Integrated proteogenomic approach identifying a protein signature of COPD and a new splice variant of SORBS1.

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.

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.

Merging clinical chemistry biomarker data with a COPD database - building a clinical infrastructure for proteomic studies.

BACKGROUND: Data from biological samples and medical evaluations plays an essential part in clinical decision making. This data is equally important in clinical studies and it is critical to have an infrastructure that ensures that its quality is preserved throughout its entire lifetime. We are running a 5-year longitudinal clinical study, KOL-Örestad, with the objective to identify new COPD (Chronic Obstructive Pulmonary Disease) biomarkers in blood. In the study, clinical data and blood samples are collected from both private and public health-care institutions and stored at our research center in databases and biobanks, respectively. The blood is analyzed by Mass Spectrometry and the results from this analysis then linked to the clinical data. METHOD: We built an infrastructure that allows us to efficiently collect and analyze the data. We chose to use REDCap as the EDC (Electronic Data Capture) tool for the study due to its short setup-time, ease of use, and flexibility. REDCap allows users to easily design data collection modules based on existing templates. In addition, it provides two functions that allow users to import batches of data; through a web API (Application Programming Interface) as well as by uploading CSV-files (Comma Separated Values). RESULTS: We created a software, DART (Data Rapid Translation), that translates our biomarker data into a format that fits REDCap's CSV-templates. In addition, DART is configurable to work with many other data formats as well. We use DART to import our clinical chemistry data to the REDCap database. CONCLUSION: We have shown that a powerful and internationally adopted EDC tool such as REDCap can be extended so that it can be used efficiently in proteomic studies. In our study, we accomplish this by using DART to translate our clinical chemistry data to a format that fits the templates of REDCap.

Use of ENCODE resources to characterize novel proteoforms and missing proteins in the human proteome.

We describe the utility of integrated strategies that employ both translation of ENCODE data and major proteomic technology pillars to improve the identification of the "missing proteins", novel proteoforms, and PTMs. On one hand, databases in combination with bioinformatic tools are efficiently utilized to establish microarray-based transcript analysis and supply rapid protein identifications in clinical samples. On the other hand, sequence libraries are the foundation of targeted protein identification and quantification using mass spectrometric and immunoaffinity techniques. The results from combining proteoENCODEdb searches with experimental mass spectral data indicate that some alternative splicing forms detected at the transcript level are in fact translated to proteins. Our results provide a step toward the directives of the C-HPP initiative and related biomedical research.

In Vitro Transcription/Translation System: A Versatile Tool in the Search for Missing Proteins.

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 to be "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. 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 18 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.

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.

Localization of sunitinib in in vivo animal and in vitro experimental models by MALDI mass spectrometry imaging.

The spatial distribution of an anticancer drug and its intended target within a tumor plays a major role on determining how effective the drug can be at tackling the tumor. This study provides data regarding the lateral distribution of sunitinib, an oral antiangiogenic receptor tyrosine kinase inhibitor using an in vitro animal model as well as an in vitro experimental model that involved deposition of a solution of sunitinib onto tissue sections. All tumor sections were analyzed by matrix-assisted laser desorption/ionization mass spectrometry imaging and compared with subsequent histology staining. Six tumors at four different time points after commencement of in vivo sunitinib treatment were examined to observe the patterns of drug uptake. The levels of sunitinib present in in vivo treated tumor sections increased continuously until day 7, but a decrease was observed at day 10. Furthermore, the in vitro experimental model was adjustable to produce a drug level similar to that obtained in the in vivo model experiments. The distribution of sunitinib in tissue sections treated in vitro appeared to agree with the histological structure of tumors, suggesting that this approach may be useful for testing drug update.

Queries of MALDI-imaging global datasets identifying ion mass signatures associated with tissue compartments.

Scanning MS by MALDI MS 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 preprocessed 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 coincident 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.

A new look at drugs targeting malignant melanoma--an application for mass spectrometry imaging.

Malignant melanoma (MM) patients are being treated with an increasing number of personalized medicine (PM) drugs, several of which are small molecule drugs developed to treat patients with specific disease genotypes and phenotypes. In particular, the clinical application of protein kinase inhibitors has been highly effective for certain subsets of MM patients. Vemurafenib, a protein kinase inhibitor targeting BRAF-mutated protein, has shown significant efficacy in slowing disease progression. In this paper, we provide an overview of this new generation of targeted drugs, and demonstrate the first data on localization of PM drugs within tumor compartments. In this study, we have introduced MALDI-MS imaging to provide new information on one of the drugs currently used in the PM treatment of MM, vemurafenib. In a proof-of-concept in vitro study, MALDI-MS imaging was used to identify vemurafenib applied to metastatic lymph nodes tumors of subjects attending the regional hospital network of Southern Sweden. The paper provides evidence of BRAF overexpression in tumors isolated from MM patients and localization of the specific drug targeting BRAF, vemurafenib, using MS fragment ion signatures. Our ability to determine drug uptake at the target sites of directed therapy provides important opportunity for increasing our understanding about the mode of action of drug activity within the disease environment.

Four areas of engagement requiring strengthening in modern proteomics today.

The global human proteomics community in 2014 is fully engaged in projects that aim to create a better understanding of human biology and its complexities and to provide products from this new knowledge that will in some way benefit humanity. Human proteomics, like any other scientific enterprise, needs to identify areas of direction and development, both for the near future in completing current research projects and into the long-term for the engagement with even more complex challenges. In this Editorial we highlight and discuss four important areas that we collectively believe require attention and demand a collective response going forward. These four areas are: (1) Provide high-quality standardized, sensitive, specific, quantitative, and readily accessible protein, peptide, or other biomarkers of health, disease, response to therapy into the approval processes of regulatory agencies (e.g., U.S. Food and Drug Administration; FDA), and obtaining approval from the relevant agencies for their use in a clinical or other testing settings. (2) Implement standard processes for collecting, processing, and storing human clinical samples in biorepositories and enforcement of measures to ensure subject integrity including informed consent for the downstream use of samples and in registrations of subject identities within study databases. (3) Test and validate mass spectrometry technology platforms that hold much promise for creating opportunities for obtaining new important knowledge at levels of detection previously not achievable. (4) Organize clinical discovery operations and activities in an intuitive manner to meet the challenges of increased interests in the science we provide and diminishing levels of centrally financed resource and infrastructure support.

Biorepository regulatory frameworks: building parallel resources that both promote scientific investigation and protect human subjects.

Clinical samples contained in biorepositories represent an important resource for investigating the many factors that drive human biology. The biological and chemical markers contained in clinical samples provide important measures of health and disease that when combined with such medical evaluation data can aid in decision making by physicians. Nearly all disciplines in medicine and every "omic" depend upon the readouts obtained from such samples, whether the measured analyte is a gene, a protein, a lipid, or a metabolite. There are many steps in sample processing, storage, and management that need to understood by the researchers who utilize biorepositories in their own work. These include not only the preservation of the desired analytes in the sample but also good understanding of the moral and legal framework required for subject protection irrespective of where the samples have been collected. Today there is a great deal of effort in the community to align and standardize both the methodology of sample collection and storage performed in different locations and the necessary frameworks of subject protection including informed consent and institutional review of the studies being performed. There is a growing trend in developing biorepositories around the focus of large population-based studies that address both active and silent nonsymptomatic disease. Logistically these studies generate large numbers of clinical samples and practically place increasing demand upon health care systems to provide uniform sample handling, processing, storage, and documentation of both the sample and the subject as well to ensure that safeguards exist to protect the rights of the study subjects for deciding upon the fates of their samples. Currently the authority to regulate the entire scope of biorepository usage exists as national practice in law in only a few countries. Such legal protection is a necessary component within the framework of biorepositories, both now and in the future. In this brief overview, we provide practical information to the potential users of biorepositories about some of the current developments in both the methodology of sample acquisition and in the regulatory environment governing their use.

Analytical validation considerations of multiplex mass-spectrometry-based proteomic platforms for measuring protein biomarkers.

Protein biomarker discovery and validation in current omics era are vital for healthcare professionals to improve diagnosis, detect cancers at an early stage, identify the likelihood of cancer recurrence, stratify stages with differential survival outcomes, and monitor therapeutic responses. The success of such biomarkers would have a huge impact on how we improve the diagnosis and treatment of patients and alleviate the financial burden of healthcare systems. In the past, the genomics community (mostly through large-scale, deep genomic sequencing technologies) has been steadily improving our understanding of the molecular basis of disease, with a number of biomarker panels already authorized by the U.S. Food and Drug Administration (FDA) for clinical use (e.g., MammaPrint, two recently cleared devices using next-generation sequencing platforms to detect DNA changes in the cystic fibrosis transmembrane conductance regulator (CFTR) gene). Clinical proteomics, on the other hand, albeit its ability to delineate the functional units of a cell, more likely driving the phenotypic differences of a disease (i.e., proteins and protein-protein interaction networks and signaling pathways underlying the disease), "staggers" to make a significant impact with only an average ∼ 1.5 protein biomarkers per year approved by the FDA over the past 15-20 years. This statistic itself raises the concern that major roadblocks have been impeding an efficient transition of protein marker candidates in biomarker development despite major technological advances in proteomics in recent years.

Feasibility study on measuring selected proteins in malignant melanoma tissue by SRM quantification.

Currently there are no clinically recognized molecular biomarkers for malignant melanoma (MM) for either diagnosing disease stage or measuring response to therapy. The aim of this feasibility study was to develop targeted selected reaction monitoring (SRM) assays for identifying candidate protein biomarkers in metastatic melanoma tissue lysate. In a pilot study applying the SRM assay, the tissue expression of nine selected proteins [complement 3 (C3), T-cell surface glycoprotein CD3 epsilon chain E (CD3E), dermatopontin, minichromosome maintenance complex component (MCM4), premelanosome protein (PMEL), S100 calcium binding protein A8 (S100A8), S100 calcium binding protein A13 (S100A13), transgelin-2 and S100B] was quantified in a small cohort of metastatic malignant melanoma patients. The SRM assay was developed using a TSQ Vantage triple quadrupole mass spectrometer that generated highly accurate peptide quantification. Repeated injection of internal standards spiked into matrix showed relative standard deviation (RSD) from 6% to 15%. All nine target proteins were identified in tumor lysate digests spiked with heavy peptide standards. The multiplex SRM peptide assay panel was then measured and quantified on a set of frozen MM tissue samples obtained from the Malignant Melanoma Biobank collected in Lund, Sweden. All nine proteins could be accurately quantified using the new SRM assay format. This study provides preliminary data on the heterogeneity of biomarker expression within MM patients. The S100B protein, which is clinically used as the pathology identifier of MM, was identified in 9 out of 10 MM tissue lysates. The use of the targeted SRM assay provides potential advancements in the diagnosis of MM that can aid in future assessments of disease in melanoma patients.

Experimental models to study drug distributions in tissue using MALDI mass spectrometry imaging.

Requirements for patient safety and improved efficacy are steadily increasing in modern healthcare and are key drivers in modern drug development. New drug characterization assays are central in providing evidence of the specificity and selectivity of drugs. Meeting this need, matrix-assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) is used to study drug localization within microenvironmental tissue compartments. Thin sections of human lung tumor and rat xenograft tissues were exposed to pharmaceutical drugs by either spotting or submerging. These drugs, the epidermal growth factor receptor antagonists, erlotinib (Tarceva) and gefitinib (Iressa), and the acetylcholine receptor antagonist, tiotropium, were characterized by microenvironment localization. Intact tissue blocks were also immersed in drug solution, followed by sectioning. MALDI-MSI was then performed using a Thermo MALDI LTQ Orbitrap XL instrument to localize drug-distribution patterns. We propose three MALDI-MSI models measuring drug disposition that have been used to map the selected compounds within tissue compartments of tumors isolated from lung cancer patients.

Chromosome 19 annotations with disease speciation: a first report from the Global Research Consortium.

A first research development progress report of the Chromosome 19 Consortium with members from Sweden, Norway, Spain, United States, China and India, a part of the Chromosome-centric Human Proteome Project (C-HPP) global initiative, is presented ( http://www.c-hpp.org ). From the chromosome 19 peptide-targeted library constituting 6159 peptides, a pilot study was conducted using a subset with 125 isotope-labeled peptides. We applied an annotation strategy with triple quadrupole, ESI-Qtrap, and MALDI mass spectrometry platforms, comparing the quality of data within and in between these instrumental set-ups. LC-MS conditions were outlined by multiplex assay developments, followed by MRM assay developments. SRM was applied to biobank samples, quantifying kallikrein 3 (prostate specific antigen) in plasma from prostate cancer patients. The antibody production has been initiated for more than 1200 genes from the entire chromosome 19, and the progress developments are presented. We developed a dedicated transcript microarray to serve as the mRNA identifier by screening cancer cell lines. NAPPA protein arrays were built to align with the transcript data with the Chromosome 19 NAPPA chip, dedicated to 90 proteins, as the first development delivery. We have introduced an IT-infrastructure utilizing a LIMS system that serves as the key interface for the research teams to share and explore data generated within the project. The cross-site data repository will form the basis for sample processing, including biological samples as well as patient samples from national Biobanks.

Correlation queries for mass spectrometry imaging.

Mass spectrometry imaging (MSI) generates large volumetric data sets consisting of mass to charge ratio (m/z), ion current, and x,y coordinate location. These data sets usually serve limited purposes centered on measuring the distribution of a small set of ions with known m/z. Such earmarked queries consider only a fraction of the full mass spectrum captured, and there are few tools to assist the exploration of the remaining volume of unknown data in terms of demonstrating similarity or discordance in tissue compartment distribution patterns. Here we present a novel, interactive approach to extract information from MSI data that relies on precalculated data structures to perform queries of large data sets with a typical laptop. We have devised methods to query the full volume to find new m/z values of potential interest based on similarity to biological structures or to the spatial distribution of known ions. We describe these query methods in detail and provide examples demonstrating the power of the methods to "discover" m/z values of ions that have such potentially interesting correlations. The "discovered" ions may be further correlated with either positional locations or the coincident distribution of other ions using successive queries. Finally, we show it is possible to gain insight to the fragmentation pattern of the parent molecule from such correlations. The ability to discover new ions of interest in the unknown bulk of an MSI data set offers the potential to further our understanding of biological and physiological processes related to health and disease.

Standardization and utilization of biobank resources in clinical protein science with examples of emerging applications.

Biobanks are a major resource to access and measure biological constituents that can be used to monitor the status of health and disease, both in unique individual samples and within populations. Most "omic" activities rely on access to these collections of stored samples to provide the basis for establishing the ranges and frequencies of expression. Furthermore, information about the relative abundance and form of protein constituents found in stored samples provides an important historical index for comparative studies of inherited, epidemic, and developing disease. Standardizations of sample quality, form, and analysis are an important unmet need and requirement for gaining the full benefit from collected samples. Coupled to this standard is the provision of annotation describing clinical status and metadata of measurements of clinical phenotype that characterizes the sample. Today we have not yet achieved consensus on how to collect, manage, and build biobank archives in order to reach goals where these efforts are translated into value for the patient. Several initiatives (OBBR, ISBER, BBMRI) that disseminate best practice examples for biobanking are expected to play an important role in ensuring the need to preserve the sample integrity of biosamples stored for periods that reach one or several decades. These developments will be of great value and importance to programs such as the Chromosome Human Protein Project (C-HPP) that will associate protein expression in healthy and disease states with genetic foci along of each of the human chromosomes.

Direct demonstration of tissue uptake of an inhaled drug: proof-of-principle study using matrix-assisted laser desorption ionization mass spectrometry imaging.

Drug therapy is often directed to specific organ and tissue compartments where the mode of action of the compound affects specifically targeted biological processes. However, the direct measurement of drug uptake in terms of a time kinetic and concentrations attained at the local sites has not been readily available as a clinical index for most drugs. A proof-of-principle study was conducted to test the utility of applying matrix-assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) to demonstrate the qualitative distribution pattern of a locally administered drug within tissue sites of targeted action. Here we have measured the occurrence of an inhaled bronchodilator, the muscarinic receptor antagonist ipratropium, within human bronchial biopsies obtained by fiber optic bronchoscopy shortly after dosing exposure. Cryo-preserved biopsy samples from five subjects being evaluated for airway obstruction or potential tumor development were prepared as thin frozen sections. Samples coated with a MALDI matrix were analyzed by a MALDI LTQ Orbitrap XL mass spectrometer at large (100 µm) and small (30 µm) raster sizes. Our results demonstrate that ipratropium is rapidly absorbed into the airway wall. Ipratropium parent ion (m/z 332.332) and daughter ions (m/z 166.2 and 290.2) were coincidently partitioned within submucosal spaces containing targeted airway smooth muscle in four out of five subjects. The signal intensity of ipratropium fragment ions provided estimates that local drug concentrations between 3 and 80 nM were achieved within the airway wall. To our knowledge, this is the first reported study in applying MALDI-MSI to demonstrate the localization of a drug administered at therapeutic levels. The study highlights the potential benefit of MALDI-MSI to provide important measurements of drug efficacy in clinical settings.

Twins studies as a model for studies on the interaction between smoking and genetic factors in the development of chronic bronchitis.

Smoking is the main risk factor for COPD (chronic obstructive pulmonary disease) but genetic factors are of importance, since only a subset of smokers develops the disease. Sex differences have been suggested both in disease prevalence and response to environmental exposures. Furthermore, it has been shown that acquisition of 'addiction' to smoking is partly genetically mediated. Disease cases and smoking habits were identified in 44919 twins aged >40 years from the Swedish Twin Registry. Disease was defined as self-reported chronic bronchitis or emphysema, or recurrent cough with phlegm. The results showed that chronic bronchitis seems to be more prevalent among females, and that the heritability estimate for chronic bronchitis was a moderate 40% and only 14% of the genetic influences were shared by smoking. In addition, 392 twins have been invited to a clinical investigation to evaluate: (i) to what extent genetic factors contribute to individual differences (variation) in FEV(1) (forced expiratory volume in 1 s), vital capacity and DL(CO) (diffusion capacity), taking sex into consideration, and (ii) whether smoking behaviour and respiratory symptoms influence these estimates.