Search

Endometrial cancer is one of the most frequently diagnosed gynecological cancers worldwide, and its prevalence has increased by more than 50% over the last two decades. Despite the understanding of the major signaling pathways driving the growth and metastasis of endometrial cancer, clinical trials targeting these signals have reported poor outcomes. The heterogeneous nature of endometrial cancer is suspected to be one of the key reasons for the failure of targeted therapies. In this study, we perform a sequential window acquisition of all theoretical fragment ion spectra (SWATH)-based comparative proteomic analysis of 63 tumor biopsies collected from 20 patients and define differences in protein signature in multiple regions of the same tumor. We develop organoids from multiple biopsies collected from the same tumor and show that organoids capture heterogeneity in endometrial cancer growth. Overall, using quantitative proteomics and patient-derived organoids, we define the heterogeneous nature of endometrial cancer within a patient's tumor., Competing Interests: Declaration of interests The author reports no conflicts of interest in this work., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). In this proof-of-concept study, we employed a mixture of selected recombinant proteins in DDA libraries to subsequently identify (not quantify) cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 recombinant human proteins that had been previously implicated as possible cancer biomarkers from both our own and other studies. The rPSL was then used to identify proteins from nondepleted colorectal cancer (CRC) EDTA plasmas by SWATH-MS. Most (32/36) of the proteins used in the rPSL were reliably identified from CRC plasma samples, including 8 proteins (i.e., BTC, CXCL10, IL1B, IL6, ITGB6, TGFα, TNF, TP53) not previously detected using high-stringency protein inference MS according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and postdigestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 could be identified using DDA-MS. The 20 additional proteins exclusively identified using the rPSL SWATH approach were almost exclusively lower abundance (i.e., <10 ng/mL) proteins. To mitigate justified FDR concerns, and to replicate a more typical library creation approach, the DDA rPSL library was merged with a human plasma DDA library and SWATH identification repeated using such a merged library. The majority (33/36) of the low abundance plasma proteins added from the rPSL were still able to be identified using such a merged library when high-stringency HPP Guidelines v3.0 protein inference criteria were applied to our data set. The MS data set has been deposited to ProteomeXchange Consortium via the PRIDE partner repository (PXD022361).

Statistically, accurate protein identification is a fundamental cornerstone of proteomics and underpins the understanding and application of this technology across all elements of medicine and biology. Proteomics, as a branch of biochemistry, has in recent years played a pivotal role in extending and developing the science of accurately identifying the biology and interactions of groups of proteins or proteomes. Proteomics has primarily used mass spectrometry (MS)-based techniques for identifying proteins, although other techniques including affinity-based identifications still play significant roles. Here, we outline the basics of MS to understand how data are generated and parameters used to inform computational tools used in protein identification. We then outline a comprehensive analysis of the bioinformatics and computational methodologies used in protein identification in proteomics including discussing the most current communally acceptable metrics to validate any identification., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Human infectious diseases are contributed equally by the host immune system's efficiency and any pathogens' infectivity. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the coronavirus strain causing the respiratory pandemic coronavirus disease 2019 (COVID-19). To understand the pathobiology of SARS-CoV-2, one needs to unravel the intricacies of host immune response to the virus, the viral pathogen's mode of transmission, and alterations in specific biological pathways in the host allowing viral survival. This review critically analyzes recent research using high-throughput "omics" technologies (including proteomics and metabolomics) on various biospecimens that allow an increased understanding of the pathobiology of SARS-CoV-2 in humans. The altered biomolecule profile facilitates an understanding of altered biological pathways. Further, we have performed a meta-analysis of significantly altered biomolecular profiles in COVID-19 patients using bioinformatics tools. Our analysis deciphered alterations in the immune response, fatty acid, and amino acid metabolism and other pathways that cumulatively result in COVID-19 disease, including symptoms such as hyperglycemic and hypoxic sequelae.

According to the 2020 Metrics of the HUPO Human Proteome Project (HPP), expression has now been detected at the protein level for >90% of the 19 773 predicted proteins coded in the human genome. The HPP annually reports on progress made throughout the world toward credibly identifying and characterizing the complete human protein parts list and promoting proteomics as an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2020-01 classified 17 874 proteins as PE1, having strong protein-level evidence, up 180 from 17 694 one year earlier. These represent 90.4% of the 19 773 predicted coding genes (all PE1,2,3,4 proteins in neXtProt). Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), was reduced by 230 from 2129 to 1899 since the neXtProt 2019-01 release. PeptideAtlas is the primary source of uniform reanalysis of raw mass spectrometry data for neXtProt, supplemented this year with extensive data from MassIVE. PeptideAtlas 2020-01 added 362 canonical proteins between 2019 and 2020 and MassIVE contributed 84 more, many of which converted PE1 entries based on non-MS evidence to the MS-based subgroup. The 19 Biology and Disease-driven B/D-HPP teams continue to pursue the identification of driver proteins that underlie disease states, the characterization of regulatory mechanisms controlling the functions of these proteins, their proteoforms, and their interactions, and the progression of transitions from correlation to coexpression to causal networks after system perturbations. And the Human Protein Atlas published Blood, Brain, and Metabolic Atlases.

The proteomic analysis of human blood and blood-derived products (e.g., plasma) offers an attractive avenue to translate research progress from the laboratory into the clinic. However, due to its unique protein composition, performing proteomics assays with plasma is challenging. Plasma proteomics has regained interest due to recent technological advances, but challenges imposed by both complications inherent to studying human biology (e.g., interindividual variability) and analysis of biospecimens (e.g., sample variability), as well as technological limitations remain. As part of the Human Proteome Project (HPP), the Human Plasma Proteome Project (HPPP) brings together key aspects of the plasma proteomics pipeline. Here, we provide considerations and recommendations concerning study design, plasma collection, quality metrics, plasma processing workflows, mass spectrometry (MS) data acquisition, data processing, and bioinformatic analysis. With exciting opportunities in studying human health and disease though this plasma proteomics pipeline, a more informed analysis of human plasma will accelerate interest while enhancing possibilities for the incorporation of proteomics-scaled assays into clinical practice.

While metastasis is the primary cause of colorectal cancer (CRC) mortality, the molecular mechanisms underpinning it remains elusive. Metastasis is propagated through driver oncogene/suppressor gene mutations, accompanied by passenger mutations and underlying genomic instability. To understand cancer biology, a unifying framework called the "hallmarks of cancer" (HoCs) has been developed, which organizes cell biological alterations under ten key hallmarks. Underlying these HoCs, genome instability generates mutational diversity that is amplified by inflammation. Recognizing how critical cancer cell-surface proteins influence, these HoCs have been proposed to accelerate precision medicine therapeutic development. A moderate decrease (43%↓) in HCT116 cell surface urokinase plasminogen activator receptor (uPAR) expression mitigates against many HoCs driven by these cell's KRAS and PIK3CA mutational signature. Comprehensive proteomics (whole cell lysis with two membrane protein enrichments) coupled with ingenuity pathway analysis (IPA) demonstrates that uPAR negates essential pathways across the HoC spectrum, particularly those associated with metastasis, resisting cell death, and sustaining proliferation, and parallels Cancer Hallmarks Analytics Tool analysis. Decreasing uPAR predominantly alters metastasis-related and uPAR-interactome protein expression (e.g., EGFR, caveolin, vitronectin, integrin β4). Collectively, it is demonstrated that uPAR is a lynchpin protein capable of regulating several HoC pathways in a classical CRC mutational background., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Oncoproteomics is the systematic study of cancer samples using omics technologies to detect changes implicated in tumorigenesis. Recent progress in oncoproteomics is already opening new avenues for the identification of novel biomarkers for early clinical stage cancer detection, targeted molecular therapies, disease monitoring, and drug development. Such information will lead to new understandings of cancer biology and impact dramatically on the future care of cancer patients. In this review, we will summarize the advantages and limitations of the key technologies used in (onco)proteogenomics, (the Omics Pipeline), explain how they can assist us in understanding the biology behind the overarching "Hallmarks of Cancer", discuss how they can advance the development of precision/personalised medicine and the future directions in the field., (Copyright © 2019. Published by Elsevier B.V.)

Introduction : Human symbiotic microbiota are now known to play important roles in human health and disease. Significant progress in our understanding of the human microbiome has been driven by recent technological advances in the fields of genomics, transcriptomics, and proteomics. As a complementary method to metagenomics, proteomics is enabling detailed protein profiling of the microbiome to decipher its structure and function and to analyze its relationship with the human body. Fecal proteomics is being increasingly applied to discover and validate potential health and disease biomarkers, and Therapeutic Goods Administration (TGA)-approved instrumentation and a range of clinical assays are being developed that will collectively play key roles in advancing personalized medicine. Areas covered : This review will introduce the complexity of the microbiome and its role in health and disease (in particular the gastrointestinal tract or gut microbiome), discuss current genomic and proteomic methods for studying this system, including the discovery of potential biomarkers, and outline the development of clinically accepted protocols leading to personalized medicine. Expert commentary : Recognition of the important role the microbiome plays in both health and disease is driving current research in this key area. A proteogenomics approach will be essential to unravel the biologies underlying this complex network.

The Human Proteome Project (HPP) annually reports on progress throughout the field in credibly identifying and characterizing the human protein parts list and making proteomics an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2018-01-17, the baseline for this sixth annual HPP special issue of the Journal of Proteome Research, contains 17 470 PE1 proteins, 89% of all neXtProt predicted PE1-4 proteins, up from 17 008 in release 2017-01-23 and 13 975 in release 2012-02-24. Conversely, the number of neXtProt PE2,3,4 missing proteins has been reduced from 2949 to 2579 to 2186 over the past two years. Of the PE1 proteins, 16 092 are based on mass spectrometry results, and 1378 on other kinds of protein studies, notably protein-protein interaction findings. PeptideAtlas has 15 798 canonical proteins, up 625 over the past year, including 269 from SUMOylation studies. The largest reason for missing proteins is low abundance. Meanwhile, the Human Protein Atlas has released its Cell Atlas, Pathology Atlas, and updated Tissue Atlas, and is applying recommendations from the International Working Group on Antibody Validation. Finally, there is progress using the quantitative multiplex organ-specific popular proteins targeted proteomics approach in various disease categories.

The pursuit of novel and effective biomarkers is essential in the struggle against cancer, which is a leading cause of mortality worldwide. Biomarkers can be used as specific diagnostic tools, prognostic predictors, markers of the development of therapeutic resistance or even as therapeutic targets themselves. Through the application of sensitive and specific proteomic techniques, oncoproteomics investigates the proteins associated with cancer processes, to better understand their biological function/s and their associated pathways during tumorigenesis. Such studies seek to identify both potential biomarkers and drug targets in order to improve patient survival and quality of life whilst reducing the global health budget. Tissue and plasma are the most commonly utilised biological samples for such studies as they are readily available, non-invasive and generally acceptable. Here, we outline the relative advantages and disadvantages of the most frequently used techniques for cancer diagnosis, prognosis, treatment and surveillance, concentrating on the latest advances and application of tissue and plasma proteomics for novel cancer biomarker discovery and disease surveillance.

Introduction: As we move from a discovery to a translational phase in proteomics, with a focus on developing validated clinical assays to assist personalized medicine, there is a growing need for strong bidirectional interactions with the clinical pathology community. Thus, while on one hand the proteomics community will provide candidate biomarkers to assist in diagnosis, prognosis, surveillance, identification of individualized patient medication, and development and validation of new assays for diagnostic use, on the other the pathology community will assist with specific tissue identification and selection (e.g. laser capture microdissection, tissue sections for MS imaging), biobanking, validation of emerging automated histopathology techniques, preparation and classification of relevant patient medical reports, and assisting with the optimization of experimental design for clinical trials. Areas covered: Here we discuss these topics with a particular emphasis on recent publications and relevant initiatives and outline some of the hurdles that still remain for personalized medicine. Expert commentary: It is clear that effective crosstalk between the proteomics and pathology communities will greatly accelerate crossover of candidate biomarkers to personalized medicine, which will have significant benefits not only for patient wellbeing, but also the global healthcare budget. However, analysis of the big data generated may become rate-limiting.

Despite decades of accumulated knowledge about proteins and their post-translational modifications (PTMs), numerous questions remain regarding their molecular composition and biological function. One of the most fundamental queries is the extent to which the combinations of DNA-, RNA- and PTM-level variations explode the complexity of the human proteome. Here, we outline what we know from current databases and measurement strategies including mass spectrometry-based proteomics. In doing so, we examine prevailing notions about the number of modifications displayed on human proteins and how they combine to generate the protein diversity underlying health and disease. We frame central issues regarding determination of protein-level variation and PTMs, including some paradoxes present in the field today. We use this framework to assess existing data and to ask the question, "How many distinct primary structures of proteins (proteoforms) are created from the 20,300 human genes?" We also explore prospects for improving measurements to better regularize protein-level biology and efficiently associate PTMs to function and phenotype.

In the past decade, proteomics and mass spectrometry have taken tremendous strides forward, particularly in the life sciences, spurred on by rapid advances in technology resulting in generation and conglomeration of vast amounts of data. Though this has led to tremendous advancements in biology, the interpretation of the data poses serious challenges for many practitioners due to the immense size and complexity of the data. Furthermore, the lack of annotation means that a potential gold mine of relevant biological information may be hiding within this data. We present here a simple and intuitive workflow for the research community to investigate and mine this data, not only to extract relevant data but also to segregate usable, quality data to develop hypotheses for investigation and validation. We apply an MS evidence workflow for verifying peptides of proteins from one's own data as well as publicly available databases. We then integrate a suite of freely available bioinformatics analysis and annotation software tools to identify homologues and map putative functional signatures, gene ontology and biochemical pathways. We also provide an example of the functional annotation of missing proteins in human chromosome 7 data from the NeXtProt database, where no evidence is available at the proteomic, antibody, or structural levels. We give examples of protocols, tools and detailed flowcharts that can be extended or tailored to interpret and annotate the proteome of any novel organism.

Ertapenem is an important first-line carbapenem antibiotic used for the treatment of aerobic Gram-negative bacterial infections. It is the only marketed carbapenem that is highly bound to plasma proteins and displays a concentration-dependent and saturable plasma protein binding profile. To date, the plasma components responsible for sequestering ertapenems antibacterial activity remain uncharacterized. In the present study, we have employed an orthogonal, multiplatform approach, including novel compound-centric displacement proteomics and surface plasmon resonance to characterize the plasma protein binding proteome of ertapenem. In proof-of-concept, the capacity of physiological cocktails of the identified plasma proteins to inhibit the antibacterial activity of ertapenem was assessed with in vitro microbiological assays. We show that fibrinogen, complement C4, haptoglobulin, α-1-antitrypsin, fibronectin, transferrin, immunoglobulin G, hemopexin, and humans serum albumin are responsible for the majority of the sequestering activity in plasma. No binding was observed to α-1-acid-glycoprotein. The findings of this study have broad reaching implications for antibiotic drug design and for dose tailoring to suit the plasma protein levels of individual patients in order to maximize the clinical efficacy of important first-line antibiotics such as ertapenem.

Globally, ∼1 in 15 men of reproductive age are infertile, yet the precise mechanisms underlying their gamete failure are unknown. Although a semen analysis is performed to determine fertilizing potential, the diagnostic suitability of this analysis has been questioned in several reports, as many men, classified as infertile according to their semen analysis, subsequently turn out to be fertile. Herein, we have used a quantitative (phospho)-proteomic analysis, using enrichment on titanium dioxide followed by ion-trap mass spectrometry (LC-MS/MS), to compare the semen of infertile versus fertile males. One protein, namely outer dense fiber 1 (ODF1), was dramatically reduced in infertile males. Using specific antibodies, we then screened the gametes of a cohort of suspected infertile men and demonstrated a reduction in the amount of ODF1 compared with fertile controls. Stress treatment of sperm deficient in ODF1 caused the head to decapitate, suggesting why these gametes fail to initiate fertilization. Interestingly, electron micrographs of ODF1-deficient spermatozoa revealed an abnormal connecting piece, indicating several developmental defects with both the implantation plate and the thin laminated fibers. In some cases, the implantation plate appeared to be reduced in size or was overburdened by granular material near the connecting piece. Hence, a strong reduction ODF1 is a marker of idiopathic male infertility and a potential driver of this condition., (© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.)

Every data-rich community research effort requires a clear plan for ensuring the quality of the data interpretation and comparability of analyses. To address this need within the Human Proteome Project (HPP) of the Human Proteome Organization (HUPO), we have developed through broad consultation a set of mass spectrometry data interpretation guidelines that should be applied to all HPP data contributions. For submission of manuscripts reporting HPP protein identification results, the guidelines are presented as a one-page checklist containing 15 essential points followed by two pages of expanded description of each. Here we present an overview of the guidelines and provide an in-depth description of each of the 15 elements to facilitate understanding of the intentions and rationale behind the guidelines, for both authors and reviewers. Broadly, these guidelines provide specific directions regarding how HPP data are to be submitted to mass spectrometry data repositories, how error analysis should be presented, and how detection of novel proteins should be supported with additional confirmatory evidence. These guidelines, developed by the HPP community, are presented to the broader scientific community for further discussion.

Claudins are the major transmembrane protein components of tight junctions in human endothelia and epithelia. Tissue-specific expression of claudin members suggests that this protein family is not only essential for sustaining the role of tight junctions in cell permeability control but also vital in organizing cell contact signaling by protein-protein interactions. How this protein family is collectively processed and regulated is key to understanding the role of junctional proteins in preserving cell identity and tissue integrity. The focus of this review is to first provide a brief overview of the functional context, on the basis of the extensive body of claudin biology research that has been thoroughly reviewed, for endogenous human claudin members and then ascertain existing and future proteomics techniques that may be applicable to systematically characterizing the chemical forms and interacting protein partners of this protein family in human. The ability to elucidate claudin-based signaling networks may provide new insight into cell development and differentiation programs that are crucial to tissue stability and manipulation.

Approximately 2.9 billion long base-pair human reference genome sequences are known to encode some 20 000 representative proteins. However, 3000 proteins, that is, ~15% of all proteins, have no or very weak proteomic evidence and are still missing. Missing proteins may be present in rare samples in very low abundance or be only temporarily expressed, causing problems in their detection and protein profiling. In particular, some technical limitations cause missing proteins to remain unassigned. For example, current mass spectrometry techniques have high limits and error rates for the detection of complex biological samples. An insufficient proteome coverage in a reference sequence database and spectral library also raises major issues. Thus, the development of a better strategy that results in greater sensitivity and accuracy in the search for missing proteins is necessary. To this end, we used a new strategy, which combines a reference spectral library search and a simulated spectral library search, to identify missing proteins. We built the human iRefSPL, which contains the original human reference spectral library and additional peptide sequence-spectrum match entries from other species. We also constructed the human simSPL, which contains the simulated spectra of 173 907 human tryptic peptides determined by MassAnalyzer (version 2.3.1). To prove the enhanced analytical performance of the combination of the human iRefSPL and simSPL methods for the identification of missing proteins, we attempted to reanalyze the placental tissue data set (PXD000754). The data from each experiment were analyzed using PeptideProphet, and the results were combined using iProphet. For the quality control, we applied the class-specific false-discovery rate filtering method. All of the results were filtered at a false-discovery rate of <1% at the peptide and protein levels. The quality-controlled results were then cross-checked with the neXtProt DB (2014-09-19 release). The two spectral libraries, iRefSPL and simSPL, were designed to ensure no overlap of the proteome coverage. They were shown to be complementary to spectral library searching and significantly increased the number of matches. From this trial, 12 new missing proteins were identified that passed the following criterion: at least 2 peptides of 7 or more amino acids in length or one of 9 or more amino acids in length with one or more unique sequences. Thus, the iRefSPL and simSPL combination can be used to help identify peptides that have not been detected by conventional sequence database searches with improved sensitivity and a low error rate.

Modern proteomics has proven instrumental in our understanding of the molecular deregulations associated with the development and progression of cancer. Herein, we profile membrane-enriched proteome of tumor and adjacent normal tissues from eight CRC patients using label-free nanoLC-MS/MS-based quantitative proteomics and advanced pathway analysis. Of the 948 identified proteins, 184 proteins were differentially expressed (P<0.05, fold change>1.5) between the tumor and non-tumor tissue (69 up-regulated and 115 down-regulated in tumor tissues). The CRC tumor and non-tumor tissues clustered tightly in separate groups using hierarchical cluster analysis of the differentially expressed proteins, indicating a strong CRC-association of this proteome subset. Specifically, cancer associated proteins such as FN1, TNC, DEFA1, ITGB2, MLEC, CDH17, EZR and pathways including actin cytoskeleton and RhoGDI signaling were deregulated. Stage-specific proteome signatures were identified including up-regulated ribosomal proteins and down-regulated annexin proteins in early stage CRC. Finally, EGFR(+) CRC tissues showed an EGFR-dependent down-regulation of cell adhesion molecules, relative to EGFR(-) tissues. Taken together, this study provides a detailed map of the altered proteome and associated protein pathways in CRC, which enhances our mechanistic understanding of CRC biology and opens avenues for a knowledge-driven search for candidate CRC protein markers., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by a mutation in the Huntingtin gene, where excessive (≥ 36) CAG repeats encode for glutamine expansion in the huntingtin protein. Research using mouse models and human pathological material has indicated dysfunctions in a myriad of systems, including mitochondrial and ubiquitin/proteasome complexes, cytoskeletal transport, signaling, and transcriptional regulation. Here, we examined the earliest biochemical and pathways involved in HD pathology. We conducted a proteomics study combined with immunocytochemical analysis of undifferentiated HD-affected and unaffected human embryonic stem cells (hESC). Analysis of 1883 identifications derived from membrane and cytosolic enriched fractions revealed mitochondria as the primary dysfunctional organ in HD-affected pluripotent cells in the absence of significant differences in huntingtin protein. Furthermore, on the basis of analysis of 645 proteins found in neurodifferentiated hESC, we show a shift to transcriptional dysregulation and cytoskeletal abnormalities as the primary pathologies in HD-affected cells differentiating along neural lineages in vitro. We also show this is concomitant with an up-regulation in expression of huntingtin protein in HD-affected cells. This study demonstrates the utility of a model that recapitulates HD pathology and offers insights into disease initiation, etiology, progression, and potential therapeutic intervention.

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.

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.

The secreted cellular sub-proteome (secretome) is a rich source of biologically active glycoproteins. N-Glycan profiling of secretomes of cultured cancer cells provides an opportunity to investigate the link between protein N-glycosylation and tumorigenesis. Utilizing carbon-LC-ESI-CID-MS/MS of protein released native N-glycans, we accurately profiled the secretome N-glycosylation of six human epithelial breast cells including normal mammary epithelial cells (HMEC) and breast cancer cells belonging to luminal A subtype (MCF7), HER2-overexpressing subtype (SKBR3), and basal B subtype (MDA-MB157, MDA-MB231, HS578T). On the basis of intact molecular mass, LC retention time, and MS/MS fragmentation, a total of 74 N-glycans were confidently identified and quantified. The secretomes comprised significant levels of highly sialylated and fucosylated complex type N-glycans, which were elevated in all cancer cells relative to HMEC (57.7-87.2% vs 24.9%, p < 0.0001 and 57.1-78.0% vs 38.4%, p < 0.0001-0.001, respectively). Similarly, other glycan features were found to be altered in breast cancer secretomes including paucimannose and complex type N-glycans containing bisecting β1,4-GlcNAc and LacdiNAc determinants. Subtype-specific glycosylation were observed, including the preferential expression of α2,3-sialylation in the basal B breast cancer cells. Pathway analysis indicated that the regulated N-glycans were biosynthetically related. Tight clustering of the breast cancer subtypes based on N-glycome signatures supported the involvement of N-glycosylation in cancer. In conclusion, we are the first to report on the secretome N-glycosylation of a panel of breast epithelial cell lines representing different subtypes. Complementing proteome and lipid profiling, N-glycome mapping yields important pieces of structural information to help understand the biomolecular deregulation in breast cancer development and progression, knowledge that may facilitate the discovery of candidate cancer markers and potential drug targets.

Posttranslational modifications represent a major mechanism by which cells control molecular events. Sample preparation is one of the biggest keys in terms of proteomic analysis, and especially when looking at phosphoproteomics. Here we describe two techniques that are used to identify phosphopeptides. These are Titanium Dioxide and Immobilized Metal Affinity Chromatography (IMAC) which enrich for phosphopeptides. These enrichment techniques typically often identify ~35 % of the same and ~65 % unique phosphopeptides. In this chapter, we describe the use of an ion-trap mass spectrometer for the identification of phosphopeptides.

Spermatozoa represent the epitome of terminally differentiated, highly specialized cells. They are transcriptionally and translationally silent and yet manage to undergo a complete functional transformation after they leave the testes, entirely fuelled by post-translational modifications occurring during epididymal maturation and capacitation. The latter have been recognized as biological processes for more than half a century. However, the biochemical mechanisms that drive these events have remained elusive, as have the pathological mechanisms that lead to defective sperm function and infertility. In the past decade the combined power of advanced proteomics, biochemistry, and functional genomics has permitted an unprecedented improvement in our understanding of sperm cell biology. We can also predict that a systems-biology approach, in concert with the new tools provided by the 'omics' revolution, will lead to dramatic gains in our understanding in the near future. As a result of such advances, insights will be generated that should ultimately lead to significant improvements in our capacity to diagnose and treat the infertile male.

The objective of the international Chromosome-Centric Human Proteome Project (C-HPP) is to map and annotate all proteins encoded by the genes on each human chromosome. The C-HPP consortium was established to organize a collaborative network among the research teams responsible for protein mapping of individual chromosomes and to identify compelling biological and genetic mechanisms influencing colocated genes and their protein products. The C-HPP aims to foster the development of proteome analysis and integration of the findings from related molecular -omics technology platforms through collaborations among universities, industries, and private research groups. The C-HPP consortium leadership has elicited broad input for standard guidelines to manage these international efforts more efficiently by mobilizing existing resources and collaborative networks. The C-HPP guidelines set out the collaborative consensus of the C-HPP teams, introduce topics associated with experimental approaches, data production, quality control, treatment, and transparency of data, governance of the consortium, and collaborative benefits. A companion approach for the Biology and Disease-Driven HPP (B/D-HPP) component of the Human Proteome Project is currently being organized, building upon the Human Proteome Organization's organ-based and biofluid-based initiatives (www.hupo.org/research). The common application of these guidelines in the participating laboratories is expected to facilitate the goal of a comprehensive analysis of the human proteome.

Cancer is well known to be associated with alterations in membrane protein glycosylation (Bird, N. C., Mangnall, D., and Majeed, A. W. (2006) Biology of colorectal liver metastases: A review. J. Surg. Oncol. 94, 68-80; Dimitroff, C. J., Pera, P., Dall'Olio, F., Matta, K. L., Chandrasekaran, E. V., Lau, J. T., and Bernacki, R. J. (1999) Cell surface n-acetylneuraminic acid alpha2,3-galactoside-dependent intercellular adhesion of human colon cancer cells. Biochem. Biophys. Res. Commun. 256, 631-636; and Arcinas, A., Yen, T. Y., Kebebew, E., and Macher, B. A. (2009) Cell surface and secreted protein profiles of human thyroid cancer cell lines reveal distinct glycoprotein patterns. J. Proteome Res. 8, 3958-3968). Equally, it has been well established that tumor-associated inflammation through the release of pro-inflammatory cytokines is a common cause of reduced hepatic drug metabolism and increased toxicity in advanced cancer patients being treated with cytotoxic chemotherapies. However, little is known about the impact of bearing a tumor (and downstream effects like inflammation) on liver membrane protein glycosylation. In this study, proteomic and glycomic analyses were used in combination to determine whether liver membrane protein glycosylation was affected in mice bearing the Engelbreth-Holm Swarm sarcoma. Peptide IPG-IEF and label-free quantitation determined that many enzymes involved in the protein glycosylation pathway specifically; mannosidases (Man1a-I, Man1b-I and Man2a-I), mannoside N-acetylglucosaminyltransferases (Mgat-I and Mgat-II), galactosyltransferases (B3GalT-VII, B4GalT-I, B4GalT-III, C1GalT-I, C1GalT-II, and GalNT-I), and sialyltransferases (ST3Gal-I, ST6Gal-I, and ST6GalNAc-VI) were up-regulated in all livers of tumor-bearing mice (n = 3) compared with nontumor bearing controls (n = 3). In addition, many cell surface lectins: Sialoadhesin-1 (Siglec-1), C-type lectin family 4f (Kupffer cell receptor), and Galactose-binding lectin 9 (Galectin-9) were determined to be up-regulated in the liver of tumor-bearing compared with control mice. Global glycan analysis identified seven N-glycans and two O-glycans that had changed on the liver membrane proteins derived from tumor-bearing mice. Interestingly, α (2,3) sialic acid was found to be up-regulated on the liver membrane of tumor-bearing mice, which reflected the increased expression of its associated sialyltransferase and lectin receptor (siglec-1). The overall increased sialylation on the liver membrane of Engelbreth-Holm Swarm bearing mice correlates with the increased expression of their associated glycosyltransferases and suggests that glycosylation of proteins in the liver plays a role in tumor-induced liver inflammation.

We hereby provide a two-year update on the HUPO Human Plasma Proteome Project (HPPP) informed by advances presented at the HPPP sessions at the HUPO World Congresses in Toronto in September 2009 and in Sydney in September 2010., (Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The Asia Oceania Human Proteome Organisation (AOHUPO) has embarked on a Membrane Proteomics Initiative with goals of systematic comparison of strategies for analysis of membrane proteomes and discovery of membrane proteins. This multilaboratory project is based on the analysis of a subcellular fraction from mouse liver that contains endoplasmic reticulum and other organelles. In this study, we present the strategy used for the preparation and initial characterization of the membrane sample, including validation that the carbonate-washing step enriches for integral and lipid-anchored membrane proteins. Analysis of 17 independent data sets from five types of proteomic workflows is in progress., (Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

An emphasis of current proteomic research is the validation of plasma protein biomarkers. The process of blood collection itself is critical to the accuracy and reproducibility of quantitative biomarker assays. We have developed selected reaction monitoring (SRM) assays to analyse thirteen abundant plasma proteins and evaluated the impact of three different blood collection tubes on the levels of these proteins. We also assessed the implications of the time taken to analyse plasma samples by evaluating the recovery of these proteins. We showed that SRM detects minor differences in the levels of some proteins which can be attributed to collection tube type. The average recovery for 12 of 18 assays was higher for proteins that were collected in tubes containing protease inhibitors compared to conventional collection tubes. For five of the assays, the differential recovery was statistically significant. Delaying MS analysis of a freeze-thawed sample for 1 hour showed greatly reduced recovery of these analytes; however differences attributed to tube type were only evident at the baseline timepoint. Finally, we assessed the natural variation of circulating levels of these proteins in a cohort of seven healthy individuals. This study provides useful information for researchers contemplating blood collection for undertaking protein biomarker studies.

Protein biomarkers are fundamental tools for the characterization of stem cells and for tracking their differentiation and maturation down developmental lineages. Technology development allowing increased coverage of difficult cellular proteomes should allow for the discovery of new and novel membrane protein biomarkers for use by the stem cell research community. The amphipathic and highly hydrophobic nature and relative low abundance of many membrane proteins present significant analytical challenges. These difficulties are amplified when the source material (tissue or cells) is only available in limited quantities (e.g., embryonic stem cells). Recent advances in enrichment for purer membrane fractions, the enzymatic and chemical digestion of membrane proteins in the presence of solvents or chaotropes, and the use of "shotgun" proteomics methodologies have gradually resulted in increased membrane proteome coverage with numbers of predicted integral membrane proteins now in excess of 1000 being routinely reported. We have recently demonstrated the advantages of using peptide isoelectric focusing in the first dimension on immobilized pH gradients (peptide IPG-IEF) followed by reversed phase chromatography and tandem MS to increase membrane proteome coverage. This study looked at achieving a similar level of membrane proteome coverage using modifications to reported methodologies while restricting the number of characterized human embryonic stem cells to 10(7) cells. Two-thousand two-hundred and ninety-two (2292) nonredundant proteins were identified with two or more high accuracy peptide matches from 260 mug of a human embryonic stem cell membrane enriched fraction with a false discovery rate of 0.32%. Gene Ontology (GO) mapping predicted 1279 (44.9%) of this list to be membrane proteins of which 395 proteins were predicted to be derived from the plasma membrane compartment. The TMHMM algorithm predicted 904 integral membrane proteins with up to 16 transmembrane helices. Collectively, we assert that the substantial membrane proteome coverage achieved using these procedures will enable rapid advances in the identification and quantitation of novel membrane proteins as markers of differentiation status and/or genetic mutation from relatively low numbers of cultured embryonic stem cells.

Understanding the cellular mechanisms that regulate mammalian sperm function is strategically important for both the management of male infertility and the development of novel approaches to male contraception. The spermatozoon is a transcriptionally and translationally suppressed cell that is released from the testes in a functionally inert state. Functional activation occurs in the epididymis and female tract via mechanisms that are entirely dependent on post-translational modifications. Proteomics is, therefore, the ideal technology to investigate this cell type. Herein, we comment on the proteomic analyses that have been applied to mammalian spermatozoa, including some concerns relating to data interpretation. Three comprehensive liquid chromatography-mass spectrometry lists of human, mouse and rat spermatozoa are then compared, insights into the molecular regulation of sperm function discussed and future directions speculated upon.

We have developed a fast and simple two column chromatographic method for the purification of the 26S proteasome from the filamentous fungus Trichoderma reesei that simplifies the overall procedure and reduces the purification time from 5 to 2.5 days. The combination of only the anionic exchange POROS HQ column (Applied Biosystems) together with a size exclusion column has not been used previously for proteasome purification. The purified complex was analysed further by two-dimensional electrophoresis (2DE) and examined by transmission electron microscopy (TEM). A total of 102 spots separated by 2DE were identified by mass spectrometry using cross-species identification (CSI) or an in-house custom-made protein database derived from the T. reesei sequencing project. Fifty-one spots out of 102 represented unique proteins. Among them, 30 were from the 20S particle and eight were from the 19S particle. In addition, seven proteasome-interacting proteins as well as several non-proteasome related proteins were identified. Co-purification of the 19S regulatory particle was confirmed by TEM and Western blotting. The rapidity of the purification procedure and largely intact nature of the complex suggest that similar procedure may be applicable to the isolation and purification of the other protein complexes.

The advent of enhanced methods for the pre-fractionation of proteins, improved high speed, high resolution, high sensitivity mass spectrometry hardware and superior informatics/bioformatics software is heralding a new era in our capacity to analyse the proteomic composition of human spermatozoa. Parallel improvements in our capacity to compare proteomic profiles from spermatozoa in different functional states (immature vs. mature, uncapacitated vs. capacitated, normal vs. defective) is also helping to define which specific elements of the proteome are of functional significance. The ultimate aim of such studies will be to integrate the proteome with the sperm metabolome so that we shall not only understand the cascade of post-translational modifications (e.g., phosphorylation, glycosylation, proteolytic cleavage) involved in generating a functional spermatozoon but also determine how these physiological changes are brought about. This fundamental information will then create a basis for identifying key points in the post-testicular maturation of spermatozoa that might be targeted for contraceptive purposes or implicated in the defective sperm function observed in a significant proportion of infertile males.

Two-dimensional gel electrophoresis (2-DE) image analysis is conventionally used for comparative proteomics. However, there are a number of technical difficulties associated with 2-DE protein separation that limit the depth of proteome coverage, and the image analysis steps are typically labor-intensive and low-throughput. Recently, mass spectrometry-based quantitation strategies have been described as alternative differential proteome analysis techniques. In this study, we investigated changes in protein expression using an ovarian cancer cell line, OVMZ6, 24 h post-stimulation with the relatively weak agonist, urokinase-type plasminogen activator (uPA). Quantitative protein profiles were obtained by MALDI-TOF/TOF from stable isotope-labeled cells in culture (SILAC), and these results were compared to the quantitative ratios obtained using 2-DE gel image analysis. MALDI-TOF/TOF mass spectrometry showed that differential quantitation using SILAC was highly reproducible (approximately 8% coefficient of variation (CV)), and this variance was considerably lower than that achieved using automated 2-DE image analysis strategies (CV approximately 25%). Both techniques revealed subtle alterations in cellular protein expression following uPA stimulation. However, due to the lower variances associated with the SILAC technique, smaller changes in expression of uPA-inducible proteins could be found with greater certainty.

Urokinase plasminogen activator (uPA) and its high affinity receptor (uPAR) play crucial proteolytic and non-proteolytic roles in cancer metastasis. In addition to promoting plasmin-mediated degradation of extracellular matrix barriers, cell surface engagement of uPA through uPAR binding results in the activation of a suite of diverse cellular signal transduction pathways. Because uPAR is bound to the plasma membrane through a glycosyl-phosphatidylinositol anchor, these signalling sequelae are thought to occur through the formation of multi-protein cell surface complexes involving uPAR. To further characterize uPAR-driven protein complexes, we co-immunoprecipitated uPAR from the human ovarian cancer cell line, OVCA 429, and employed sensitive proteomic methods to identify the uPAR-associated proteins. Using this strategy, we identified several known, as well as numerous novel, uPAR associating proteins, including the epithelial restricted integrin, alphavbeta6. Reverse immunoprecipitation using anti-beta6 integrin subunit monoclonal antibodies confirmed the co-purification of this protein with uPAR. Inhibition of uPAR and/or beta6 integrin subunit using neutralizing antibodies resulted in the inhibition of uPA-mediated ERK 1/2 phosphorylation and subsequent cell proliferation. These data suggest that the association of beta6 integrin (and possibly other lynchpin cancer regulatory proteins) with uPAR may be crucial in co-transmitting uPA signals that induce cell proliferation. Our findings support the notion that uPAR behaves as a lynchpin in promoting tumorigenesis by forming functionally active multiprotein complexes.

Hypertension and estrogen deficiency in women have been identified as significant risk factors for cerebrovascular diseases. Hypertension causes excessive vascular stretch and contributes to the initiation of cellular injury in blood vessels while estrogen has been demonstrated to exert beneficial protective effects on the vascular system. Although the specific biological outcomes exerted by either excessive stretch or estrogen exposure are well established, the combined biochemical effects of both stimuli remain unclear. Therefore, this study was conducted for quantitative proteomics study on human cerebral microvascular endothelial cells (HCMECs) subjected to 20% "pathological" cyclic stretch for a period of 18 hour in the presence or absence of 17β-estradiol by isobaric Taqs for Relative and Absolute Quantification. The results showed that only some proteins responded to 17β-estradiol (e.g., thioredoxin reductase-1), stretch (e.g., 14- 3-3 protein epsilon or acidic leucine-rich nuclear phosphoprotein 32 family member B) and interestingly, some proteins returned to control pre-treatment levels when exposed to both (e.g., d-dopachrome decarboxylase, thrombospondin-1). In addition, HCMECs that exposed only to estrogen had a very similar proteomic profile (i.e., up-regulation of structural, cellular adhesion and proliferation proteins) as to those exposed to estrogen with 20% stretching for 18 hour, suggesting that estrogen ablated the detrimental effects by the stretch alone. These findings sheds light on the molecular mechanisms by which the cerebrovascular protective actions of estrogen on HCMEC exposed to pathological levels of cyclic stretch which could provide a platform for future research in therapeutic approach. [ABSTRACT FROM AUTHOR]

It is hard to fathom that one of the most highly differentiated cells in the body, the spermatozoon, spends over half of its developmental life without the capacity for nuclear protein biosynthesis. This is even more incredible when considering that protein synthesis is switched off long before the sperm is mature. As such, in order to obtain full functionality, spermatozoa rely on post-translational modifications (PTM) of existing proteins. Many PTM have been shown to play a role in the development of a sperm cell. These include phosphorylation and glycosylation events that occur both in the epididymis and during capacitation. In addition, several other PTM such as disulfide cross-linking, ubiquitination, acetylation and methylation all play a role to both develop and enable a spermatozoon to achieve its final destiny. [ABSTRACT FROM AUTHOR]

The Human Proteome Project stands to eclipse the Human Genome Project in terms of scope, content and interpretation. Its outputs, in conjunction with recent developments across the proteomics community, provide new tools for cancer research with the potential of providing clinically relevant insights into the disease. These collectively may guide the development of future diagnosis, surveillance and treatment strategies. Having established a robust organizational framework within the international community, the Human Proteome Organization and the proteomics community at large have made significant advances in biomarker discovery, detection, molecular imaging and in exploring tumor heterogeneity. Here, the authors discuss some developments in cancer proteomics and how they can be implemented to reduce the global burden of the disease. [ABSTRACT FROM AUTHOR]

The sperm anterior head plasma membrane (APM) is the site where sperm first bind to the zona pellucida (ZP). This binding reaches the maximum following the sperm capacitation process. To gain a better understanding of the sperm-ZP binding mechanisms, we compared protein profiles obtained from mass spectrometry of APM vesicles isolated from non-capacitated and capacitated sperm. The results revealed that ZP-binding proteins were the most abundant group of proteins, with a number of them showing increased levels in capacitated sperm. Blue native gel electrophoresis and far-western blotting revealed presence of high molecular weight (HMW) protein complexes in APM vesicles of both non-capacitated and capacitated sperm, but the complexes (∼750-1300 kDa) from capacitated sperm possessed much higher binding capacity to pig ZP3 glycoprotein. Proteomic analyses indicated that a number of proteins known for their acrosome localization, including zonadhesin, proacrosin/acrosin and ACRBP, were components of capacitated APM HMW complexes, with zonadhesin being the most enriched protein. Our immunofluorescence results further demonstrated that a fraction of these acrosomal proteins was transported to the surface of live acrosome-intact sperm during capacitation. Co-immunoprecipitation indicated that zonadhesin, proacrosin/acrosin and ACRBP interacted with each other and they may traffic as a complex from the acrosome to the sperm surface. Finally, the significance of zonadhesin in the binding of APM HMW complexes to pig ZP3 was demonstrated; the binding ability was decreased following treatment of the complexes with anti-zonadhesin antibody. Our results suggested that acrosomal proteins, especially zonadhesin, played roles in the initial sperm-ZP binding during capacitation. J. Cell. Physiol. 230: 449-463, 2015. © 2014 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Importin α proteins function as adaptors to connect a cargo protein and importin β1 in the classical nuclear import pathway. Here we measure for the first time the stoichiometry of importins α2, α3, α4, and β1 in primary cells corresponding to 2 successive stages of rat spermatogenesis: meiotic spermatocytes and haploid round spermatids. Importin α2 levels were more than 2-fold higher in spermatocytes than in spermatids, while importins α4 and β1 levels did not differ significantly. We performed a comprehensive proteomics analysis to identify binding proteins in spermatocytes and spermatids using recombinant importin α2 and α4 proteins. Among the 100 candidate partners, 42 contained a strong classical nuclear localization signal (cNLS; score of>6 by cNLS Mapper), while 8 nuclear proteins lacked any cNLS. hi addition, we developed a new strategy to predict which cargoes bind to importin α through the conserved C-terminal acidic domain (ARM repeats 9-10), and provided functional validation of a predicted importin α C-terminal binding segment in Senataxin and Smarca4. Evaluation of this set of candidate binding partners from spermatogenic cells using several bioinformatics approaches provides new evidence that individual importin as may serve unique and nonredundant roles in mediating cellular differentiation. [ABSTRACT FROM AUTHOR]

Izumo1 is a testis-specific gene product, whose function is essential for sperm-egg fusion. Throughout its lifespan, Izumo1 is posttranslationally modified, being both N-linked glycosylated on its extracellular domain and phosphorylated on the intracellular C-terminal tail. Within the caput regions of the rat epididymis, two phosphorylation events have been documented. However, as sperm pass through the epididymis, this cytoplasmic portion of Izumo1 has been shown to contain up to seven phosphorylation sites. Remarkably, in the rat, in correlation with these events, Izumo1 undergoes sub-cellular re-location, moving from the head/tail regions of the spermatozoa, to a predominantly equatorial segment location once they have reached the caudal end of the epididymis. [ABSTRACT FROM AUTHOR]

Background: One of the most significant challenges in colorectal cancer (CRC) management is the use of compliant early stage population-based diagnostic tests as adjuncts to confirmatory colonoscopy. Despite the near curative nature of early clinical stage surgical resection, mortality remains unacceptably high—as the majority of patients diagnosed by faecal haemoglobin followed by colonoscopy occur at latter stages. Additionally, current population-based screens reliant on fecal occult blood test (FOBT) have low compliance (~ 40%) and tests suffer low sensitivities. Therefore, blood-based diagnostic tests offer survival benefits from their higher compliance (≥ 97%), if they can at least match the sensitivity and specificity of FOBTs. However, discovery of low abundance plasma biomarkers is difficult due to occupancy of a high percentage of proteomic discovery space by many high abundance plasma proteins (e.g., human serum albumin). Methods: A combination of high abundance protein ultradepletion (e.g., MARS-14 and an in-house IgY depletion columns) strategies, extensive peptide fractionation methods (SCX, SAX, High pH and SEC) and SWATH-MS were utilized to uncover protein biomarkers from a cohort of 100 plasma samples (i.e., pools of 20 healthy and 20 stages I–IV CRC plasmas). The differentially expressed proteins were analyzed using ANOVA and pairwise t-tests (p < 0.05; fold-change > 1.5), and further examined with a neural network classification method using in silico augmented 5000 patient datasets. Results: Ultradepletion combined with peptide fractionation allowed for the identification of a total of 513 plasma proteins, 8 of which had not been previously reported in human plasma (based on PeptideAtlas database). SWATH-MS analysis revealed 37 protein biomarker candidates that exhibited differential expression across CRC stages compared to healthy controls. Of those, 7 candidates (CST3, GPX3, CFD, MRC1, COMP, PON1 and ADAMDEC1) were validated using Western blotting and/or ELISA. The neural network classification narrowed down candidate biomarkers to 5 proteins (SAA2, APCS, APOA4, F2 and AMBP) that had maintained accuracy which could discern early (I/II) from late (III/IV) stage CRC. Conclusion: MS-based proteomics in combination with ultradepletion strategies have an immense potential of identifying diagnostic protein biosignature. [ABSTRACT FROM AUTHOR]