take the abundance of the therapeutic target, i.e., the B-raf V600E protein, into consideration. As shown by immunohistochemistry, the protein expression profiles of metastatic melanomas clearly reveal the existence of inter- and intra-tumor variability. Nevertheless, the technique is only semi-quantitative. To quantitate the mutant protein there is a fundamental need for more precise techniques that are aimed at defining the currently non-existent link between the levels of the target protein and subsequent drug efficacy. Using cutting-edge mass spectrometry combined with DNA and mRNA sequencing, the mutated B-raf protein within metastatic tumors was quantitated for the first time. B-raf V600E protein analysis revealed a subjacent layer of heterogeneity for mutation-positive metastatic melanomas. These were characterized into two distinct groups with different tumor morphologies, protein profiles and patient clinical outcomes. This study provides evidence that a higher level of expression in the mutated protein is associated with a more aggressive tumor progression. Our study design, comprised of surgical isolation of tumors, histopathological characterization, tissue biobanking, and protein analysis, may enable the eventual delineation of patient responders/non-responders and subsequent therapy for malignant melanoma.

Automated phosphopeptide enrichment from minute quantities of frozen malignant melanoma tissue.

To acquire a deeper understanding of malignant melanoma (MM), it is essential to study the proteome of patient tissues. In particular, phosphoproteomics of MM has become of significant importance because of the central role that phosphorylation plays in the development of MM. Investigating clinical samples, however, is an extremely challenging task as there is usually only very limited quantities of material available to perform targeted enrichment approaches. Here, an automated phosphopeptide enrichment protocol using the AssayMap Bravo platform was applied to MM tissues and assessed for performance. The strategy proved to be highly-sensitive, less prone to variability, less laborious than existing techniques and adequate for starting quantities at the microgram level. An Fe(III)-NTA-IMAC-based enrichment workflow was applied to a dilution series of MM tissue lysates. The workflow was efficient in terms of sensitivity, reproducibility and phosphosite localization; and from only 12.5 µg of sample, more than 1,000 phosphopeptides were identified. In addition, from 60 µg of protein material the number of identified phosphoproteins from individual MM samples was comparable to previous reports that used extensive fractionation methods. Our data set included key pathways that are involved in MM progression; such as MAPK, melanocyte development and integrin signaling. Moreover, tissue-specific immunological proteins were identified, that have not been previously observed in the proteome of MM-derived cell lines. In conclusion, this workflow is suitable to study large cohorts of clinical samples that demand automatic and careful handling.