Intra-epithelial non-canonical Activin A signaling safeguards prostate progenitor quiescence.

The healthy prostate is a relatively quiescent tissue. Yet, prostate epithelium overgrowth is a common condition during aging, associated with urinary dysfunction and tumorigenesis. For over thirty years, TGF-ß ligands have been known to induce cytostasis in a variety of epithelia, but the intracellular pathway mediating this signal in the prostate, and its relevance for quiescence, have remained elusive. Here, using mouse prostate organoids to model epithelial progenitors, we find that intra-epithelial non-canonical Activin A signaling inhibits cell proliferation in a Smad-independent manner. Mechanistically, Activin A triggers Tak1 and p38 ΜAPK activity, leading to p16 and p21 nuclear import. Spontaneous evasion from this quiescent state occurs upon prolonged culture, due to reduced Activin A secretion, a condition associated with DNA replication stress and aneuploidy. Organoids capable to escape quiescence in vitro are also able to implant with increased frequency into immunocompetent mice. This study demonstrates that non-canonical Activin A signaling safeguards epithelial quiescence in the healthy prostate, with potential implications for the understanding of cancer initiation, and the development of therapies targeting quiescent tumor progenitors.

Machine learning pipeline to analyze clinical and proteomics data: experiences on a prostate cancer case.

Proteomic-based analysis is used to identify biomarkers in blood samples and tissues. Data produced by devices such as mass spectrometry requires platforms to identify and quantify proteins (or peptides). Clinical information can be related to mass spectrometry data to identify diseases at an early stage. Machine learning techniques can be used to support physicians and biologists in studying and classifying pathologies. We present the application of machine learning techniques to define a pipeline aimed at studying and classifying proteomics data enriched using clinical information. The pipeline allows users to relate established blood biomarkers with clinical parameters and proteomics data. The proposed pipeline entails three main phases: (i) feature selection, (ii) models training, and (iii) models ensembling. We report the experience of applying such a pipeline to prostate-related diseases. Models have been trained on several biological datasets. We report experimental results about two datasets that result from the integration of clinical and mass spectrometry-based data in the contexts of serum and urine analysis. The pipeline receives input data from blood analytes, tissue samples, proteomic analysis, and urine biomarkers. It then trains different models for feature selection, classification and voting. The presented pipeline has been applied on two datasets obtained in a 2 years research project which aimed to extract hidden information from mass spectrometry, serum, and urine samples from hundreds of patients. We report results on analyzing prostate datasets serum with 143 samples, including 79 PCa and 84 BPH patients, and an urine dataset with 121 samples, including 67 PCa and 54 BPH patients. As results pipeline allowed to identify interesting peptides in the two datasets, 6 for the first one and 2 for the second one. The best model for both serum (AUC=0.87, Accuracy=0.83, F1=0.81, Sensitivity=0.84, Specificity=0.81) and urine (AUC=0.88, Accuracy=0.83, F1=0.83, Sensitivity=0.85, Specificity=0.80) datasets showed good predictive performances. We made the pipeline code available on GitHub and we are confident that it will be successfully adopted in similar clinical setups.

Evaluation of PAC and FASP Performance: DIA-Based Quantitative Proteomic Analysis.

The aim of this study was to compare filter-aided sample preparation (FASP) and protein aggregation capture (PAC) starting from a three-species protein mix (Human, Soybean and Pisum sativum) and two different starting amounts (1 and 10 µg). Peptide mixtures were analyzed by data-independent acquisition (DIA) and raw files were processed by three commonly used software: Spectronaut, MaxDIA and DIA-NN. Overall, the highest number of proteins (mean value of 5491) were identified by PAC (10 µg), while the lowest number (4855) was identified by FASP (1 µg). The latter experiment displayed the worst performance in terms of both specificity (0.73) and precision (0.24). Other tested conditions showed better diagnostic accuracy, with specificity values of 0.95-0.99 and precision values between 0.61 and 0.86. In order to provide guidance on the data analysis pipeline, the accuracy diagnostic of three software was investigated: (i) the highest sensitivity was obtained with Spectronaut (median of 0.67) highlighting the ability of Spectronaut to quantify low-abundance proteins, (ii) the best precision value was obtained by MaxDIA (median of 0.84), but with a reduced number of identifications compared to Spectronaut and DIA-NN data, and (iii) the specificity values were similar (between 0.93 and 0.99). The data are available on ProteomeXchange with the identifier PXD044349.

Development of a predictive model to distinguish prostate cancer from benign prostatic hyperplasia by integrating serum glycoproteomics and clinical variables.

BACKGROUND: Prostate Cancer (PCa) represents the second leading cause of cancer-related death in men. Prostate-specific antigen (PSA) serum testing, currently used for PCa screening, lacks the necessary sensitivity and specificity. New non-invasive diagnostic tools able to discriminate tumoral from benign conditions and aggressive (AG-PCa) from indolent forms of PCa (NAG-PCa) are required to avoid unnecessary biopsies. METHODS: In this work, 32 formerly N-glycosylated peptides were quantified by PRM (parallel reaction monitoring) in 163 serum samples (79 from PCa patients and 84 from individuals affected by benign prostatic hyperplasia (BPH)) in two technical replicates. These potential biomarker candidates were prioritized through a multi-stage biomarker discovery pipeline articulated in: discovery, LC-PRM assay development and verification phases. Because of the well-established involvement of glycoproteins in cancer development and progression, the proteomic analysis was focused on glycoproteins enriched by TiO2 (titanium dioxide) strategy. RESULTS: Machine learning algorithms have been applied to the combined matrix comprising proteomic and clinical variables, resulting in a predictive model based on six proteomic variables (RNASE1, LAMP2, LUM, MASP1, NCAM1, GPLD1) and five clinical variables (prostate dimension, proPSA, free-PSA, total-PSA, free/total-PSA) able to distinguish PCa from BPH with an area under the Receiver Operating Characteristic (ROC) curve of 0.93. This model outperformed PSA alone which, on the same sample set, was able to discriminate PCa from BPH with an AUC of 0.79. To improve the clinical managing of PCa patients, an explorative small-scale analysis (79 samples) aimed at distinguishing AG-PCa from NAG-PCa was conducted. A predictor of PCa aggressiveness based on the combination of 7 proteomic variables (FCN3, LGALS3BP, AZU1, C6, LAMB1, CHL1, POSTN) and proPSA was developed (AUC of 0.69). CONCLUSIONS: To address the impelling need of more sensitive and specific serum diagnostic tests, a predictive model combining proteomic and clinical variables was developed. A preliminary evaluation to build a new tool able to discriminate aggressive presentations of PCa from tumors with benign behavior was exploited. This predictor displayed moderate performances, but no conclusions can be drawn due to the limited number of the sample cohort. Data are available via ProteomeXchange with identifier PXD035935.

2H-chromene and 7H-furo-chromene derivatives selectively inhibit tumour associated human carbonic anhydrase IX and XII isoforms.

Tumour associated carbonic anhydrases (CAs) IX and XII have been recognised as potential targets for the treatment of hypoxic tumours. Therefore, considering the high pharmacological potential of the chromene scaffold as selective ligand of the IX and XII isoforms, two libraries of compounds, namely 2H-chromene and 7H-furo-chromene derivatives, with diverse substitution patterns were designed and synthesised. The structure of the newly synthesised compounds was characterised and their inhibitory potency and selectivity towards human CA off target isoforms I, II and cancer-associated CA isoforms IX and XII were evaluated. Most of the compounds inhibit CA isoforms IX and XII with no activity against the I and II isozymes. Thus, while the potency was influenced by the substitution pattern along the chromene scaffold, the selectivity was conserved along the series, confirming the high potential of both 2H-chromene and 7H-furo-chromene scaffolds for the design of isozyme selective inhibitors.

Forensic Proteomics for the Discovery of New post mortem Interval Biomarkers: A Preliminary Study.

Estimating the time since death (post mortem interval, PMI) represents one of the most important tasks in daily forensic casework. For decades, forensic scientists have investigated changes in post mortem body composition, focusing on different physical, chemical, or biological aspects, to discover a reliable method for estimating PMI; nevertheless, all of these attempts remain unsuccessful considering the currently available methodical spectrum characterized by great inaccuracies and limitations. However, recent promising approaches focus on the post mortem decomposition of biomolecules. In particular, significant advances have been made in research on the post mortem degradation of proteins. In the present study, we investigated early post mortem changes (during the first 24 h) in the proteome profile of the pig skeletal muscle looking for new PMI specific biomarkers. By mass spectrometry (MS)-based proteomics, we were able to identify a total of nine potential PMI biomarkers, whose quantity changed constantly and progressively over time, directly or inversely proportional to the advancement of post mortem hours. Our preliminary study underlines the importance of the proteomic approach in the search for a reliable method for PMI determination and highlights the need to characterize a large number of reliable marker proteins useful in forensic practice for PMI estimation.

Proteomic analysis from skin swabs reveals a new set of proteins identifying skin impairment in atopic dermatitis.

Atopic Dermatitis (AD) is a common inflammatory skin disease characterized by skin and systemic inflammation, and barrier dysfunction. Herein, we investigate the proteomic profile of AD skin barrier to identify a unique signature with an easy-performed sampling approach. We enrolled 8 moderate-to-severe AD patients and 8 age- and gender-matched healthy controls. Swabs were obtained from non-lesional skin of retroauricular area and antecubital fold. Peptide mixtures obtained through protein precipitation and in-solution digestion were analysed using NanoLC-MS/MS. Label-free quantification and statistical analysis were conducted in MaxQuant and Perseus. Bioinformatics analysis was performed using Gene Ontology and STRING. We identified 908 proteins and 35 differentially expressed proteins were selected (fold change 2, FDR < 0.05). Particularly, AD skin showed downregulation of skin hydration factors, structural and epidermal proteins, abnormalities in protease-proteasome complex and lipid metabolism profile. Imbalance of antioxidant and inflammatory processes, along with TDRD15 upregulation was also observed. Our result showed partial overlap with skin biopsy/tape-strips studies, showing the reliability of our sampling approach which could be an easier method of detection of hallmark barrier proteins in AD. Furthermore, we displayed a new differentially expressed set of proteins, not yet explored in AD which can have a potential role in AD pathomechanisms.

Mass Spectrometry-Based Glycoproteomics and Prostate Cancer.

Aberrant glycosylation has long been known to be associated with cancer, since it is involved in key mechanisms such as tumour onset, development and progression. This review will focus on protein glycosylation studies in cells, tissue, urine and serum in the context of prostate cancer. A dedicated section will cover the glycoforms of prostate specific antigen, the molecule that, despite some important limitations, is routinely tested for helping prostate cancer diagnosis. Our aim is to provide readers with an overview of mass spectrometry-based glycoproteomics of prostate cancer. From this perspective, the first part of this review will illustrate the main strategies for glycopeptide enrichment and mass spectrometric analysis. The molecular information obtained by glycoproteomic analysis performed by mass spectrometry has led to new insights into the mechanism linking aberrant glycosylation to cancer cell proliferation, migration and immunoescape.

Comprehensive proteogenomic analysis of human embryonic and induced pluripotent stem cells.

Although the concepts of somatic cell reprogramming and human-induced pluripotent stem cells (hiPSCs) generation have undergone several analyses to validate the usefulness of these cells in research and clinic, it remains still controversial whether the hiPSCs are equivalent to human embryonic stem cells (hESCs), pointing to the need of further characterization for a more comprehensive understanding of pluripotency. Most of the experimental evidence comes from the transcriptome analysis, while a little is available on protein data, and even less is known about the post-translational modifications. Here, we report a combined strategy of mass spectrometry and gene expression profiling for proteogenomic analysis of reprogrammed and embryonic stem cells. The data obtained through this integrated, multi-"omics" approach indicate that a small, but still significant, number of distinct pathways is enriched in reprogrammed versus embryonic stem cells, supporting the view that pluripotency is an extremely complex, multifaceted phenomenon, with peculiarities that are characteristic of each cell type.

High-throughput detection of low abundance sialylated glycoproteins in human serum by TiO2 enrichment and targeted LC-MS/MS analysis: application to a prostate cancer sample set.

Glycopeptide enrichment can be a strategy to allow the detection of peptides belonging to low abundance proteins in complex matrixes such as blood serum or plasma. Though several glycopeptide enrichment protocols have shown excellent sensitivities in this respect, few reports have demonstrated the applicability of these methods to relatively large sample cohorts. In this work, a fast protocol based on TiO2 enrichment and highly sensitive mass spectrometric analysis by Selected Reaction Monitoring (SRM) has been applied to a cohort of serum samples from prostate cancer and benign prostatic hyperplasia patients in order to detect low abundance proteins in a single LC-MS/MS analysis in nanoscale format, without immunodepletion or peptide fractionation. A peptide library of over 700 formerly N-glycosylated peptides was created by data dependent analysis. Then, 16 medium to low abundance proteins were selected for detection by single injection LC-MS/MS based on selected-reaction monitoring. Results demonstrated the consistent detection of the low-level proteins under investigation. Following label-free quantification, four proteins (Adipocyte plasma membrane-associated protein, Periostin, Cathepsin D and Lysosome-associated membrane glycoprotein 2) were found significantly increased in prostate cancer sera compared to the control group. Graphical abstract ᅟ.

Secretome Analysis of Hypoxia-Induced 3T3-L1 Adipocytes Uncovers Novel Proteins Potentially Involved in Obesity.

In the obese state, as adipose tissue expands, adipocytes become hypoxic and dysfunctional, leading to changes in the pattern of adipocyte-secreted proteins. To better understand the role of hypoxia in the mechanisms linked to obesity, we comparatively analyzed the secretome of murine differentiated 3T3-L1 adipocytes exposed to normoxia or hypoxia for 24 h. Proteins secreted into the culture media were precipitated by trichloroacetic acid and then digested with trypsin. The peptides were labeled with dimethyl labeling and analyzed by reversed phase nanoscale liquid chromatography coupled to a quadrupole Orbitrap mass spectrometer. From a total of 1508 identified proteins, 109 were differentially regulated, of which 108 were genuinely secreted. Factors significantly downregulated in hypoxic conditions included adiponectin, a known adipokine implicated in metabolic processes, as well as thrombospondin-1 and -2, and matrix metalloproteinase-11, all multifunctional proteins involved in extracellular matrix (ECM) homeostasis. Findings were validated by Western blot analysis. Expression studies of the relative genes were performed in parallel experiments in vitro, in differentiated 3T3-L1 adipocytes, and in vivo, in fat tissues from obese versus lean mice. Our observations are compatible with the concept that hypoxia may be an early trigger for both adipose cell dysfunction and ECM remodeling.

Proteomic analysis of protein purified derivative of Mycobacterium bovis.

BACKGROUND: Tuberculin skin test based on in vivo intradermal inoculation of purified protein derivative from Mycobacterium bovis (bPPD) is the diagnostic test for the control and surveillance of bovine tuberculosis (bTB). METHODS: Proteomic analysis was performed on different bPPD preparations from M. bovis, strain AN5. Proteins were precipitated from bPPD solutions by TCA precipitation. The proteome of bPPD preparations was investigated by bottom-up proteomics, which consisted in protein digestion and nano-LC-MS/MS analysis. Mass spectrometry analysis was performed on a Q-exactive hybrid quadrupole-Orbitrap mass spectrometer coupled online to an Easy nano-LC1000 system. RESULTS: Three hundred and fifty-six proteins were identified and quantified by at least 2 peptides (99% confidence per peptide). One hundred and ninety-eight proteins, which had not been previously described, were detected; furthermore, the proteomic profile shared 80 proteins with previous proteomes from bPPDs from the United Kingdom and Brazil and 139 protein components from bPPD from Korea. Locus name of M. bovis (Mb) with orthologs from M. tuberculosis H37Rv, comparative gene and protein length, molecular mass, functional categories, gene name and function of each protein were reported. Ninety-two T cell mycobacterial antigens responsible for delayed-type hypersensitivity were detected, fifty-two of which were not previously reported in any bPPD proteome. Data are available via ProteomeXchange with identifier PXD005920. CONCLUSIONS: This study represents the highest proteome coverage of bPPD preparations to date. Since proteins perform cellular functions essential to health and/or disease, obtaining knowledge of their presence and variance is of great importance in understanding disease states and for advancing translational studies. Therefore, to better understand Mycobacterium tuberculosis complex biology during infection, survival, and persistence, the reproducible evaluation of the proteins that catalyze and control these processes is critically important. More active and more specific tuberculins would be desirable. Indeed, many antigens contained within bPPD are currently responsible for the cross-reactivity resulting in false-positive results as they are shared between non-tuberculous and tuberculous mycobacteria.

An optimized procedure for on-tissue localized protein digestion and quantification using hydrogel discs and isobaric mass tags: analysis of cardiac myxoma.

An optimized workflow for multiplexed and spatially localized on-tissue quantitative protein analysis is here presented. The method is based on the use of an enzyme delivery platform, a polymeric hydrogel disc, allowing for a localized digestion directly onto the tissue surface coupled with an isobaric mass tag strategy for peptide labeling and relative quantification. The digestion occurs within such hydrogels, followed by peptide solvent extraction and identification by liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-MS/MS). Since this is a histology-directed on-tissue analysis, multiple hydrogels were placed onto morphologically and spatially different regions of interest (ROIs) within the tissue surface, e.g., cardiac myxoma tumor vascularized region and the adjacent hypocellular area. After a microwave digestion step (2 min), enzymatically cleaved peptides were labeled using TMT reagents with isobaric mass tags, enabling analysis of multiple samples per experiment. Thus, N = 8 hydrogel-digested samples from cardiac myxoma serial tissue sections (N = 4 from the vascularized ROIs and N = 4 from the adjacent hypocellular areas) were processed and then combined before a single LC-MS/MS analysis. Regulated proteins from both cardiac myxoma regions were assayed in a single experiment. Graphical abstract The workflow for histology-guided on-tissue localized protein digestion followed by isobaric mass tagging and LC-MS/MS analysis for proteins quantification is here summarized.

Evidence of Altered Glycosylation of Serum Proteins Prior to Pancreatic Cancer Diagnosis.

Biomarkers for the early detection of pancreatic cancer are urgently needed. The aim of this pilot study was to evaluate changes in serum N-glycoproteins and their glycosylation status prior to clinical presentation of pancreatic cancer that may be potential biomarkers. Prediagnosis serum samples pooled according to five time-to-diagnosis groups and a non-cancer control pool were digested with trypsin, labelled with mass tags, and subjected to titanium dioxide capture, deglycosylation, and 2D-LC-MS/MS profiling. Unbound peptides were profiled in parallel. Across the sample groups, 703 proteins were quantified and 426 putative sites of N-glycosylation were identified with evidence of several novel sites. Altered proteins with biomarker potential were predominantly abundant inflammatory response, coagulation, and immune-related proteins. Whilst glycopeptide profiles largely paralleled those of their parent proteins, there was evidence of altered N-glycosylation site occupancy or sialic acid content prior to diagnosis for some proteins, most notably of immunoglobulin gamma chains. α-1-Antitrypsin was tested as a biomarker, but found not to complement carbohydrate antigen 19-9 (CA19-9) in early detection of cancer. In conclusion, we provide preliminary evidence of altered glycosylation of several serum proteins prior to pancreatic cancer diagnosis, warranting further investigation of these proteins as early biomarkers. These changes may be largely driven by inflammatory processes that occur in response to tumour formation and progression.

Temperature-dependent regulation of the Ochrobactrum anthropi proteome.

Ochrobactrum anthropi is a Gram-negative rod belonging to the Brucellaceae family, able to colonize a variety of environments, and actually reported as a human opportunistic pathogen. Despite its low virulence, the bacterium causes a growing number of hospital-acquired infections mainly, but not exclusively, in immunocompromised patients. The aim of this study was to obtain an overview of the global proteome changes occurring in O. anthropi in response to different growth temperatures, in order to achieve a major understanding of the mechanisms by which the bacterium adapts to different habitats and to identify some potential virulence factors. Combined quantitative mass spectrometry-based proteomics and bioinformatics approaches were carried out on two O. anthropi strains grown at temperatures miming soil/plants habitat (25°C) and human host environment (37°C), respectively. Proteomic analysis led to the identification of over 150 differentially expressed proteins in both strains, out of over 1200 total protein identifications. Among them, proteins responsible for heat shock response (DnaK, GrpE), motility (FliC, FlgG, FlgE), and putative virulence factors (TolB) were identified. The study represents the first quantitative proteomic analysis of O. anthropi performed by high-resolution quantitative mass spectrometry.

CRL3IBTK Regulates the Tumor Suppressor Pdcd4 through Ubiquitylation Coupled to Proteasomal Degradation.

The human inhibitor of Bruton's tyrosine kinase isoform α (IBtkα) is a BTB protein encoded by the IBTK gene, which maps to chromosomal locus 6q14.1, a mutational hot spot in lymphoproliferative disorders. Here, we demonstrate that IBtkα forms a CRL3(IBTK) complex promoting its self-ubiquitylation. We identified the tumor suppressor Pdcd4 as IBtkα interactor and ubiquitylation substrate of CRL3(IBTK) for proteasomal degradation. Serum-induced degradation of Pdcd4 required both IBtkα and Cul3, indicating that CRL3(IBTK) regulated the Pdcd4 stability in serum signaling. By promoting Pdcd4 degradation, IBtkα counteracted the suppressive effect of Pdcd4 on translation of reporter luciferase mRNAs with stem-loop structured or unstructured 5'-UTR. IBtkα depletion by RNAi caused Pdcd4 accumulation and decreased the translation of Bcl-xL mRNA, a well known target of Pdcd4 repression. By characterizing CRL3(IBTK) as a novel ubiquitin ligase, this study provides new insights into regulatory mechanisms of cellular pathways, such as the Pdcd4-dependent translation of mRNAs.

Proteome Speciation by Mass Spectrometry: Characterization of Composite Protein Mixtures in Milk Replacers.

The ability of tandem mass spectrometry to determine the primary structure of proteolytic peptides can be exploited to trace back the organisms from which the corresponding proteins were extracted. This information can be important when food products, such as protein powders, can be supplemented with lower-quality starting materials. In order to dissect the origin of proteinaceous material composing a given unknown mixture, a two-step database search strategy for bottom-up nanoscale liquid chromatography-tandem mass spectrometry (nanoLC-MS/MS) data was implemented. A single nanoLC-MS/MS analysis was sufficient not only to determine the qualitative composition of the mixtures under examination, but also to assess the relative percent composition of the various proteomes, if dedicated calibration curves were previously generated. The approach of two-step database search for qualitative analysis and proteome total ion current (pTIC) calculation for quantitative analysis was applied to several binary and ternary mixtures which mimic the composition of milk replacers typically used in calf feeding.

Validation of a novel shotgun proteomic workflow for the discovery of protein-protein interactions: focus on ZNF521.

The study of protein-protein interactions is increasingly relying on mass spectrometry (MS). The classical approach of separating immunoprecipitated proteins by SDS-PAGE followed by in-gel digestion is long and labor-intensive. Besides, it is difficult to integrate it with most quantitative MS-based workflows, except for stable isotopic labeling of amino acids in cell culture (SILAC). This work describes a fast, flexible and quantitative workflow for the discovery of novel protein-protein interactions. A cleavable cross-linker, dithiobis[succinimidyl propionate] (DSP), is utilized to stabilize protein complexes before immunoprecipitation. Protein complex detachment from the antibody is achieved by limited proteolysis. Finally, protein quantitation is performed via (18)O labeling. The workflow has been optimized concerning (i) DSP concentration and (ii) incubation times for limited proteolysis, using the stem cell-associated transcription cofactor ZNF521 as a model target. The interaction of ZNF521 with the core components of the nuclear remodelling and histone deacetylase (NuRD) complex, already reported in the literature, was confirmed. Additionally, interactions with newly discovered molecular partners of potentially relevant functional role, such as ZNF423, Spt16, Spt5, were discovered and validated by Western blotting.

N-glycoprotein analysis discovers new up-regulated glycoproteins in colorectal cancer tissue.

Colorectal cancer is one of the leading causes of death due to cancer worldwide. Therefore, the identification of high-specificity and -sensitivity biomarkers for the early detection of colorectal cancer is urgently needed. Post-translational modifications, such as glycosylation, are known to play an important role in cancer progression. In the present work, we used a quantitative proteomic technique based on (18)O stable isotope labeling to identify differentially expressed N-linked glycoproteins in colorectal cancer tissue samples compared with healthy colorectal tissue from 19 patients undergoing colorectal cancer surgery. We identified 54 up-regulated glycoproteins in colorectal cancer samples, therefore potentially involved in the biological processes of tumorigenesis. In particular, nine of these (PLOD2, DPEP1, SE1L1, CD82, PAR1, PLOD3, S12A2, LAMP3, OLFM4) were found to be up-regulated in the great majority of the cohort, and, interestingly, the association with colorectal cancer of four (PLOD2, S12A2, PLOD3, CD82) has not been hitherto described.