Dual targeting of BCL-2 and MCL-1 in the presence of BAX breaks venetoclax resistance in human small cell lung cancer.

BACKGROUND: No targeted drugs are currently available against small cell lung cancer (SCLC). BCL-2 family members are involved in apoptosis regulation and represent therapeutic targets in many malignancies. METHODS: Expression of BCL-2 family members in 27 SCLC cell lines representing all known four SCLC molecular subtypes was assessed by qPCR, Western blot and mass spectrometry-based proteomics. BCL-2 and MCL-1 inhibition (venetoclax and S63845, respectively) was assessed by MTT assay and flow cytometry and in mice bearing human SCLC tumours. Drug interactions were calculated using the Combenefit software. Ectopic BAX overexpression was achieved by expression plasmids. RESULTS: The highest BCL-2 expression levels were detected in ASCL1- and POU2F3-driven SCLC cells. Although sensitivity to venetoclax was reflected by BCL-2 levels, not all cell lines responded consistently despite their high BCL-2 expression. MCL-1 overexpression and low BAX levels were both characteristic for venetoclax resistance in SCLC, whereas the expression of other BCL-2 family members did not affect therapeutic efficacy. Combination of venetoclax and S63845 resulted in significant, synergistic in vitro and in vivo anti-tumour activity and apoptosis induction in double-resistant cells; however, this was seen only in a subset with detectable BAX. In non-responding cells, ectopic BAX overexpression sensitised to venetoclax and S63845 and, furthermore, induced synergistic drug interaction. CONCLUSIONS: The current study reveals the subtype specificity of BCL-2 expression and sheds light on the mechanism of venetoclax resistance in SCLC. Additionally, we provide preclinical evidence that combined BCL-2 and MCL-1 targeting is an effective approach to overcome venetoclax resistance in high BCL-2-expressing SCLCs with intact BAX.

Expression patterns and prognostic relevance of subtype-specific transcription factors in surgically resected small-cell lung cancer: an international multicenter study.

The tissue distribution and prognostic relevance of subtype-specific proteins (ASCL1, NEUROD1, POU2F3, YAP1) present an evolving area of research in small-cell lung cancer (SCLC). The expression of subtype-specific transcription factors and P53 and RB1 proteins were measured by immunohistochemistry (IHC) in 386 surgically resected SCLC samples. Correlations between subtype-specific proteins and in vitro efficacy of various therapeutic agents were investigated by proteomics and cell viability assays in 26 human SCLC cell lines. Besides SCLC-A (ASCL1-dominant), SCLC-AN (combined ASCL1/NEUROD1), SCLC-N (NEUROD1-dominant), and SCLC-P (POU2F3-dominant), IHC and cluster analyses identified a quadruple-negative SCLC subtype (SCLC-QN). No unique YAP1-subtype was found. The highest overall survival rates were associated with non-neuroendocrine subtypes (SCLC-P and SCLC-QN) and the lowest with neuroendocrine subtypes (SCLC-A, SCLC-N, SCLC-AN). In univariate analyses, high ASCL1 expression was associated with poor prognosis and high POU2F3 expression with good prognosis. Notably, high ASCL1 expression influenced survival outcomes independently of other variables in a multivariate model. High POU2F3 and YAP1 protein abundances correlated with sensitivity and resistance to standard-of-care chemotherapeutics, respectively. Specific correlation patterns were also found between the efficacy of targeted agents and subtype-specific protein abundances. In conclusion, we investigated the clinicopathological relevance of SCLC molecular subtypes in a large cohort of surgically resected specimens. Differential IHC expression of ASCL1, NEUROD1, and POU2F3 defines SCLC subtypes. No YAP1-subtype can be distinguished by IHC. High POU2F3 expression is associated with improved survival in a univariate analysis, whereas elevated ASCL1 expression is an independent negative prognosticator. Proteomic and cell viability assays of human SCLC cell lines revealed distinct vulnerability profiles defined by transcription regulators. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Distinct subcellular autophagy impairments in induced neurons from patients with Huntington's disease.

Huntington's disease is a neurodegenerative disorder caused by CAG expansions in the huntingtin (HTT) gene. Modelling Huntington's disease is challenging, as rodent and cellular models poorly recapitulate the disease as seen in ageing humans. To address this, we generated induced neurons through direct reprogramming of human skin fibroblasts, which retain age-dependent epigenetic characteristics. Huntington's disease induced neurons (HD-iNs) displayed profound deficits in autophagy, characterized by reduced transport of late autophagic structures from the neurites to the soma. These neurite-specific alterations in autophagy resulted in shorter, thinner and fewer neurites specifically in HD-iNs. CRISPRi-mediated silencing of HTT did not rescue this phenotype but rather resulted in additional autophagy alterations in control induced neurons, highlighting the importance of wild-type HTT in normal neuronal autophagy. In summary, our work identifies a distinct subcellular autophagy impairment in adult patient derived Huntington's disease neurons and provides a new rationale for future development of autophagy activation therapies.

Non-Invasive, Topical Sampling of Potential, Low-Molecular Weight, Skin Cancer Biomarkers: A Study on Healthy Volunteers.

Monitoring of low-molecular weight cancer biomarkers, such as tryptophan (Trp) and its derivative kynurenine (Kyn), might be advantageous to non-invasive skin cancer detection. Thus, we assessed several approaches of topical sampling of Trp and Kyn, in relation to phenylalanine (Phe) and tyrosine (Tyr), on the volar forearm of six healthy volunteers. The sampling was performed with three hydrogels (made of agarose or/and chitosan), hydrated starch films, cotton swabs, and tape stripping. The biomarkers were successfully sampled by all approaches, but the amount of collected Kyn was low, 20 ± 10 pmol/cm2. Kyn quantification was below LOQ, and thus, it was detected only in 20% of topical samples. To mitigate variability problems of absolute amounts of sampled amino acids, Tyr/Trp, Phe/Trp, and Phe/Tyr ratios were assessed, proving reduced inter-individual variation from 79 to 45% and intra-individual variation from 42 to 21%. Strong positive correlation was found between Phe and Trp, pointing to the Phe/Trp ratio (being in the 1.0-2.0 range, at 95% confidence) being least dependent on sampling materials, approaches, and sweating. This study leads to conclusion that due to the difficulty in quantifying less abundant Kyn, and thus the Trp/Kyn ratio, the Phe/Trp ratio might be a possible, alternative biomarker for detecting skin cancers.

Proteomic Workflows for High-Quality Quantitative Proteome and Post-Translational Modification Analysis of Clinically Relevant Samples from Formalin-Fixed Paraffin-Embedded Archives.

Well-characterized archival formalin-fixed paraffin-embedded (FFPE) tissues are of much value for prospective biomarker discovery studies, and protocols that offer high throughput and good reproducibility are essential in proteomics. Therefore, we implemented efficient paraffin removal and protein extraction from FFPE tissues followed by an optimized two-enzyme digestion using suspension trapping (S-Trap). The protocol was then combined with TMTpro 16plex labeling and applied to lung adenocarcinoma patient samples. In total, 9585 proteins were identified, and proteins related to the clinical outcome were detected. Because acetylation is known to play a major role in cancer development, a fast on-trap acetylation protocol was developed for studying endogenous lysine acetylation, which allows identification and localization of the lysine acetylation together with quantitative comparison between samples. We demonstrated that FFPE tissues are equivalent to frozen tissues to study the degree of acetylation between patients. In summary, we present a reproducible sample preparation workflow optimized for FFPE tissues that resolves known proteomic-related challenges. We demonstrate compatibility of the S-Trap with isobaric labeling and for the first time, we prove that it is feasible to study endogenous lysine acetylation stoichiometry in FFPE tissues, contributing to better utility of the existing global tissue archives. The MS proteomic data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifiers PXD020157, PXD021986, and PXD021964.

MSIWarp: A General Approach to Mass Alignment in Mass Spectrometry Imaging.

Mass spectrometry imaging (MSI) is a technique that provides comprehensive molecular information with high spatial resolution from tissue. Today, there is a strong push toward sharing data sets through public repositories in many research fields where MSI is commonly applied; yet, there is no standardized protocol for analyzing these data sets in a reproducible manner. Shifts in the mass-to-charge ratio (m/z) of molecular peaks present a major obstacle that can make it impossible to distinguish one compound from another. Here, we present a label-free m/z alignment approach that is compatible with multiple instrument types and makes no assumptions on the sample's molecular composition. Our approach, MSIWarp (https://github.com/horvatovichlab/MSIWarp), finds an m/z recalibration function by maximizing a similarity score that considers both the intensity and m/z position of peaks matched between two spectra. MSIWarp requires only centroid spectra to find the recalibration function and is thereby readily applicable to almost any MSI data set. To deal with particularly misaligned or peak-sparse spectra, we provide an option to detect and exclude spurious peak matches with a tailored random sample consensus (RANSAC) procedure. We evaluate our approach with four publicly available data sets from both time-of-flight (TOF) and Orbitrap instruments and demonstrate up to 88% improvement in m/z alignment.

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.

Visualisation of H2O2 penetration through skin indicates importance to develop pathway-specific epidermal sensing.

Elevated amounts of reactive oxygen species (ROS) including hydrogen peroxide (H2O2) are observed in the epidermis in different skin disorders. Thus, epidermal sensing of H2O2 should be useful to monitor the progression of skin pathologies. We have evaluated epidermal sensing of H2O2 in vitro, by visualising H2O2 permeation through the skin. Skin membranes were mounted in Franz cells, and a suspension of Prussian white microparticles was deposited on the stratum corneum face of the skin. Upon H2O2 permeation, Prussian white was oxidised to Prussian blue, resulting in a pattern of blue dots. Comparison of skin surface images with the dot patterns revealed that about 74% of the blue dots were associated with hair shafts. The degree of the Prussian white to Prussian blue conversion strongly correlated with the reciprocal resistance of the skin membranes. Together, the results demonstrate that hair follicles are the major pathways of H2O2 transdermal penetration. The study recommends that the development of H2O2 monitoring on skin should aim for pathway-specific epidermal sensing, allowing micrometre resolution to detect and quantify this ROS biomarker at hair follicles.Graphical abstract.

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.

Proteomic signatures of brain regions affected by tau pathology in early and late stages of Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is the most common neurodegenerative disorder. Depositions of amyloid ß peptide (Aß) and tau protein are among the major pathological hallmarks of AD. Aß and tau burden follows predictable spatial patterns during the progression of AD. Nevertheless, it remains obscure why certain brain regions are more vulnerable than others; to investigate this and dysregulated pathways during AD progression, a mass spectrometry-based proteomics study was performed. METHODS: In total 103 tissue samples from regions early (entorhinal and parahippocampal cortices - medial temporal lobe (MTL)) and late affected (temporal and frontal cortices - neocortex) by tau pathology were subjected to label-free quantitative proteomics analysis. RESULTS: Considering dysregulated proteins during AD progression, the majority (625 out of 737 proteins) was region specific, while some proteins were shared between regions (101 proteins altered in two areas and 11 proteins altered in three areas). Analogously, many dysregulated pathways during disease progression were exclusive to certain regions, but a few pathways altered in two or more areas. Changes in protein expression indicate that synapse loss occurred in all analyzed regions, while translation dysregulation was preponderant in entorhinal, parahippocampal and frontal cortices. Oxidative phosphorylation impairment was prominent in MTL. Differential proteomic analysis of brain areas in health state (controls) showed higher metabolism and increased expression of AD-related proteins in the MTL compared to the neocortex. In addition, several proteins that differentiate brain regions in control tissue were dysregulated in AD. CONCLUSIONS: This work provides the comparison of proteomic changes in brain regions affected by tau pathology at different stages of AD. Although we identified commonly regulated proteins and pathways during disease advancement, we found that the dysregulated processes are predominantly region specific. In addition, a distinct proteomic signature was found between MTL and neocortex in healthy subjects that might be related to AD vulnerability. These findings highlight the need for investigating AD's cascade of events throughout the whole brain and studies spanning more brain areas are required to better understand AD etiology and region vulnerability to disease.

Clusterwise Peak Detection and Filtering Based on Spatial Distribution To Efficiently Mine Mass Spectrometry Imaging Data.

Mass spectrometry imaging (MSI) has the potential to reveal the localization of thousands of biomolecules such as metabolites and lipids in tissue sections. The increase in both mass and spatial resolution of today's instruments brings on considerable challenges in terms of data processing; accurately extracting meaningful signals from the large data sets generated by MSI without losing information that could be clinically relevant is one of the most fundamental tasks of analysis software. Ion images of the biomolecules are generated by visualizing their intensities in 2-D space using mass spectra collected across the tissue section. The intensities are often calculated by summing each compound's signal between predefined sets of borders (bins) in the m/z dimension. This approach, however, can result in mixed signals from different compounds in the same bin or splitting the signal from one compound between two adjacent bins, leading to low quality ion images. To remedy this problem, we propose a novel data processing approach. Our approach consists of a sensitive peak detection method able to discover both faint and localized signals by utilizing clusterwise kernel density estimates (KDEs) of peak distributions. We show that our method can recall more ground-truth molecules, molecule fragments, and isotopes than existing methods based on binning. Furthermore, it automatically detects previously reported molecular ions of lipids, including those close in m/z, in an experimental data set.

Challenging the heterogeneity of disease presentation in malignant melanoma-impact on patient treatment.

There is an increasing global interest to support research areas that can assist in understanding disease and improving patient care. The National Cancer Institute (NIH) has identified precision medicine-based approaches as key research strategies to expedite advances in cancer research. The Cancer Moonshot program ( https://www.cancer.gov/research/key-initiatives/moonshot-cancer-initiative ) is the largest cancer program of all time, and has been launched to accelerate cancer research that aims to increase the availability of therapies to more patients and, ultimately, to eradicate cancer. Mass spectrometry-based proteomics has been extensively used to study the molecular mechanisms of cancer, to define molecular subtypes of tumors, to map cancer-associated protein interaction networks and post-translational modifications, and to aid in the development of new therapeutics and new diagnostic and prognostic tests. To establish the basis for our melanoma studies, we have established the Southern Sweden Malignant Melanoma Biobank. Tissues collected over many years have been accurately characterized with respect to the tumor and patient information. The extreme variability displayed in the protein profiles and the detection of missense mutations has confirmed the complexity and heterogeneity of the disease. It is envisaged that the combined analysis of clinical, histological, and proteomic data will provide patients with a more personalized medical treatment. With respect to disease presentation, targeted treatment and medical mass spectrometry analysis and imaging, this overview report will outline and summarize the current achievements and status within malignant melanoma. We present data generated by our cancer research center in Lund, Sweden, where we have built extensive capabilities in biobanking, proteogenomics, and patient treatments over an extensive time period.

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.

Biology/Disease-Driven Initiative on Protein-Aggregation Diseases of the Human Proteome Project: Goals and Progress to Date.

The Biology/Disease-driven (B/D) working groups of the Human Proteome Project are alliances of research groups aimed at developing or improving proteomic tools to support specific biological or disease-related research areas. Here, we describe the activities and progress to date of the B/D working group focused on protein aggregation diseases (PADs). PADs are characterized by the intra- or extracellular accumulation of aggregated proteins and include devastating diseases such as Parkinson's and Alzheimer's disease and systemic amyloidosis. The PAD B/D working group aims for the development of proteomic assays for the quantification of aggregation-prone proteins involved in PADs to support basic and clinical research on PADs. Because the proteins in PADs undergo aberrant conformational changes, a goal is to quantitatively resolve altered protein structures and aggregation states in complex biological specimens. We have developed protein-extraction protocols and a set of mass spectrometric (MS) methods that enable the detection and quantification of proteins involved in the systemic and localized amyloidosis and the probing of aberrant protein conformational transitions in cell and tissue extracts. In several studies, we have demonstrated the potential of MS-based proteomics approaches for specific and sensitive clinical diagnoses and for the subtyping of PADs. The developed methods have been detailed in both protocol papers and manuscripts describing applications to facilitate implementation by nonspecialized laboratories, and assay coordinates are shared through public repositories and databases. Clinicians actively involved in the PAD working group support the transfer to clinical practice of the developed methods, such as assays to quantify specific disease-related proteins and their fragments in biofluids and multiplexed MS-based methods for the diagnosis and typing of systemic amyloidosis. We believe that the increasing availability of tools to precisely measure proteins involved in PADs will positively impact research on the molecular bases of these diseases and support early disease diagnosis and a more-confident subtyping.

Quantitation of 87 Proteins by nLC-MRM/MS in Human Plasma: Workflow for Large-Scale Analysis of Biobank Samples.

A multiple reaction monitoring (MRM) assay was developed for precise quantitation of 87 plasma proteins including the three isoforms of apolipoprotein E (APOE) associated with cardiovascular diseases using nanoscale liquid chromatography separation and stable isotope dilution strategy. The analytical performance of the assay was evaluated and we found an average technical variation of 4.7% in 4-5 orders of magnitude dynamic range (≈0.2 mg/L to 4.5 g/L) from whole plasma digest. Here, we report a complete workflow, including sample processing adapted to 96-well plate format and normalization strategy for large-scale studies. To further investigate the MS-based quantitation the amount of six selected proteins was measured by routinely used clinical chemistry assays as well and the two methods showed excellent correlation with high significance (p-value < 10e-5) for the six proteins, in addition for the cardiovascular predictor factor, APOB: APOA1 ratio (r = 0.969, p-value < 10e-5). Moreover, we utilized the developed assay for screening of biobank samples from patients with myocardial infarction and performed the comparative analysis of patient groups with STEMI (ST- segment elevation myocardial infarction), NSTEMI (non ST- segment elevation myocardial infarction) and type-2 AMI (type-2 myocardial infarction) patients.

Erratum to: Association of chromosome 19 to lung cancer genotypes and phenotypes.

Erratum to: Cancer and Metastasis Review, DOI 10.1007/s10555-015-9556-2. There are changes in authors' affiliations and a new affiliations for Carol L. Nilsson and Thomas E. Fehniger has been added. The corresponding author also missed out to include Peter Horvatovich as a co-author of this work. The complete list of authors is now listed above.

Association of chromosome 19 to lung cancer genotypes and phenotypes.

The Chromosome 19 Consortium, a part of the Chromosome-Centric Human Proteome Project (C-HPP, http://www.C-HPP.org ), is tasked with the understanding chromosome 19 functions at the gene and protein levels, as well as their roles in lung oncogenesis. Comparative genomic hybridization (CGH) studies revealed chromosome aberration in lung cancer subtypes, including ADC, SCC, LCC, and SCLC. The most common abnormality is 19p loss and 19q gain. Sixty-four aberrant genes identified in previous genomic studies and their encoded protein functions were further validated in the neXtProt database ( http://www.nextprot.org/ ). Among those, the loss of tumor suppressor genes STK11, MUM1, KISS1R (19p13.3), and BRG1 (19p13.13) is associated with lung oncogenesis or remote metastasis. Gene aberrations include translocation t(15, 19) (q13, p13.1) fusion oncogene BRD4-NUT, DNA repair genes (ERCC1, ERCC2, XRCC1), TGFß1 pathway activation genes (TGFB1, LTBP4), Dyrk1B, and potential oncogenesis protector genes such as NFkB pathway inhibition genes (NFKBIB, PPP1R13L) and EGLN2. In conclusion, neXtProt is an effective resource for the validation of gene aberrations identified in genomic studies. It promises to enhance our understanding of lung cancer oncogenesis.

Comparative Proteomic Analysis of Extracellular Vesicles Isolated by Acoustic Trapping or Differential Centrifugation.

Extracellular vesicles (ECVs), including microparticles and exosomes, are submicrometer membrane vesicles released by diverse cell types upon activation or stress. Circulating ECVs are potential reservoirs of disease biomarkers, and the complexity of these vesicles is significantly lower compared to their source, blood plasma, which makes ECV-based biomarker studies more promising. Proteomic profiling of ECVs is important not only to discover new diagnostic or prognostic markers but also to understand their roles in biological function. In the current study, we investigated the protein composition of plasma-derived ECVs isolated by acoustic seed trapping. Additionally, the protein composition of ECVs isolated with acoustic trapping was compared to that isolated with a conventional differential centrifugation protocol. Finally, the proteome of ECVs originating from ST-elevation myocardial infarction patients was compared with that of healthy controls using label-free LC-MS quantification. The acoustic trapping platform allows rapid and automated preparation of ECVs from small sample volumes, which are therefore well-suited for biobank repositories. We found that the protein composition of trapped ECVs is very similar to that isolated by the conventional differential centrifugation method.

Systematic identification of single amino acid variants in glioma stem-cell-derived chromosome 19 proteins.

Novel proteoforms with single amino acid variations represent proteins that often have altered biological functions but are less explored in the human proteome. We have developed an approach, searching high quality shotgun proteomic data against an extended protein database, to identify expressed mutant proteoforms in glioma stem cell (GSC) lines. The systematic search of MS/MS spectra using PEAKS 7.0 as the search engine has recognized 17 chromosome 19 proteins in GSCs with altered amino acid sequences. The results were further verified by manual spectral examination, validating 19 proteoforms. One of the novel findings, a mutant form of branched-chain aminotransferase 2 (p.Thr186Arg), was verified at the transcript level and by targeted proteomics in several glioma stem cell lines. The structure of this proteoform was examined by molecular modeling in order to estimate conformational changes due to mutation that might lead to functional modifications potentially linked to glioma. Based on our initial findings, we believe that our approach presented could contribute to construct a more complete map of the human functional proteome.

Quest for Missing Proteins: Update 2015 on Chromosome-Centric Human Proteome Project.

This paper summarizes the recent activities of the Chromosome-Centric Human Proteome Project (C-HPP) consortium, which develops new technologies to identify yet-to-be annotated proteins (termed "missing proteins") in biological samples that lack sufficient experimental evidence at the protein level for confident protein identification. The C-HPP also aims to identify new protein forms that may be caused by genetic variability, post-translational modifications, and alternative splicing. Proteogenomic data integration forms the basis of the C-HPP's activities; therefore, we have summarized some of the key approaches and their roles in the project. We present new analytical technologies that improve the chemical space and lower detection limits coupled to bioinformatics tools and some publicly available resources that can be used to improve data analysis or support the development of analytical assays. Most of this paper's content has been compiled from posters, slides, and discussions presented in the series of C-HPP workshops held during 2014. All data (posters, presentations) used are available at the C-HPP Wiki (http://c-hpp.webhosting.rug.nl/) and in the Supporting Information.