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.

Endogenous expression mapping of malignant melanoma by mass spectrometry imaging.

BACKGROUND: Currently, only a limited number of molecular biomarkers for malignant melanoma exist. This is the case for both diagnosing the disease, staging, and efficiently measuring the response to therapy by tracing the progression of disease development and drug impact. There is a great need to identify novel landmarks of disease progression and alterations. METHODS: Matrix-assisted laser desorption ionisation mass spectrometry imaging (MALDI-MSI) has been developed within our group to study drug localisation within micro-environmental tissue compartments. Here, we expand further on this technology development and introduce for the first time melanoma tumour tissues to map metabolite localisation utilising high resolution mass spectrometry. MALDI-MSI can measure and localise the distribution pattern of a number of small molecule metabolites within tissue compartments of tumours isolated from melanoma patients. Data on direct measurements of metabolite identities attained at the local sites in tissue compartments has not been readily available as a measure of a clinical index for most cancer diseases. The current development on the mapping of endogenous molecular expression melanoma tumours by mass spectrometry imaging focuses on the establishment of a cancer tissue preparation process whereby a matrix crystal formation is homogenously built on the tissue surface, providing uniform molecular mapping. We apply this micro-preparation technology to disease presentation by mapping the molecular signatures from patient tumour sections. RESULTS: We have automated the process with a micro-technological dispensing platform. This provides the basis for thin film generation of the cancer patient tissues prior to imaging screening. Compartmentalisation of the tumour regions are displayed within the image analysis interfaced with histopathological grading and characterisation. CONCLUSIONS: This enables site localisation within the tumour with image mapping to disease target areas such as melanoma cells, macrophages, and lymphocytes.

A selected reaction monitoring mass spectrometric assessment of biomarker candidates diagnosing large-cell neuroendocrine lung carcinoma by the scaling method using endogenous references.

Selected reaction monitoring mass spectrometry (SRM-MS) -based semi-quantitation was performed to assess the validity of 46 selected candidate proteins for specifically diagnosing large-cell neuroendocrine lung carcinoma (LCNEC) and differentiating it from other lung cancer subtypes. The scaling method was applied in this study using specific SRM peak areas (AUCs) derived from the endogenous reference protein that normalizes all SRM AUCs obtained for the candidate proteins. In a screening verification study, we found that seven out of the 46 candidate proteins were statistically significant for the LCNEC phenotype, including 4F2hc cell surface antigen heavy chain (4F2hc/CD98) (p-ANOVA ≤ 0.0012), retinal dehydrogenase 1 (p-ANOVA ≤ 0.0029), apolipoprotein A-I (p-ANOVA ≤ 0.0004), ß-enolase (p-ANOVA ≤ 0.0043), creatine kinase B-type (p-ANOVA ≤ 0.0070), and galectin-3-binding protein (p-ANOVA = 0.0080), and phosphatidylethanolamine-binding protein 1 (p-ANOVA ≤ 0.0012). In addition, we also identified candidate proteins specific to the small-cell lung carcinoma (SCLC) subtype. These candidates include brain acid soluble protein 1 (p-ANOVA < 0.0001) and γ-enolase (p-ANOVA ≤ 0.0013). This new relative quantitation-based approach utilizing the scaling method can be applied to assess hundreds of protein candidates obtained from discovery proteomic studies as a first step of the verification phase in biomarker development processes.

Localization of tamoxifen in human breast cancer tumors by MALDI mass spectrometry imaging.

BACKGROUND: Tamoxifen is used in endocrine treatment of breast cancer to inhibit estrogen signaling. A set of stratified ER-positive and ER-negative tumor sections was subjected to manual deposition of tamoxifen solution in order to investigate its spatial distribution upon exposure to interaction within thin tissue sections. METHODS: The localization of tamoxifen in tumor sections was assessed by matrix assisted laser deposition/ionization mass spectrometry imaging. The images of extracted ion maps were analyzed for comparison of signal intensity distributions. RESULTS: The precursor ion of tamoxifen (m/z 372.233) displayed heterogeneous signal intensity distributions in histological compartments of tumor tissue sections. The levels of tamoxifen in tumor cells compared with stroma were higher in ER-positive tissues, whereas ER-negative tissue sections showed lower signal intensities in tumor cells. CONCLUSIONS: The experimental model was successfully applied on frozen tumor samples allowing for differentiation between ER groups based on distribution of tamoxifen.

Biomarkers of early chronic obstructive pulmonary disease (COPD) in smokers and former smokers. Protocol of a longitudinal study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is an irreversible disease, diagnosed predominantly in smokers. COPD is currently the third leading cause of death worldwide. Far more than 15 % of smokers get COPD: in fact, most develop some amount of pulmonary impairment. Smoking-related COPD is associated with both acute exacerbations and is closely correlated to comorbidities, such as cardiovascular disease and lung cancer. The objective of our study (KOL-Örestad) is to identify biomarkers in smokers and ex-smokers, with early signs of COPD, and compare these biomarkers with those of non-smokers and healthy smokers/ex-smokers. The participants in the study are recruited from Örestadskliniken, a primary health care clinic in Malmö, Sweden. METHODS: Two hundred smokers and ex-smokers diagnosed with COPD with airflow restriction according to GOLD stages 1-4 will be included and compared with 50 healthy never-smokers, and 50 healthy smokers/ex-smokers without airflow restriction (total n = 300). The age distribution is 35-80 years. The participants undergo a health examination including medical history, smoking history, lung function measurements, and respond to a "Quality of Life" questionnaire. Blood samples are drawn every 6 months during a period of 5 years. Additional blood sample collection is performed if participants are experiencing an exacerbation. The blood fractions will be analyzed by standard clinical chemistry assays and by proteomics utilizing mass spectrometry platforms. Optimal sample integrity is ensured by rapid handling with robotic biobank processing followed by storage at -80 °C. The study has been approved by the Regional Ethical Review Board in Lund ( http://epn.se/en ), (Approval number: DNR 2013/480), and registered at the NIH clinical trial registry ( http://clinicaltrials.gov ). RESULTS AND DISCUSSION: Currently, 220 subjects are enrolled in the study. CONCLUSIONS AND FUTURE DIRECTIONS: The study design will enable discovery of new biomarkers by using novel mass spectrometric techniques that define early changes of COPD. Such panels of novel biomarkers may be able to distinguish COPD from closely related diseases, co-morbidities, and contribute to an increased understanding of these diseases. Graphical abstract KOL-Örestad Study.

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.

Semi-automated biobank sample processing with a 384 high density sample tube robot used in cancer and cardiovascular studies.

BACKGROUND: In the postgenomic era, it has become evident that analysis of genetic and protein expression changes alone is not sufficient to understand most disease processes in e.g. cardiovascular and cancer disease. Biobanking has been identified as an important area for development and discovery of better diagnostic tools and new treatment modalities. Biobanks are developed in order to integrate the collection of clinical samples from both healthy individuals and patients and provide valuable information that will make possible improved patient care. Modern healthcare developments are intimately linked to information based on studies of patient samples from biobank archives in large scale studies. Today biobanks form important national, as well as international, networks that share and combine global resources. METHODS: We have developed and validated a novel biobanking workflow process that utilizes 384-tube systems with a high speed sample array robot with unique processing principles. RESULTS: The 384-tube format and robotic processing is incorporated into a cancer and cardiovascular diagnostic/prognostic research program with therapeutic interventions. Our biobank practice has gained acceptance within many hospitals and research units and is based on high-density sample storage with small aliquot sample volumes. The previous standard of 5-10 mL sample volume tubes is being replaced by smaller volumes of 50-70 µL blood fractions that typically result in hundreds of thousands of aliquot fractions in 384-tube systems. CONCLUSIONS: Our novel biobanking workflow process is robust and well suited for clinical studies.

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.

Drug compound characterization by mass spectrometry imaging in cancer tissue.

MALDI mass spectrometry imaging (MSI) provides a technology platform that allows the accurate visualization of unlabeled small molecules within the two-dimensional spaces of tissue samples. MSI has proven to be a powerful tool-box concept in the development of new drugs. MSI allows unlabeled drug compounds and drug metabolites to be detected and identified and quantified according to their mass-to-charge ratios (m/z) at high resolution in complex tissue environments. Such drug characterization in situ, by both spatial and temporal behaviors within tissue compartments, provide new understandings of the dynamic processes impacting drug uptake and metabolism at the local sites targeted by therapy. Further, MSI in combination with histology and immunohistochemistry, provides the added value of defining the context of cell biology present at the sites of drug localization thus providing invaluable information relating to treatment efficacy. In this report we provide mass spectrometry imaging data within various cancers such as malignant melanoma in patients administered with vemurafenib, a protein kinase inhibitor that is targeting BRAF mutated proteins and that has shown significant efficacy in restraining disease progression. We also provide an overview of other examples of the new generation of targeted drugs, and demonstrate the data on personalized medicine drugs localization within tumor compartments within in vivo models. In these cancer models we provide detailed data on drug and target protein co-localization of YCG185 and sunitinib. These drugs are targeting VEGFR2 within the angiogenesis mechanism. Our ability to resolve drug uptake at targeted sites of directed therapy provides important opportunities for increasing our understanding about the mode of action of drug activity within the environment of disease.

A proteomic profiling of laser-microdissected lung adenocarcinoma cells of early lepidic-types.

BACKGROUND: In the new pathologic classification of lung adenocarcinoma proposed by IASLC/ATS/ERS in 2011, lepidic type adenocarcinomas are constituted by three subtypes; adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and lepidic predominant invasive adenocarcinoma (LPIA). Although these subtypes are speculated to show sequential progression from preinvasive lesion to invasive lung cancer, changes of protein expressions during these processes have not been fully studied yet. This study aims to glimpse a proteomic view of the early lepidic type lung adenocarcinomas. METHODS: A total of nine formalin-fixed and paraffin-embedded (FFPE) lepidic type lung adenocarcinoma tissues were selected from our archives, three tissues each in AIS, MIA and LPIA. The tumor and peripheral non-tumor cells in these FFPE tissues were collected with laser microdissection (LMD). Using liquid chromatography-tandem mass spectrometry (MS/MS), protein compositions were compared with respect to the peptide separation profiles among tumors collected from three types of tissues, AIS, MIA and LPIA. Proteins identified were semi-quantified by spectral counting-based or identification-based protein-based approach, and statistical evaluation was performed by pairwise G-tests. RESULTS: A total of 840 proteins were identified. Spectral counting-based semi-quantitative comparisons of all identified proteins through AIS to LPIA have revealed that the protein expression profile of LPIA was significantly differentiated from other subtypes. 70 proteins including HPX, CTTN, CDH1, EGFR, MUC1 were found as LPIA-type marker candidates, 15 protein candidates for MIA-type marker included CRABP2, LMO7, and NPEP, and 26 protein candidates for AIS-type marker included LTA4H and SOD2. The STRING gene set enrichment resulted from the protein-protein interaction (PPI) network analysis suggested that AIS was rather associated with pathways of focal adhesion, adherens junction, tight junction, that MIA had a strong association predominantly with pathways of proteoglycans in cancer and with PI3K-Akt. In contrast, LPIA was associated broadly with numerous tumor-progression pathways including ErbB, Ras, Rap1 and HIF-1 signalings. CONCLUSIONS: The proteomic profiles obtained in this study demonstrated the technical feasibility to elucidate protein candidates differentially expressed in FFPE tissues of LPIA. Our results may provide candidates of disease-oriented proteins which may be related to mechanisms of the early-stage progression of lung adenocarcinoma.

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.

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.

A protein deep sequencing evaluation of metastatic melanoma tissues.

Malignant melanoma has the highest increase of incidence of malignancies in the western world. In early stages, front line therapy is surgical excision of the primary tumor. Metastatic disease has very limited possibilities for cure. Recently, several protein kinase inhibitors and immune modifiers have shown promising clinical results but drug resistance in metastasized melanoma remains a major problem. The need for routine clinical biomarkers to follow disease progression and treatment efficacy is high. The aim of the present study was to build a protein sequence database in metastatic melanoma, searching for novel, relevant biomarkers. Ten lymph node metastases (South-Swedish Malignant Melanoma Biobank) were subjected to global protein expression analysis using two proteomics approaches (with/without orthogonal fractionation). Fractionation produced higher numbers of protein identifications (4284). Combining both methods, 5326 unique proteins were identified (2641 proteins overlapping). Deep mining proteomics may contribute to the discovery of novel biomarkers for metastatic melanoma, for example dividing the samples into two metastatic melanoma "genomic subtypes", ("pigmentation" and "high immune") revealed several proteins showing differential levels of expression. In conclusion, the present study provides an initial version of a metastatic melanoma protein sequence database producing a total of more than 5000 unique protein identifications. The raw data have been deposited to the ProteomeXchange with identifiers PXD001724 and PXD001725.

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.

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.

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.

Analysis of alpha-synuclein in malignant melanoma - development of a SRM quantification assay.

Globally, malignant melanoma shows a steady increase in the incidence among cancer diseases. Malignant melanoma represents a cancer type where currently no biomarker or diagnostics is available to identify disease stage, progression of disease or personalized medicine treatment. The aim of this study was to assess the tissue expression of alpha-synuclein, a protein implicated in several disease processes, in metastatic tissues from malignant melanoma patients. A targeted Selected Reaction Monitoring (SRM) assay was developed and utilized together with stable isotope labeling for the relative quantification of two target peptides of alpha-synuclein. Analysis of alpha-synuclein protein was then performed in ten metastatic tissue samples from the Lund Melanoma Biobank. The calibration curve using peak area ratio (heavy/light) versus concentration ratios showed linear regression over three orders of magnitude, for both of the selected target peptide sequences. In support of the measurements of specific protein expression levels, we also observed significant correlation between the protein and mRNA levels of alpha-synuclein in these tissues. Investigating levels of tissue alpha-synuclein may add novel aspect to biomarker development in melanoma, help to understand disease mechanisms and ultimately contribute to discriminate melanoma patients with different prognosis.

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.