| 1. |
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| 2. |
- Betancourt, Lazaro Hiram, et al.
(author)
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The human melanoma proteome atlas-Defining the molecular pathology
- 2021
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In: Clinical and Translational Medicine. - : Wiley. - 2001-1326. ; 11:7, s. 1-20
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Journal article (peer-reviewed)abstract
- 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.
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| 3. |
- Betancourt, Lazaro Hiram, et al.
(author)
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Improved survival prognostication of node-positive malignant melanoma patients utilizing shotgun proteomics guided by histopathological characterization and genomic data
- 2019
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In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1
-
Journal article (peer-reviewed)abstract
- Metastatic melanoma is one of the most common deadly cancers, and robust biomarkers are still needed, e.g. to predict survival and treatment efficiency. Here, protein expression analysis of one hundred eleven melanoma lymph node metastases using high resolution mass spectrometry is coupled with in-depth histopathology analysis, clinical data and genomics profiles. This broad view of protein expression allowed to identify novel candidate protein markers that improved prediction of survival in melanoma patients. Some of the prognostic proteins have not been reported in the context of melanoma before, and few of them exhibit unexpected relationship to survival, which likely reflects the limitations of current knowledge on melanoma and shows the potential of proteomics in clinical cancer research.
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| 4. |
- Betancourt, Lazaro Hiram, et al.
(author)
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The hidden story of heterogeneous B-raf V600E mutation quantitative protein expression in metastatic melanoma—association with clinical outcome and tumor phenotypes
- 2019
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In: Cancers. - : MDPI AG. - 2072-6694. ; 11:12
-
Journal article (peer-reviewed)abstract
- 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.
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| 5. |
- Boekel, Jorrit, et al.
(author)
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Multi-omic data analysis using Galaxy
- 2015
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In: Nature Biotechnology. - : Springer Science and Business Media LLC. - 1087-0156 .- 1546-1696. ; 33:2, s. 137-9
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Journal article (peer-reviewed)
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| 6. |
- Bouyssié, David, et al.
(author)
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WOMBAT-P : Benchmarking Label-Free Proteomics Data Analysis Workflows
- 2024
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In: Journal of Proteome Research. - 1535-3893. ; 23:1, s. 418-429
-
Journal article (peer-reviewed)abstract
- The inherent diversity of approaches in proteomics research has led to a wide range of software solutions for data analysis. These software solutions encompass multiple tools, each employing different algorithms for various tasks such as peptide-spectrum matching, protein inference, quantification, statistical analysis, and visualization. To enable an unbiased comparison of commonly used bottom-up label-free proteomics workflows, we introduce WOMBAT-P, a versatile platform designed for automated benchmarking and comparison. WOMBAT-P simplifies the processing of public data by utilizing the sample and data relationship format for proteomics (SDRF-Proteomics) as input. This feature streamlines the analysis of annotated local or public ProteomeXchange data sets, promoting efficient comparisons among diverse outputs. Through an evaluation using experimental ground truth data and a realistic biological data set, we uncover significant disparities and a limited overlap in the quantified proteins. WOMBAT-P not only enables rapid execution and seamless comparison of workflows but also provides valuable insights into the capabilities of different software solutions. These benchmarking metrics are a valuable resource for researchers in selecting the most suitable workflow for their specific data sets. The modular architecture of WOMBAT-P promotes extensibility and customization. The software is available at https://github.com/wombat-p/WOMBAT-Pipelines.
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| 7. |
- Brandsma, Corry Anke, et al.
(author)
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Integrated proteogenomic approach identifying a protein signature of COPD and a new splice variant of SORBS1
- 2020
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In: Thorax. - : BMJ. - 0040-6376 .- 1468-3296. ; 75:2, s. 180-183
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Journal article (peer-reviewed)abstract
- Translation of genomic alterations to protein changes in chronic obstructive pulmonary disease (COPD) is largely unexplored. Using integrated proteomic and RNA sequencing analysis of COPD and control lung tissues, we identified a protein signature in COPD characterised by extracellular matrix changes and a potential regulatory role for SUMO2. Furthermore, we identified 61 differentially expressed novel, non-reference, peptides in COPD compared with control lungs. This included two peptides encoding for a new splice variant of SORBS1, of which the transcript usage was higher in COPD compared with control lungs. These explorative findings and integrative proteogenomic approach open new avenues to further unravel the pathology of COPD.
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| 8. |
- Eriksson, Jonatan O., et al.
(author)
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Clusterwise Peak Detection and Filtering Based on Spatial Distribution to Efficiently Mine Mass Spectrometry Imaging Data
- 2019
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In: Analytical Chemistry. - : American Chemical Society (ACS). - 0003-2700 .- 1520-6882. ; , s. 11888-11896
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Journal article (peer-reviewed)abstract
- 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.
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| 9. |
- Eriksson, Jonatan O., et al.
(author)
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MSIWarp : A General Approach to Mass Alignment in Mass Spectrometry Imaging
- 2020
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In: Analytical Chemistry. - : American Chemical Society (ACS). - 0003-2700 .- 1520-6882. ; 92:24, s. 16138-16148
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Journal article (peer-reviewed)abstract
- 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.
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| 10. |
- Fehniger, Thomas, et al.
(author)
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Queries of MALDI-Imaging Global Datasets Identifying Ion Mass Signatures Associated with Tissue Compartments
- 2014
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In: Proteomics. - : Wiley. - 1615-9861 .- 1615-9853. ; 14:7-8, s. 862-871
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Journal article (peer-reviewed)abstract
- Scanning mass spectrometry by matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) creates large volumetric global datasets that describe the location and identity of ions registered at each sampling location. While thousands of ion peaks are recorded in a typical whole tissue analysis, only a fraction of these measured molecules are purposefully scrutinized within a given experimental design. To address this need, we recently reported new methods to query the full volume of MALDI-MSI data that correlate all ion masses to one another. As an example of this utility we demonstrate that specific ion peak m/z signatures can be used to localize similar histological structures within tissue samples. In this study we use the example of ion peak masses that are associated with tissue spaces occupied by airway bronchioles in rat lung samples. The volume of raw data was pre-processed into structures of 0.1 mass unit bins containing metadata collected at each sampling position. Interactive visualization in Paraview identified ion peaks that especially showed strong association with airway bronchioles but not vascular or parenchymal tissue compartments. Further iterative statistical correlation queries provided ranked indices of all m/z values in the global dataset regarding co-incident distributions at any given X,Y position in the histological spaces occupied by bronchioles The study further provides methods for extracting important information contained in global datasets that previously was unseen or inaccessible. This article is protected by copyright. All rights reserved.
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| 11. |
- Gil, Jeovanis, et al.
(author)
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Clinical protein science in translational medicine targeting malignant melanoma
- 2019
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In: Cell Biology and Toxicology. - : Springer Science and Business Media LLC. - 0742-2091 .- 1573-6822. ; 35:4, s. 293-332
-
Journal article (peer-reviewed)abstract
- 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.
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| 12. |
- Horvatovich, Péter, et al.
(author)
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In vitro Transcription/Translation System: A Versatile Tool in the Search for Missing Proteins
- 2015
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In: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 14:9, s. 3441-3451
-
Journal article (peer-reviewed)abstract
- Approximately 18% of all human genes purported to encode proteins have not been directly evidenced at the protein level, according to the validation criteria established by neXtProt, and are considered as “missing” proteins. One of the goals of the Chromosome-Centric Human Proteome Project (C-HPP) is to identify as many of these “missing” proteins as possible in human samples using mass spectrometry-based methods. To further this goal, a consortium of C–HPP teams (chromosomes 5, 10, 16 and 19) has joined forces to devise new strategies to identify “missing” proteins by use of a cell-free in vitro transcription/translation system (IVTT). The proposed strategy employs LC-MS/MS data-dependent acquisition (DDA) and targeted selective reaction monitoring (SRM) methods to scrutinize low complexity samples derived from IVTT translation. The optimized assays are then applied to identify “missing” proteins in human cells and tissues. We describe the approach and show proof-of-concept results for development of LC-SRM assays for identification of eighteen “missing” proteins. We believe that the IVTT system, when coupled with downstream mass spectrometric identification, can be applied to identify proteins that have eluded more traditional methods of detection.
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| 13. |
- Horvatovich, Peter, et al.
(author)
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Quest for Missing Proteins : Update 2015 on Chromosome-Centric Human Proteome Project
- 2015
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In: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 14:9, s. 3415-3431
-
Journal article (other academic/artistic)abstract
- 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 Wild (http://c-hpp.webhosting.rug.nl/) and in the Supporting Information.
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| 14. |
- Ngassie, Maunick Lefin Koloko, et al.
(author)
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Age-associated differences in the human lung extracellular matrix
- 2023
-
In: American Journal of Physiology - Lung Cellular and Molecular Physiology. - 1040-0605. ; 324:5, s. 799-814
-
Journal article (peer-reviewed)abstract
- Extracellular matrix (ECM) remodeling has been associated with chronic lung diseases. However, information about specific age-associated differences in lung ECM is currently limited. In this study, we aimed to identify and localize age-associated ECM differences in human lungs using comprehensive transcriptomic, proteomic, and immunohistochemical analyses. Our previously identified age-associated gene expression signature of the lung was re-analyzed limiting it to an aging signature based on 270 control patients (37–80 years) and focused on the Matrisome core geneset using geneset enrichment analysis. To validate the age-associated transcriptomic differences on protein level, we compared the age-associated ECM genes (false discovery rate, FDR < 0.05) with a profile of age-associated proteins identified from a lung tissue proteomics dataset from nine control patients (49–76 years) (FDR < 0.05). Extensive immunohistochemical analysis was used to localize and semi-quantify the age-associated ECM differences in lung tissues from 62 control patients (18–82 years). Comparative analysis of transcriptomic and proteomic data identified seven ECM proteins with higher expression with age at both gene and protein levels: COL1A1, COL6A1, COL6A2, COL14A1, FBLN2, LTBP4, and LUM. With immunohistochemistry, we demonstrated higher protein levels with age for COL6A2 in whole tissue, parenchyma, airway wall, and blood vessel, for COL14A1 and LUM in bronchial epithelium, and COL1A1 in lung parenchyma. Our study revealed that higher age is associated with lung ECM remodeling, with specific differences occurring in defined regions within the lung. These differences may affect lung structure and physiology with aging and as such may increase susceptibility to developing chronic lung diseases.
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| 15. |
- Rezeli, Melinda, et al.
(author)
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Comparative Proteomic Analysis of Extracellular Vesicles Isolated by Acoustic Trapping or Differential Centrifugation
- 2016
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In: Analytical Chemistry. - : American Chemical Society (ACS). - 0003-2700 .- 1520-6882. ; 88:17, s. 8577-8586
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Journal article (peer-reviewed)abstract
- 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.
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| 16. |
- Rosenling, Therese, et al.
(author)
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Profiling and Identification of Cerebrospinal Fluid Proteins in a Rat EAE Model of Multiple Sclerosis.
- 2012
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In: Journal of Proteome Research. - 1535-3893 .- 1535-3907. ; 11:4, s. 2048-2060
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Journal article (peer-reviewed)abstract
- The experimental autoimmune encephalomyelitis (EAE) model resembles certain aspects of multiple sclerosis (MScl), with common features such as motor dysfunction, axonal degradation, and infiltration of T-cells. We studied the cerebrospinal fluid (CSF) proteome in the EAE rat model to identify proteomic changes relevant for MScl disease pathology. EAE was induced in male Lewis rats by injection of myelin basic protein (MBP) together with complete Freund's adjuvant (CFA). An inflammatory control group was injected with CFA alone, and a nontreated group served as healthy control. CSF was collected at day 10 and 14 after immunization and analyzed by bottom-up proteomics on Orbitrap LC-MS and QTOF LC-MS platforms in two independent laboratories. By combining results, 44 proteins were discovered to be significantly increased in EAE animals compared to both control groups, 25 of which have not been mentioned in relation to the EAE model before. Lysozyme C1, fetuin B, T-kininogen, serum paraoxonase/arylesterase 1, glutathione peroxidase 3, complement C3, and afamin are among the proteins significantly elevated in this rat EAE model. Two proteins, afamin and complement C3, were validated in an independent sample set using quantitative selected reaction monitoring mass spectrometry. The molecular weights of the identified differentially abundant proteins indicated an increased transport across the blood-brain barrier (BBB) at the peak of the disease, caused by an increase in BBB permeability.
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| 17. |
- Rosenling, Therese, 1980-, et al.
(author)
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The effect of preanalytical factors on stability of the proteome and selected metabolites in cerebrospinal fluid (CSF).
- 2009
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In: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 8:12, s. 5511-22
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Journal article (peer-reviewed)abstract
- To standardize the use of cerebrospinal fluid (CSF) for biomarker research, a set of stability studies have been performed on porcine samples to investigate the influence of common sample handling procedures on proteins, peptides, metabolites and free amino acids. This study focuses at the effect on proteins and peptides, analyzed by applying label-free quantitation using microfluidics nanoscale liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (chipLC-MS) as well as matrix-assisted laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FT-ICR-MS) and Orbitrap LC-MS/MS to trypsin-digested CSF samples. The factors assessed were a 30 or 120 min time delay at room temperature before storage at -80 degrees C after the collection of CSF in order to mimic potential delays in the clinic (delayed storage), storage at 4 degrees C after trypsin digestion to mimic the time that samples remain in the cooled autosampler of the analyzer, and repeated freeze-thaw cycles to mimic storage and handling procedures in the laboratory. The delayed storage factor was also analyzed by gas chromatography mass spectrometry (GC-MS) and liquid chromatography mass spectrometry (LC-MS) for changes of metabolites and free amino acids, respectively. Our results show that repeated freeze/thawing introduced changes in transthyretin peptide levels. The trypsin digested samples left at 4 degrees C in the autosampler showed a time-dependent decrease of peak areas for peptides from prostaglandin D-synthase and serotransferrin. Delayed storage of CSF led to changes in prostaglandin D-synthase derived peptides as well as to increased levels of certain amino acids and metabolites. The changes of metabolites, amino acids and proteins in the delayed storage study appear to be related to remaining white blood cells. Our recommendations are to centrifuge CSF samples immediately after collection to remove white blood cells, aliquot, and then snap-freeze the supernatant in liquid nitrogen for storage at -80 degrees C. Preferably samples should not be left in the autosampler for more than 24 h and freeze/thaw cycles should be avoided if at all possible.
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| 18. |
- Rosenling, Therese, et al.
(author)
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The Impact of Delayed Storage on the Measured Proteome and Metabolome of Human Cerebrospinal Fluid
- 2011
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In: Clinical Chemistry. - : Oxford University Press (OUP). - 0009-9147 .- 1530-8561. ; 57:12, s. 1703-1711
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Journal article (peer-reviewed)abstract
- BACKGROUND: Because cerebrospinal fluid (CSF) is in close contact with diseased areas in neurological disorders, it is an important source of material in the search for molecular biomarkers. However, sample handling for CSF collected from patients in a clinical setting might not always be adequate for use in proteomics and metabolomics studies. METHODS: We left CSF for 0, 30, and 120 min at room temperature immediately after sample collection and centrifugation/removal of cells. After tryptic digestion at 2 laboratories by nanoLC Orbitrap-MS and chipLC QTOF-MS, CSF proteomes were analyzed. Metabolome analysis was performed at 3 laboratories by NMR, GC-MS, and LC-MS. Targeted analyses of cystatin C and albumin were performed by LC-MS/MS in the selected reaction monitoring mode. RESULTS: We did not find significant changes in the measured proteome and metabolome of CSF stored at room temperature after centrifugation, except for 2 peptides and 1 metabolite, 2,3,4-trihydrobutanoic acid, of 5780 identified peptides and 93 identified metabolites. A sensitive protein stability marker, cystatin C, was not affected. CONCLUSIONS: The measured proteome and metabolome of centrifuged, human CSF is stable at room temperature for up to 2 hours. We cannot exclude, however, that changes undetectable with our current methodology, such as denaturation or proteolysis, might occur due to sample handling conditions. The stability we observed gives laboratory personnel at the collection site sufficient time to aliquot samples before freezing and storage at -80 °C.
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| 19. |
- Sanchez, Aniel, et al.
(author)
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Novel functional proteins coded by the human genome discovered in metastases of melanoma patients
- 2020
-
In: Cell Biology and Toxicology. - : Springer Science and Business Media LLC. - 0742-2091 .- 1573-6822. ; 36:3, s. 261-272
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Journal article (peer-reviewed)abstract
- 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.
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| 20. |
- Sánchez Brotons, Alejandro, et al.
(author)
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Pipelines and Systems for Threshold-Avoiding Quantification of LC-MS/MS Data
- 2021
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In: Analytical Chemistry. - : American Chemical Society (ACS). - 0003-2700 .- 1520-6882. ; 93:32, s. 11215-11224
-
Journal article (peer-reviewed)abstract
- The accurate processing of complex liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) data from biological samples is a major challenge for metabolomics, proteomics, and related approaches. Here, we present the pipelines and systems for threshold-avoiding quantification (PASTAQ) LC-MS/MS preprocessing toolset, which allows highly accurate quantification of data-dependent acquisition LC-MS/MS datasets. PASTAQ performs compound quantification using single-stage (MS1) data and implements novel algorithms for high-performance and accurate quantification, retention time alignment, feature detection, and linking annotations from multiple identification engines. PASTAQ offers straightforward parameterization and automatic generation of quality control plots for data and preprocessing assessment. This design results in smaller variance when analyzing replicates of proteomes mixed with known ratios and allows the detection of peptides over a larger dynamic concentration range compared to widely used proteomics preprocessing tools. The performance of the pipeline is also demonstrated in a biological human serum dataset for the identification of gender-related proteins.
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| 21. |
- Suits, Frank, et al.
(author)
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Threshold-avoiding proteomics pipeline.
- 2011
-
In: Analytical Chemistry. - : American Chemical Society (ACS). - 0003-2700 .- 1520-6882. ; 83:20, s. 7786-94
-
Journal article (peer-reviewed)abstract
- We present a new proteomics analysis pipeline focused on maximizing the dynamic range of detected molecules in liquid chromatography-mass spectrometry (LC-MS) data and accurately quantifying low-abundance peaks to identify those with biological relevance. Although there has been much work to improve the quality of data derived from LC-MS instruments, the goal of this study was to extend the dynamic range of analyzed compounds by making full use of the information available within each data set and across multiple related chromatograms in an experiment. Our aim was to distinguish low-abundance signal peaks from noise by noting their coherent behavior across multiple data sets, and central to this is the need to delay the culling of noise peaks until the final peak-matching stage of the pipeline, when peaks from a single sample appear in the context of all others. The application of thresholds that might discard signal peaks early is thereby avoided, hence the name TAPP: threshold-avoiding proteomics pipeline. TAPP focuses on quantitative low-level processing of raw LC-MS data and includes novel preprocessing, peak detection, time alignment, and cluster-based matching. We demonstrate the performance of TAPP on biologically relevant sample data consisting of porcine cerebrospinal fluid spiked over a wide range of concentrations with horse heart cytochrome c.
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| 22. |
- Szadai, Leticia, et al.
(author)
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Deep proteomic analysis on biobanked paraffine-archived melanoma with prognostic/predictive biomarker read-out
- 2021
-
In: Cancers. - : MDPI AG. - 2072-6694. ; 13:23
-
Journal article (peer-reviewed)abstract
- The discovery of novel protein biomarkers in melanoma is crucial. Our introduction of formalin-fixed paraffin-embedded (FFPE) tumor protocol provides new opportunities to understand the progression of melanoma and open the possibility to screen thousands of FFPE samples deposited in tumor biobanks and available at hospital pathology departments. In our retrospective biobank pilot study, 90 FFPE samples from 77 patients were processed. Protein quantitation was performed by high-resolution mass spectrometry and validated by histopathologic analysis. The global protein expression formed six sample clusters. Proteins such as TRAF6 and ARMC10 were upregulated in clusters with enrichment for shorter survival, and proteins such as AIFI1 were upregulated in clusters with enrichment for longer survival. The cohort’s heterogeneity was addressed by comparing primary and metastasis samples, as well comparing clinical stages. Within immunotherapy and targeted therapy subgroups, the upregulation of the VEGFA-VEGFR2 pathway, RNA splicing, increased activity of immune cells, extracellular matrix, and metabolic pathways were positively associated with patient outcome. To summarize, we were able to (i) link global protein expression profiles to survival, and they proved to be an independent prognostic indicator, as well as (ii) identify proteins that are potential predictors of a patient’s response to immunotherapy and targeted therapy, suggesting new opportunities for precision medicine developments.
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| 23. |
- Szeitz, Beáta, et al.
(author)
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In-depth proteomic analysis reveals unique subtype-specific signatures in human small-cell lung cancer
- 2022
-
In: Clinical and Translational Medicine. - : Wiley. - 2001-1326. ; 12:9, s. 1060-1060
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Journal article (peer-reviewed)abstract
- BACKGROUND: Small-cell lung cancer (SCLC) molecular subtypes have been primarily characterized based on the expression pattern of the following key transcription regulators: ASCL1 (SCLC-A), NEUROD1 (SCLC-N), POU2F3 (SCLC-P) and YAP1 (SCLC-Y). Here, we investigated the proteomic landscape of these molecular subsets with the aim to identify novel subtype-specific proteins of diagnostic and therapeutic relevance.METHODS: Pellets and cell media of 26 human SCLC cell lines were subjected to label-free shotgun proteomics for large-scale protein identification and quantitation, followed by in-depth bioinformatic analyses. Proteomic data were correlated with the cell lines' phenotypic characteristics and with public transcriptomic data of SCLC cell lines and tissues.RESULTS: Our quantitative proteomic data highlighted that four molecular subtypes are clearly distinguishable at the protein level. The cell lines exhibited diverse neuroendocrine and epithelial-mesenchymal characteristics that varied by subtype. A total of 367 proteins were identified in the cell pellet and 34 in the culture media that showed significant up- or downregulation in one subtype, including known druggable proteins and potential blood-based markers. Pathway enrichment analysis and parallel investigation of transcriptomics from SCLC cell lines outlined unique signatures for each subtype, such as upregulated oxidative phosphorylation in SCLC-A, DNA replication in SCLC-N, neurotrophin signalling in SCLC-P and epithelial-mesenchymal transition in SCLC-Y. Importantly, we identified the YAP1-driven subtype as the most distinct SCLC subgroup. Using sparse partial least squares discriminant analysis, we identified proteins that clearly distinguish four SCLC subtypes based on their expression pattern, including potential diagnostic markers for SCLC-Y (e.g. GPX8, PKD2 and UFO).CONCLUSIONS: We report for the first time, the protein expression differences among SCLC subtypes. By shedding light on potential subtype-specific therapeutic vulnerabilities and diagnostic biomarkers, our results may contribute to a better understanding of SCLC biology and the development of novel therapies.
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- Vizcaíno, Juan Antonio, et al.
(author)
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A community proposal to integrate proteomics activities in ELIXIR
- 2017
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In: F1000Research. - : F1000 Research Ltd. - 2046-1402. ; 6
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Journal article (peer-reviewed)abstract
- Computational approaches have been major drivers behind the progress of proteomics in recent years. The aim of this white paper is to provide a framework for integrating computational proteomics into ELIXIR in the near future, and thus to broaden the portfolio of omics technologies supported by this European distributed infrastructure. This white paper is the direct result of a strategy meeting on 'The Future of Proteomics in ELIXIR' that took place in March 2017 in Tübingen (Germany), and involved representatives of eleven ELIXIR nodes. These discussions led to a list of priority areas in computational proteomics that would complement existing activities and close gaps in the portfolio of tools and services offered by ELIXIR so far. We provide some suggestions on how these activities could be integrated into ELIXIR's existing platforms, and how it could lead to a new ELIXIR use case in proteomics. We also highlight connections to the related field of metabolomics, where similar activities are ongoing. This white paper could thus serve as a starting point for the integration of computational proteomics into ELIXIR. Over the next few months we will be working closely with all stakeholders involved, and in particular with other representatives of the proteomics community, to further refine this paper.
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