Showing papers in "Proteomics Clinical Applications in 2019"

The Case for Proteomics and Phospho-Proteomics in Personalized Cancer Medicine.

Abstract: The concept of personalized medicine is predominantly been pursued through genomic and transcriptomic technologies, leading to the identification of multiple mutations in a large variety of cancers. However, it has proven challenging to distinguish driver and passenger mutations and to deal with tumor heterogeneity and resistant clonal populations. More generally, these heterogeneous mutation patterns do not in themselves predict the tumor phenotype. Analysis of the expressed proteins in a tumor and their modification states reveals if and how these mutations are translated to the functional level. It is already known that proteomic changes including posttranslational modifications are crucial drivers of oncogenesis, but proteomics technology has only recently become comparable in depth and accuracy to RNAseq. These advances also allow the rapid and highly sensitive analysis of formalin-fixed and paraffin-embedded biobank tissues, on both the proteome and phosphoproteome levels. In this perspective, pioneering mass spectrometry-based proteomic studies are highlighted that pave the way toward clinical implementation. It is argued that proteomics and phosphoproteomics could provide the missing link to make omics analysis actionable in the clinic.

Quantitative Proteomic Profiling of Cerebrospinal Fluid to Identify Candidate Biomarkers for Alzheimer's Disease.

Abstract: Purpose The aim of this study is to identify the potential cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease and to evaluate these markers on independent CSF samples using parallel reaction monitoring (PRM) assays. Experimental design High-Resolution mass spectrometry and tandem mass tag (TMT) multiplexing technology are employed to identify potential biomarkers for Alzheimer's disease. Some of the identified potential biomarkers are validated using PRM assays. Results A total of 2327 proteins are identified in the CSF of which 139 are observed to be significantly altered in the CSF of AD patients. The proteins altered in AD includes a number of known AD marker such as MAPT, NPTX2, VGF, GFAP, and NCAM1 as well as novel biomarkers such as PKM and YWHAG. These findings are validated in a separate set of CSF specimens from AD dementia patients and controls. NPTX2, in combination with PKM or YWHAG, leads to the best results with AUCs of 0.935 and 0.933, respectively. Conclusions and clinical relevance The proteins that are found to be altered in the CSF of patients with AD could be used for monitoring disease progression and therapeutic response and perhaps also for early detection once they are validated in larger studies.

Site-to-Site Reproducibility and Spatial Resolution in MALDI-MSI of Peptides from Formalin-Fixed Paraffin-Embedded Samples.

Abstract: Purpose To facilitate the transition of MALDI-MS Imaging (MALDI-MSI) from basic science to clinical application, it is necessary to analyze formalin-fixed paraffin-embedded (FFPE) tissues. The aim is to improve in situ tryptic digestion for MALDI-MSI of FFPE samples and determine if similar results would be reproducible if obtained from different sites. Experimental design FFPE tissues (mouse intestine, human ovarian teratoma, tissue microarray of tumor entities sampled from three different sites) are prepared for MALDI-MSI. Samples are coated with trypsin using an automated sprayer then incubated using deliquescence to maintain a stable humid environment. After digestion, samples are sprayed with CHCA using the same spraying device and analyzed with a rapifleX MALDI Tissuetyper at 50 µm spatial resolution. Data are analyzed using flexImaging, SCiLS, and R. Results Trypsin application and digestion are identified as sources of variation and loss of spatial resolution in the MALDI-MSI of FFPE samples. Using the described workflow, it is possible to discriminate discrete histological features in different tissues and enabled different sites to generate images of similar quality when assessed by spatial segmentation and PCA. Conclusions and clinical relevance Spatial resolution and site-to-site reproducibility can be maintained by adhering to a standardized MALDI-MSI workflow.

MALDI-Imaging for Classification of Epithelial Ovarian Cancer Histotypes from a Tissue Microarray Using Machine Learning Methods

Abstract: Purpose Precise histological classification of epithelial ovarian cancer (EOC) has immanent diagnostic and therapeutic consequences, but remains challenging in histological routine. The aim of this pilot study is to examine the potential of matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry in combination with machine learning methods to classify EOC histological subtypes from tissue microarray. Experimental design Formalin-fixed-paraffin-embedded tissue of 20 patients with ovarian clear-cell, 14 low-grade serous, 19 high-grade serous ovarian carcinomas, and 14 serous borderline tumors are analyzed using MALDI-Imaging. Classifications are computed by linear discriminant analysis (LDA), support vector machines with linear (SVM-lin) and radial basis function kernels (SVM-rbf), a neural network (NN), and a convolutional neural network (CNN). Results MALDI-Imaging and machine learning methods result in classification of EOC histotypes with mean accuracy of 80% for LDA, 80% SVM-lin, 74% SVM-rbf, 83% NN, and 85% CNN. Based on sensitivity (69-100%) and specificity (90-99%), CCN and NN are most suited to EOC classification. Conclusion and clinical relevance The pilot study demonstrates the potential of MALDI-Imaging derived proteomic classifiers in combination with machine learning algorithms to discriminate EOC histotypes. Applications may support the development of new prognostic parameters in the assessment of EOC.

Increases in Tumor N-Glycan Polylactosamines Associated with Advanced HER2-Positive and Triple-Negative Breast Cancer Tissues

Abstract: Purpose Using a recently developed matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) method, human breast cancer formalin-fixed paraffin-embedded (FFPE) tissue sections and tissue microarrays (TMA) are evaluated for N-linked glycan distribution in the tumor microenvironment. Experimental design Tissue sections representing multiple human epidermal growth factor receptor 2 (HER2) receptor-positive and triple-negative breast cancers (TNBC) in both TMA and FFPE slide format are processed for high resolution N-glycan MALDI-IMS. An additional FFPE tissue cohort of primary and metastatic breast tumors from the same donors are also evaluated. Results The cumulative N-glycan MALDI-IMS analysis of breast cancer FFPE tissues and TMAs indicate the distribution of specific glycan structural classes to stromal, necrotic, and tumor regions. A series of high-mannose, branched and fucosylated glycans are detected predominantly within tumor regions. Additionally, a series of polylactosamine glycans are detected in advanced HER2+, TNBC, and metastatic breast cancer tissues. Comparison of tumor N-glycan species detected in paired primary and metastatic tissues indicate minimal changes between the two conditions. Conclusions and clinical relevance The prevalence of tumor-associated polylactosamine glycans in primary and metastatic breast cancer tissues indicates new mechanistic insights into the development and progression of breast cancers. The presence of these glycans could be targeted for therapeutic strategies and further evaluation as potential prognostic biomarkers.

Extracellular Matrix Imaging of Breast Tissue Pathologies by MALDI-Imaging Mass Spectrometry.

Abstract: Purpose A new method accessing proteins from extracellular matrix by imaging mass spectrometry (ECM IMS) has been recently reported. ECM IMS is evaluated for use in exploring breast tissue pathologies. Experimental design A tissue microarray (TMA) is analyzed that has 176 cores of biopsies and lumpectomies spanning breast pathologies of inflammation, hyperplasia, fibroadenoma, invasive ductal carcinoma, and invasive lobular carcinoma and normal adjacent to tumor (NAT). NAT is compared to subtypes by area under the receiver operating curve (ROC) >0.7. A lumpectomy is also characterized for collagen organization by microscopy and stromal protein distribution by IMS. LC-based high-resolution accurate mass (HRAM) proteomics is used to identify proteins from the lumpectomy. Results TMA analysis shows distinct spectral signatures reflecting a heterogeneous tissue microenvironment. Ninety-four peaks show an ROC > 0.7 compared to NAT; NAT has overall higher intensities. Lumpectomy analysis by IMS visualizes a complex central tumor region with distal tumor regions. A total of 39 stromal proteins are identified by HRAM LC-based proteomics. Accurate mass matches between image data and LC-based proteomics demonstrate a heterogeneous collagen type environment in the central tumor. Conclusions Data portray the heterogeneous stromal microenvironment of breast pathologies, including alteration of multiple collagen-type patterns. ECM IMS is a promising new tool for investigating the stromal microenvironment of breast tissue including cancer.

Proteomics in Drug Development: The Dawn of a New Era?

Abstract: Mass spectrometry offers the potential of acquiring high resolution data depicting the functional status of a group of healthy or diseased individuals, according to different conditions. As most of the drugs are currently targeting proteins, proteomics has a dual value, both in the discovery of new molecules as therapeutic targets, but also as a methodology to perform high throughput drug profiling. As there is an evident need for drugs to be improved in terms of efficacy, a mechanistic insight for downstream effectors can be valuable in order to predict side effects and resistance mechanisms. Recently developed assays, like thermal proteome profiling enables comprehensive drug target profiling and is, therefore, of high value in drug discovery. In this review, a systematic literature search is conducted and the most prominent proteomics studies as implicated in assisting drug discovery and development is presented. Focus is placed on investigations that are closer to implementation, therefore particular emphasis is given in studies conducted in human diseased population and further verified in vitro or in vivo.

Identification of Protein Abundance Changes in Hepatocellular Carcinoma Tissues Using PCT-SWATH.

Abstract: Purpose To rapidly identify protein abundance changes in biopsy-level fresh-frozen hepatocellular carcinoma (HCC). Experimental design The pressure-cycling technology (PCT) is applied and sequential window acquisition of all theoretical mass spectra (SWATH-MS) workflow is optimized to analyze 38 biopsy-level tissue samples from 19 HCC patients. Each proteome is analyzed with 45 min LC gradient. MCM7 is validated using immunohistochemistry (IHC). Results A total of 11 787 proteotypic peptides from 2579 SwissProt proteins are quantified with high confidence. The coefficient of variation (CV) of peptide yield using PCT is 32.9%, and the R2 of peptide quantification is 0.9729. Five hundred forty-one proteins showed significant abundance change between the tumor area and its adjacent benign area. From 24 upregulated pathways and 13 suppressed ones, enhanced biomolecule synthesis and suppressed small molecular metabolism in liver tumor tissues are observed. Protein changes based on α-fetoprotein expression and hepatitis B virus infection are further analyzed. The data altogether highlight 16 promising tumor marker candidates. The upregulation of minichromosome maintenance complex component 7 (MCM7) is further observed in multiple HCC tumor tissues by IHC. Conclusions and clinical relevance The practicality of rapid proteomic analysis of biopsy-level fresh-frozen HCC tissue samples with PCT-SWATH has been demonstrated and promising tumor marker candidates including MCM7 are identified.

Identification of Proteomic Markers in Head and Neck Cancer Using MALDI-MS Imaging, LC-MS/MS, and Immunohistochemistry.

Abstract: Purpose The heterogeneity of squamous cell carcinoma tissue greatly complicates diagnosis and individualized therapy. Therefore, characterizing the heterogeneity of tissue spatially and identifying appropriate biomarkers is crucial. MALDI-MS imaging (MSI) is capable of analyzing spatially resolved tissue biopsies on a molecular level. Experimental design MALDI-MSI is used on snap frozen and formalin-fixed and paraffin-embedded (FFPE) tissue samples from patients with head and neck cancer (HNC) to analyze m/z values localized in tumor and nontumor regions. Peptide identification is performed using LC-MS/MS and immunohistochemistry (IHC). Results In both FFPE and frozen tissue specimens, eight characteristic masses of the tumor's epithelial region are found. Using LC-MS/MS, the peaks are identified as vimentin, keratin type II, nucleolin, heat shock protein 90, prelamin-A/C, junction plakoglobin, and PGAM1. Lastly, vimentin, nucleolin, and PGAM1 are verified with IHC. Conclusions and clinical relevance The combination of MALDI-MSI, LC-MS/MS, and subsequent IHC furnishes a tool suitable for characterizing the molecular heterogeneity of tissue. It is also suited for use in identifying new representative biomarkers to enable a more individualized therapy.

High Spatial Resolution MALDI-MS Imaging in the Study of Membranous Nephropathy.

Abstract: Purpose Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) technology has advanced rapidly during recent years with the development of instruments equipped with low-diameter lasers that are suitable for high spatial resolution imaging. This may provide significant advantages in certain fields of molecular pathology where more specific protein fingerprints of individual cell types are required, such as renal pathology. Experimental design Here MALDI-MSI analysis of a cohort of membranous nephropathy (MN) patients is performed among which patients either responded favorably (R; n = 6), or unfavorably (NR; n = 4), to immunosuppressive treatment (Ponticelli Regimen), employing a 10 µm laser spot diameter. Results Specific tryptic peptide profiles of the different cellular regions within the glomerulus can be generated, similarly for the epithelial cells belonging to the proximal and distal tubules. Conversely, specific glomerular and sub-glomerular profiles cannot be obtained while using the pixel size performed in previous studies (50 µm). Furthermore, two proteins are highlighted, sonic hedgehog and α-smooth muscle actin, whose signal intensity and spatial localization within the sub-glomerular and tubulointerstitial compartments differ between treatment responders and non-responders. Conclusions and clinical relevance The present study exemplifies the advantage of using high spatial resolution MALDI-MSI for the study of MN and highlights that such findings have the potential to provide complementary support in the routine prognostic assessment of MN patients.

Proteomic Analysis of the Initial Oral Pellicle in Caries-Active and Caries-Free Individuals

Abstract: Purpose To 1) elucidate individual proteomic profiles of the 3-min biofilm of caries-active and caries-free individuals and 2) compare these proteomic profiles against the background of caries. Experimental design The initial oral pellicle of 12 caries-active and 12 caries-free individuals is generated in situ on ceramics specimens. The individual, host-specific proteomic profiles of this basic pellicle layer are analyzed by a chemical elution protocol combined with an elaborate mass spectrometry and evaluated bioinformatically. Results A total of 1188 different proteins are identified. Additionally, 68 proteins are present in the profiles of all individuals, suggesting them as ubiquitously occurring base-proteins of the initial human pellicle. Thereof, the single profiles exhibit high inter-individual differences independent of their group affiliation, stating the initial pellicle to represent a rather "individual fingerprint". Quantitative analyses imply slight indication for 23 proteins potentially capable of counting for caries-specific biomarkers. Conclusions and clinical relevance The introduced protocol enables the individual analysis of minimal protein amounts and allows for highly precise characterizations and comparisons of individual proteomic profiles. The results contain a considerable higher extent of protein identifications and might serve as a base for future large scale analyzes to identify discrimination factors for the development of caries susceptibility tests.

Combined Immunohistochemistry after Mass Spectrometry Imaging for Superior Spatial Information.

Abstract: Objective Tissue slides analyzed by MS imaging (MSI) are stained by H&E (Haematoxylin and Eosin) to identify regions of interest. As it can be difficult to identify specific cells of interest by H&E alone, data analysis may be impaired. Immunohistochemistry (IHC) can highlight cells of interest but single or combined IHC on tissue sections analyzed by MSI have not been performed. Methods We performed MSI on bone marrow biopsies from patients with multiple myeloma and stained different antibodies (CD38, CD138, MUM1, kappa- and lambda). A combination of CK5/6/TTF1 and Napsin-A/p40 is stained after MSI on adenocarcinoma and squamous cell carcinoma of the lung. Staining intensities of p40 after MSI and on a serial section are quantified on a tissue microarray (n = 44) by digital analysis. Results Digital evaluation reveals weaker staining intensities after MSI as compared to serial sections. Staining quality and quantity after MSI enables to identify cells of interest. On the tissue microarray, one out of 44 tissue specimens shows no staining of p40 after MSI, but weak nuclear staining on a serial section. Conclusion We demonstrated that single and double IHC staining is feasible on tissue sections previously analyzed by MSI, with decreased staining intensities.

The Proteomic Profile of Keratinocytes and Lymphocytes in Psoriatic Patients

Abstract: Purpose Psoriatic skin lesions are associated with chronic inflammation related to immune cell activity. Therefore, the aim of this study is to compare changes in the proteome of psoriatic keratinocytes and lymphocytes. Experimental design A proteomics approach is used to analyze the expression of proteins in keratinocytes and lymphocytes from psoriatic patients and healthy controls. Results As a result 2119 proteins for keratinocytes and 1235 proteins for lymphocytes are identified. Psoriatic keratinocytes has 68 downregulated and 7 upregulated proteins and psoriatic lymphocytes has 106 downregulated and 67 upregulated proteins compared to healthy individuals. The list of downregulated proteins includes proteins involved in antioxidant homeostasis and, transcription regulation; upregulated proteins are involved in glycolytic processes and translation. These changes are accompanied by an increased level of 4-Hydroxynonenal-protein adducts; control cells are characterized by 4-Hydroxynonenal-Lysine adducts formed with structural and binding proteins, while in psoriatic cells 4-Hydroxynonenal-Lysine, 4-Hydroxynonenal-Histidine, and 4-Hydroxynonenal-Cysteine adducts with various molecular function proteins occur. Conclusions and clinical relevance This study highlights the changes in psoriatic keratinocytes and lymphocytes that can be directly involved in the development of psoriasis. In both cell types the most significant changes are associated with upregulation of phosphoglycerate mutase 1 and downregulation of thioredoxin reductase.

In-Depth Proteomic Analysis of Human Bronchoalveolar Lavage Fluid toward the Biomarker Discovery for Lung Cancers.

Abstract: Purpose Lung cancer is among the most common cancers. Bronchoalveolar lavage fluid (BALF) can be easily obtained from patients with lung cancers. The aim is to develop a novel proteomic method of the molecule-based sensitive detection of biomarkers from BALF. Experimental design BALF samples are collected from segmental bronchus of 14 patients with lung cancers from Kyung Hee University Hospital. First, BALF proteome is depleted using a depletion column, and then peptides are prepared from the enriched low abundant proteins and fractionated by high pH reverse phase liquid chromatography prior to LC-MS/MS. Data are available via ProteomeXchange with identifier PXD012645. Results A novel method is developed for in-depth proteomic analysis of BALF by combining antibody-based depletion of high abundant proteins from BALF with high pH peptide fractionation. Peptides are analyzed on a high resolution Orbitrap Fusion mass spectrometer. MaxQuant search result in the identification of 4615 protein groups mapped to 4534 genes. Conclusions and clinical relevance It is found that the method outperformed conventional BALF proteomic methods and it is believed that this method will facilitate the biomarker research for lung cancer. In addition, it is shown that BALF will be a great source of biomarkers of lung diseases.

Management of Tamm-Horsfall Protein for Reliable Urinary Analytics.

Abstract: Purpose Urinary extracellular vesicles (uEVs) are a novel source of biomarkers. However, urinary Tamm-Horsfall Protein (THP; uromodulin) interferes with all vesicle isolation attempts, precipitates with normal urinary proteins, thus, representing an unwanted "contaminant" in urinary assays. Thus, the aim is to develop a simple method to manage THP efficiently. Experimental design The uEVs are isolated by hydrostatic filtration dialysis (HFD) and treated with a defined solution of urea to optimize release of uEVs from sample. Presence of uEVs is confirmed by transmission electron microscopy, Western blotting, and proteomic profiling in MS. Results Using HFD with urea treatment for uEV isolation reduces sample complexity to a great extent. The novel simplified uEV isolation protocol allows comprehensive vesicle proteomics analysis and should be part of any urine analytics to release all sample constituents from THP trap. Conclusions and clinical relevance The method brings a quick and easy protocol for THP management during uEV isolation, providing major benefits for comprehensive sample analytics.

Implementation of Proteomics in Clinical Trials

Abstract: The application of protein (or peptide) biomarkers in clinical studies is a dynamic, ever-growing field. The introduction of clinical proteomics/peptidomics, such as mass spectrometry-based assays and multiplexed antibody-based protein arrays, has reshaped the landscape of biomarker identification and validation, allowing the discovery of novel biomarkers at an unprecedented rate and reliability. To reflect the current status with respect to implementation of protein/peptide biomarkers, an investigation of the most recent (last 6 years) clinical studies from clinicaltrials.gov is presented. Forty-two clinical trials involving the direct use of protein or peptide biomarkers in patient stratification and/or disease diagnosis and prognosis are highlighted. Most of the clinical trials that include proteomics/protein assays are aiming toward implementation of non-invasive diagnostic tools for early detection, while many of the clinical trials are targeting to correlate the protein abundance with the risk of a disease event. Less in number are the studies in which the protein biomarkers are applied to stratify the patients for intervention. All the above areas of application are considered of great importance for improving disease management, in an era where implementation toward precision medicine is the desired outcome of proteomics biomarker research.

Comparative Proteomics Analysis of Serum Proteins in Gestational Diabetes during Early and Middle Stages of Pregnancy.

Abstract: Purpose This study is designed to screen serum proteins that may serve as biomarkers for gestational diabetes mellitus (GDM), and clarify the mechanisms of disease. Experimental design By using isobaric tags for relative and absolute quantitation proteomics analysis, serum proteins levels were quantified in pregnant women who subsequently developed GDM (12-16 weeks), GDM patients (24-28 weeks), and their corresponding controls. The strategy of mixing samples is used in proteomic analysis. Results Thirty-one and 27 differentially expressed proteins are identified in the serum of pregnant women with developed GDM at 12-16 weeks and GDM patients during 24-28 weeks, respectively. Thirty eight and 28 proteins are identified in 24-28 weeks versus 12-16 weeks controls (24/12 CTR group), and 24-28 weeks GDM patients versus 12-16 weeks women with subsequently developed GDM (24/12 GDM group), respectively. Most of these proteins in the case and control subjects are associated with diabetes and maternal and perinatal short- and long-term complications. Conclusions and clinical relevance The results highlight the roles of complement system and the blood clotting cascade in the pathogenesis of GDM. Differentially expressed proteins may serve as potential biomarkers for GDM prediction and diagnosis in the future.

MALDI-TOF MS-Based Identification of Melanized Fungi is Faster and Reliable After the Expansion of In-House Database.

Abstract: Purpose Invasive fungal infections caused by melanized fungi are a growing concern. Rapid and reliable identification plays an important role in optimizing therapy. Matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS)-based identification has emerged as a faster and more accurate diagnostic technique. However, lack of a protein extraction protocol and limited database restricts the identification of melanized fungi by MALDI-TOF MS. The study is designed to standardize protein extraction protocol, to enrich the existing, and to create an in-house database for the rapid identification of melanized fungi. Experimental design In this study, 59 sequence-confirmed, melanized fungi were used to expand and to create an in-house database using a modified protein extraction protocol. A total of 117 clinical isolates are further used to validate the created database. Result Using existing Bruker database, only 29(24.8%) out of 117 moulds could be identified. However, all the isolates are identified accurately by supplementing the Bruker database with the created in-house database. MALDI-TOF MS takes significantly lesser time for identification compared to DNA sequencing. Conclusion and clinical relevance An expanded database with modified protein extraction protocol can reduce significant time to identify melanized fungi by MALDI-TOF MS.

iTRAQ‐Based Quantitative Proteomics Approach Identifies Novel Diagnostic Biomarkers That Were Essential for Glutamine Metabolism and Redox Homeostasis for Gastric Cancer

Abstract: Purpose To screen the novel biomarkers for gastric cancer and to determine the values of glutaminase 1 (GLS1) and gamma-glutamylcyclotransferase (GGCT) for detecting gastric cancer. Experimental design A discovery group of four paired gastric cancer tissue samples are labeled with Isobaric tag for relative and absolute quantitation agents and identified with LC-ESI-MS/MS. A validation group of 168 gastric cancer samples and 30 healthy controls are used to validate the expression of GLS1 and GGCT. Results Four hundred and thirty-one proteins are found differentially expressed in gastric cancer tissues. Of these proteins, GLS1 and GGCT are found overexpressed in gastric cancer patients, with sensitivity of 75.6% (95% CI: 69-82.2%) and specificity of 81% (95% CI: 75-87%) for GLS1, and with sensitivity of 63.1% (95% CI: 55.7-71.5%) and specificity of 60.7% (95% CI: 53.3-68.2%) for GGCT. The co-expression of GLS1 and GGCT in gastric cancer tissues has sensitivity of 78.1% (95% CI: 70.1-86.1%) and specificity of 86.5% (95% CI: 79.5-93.4%). Moreover, both GLS1 and GGCT present higher expression of 82.6% (95% CI: 68.5-99.4%) and 73.9% (95% CI: 54.5-93.3%) in lymph node metastasis specimen than those in non-lymph node metastasis specimen. The areas under ROC curves are up to 0.734 for the co-expression of GLS1 and GGCT in gastric cancer. The co-expression of GLS1 and GGCT is strongly associated with histological grade, lymph node metastasis, and TNM stage Ⅲ/Ⅳ. Conclusions and clinical relevance The present study provides the quantitative proteomic analysis of gastric cancer tissues to identify prognostic biomarkers of gastric cancer. The co-expression level of GLS1 and GGCT is of great clinical value to serve as diagnostic and therapeutic biomarkers for early gastric cancer.

Cytomine: Toward an Open and Collaborative Software Platform for Digital Pathology Bridged to Molecular Investigations.

Abstract: Purpose Digital histology is being increasingly used in research and clinical applications. In parallel, new tissue imaging methods (e.g., imaging mass spectrometry) are currently regarded as very promising approaches for better molecular diagnosis in pathology. However, these new data sources are still often underexploited because of the lack of collaborative software to share and correlate information for multimodal analysis. Experimental design The open science paradigm is followed to develop new features in the web-based Cytomine software to support next-generation digital pathology bridged to molecular investigations. Results New open-source developments allow to explore whole-slide classical histology with Matrix Assisted Laser Desorption Ionisation (MALDI) imaging and to support preprocessing for biomarker discovery using laser microdissection-based microproteomics. Conclusions and clinical relevance The updated version of Cytomine is the first open and web-based tool to enable sharing data from classical histology, molecular imaging, and cell counting for proteomics preprocessing. It holds good promise to fulfill imminent needs in molecular histopathology.

Digital PCR After MALDI-Mass Spectrometry Imaging to Combine Proteomic Mapping and Identification of Activating Mutations in Pulmonary Adenocarcinoma.

Abstract: Purpose Matrix assisted laser desorption/ionization time-of-flight mass spectrometry imaging (MALDI-MSI) is a powerful tool to analyze the spatial distribution of peptides in tissues Digital PCR (dPCR) is a method to reliably detect genetic mutations Biopsy material is often limited due to minimally invasive techniques, but information on diagnosis, prognosis, and prediction is required for subsequent clinical decision making Thus, saving tissue material during diagnostic workup is highly warranted for best patient care The possibility to combine proteomic analysis by MALDI-MSI and mutational analysis by dPCR from the same tissue section is evaluated Experimental design Ten 05 × 05 cm formalin-fixed paraffin embedded tissue samples of pulmonary adenocarcinomas with known EGFR or KRAS mutations are analyzed by MALDI-MSI Subsequently, DNA is extracted from the analyzed tissue material and tested for the respective driver mutation by dPCR Results Detection of driver gene mutations after MALDI MSI analysis is successful in all analyzed samples Determined mutant allele frequencies are in good agreement with values assessed from untreated serial tissue sections with a mean absolute deviation of 016 Conclusion and clinical relevance It has been demonstrated that MALDI-MSI can be combined with genetic analysis, like dPCR Workflows enabling the subsequent analysis of proteomic and genetic markers are particularly promising for the analysis of limited sample material such as biopsy specimen

Development of a Class Prediction Model to Discriminate Pancreatic Ductal Adenocarcinoma from Pancreatic Neuroendocrine Tumor by MALDI Mass Spectrometry Imaging.

Abstract: PURPOSE To define proteomic differences between pancreatic ductal adenocarcinoma (pDAC) and pancreatic neuroendocrine tumor (pNET) by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI). EXPERIMENTAL DESIGN Ninety-three pDAC and 126 pNET individual tissues are assembled in tissue microarrays and analyzed by MALDI MSI. The cohort is separated in a training (52 pDAC and 83 pNET) and validation set (41 pDAC and 43 pNET). Subsequently, a linear discriminant analysis (LDA) model based on 46 peptide ions is performed on the training set and evaluated on the validation cohort. Additionally, two liver metastases and a whole slide of pDAC are analyzed by the same LDA algorithm. RESULTS Classification of pDAC and pNET by the LDA model is correct in 95% (39/41) and 100% (43/43) of patients in the validation cohort, respectively. The two liver metastases and the whole slide of pDAC are also correctly classified in agreement with the histopathological diagnosis. CONCLUSION AND CLINICAL RELEVANCE In the present study, a large dataset of pDAC and pNET by MALDI MSI is investigated, a class prediction model that allowed separation of both entities with high accuracy is developed, and differential peptide peaks with potential diagnostic, prognostic, and predictive values are highlighted.

TMT-Based Quantitative Proteomic Analysis Reveals Proteomic Changes Involved in Longevity.

Abstract: PURPOSE Individual lifespans vary widely, and longevity is the main concern from ancient to modern times. This study is aimed to identify plasma proteins associated with longevity by proteomics technique. EXPERIMENTAL DESIGN Tandem mass tags (TMT)-based proteomics analysis is performed for the plasma of Bama longevity group and a control group to analyze the differentially expressed proteins (DEPs). A validation set is used to verify the results of TMT-based proteomics. RESULTS Between Bama natives and the control individuals, the authors identify 175 DEPs, which are mainly involved in complement and coagulation cascades, metabolism of glyco and lipid, and regulation of actin cytoskeleton. Consistent with the proteomic analysis, plasma levels of MMP2, CCL5, and PF4 are significantly lower in Bama participants than in controls, whereas IGFBP2 and C9 increase in Bama individuals, in the validation set. By ROC analysis, combinations of these five proteins result in a high AUC value (0.991, 95% CI, 0.929-1.000, p < 0.0001) to distinguish longevous participants from controls. CONCLUSIONS AND CLINICAL RELEVANCE The results highlight the roles of complement and coagulation cascades, metabolism of glyco and lipid, and inflammatory and immune response may play important roles in longevity. And the DEPs may serve as clinically useful biomarkers for healthy aging and predicting longevity.

Urinary Proteomics and Precision Medicine for Chronic Kidney Disease: Current Status and Future Perspectives.

Abstract: Precision medicine is since long an ongoing refinement of classical medicine, integrating improved and more detailed pathophysiological understanding with rapid technological advances. In the heterogenous area of chronic kidney disease there seems to be a high potential for the improvement in treatment and prognosis for several causes, with new technologies under development, that are yet to be introduced in clinical practice. As in other medical disciplines, investigation of abundant peptide patterns (proteomics) has gained recent interest. Especially relevant for kidney disease, urinary proteomics may provide both improved diagnosis and, as reviewed here, also holds promise for personalized treatment in the future. So far, capillary electrophoresis coupled to mass spectrometry (CE-MS) is the most widely applied technique, and in addition to several cross-sectional and cohort studies, there is even an ongoing randomized controlled trial that will soon report on the concept used as a method of personalizing treatment. In addition, there is hope that urinary proteomics can turn into a "liquid biopsy," replacing the invasive diagnostic procedure. The next couple of years will provide more answers on the topic.

Proteomics Analysis for Verification of Rheumatoid Arthritis Biomarker Candidates Using Multiple Reaction Monitoring.

Abstract: Purpose Rheumatoid arthritis (RA) is an autoimmune disease in which autoantibodies attack the synovial membrane, causing joint inflammation Blood tests would offer a powerful, minimally invasive method for early diagnosis of RA However, no reliable biomarkers for RA are presently available The aim is to develop biomarkers for RA by multiple reaction monitoring (MRM)-based quantification of candidate biomarkers Experimental design Proteomics approaches are commonly used to identify and verify disease biomarkers For discovery of biomarkers for RA, SWATH acquisition is performed and selected candidate biomarkers are validated by MRM Target serum proteins are compared between patients with RA and healthy controls divided into three groups based on rheumatoid factor level Results A total of 45 differentially expressed proteins are identified, as determined by SWATH acquisition Of these, 13 proteins are selected as novel candidate biomarkers A total of five proteins (transthyretin, gelsolin, angiotensinogen, lipopolysaccharide-binding protein, and protein S100-A9) are shown to have the potential to distinguish patients with RA from healthy controls Conclusions and clinical relevance These five proteins may improve the efficiency of diagnosis of RA MRM can be used to easily diagnose RA by detecting five proteins simultaneously in a single sample with high sensitivity

Urinary Proteomics as a Tool to Identify Kidney Responders to Dipeptidyl Peptidase-4 Inhibition: A Hypothesis-Generating Analysis from the MARLINA-T2D Trial.

Abstract: PURPOSE Chronic kidney disease (CKD) is a serious complication of hyperglycemia and treatment options to slow its progression are scarce. Dipeptidyl peptidase-4 (DPP-4) inhibitors are common glucose-lowering drugs in type 2 diabetes (T2D). Among these, linagliptin has been suggested to exert kidney protective effects. It is investigated whether an effect of linagliptin on kidney function could be unmasked by characterizing the urinary proteome profile (UPP) in albuminuric T2D individuals. EXPERIMENTAL DESIGN Participants of the MARLINA-T2D trial (NCT01792518) are randomized 1:1 to receive either linagliptin 5 mg or placebo for 24 weeks. A previously developed proteome-based classifier, CKD273, is assessed. RESULTS Results confirm a significant correlation between CKD273 and clinical kidney parameters as well as with eGFR decline. Patient stratification using CKD273 at baseline, show a trend toward attenuation of renal function loss in high CKD-risk patients treated with linagliptin. Moreover, characterized are linagliptin affected peptides of which the majority contained a DPP-4 target sequence. CONCLUSIONS AND CLINICAL RELEVANCE CKD273 is a promising tool for identifying patients at high risk for CKD progression and may unmask a potential of linagliptin to slow progressive kidney function loss in high CKD-risk patients. UPP characterization reveals a significant impact of linagliptin on urinary peptides.

In MALDI–Mass Spectrometry Imaging on Formalin‐Fixed Paraffin‐Embedded Tissue Specimen Section Thickness Significantly Influences m/z Peak Intensity

Abstract: BACKGROUND In matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) standardized sample preparation is important to obtain reliable results. Herein, the impact of section thickness in formalin-fixed paraffin embedded (FFPE) tissue microarrays (TMA) on spectral intensities is investigated. PATIENTS AND METHODS TMAs consisting of ten different tissues represented by duplicates of ten patients (n = 200 cores) are cut at 1, 3, and 5 μm. MSI analysis is performed and mean intensities of all evaluable cores are extracted. Measurements are merged and mean m/z intensities are compared. RESULTS Visual inspection of spectral intensities between 1, 3, and 5 μm reveals generally higher intensities in thinner tissue sections. Specifically, higher intensities are observed in the vast majority of peaks (98.6%, p < 0.01) in 1 μm compared with 5 μm sections. Note that 28.4% and 2.1% of m/z values exhibit a at least two- and threefold intensity difference (p < 0.01) in 1 μm compared to 5 μm sections, respectively. CONCLUSION A section thickness of 1 μm results in higher spectral intensities compared with 5 μm. The results highlight the importance of standardized protocols in light of recent efforts to identify clinically relevant biomarkers using MSI. The use of TMAs for comparative analysis seems advantageous, as section thickness displays less variability.

Identification of MALDI Imaging Proteolytic Peptides Using LC-MS/MS-Based Biomarker Discovery Data: A Proof of Concept.

Abstract: Purpose Identification of proteolytic peptides from matrix-assisted laser desorption/ionization (MALDI) imaging remains a challenge. The low fragmentation yields obtained using in situ post source decay impairs identification. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is an alternative to in situ MS/MS, but leads to multiple identification candidates for a given mass. The authors propose to use LC-MS/MS-based biomarker discovery results to reliably identify proteolytic peptides from MALDI imaging. Experimental design The authors defined m/z values of interest for high grade squamous intraepithelial lesion (HSIL) by MALDI imaging. In parallel the authors used data from a biomarker discovery study to correlate m/z from MALDI imaging with masses of peptides identified by LC-MS/MS in HSIL. The authors neglected candidates that were not significantly more abundant in HSIL according to the biomarker discovery investigation. Results The authors assigned identifications to three m/z of interest. The number of possible identifiers for MALDI imaging m/z peaks using LC-MS/MS-based biomarker discovery studies was reduced by about tenfold compared using a single LC-MS/MS experiment. One peptide identification candidate was validated by immunohistochemistry. Conclusion and clinical relevance This concept combines LC-MS/MS-based quantitative proteomics with MALDI imaging and allows reliable peptide identification. Public datasets from LC-MS/MS biomarker discovery experiments will be useful to identify MALDI imaging m/z peaks.

Urinary Glycopeptide Analysis for the Investigation of Novel Biomarkers.

Abstract: Purpose Urine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of glycans. Nevertheless, recent advances in glycoproteomics software solutions facilitate glycopeptide identification and characterization. The aim is to investigate intact glycopeptides in the urinary peptide profiles of normal subjects using a novel PTM-centric software-Byonic. Experimental design The urinary peptide profiles of 238 normal subjects, previously analyzed using CE-MS and CE-MS/MS and/or LC-MS/MS, are subjected to glycopeptide analysis. Additionally, glycopeptide distribution is assessed in a set of 969 patients with five different cancer types: bladder, prostate and pancreatic cancer, cholangiocarcinoma, and renal cell carcinoma. Results A total of 37 intact O-glycopeptides and 23 intact N-glycopeptides are identified in the urinary profiles of 238 normal subjects. Among the most commonly identified O-glycoproteins are Apolipoprotein C-III and insulin-like growth factor II, while titin among the N-glycoproteins. Further statistical analysis reveals that three O-glycopeptides and five N-glycopeptides differed significantly in their abundance among the different cancer types, comparing to normal subjects. Conclusions and clinical relevance Through the established glycoproteomics workflow, intact O- and N-glycopeptides in human urine are identified and characterized, providing novel insights for further exploration of the glycoproteome with respect to specific diseases.

Urinary Peptidomic Biomarker for Personalized Prevention and Treatment of Diastolic Left Ventricular Dysfunction

Abstract: Diastolic heart failure (DHF) is characterized by slow left ventricular (LV) relaxation, increased LV stiffness, interstitial deposition of collagen, and a modified extracellular matrix proteins. Among Europeans, the frequency of asymptomatic diastolic LV dysfunction (DD) is 25%. This constitutes a large pool of people at high risk of DHF. The goal of this review was to describe the discovery and the initial validation of new multidimensional urinary peptidomic biomarkers (UPB) indicative of DD, mainly consisting of collagen fragments, and to describe a roadmap for their introduction into clinical practice. The availability of new drugs creates a window of opportunity for mounting a randomized clinical trial consolidating the clinical applicability of UPB to screen for DD. If successfully completed, such trial will benefit ≈25% of all people older than 50 years and open a large market for a UPB diagnostic tool and the drug tested. Moreover, sequenced peptides making up UPB will generate novel insights in the pathophysiology of DD and facilitate personalized treatment of patients with DHF for whom prevention came too late. If proven cost-effective, the clinical application of UPB will contribute to the sustainability of health care in aging population in epidemiologic transition.