Dysregulated iron homeostasis is strongly associated with multiorgan failure and early mortality in acute-on-chronic liver failure.

UNLABELLED: Acute-on-chronic liver failure (ACLF) is an ailment with high incidence of multiorgan failure (MOF) and consequent mortality. Dysregulated iron homeostasis and macrophage dysfunction are linked to increased incidence of MOF. We investigated whether a panel of circulating iron-regulating proteins are associated with development of MOF and can predict 15- or 30-day mortality in ACLF patients. One hundred twenty patients with ACLF, 20 patients with compensated cirrhosis, and 20 healthy controls were studied. Relative protein expression profiling was performed in the derivative cohort and confirmed in the validation cohort. A panel of iron regulators and indices were determined. Multiparametric flow cytometry for quantitation of labile iron pool (LIP) was performed. Validation studies confirmed lower serum transferrin (Tf) and ceruloplasmin levels in ACLF and ACLF-MOF, compared to patients with cirrhosis and controls (P < 0.01). Serum iron and ferritin levels were markedly elevated (P < 0.001; P < 0.05) and hepcidin levels were lower (P < 0.001) in ACLF patients with MOF than those without and other groups (P < 0.001). Percentage Tf saturation (%SAT) was higher in ACLF-MOF (39.2%; P < 0.001) and correlated with poor outcome (hazard ratio: 6.970; P < 0.01). Intracellular LIP indices were significantly elevated in the subsets of circulating macrophages in ACLF-MOF, compared to other groups (P < 0.01). Whereas expression of iron-regulatory genes was markedly down-regulated, genes related to endoplasmic reticulum stress, apoptosis, and inflammation were up-regulated in ACLF patients, compared to patients with cirrhosis. Severe dysregulation of autophagy mechanisms was also observed in the former. CONCLUSIONS: Iron metabolism and transport are severely deranged in ACLF patients and more so in those with MOF. %SAT, circulating hepcidin, and LIP in macrophages correlate with disease severity and %SAT could be used for early prognostication in ACLF patients.

Neglected tropical diseases and omics science: proteogenomics analysis of the promastigote stage of Leishmania major parasite.

Among the neglected tropical diseases, leishmaniasis is one of the most devastating, resulting in significant mortality and contributing to nearly 2 million disability-adjusted life years. Cutaneous leishmaniasis is a debilitating disorder caused by the kinetoplastid protozoan parasite Leishmania major, which results in disfiguration and scars. L. major genome was the first to be sequenced within the genus Leishmania. Use of proteomic data for annotating genomes is a complementary approach to conventional genome annotation approaches and is referred to as proteogenomics. We have used a proteogenomics-based approach to map the proteome of L. major and also annotate its genome. In this study, we searched L. major promastigote proteomic data against the annotated L. major protein database. Additionally, we searched the proteomic data against six-frame translated L. major genome. In all, we identified 3613 proteins in L. major promastigotes, which covered 43% of its proteome. We also identified 26 genome search-specific peptides, which led to the identification of three novel genes previously not identified in L. major. We also corrected the annotation of N-termini of 15 genes, which resulted in extension of their protein products. We have validated our proteogenomics findings by RT-PCR and sequencing. In addition, our study resulted in identification of 266 N-terminally acetylated peptides in L. major, one of the largest acetylated peptide datasets thus far in Leishmania. This dataset should be a valuable resource to researchers focusing on neglected tropical diseases.

Moving from unsequenced to sequenced genome: reanalysis of the proteome of Leishmania donovani.

The kinetoplastid protozoan parasite, Leishmania donovani, is the causative agent of kala azar or visceral leishmaniasis. Kala azar is a severe form of leishmaniasis that is fatal in the majority of untreated cases. Studies on proteomic analysis of L. donovani thus far have been carried out using homology-based identification based on related Leishmania species (L. infantum, L. major and L. braziliensis) whose genomes have been sequenced. Recently, the genome of L. donovani was fully sequenced and the data became publicly available. We took advantage of the availability of its genomic sequence to carry out a more accurate proteogenomic analysis of L. donovani proteome using our previously generated dataset. This resulted in identification of 17,504 unique peptides upon database-dependent search against the annotated proteins in L. donovani. These peptides were assigned to 3999 unique proteins in L. donovani. 2296 proteins were identified in both the life stages of L. donovani, while 613 and 1090 proteins were identified only from amastigote and promastigote stages, respectively. The proteomic data was also searched against six-frame translated L. donovani genome, which led to 255 genome search-specific peptides (GSSPs) resulting in identification of 20 novel genes and correction of 40 existing gene models in L. donovani. BIOLOGICAL SIGNIFICANCE: Leishmania donovani genome sequencing was recently completed, which permitted us to use a proteogenomic approach to map its proteome and to carry out annotation of it genome. This resulted in mapping of 50% (3999 proteins) of L. donovani proteome. Our study identified 20 novel genes previously not predicted from the L. donovani genome in addition to correcting annotations of 40 existing gene models. The identified proteins may help in better understanding of stage-specific protein expression profiles in L. donovani and to identify novel stage-specific drug targets in L. donovani which could be used in the treatment of leishmaniasis. This article is part of a Special Issue entitled: Trends in Microbial Proteomics.

Phosphoproteome of Cryptococcus neoformans.

Cryptococcus neoformans is an encapsulated pathogenic yeast, which causes life threatening meningitis in immunocompromised individuals. C. neoformans var. grubii is the most prevalent and virulent form among the two varieties of C. neoformans - C. neoformans var. grubii and C. neoformans var. neoformans. The virulence of C. neoformans is mainly conferred by its capsule and melanin. cAMP dependent PKA-induced phosphorylation events are reported to be associated with the expression of these virulence traits, which highlights the importance of phosphoproteins in virulence and infection. Therefore, we performed global profiling of phosphoproteome of C. neoformans to enable a better understanding of molecular regulation of its virulence and pathogenesis. High resolution mass spectrometry of TiO2 enriched phosphopeptides from C. neoformans var. grubii grown in culture led to the identification of 1089 phosphopeptides derived from 648 proteins including about 45 kinases. Motif enrichment analysis revealed that most CDK family substrates were found to be phosphorylated. This indicates that cyclin-dependent kinases were among the active kinases in the pathogen in culture. These studies provide a framework for understanding virulence mechanisms in the context of signalling pathways in pathogenic yeast. This article is part of a Special Issue entitled: Trends in Microbial Proteomics. BIOLOGICAL SIGNIFICANCE: C. neoformans is a pathogenic yeast responsible for cryptococcal meningitis. Melanin and polysaccharide capsule have been established as some of the key virulence factors that play a major role in the pathogenesis of C. neoformans. Recent studies have shown the role of kinase mediated signalling pathways in governing biosynthesis of these virulence factors. This study revealed 1540 phosphorylation sites in 648 proteins providing a comprehensive view of phosphoproteins in C. neoformans. This should serve as a useful resource to explore activated signalling pathways in C. neoformans and their association with its virulence and pathogenesis.

Plasma Proteome Database as a resource for proteomics research: 2014 update.

Plasma Proteome Database (PPD; http://www.plasmaproteomedatabase.org/) was initially described in the year 2005 as a part of Human Proteome Organization's (HUPO's) pilot initiative on Human Plasma Proteome Project. Since then, improvements in proteomic technologies and increased throughput have led to identification of a large number of novel plasma proteins. To keep up with this increase in data, we have significantly enriched the proteomic information in PPD. This database currently contains information on 10,546 proteins detected in serum/plasma of which 3784 have been reported in two or more studies. The latest version of the database also incorporates mass spectrometry-derived data including experimentally verified proteotypic peptides used for multiple reaction monitoring assays. Other novel features include published plasma/serum concentrations for 1278 proteins along with a separate category of plasma-derived extracellular vesicle proteins. As plasma proteins have become a major thrust in the field of biomarkers, we have enabled a batch-based query designated Plasma Proteome Explorer, which will permit the users in screening a list of proteins or peptides against known plasma proteins to assess novelty of their data set. We believe that PPD will facilitate both clinical and basic research by serving as a comprehensive reference of plasma proteins in humans and accelerate biomarker discovery and translation efforts.

Proteomic profiling of serum samples from chikungunya-infected patients provides insights into host response.

BACKGROUND: Chikungunya is a highly debilitating febrile illness caused by Chikungunya virus, a single-stranded RNA virus, which is transmitted by Aedes aegypti or Aedes albopictus mosquito species. The pathogenesis and host responses in individuals infected with the chikungunya virus are not well understood at the molecular level. We carried out proteomic profiling of serum samples from chikungunya patients in order to identify molecules associated with the host response to infection by this virus. RESULTS: Proteomic profiling of serum obtained from the infected individuals resulted in identification of 569 proteins. Of these, 63 proteins were found to be differentially expressed (≥ 2-fold) in patient as compared to control sera. These differentially expressed proteins were involved in various processes such as lipid metabolism, immune response, transport, signal transduction and apoptosis. CONCLUSIONS: This is the first report providing a global proteomic profile of serum samples from individuals infected with the chikungunya virus. Our data provide an insight into the proteins that are involved as host response factors during an infection. These proteins include clusterin, apolipoproteins and S100A family of proteins.

A multilectin affinity approach for comparative glycoprotein profiling of rheumatoid arthritis and spondyloarthropathy.

BACKGROUND: Arthritis refers to inflammation of joints and includes common disorders such as rheumatoid arthritis (RA) and spondyloarthropathies (SpAs). These diseases differ mainly in terms of their clinical manifestations and the underlying pathogenesis. Glycoproteins in synovial fluid might reflect the disease activity status in the joints affected by arthritis; yet they have not been systematically studied previously. Although markers have been described for assisting in the diagnosis of RA, there are currently no known biomarkers for SpA. MATERIALS AND METHODS: We sought to determine the relative abundance of glycoproteins in RA and SpA by lectin affinity chromatography coupled to iTRAQ labeling and LC-MS/MS analysis. We also used ELISA to validate the overexpression of VCAM-1, one of the candidate proteins identified in this study, in synovial fluid from RA patients. RESULTS AND DISCUSSION: We identified proteins that were previously reported to be overexpressed in RA including metalloproteinase inhibitor 1 (TIMP1), myeloperoxidase (MPO) and several S100 proteins. In addition, we discovered several novel candidates that were overexpressed in SpA including Apolipoproteins C-II and C-III and the SUN domain-containing protein 3 (SUN3). Novel molecules found overexpressed in RA included extracellular matrix protein 1 (ECM1) and lumican (LUM). We validated one of the candidate biomarkers, vascular cell adhesion molecule 1 (VCAM1), in 20 RA and SpA samples using ELISA and confirmed its overexpression in RA (p-value <0.01). Our quantitative glycoproteomic approach to study arthritic disorders should open up new avenues for additional proteomics-based discovery studies in rheumatological disorders.

Characterizing the normal proteome of human ciliary body.

BACKGROUND: The ciliary body is the circumferential muscular tissue located just behind the iris in the anterior chamber of the eye. It plays a pivotal role in the production of aqueous humor, maintenance of the lens zonules and accommodation by changing the shape of the crystalline lens. The ciliary body is the major target of drugs against glaucoma as its inhibition leads to a drop in intraocular pressure. A molecular study of the ciliary body could provide a better understanding about the pathophysiological processes that occur in glaucoma. Thus far, no large-scale proteomic investigation has been reported for the human ciliary body. RESULTS: In this study, we have carried out an in-depth LC-MS/MS-based proteomic analysis of normal human ciliary body and have identified 2,815 proteins. We identified a number of proteins that were previously not described in the ciliary body including importin 5 (IPO5), atlastin-2 (ATL2), B-cell receptor associated protein 29 (BCAP29), basigin (BSG), calpain-1 (CAPN1), copine 6 (CPNE6), fibulin 1 (FBLN1) and galectin 1 (LGALS1). We compared the plasma proteome with the ciliary body proteome and found that the large majority of proteins in the ciliary body were also detectable in the plasma while 896 proteins were unique to the ciliary body. We also classified proteins using pathway enrichment analysis and found most of proteins associated with ubiquitin pathway, EIF2 signaling, glycolysis and gluconeogenesis. CONCLUSIONS: More than 95% of the identified proteins have not been previously described in the ciliary body proteome. This is the largest catalogue of proteins reported thus far in the ciliary body that should provide new insights into our understanding of the factors involved in maintaining the secretion of aqueous humor. The identification of these proteins will aid in understanding various eye diseases of the anterior segment such as glaucoma and presbyopia.

Heterogeneous nuclear ribonucleoproteins and their interactors are a major class of deregulated proteins in anaplastic astrocytoma: a grade III malignant glioma.

Anaplastic astrocytoma is a high grade malignant glioma (WHO grade III) of the central nervous system which arises from a low grade II tumor and invariably progresses into lethal glioblastoma (WHO grade IV). We have studied differentially expressed proteins from the microsomal fraction of the clinical specimens of these tumors, using iTRAQ and high-resolution mass spectrometry followed by immunohistochemistry for representative proteins on tissue sections. A total of 2642 proteins were identified, 266 of them with minimum 2 peptide signatures and 2-fold change in expression. The major groups of proteins revealed to be differentially expressed were associated with key cellular processes such as post transcriptional processing, protein translation, and acute phase response signaling. A distinct inclusion among these important proteins is 10 heterogeneous nuclear ribonucleoproteins (hnRNPs) and their interacting partners which have regulatory functions in the cell. hnRNP-mediated post transcriptional events are known to play a major role in mRNA processing, stability, and distribution. Their altered levels have also been observed by us in lower (diffused astrocytoma) and higher (glioblastoma) grades of gliomas, and membrane localization of hnRNPs has also been documented in the literature. hnRNPs may thus be major factors underlying global gene expression changes observed in glial tumors while their differential presence in the microsomal fraction suggests yet additional and unknown roles in tumorigenesis.

A compendium of molecules involved in vector-pathogen interactions pertaining to malaria.

Malaria is a vector-borne disease causing extensive morbidity, debility and mortality. Development of resistance to drugs among parasites and to conventional insecticides among vector-mosquitoes necessitates innovative measures to combat this disease. Identification of molecules involved in the maintenance of complex developmental cycles of the parasites within the vector and the host can provide attractive targets to intervene in the disease transmission. In the last decade, several efforts have been made in identifying such molecules involved in mosquito-parasite interactions and, subsequently, validating their role in the development of parasites within the vector. In this study, a list of mosquito proteins, which facilitate or inhibit the development of malaria parasites in the midgut, haemolymph and salivary glands of mosquitoes, is compiled. A total of 94 molecules have been reported and validated for their role in the development of malaria parasites inside the vector. This compendium of molecules will serve as a centralized resource to biomedical researchers investigating vector-pathogen interactions and malaria transmission.

Identification of head and neck squamous cell carcinoma biomarker candidates through proteomic analysis of cancer cell secretome.

Protein biomarker discovery for early detection of head and neck squamous cell carcinoma (HNSCC) is a crucial unmet need to improve patient outcomes. Mass spectrometry-based proteomics has emerged as a promising tool for identification of biomarkers in different cancer types. Proteins secreted from cancer cells can serve as potential biomarkers for early diagnosis. In the current study, we have used isobaric tag for relative and absolute quantitation (iTRAQ) labeling methodology coupled with high resolution mass spectrometry to identify and quantitate secreted proteins from a panel of head and neck carcinoma cell lines. In all, we identified 2,472 proteins, of which 225 proteins were secreted at higher or lower abundance in HNSCC-derived cell lines. Of these, 148 were present in higher abundance and 77 were present in lower abundance in the cancer-cell derived secretome. We detected a higher abundance of some previously known markers for HNSCC including insulin like growth factor binding protein 3, IGFBP3 (11-fold) and opioid growth factor receptor, OGFR (10-fold) demonstrating the validity of our approach. We also identified several novel secreted proteins in HNSCC including olfactomedin-4, OLFM4 (12-fold) and hepatocyte growth factor activator, HGFA (5-fold). IHC-based validation was conducted in HNSCC using tissue microarrays which revealed overexpression of IGFBP3 and OLFM4 in 70% and 75% of the tested cases, respectively. Our study illustrates quantitative proteomics of secretome as a robust approach for identification of potential HNSCC biomarkers. This article is part of a Special Issue entitled: An Updated Secretome.

IL-11/IL11RA receptor mediated signaling: a web accessible knowledgebase.

Abstract Interleukin-11 (IL-11) is a pleiotropic cytokine that belongs to gp130 family. It plays a significant role in the synthesis and maturation of hematopoietic cells, inhibition of adipogenesis, regulation of embryo implantation, and trophoblasts invasion. Although IL-11 signaling has been described in several biological processes, a centralized resource documenting these molecular reactions induced by IL-11 is not publicly available. In the current study, we have manually annotated the molecular reactions and interactions induced by IL-11 from literature available. We have documented 40 unique molecules involved in 18 protein-protein interactions, 26 enzyme-substrate reactions, 7 translocation events, and 4 activation/ inhibition reactions. We have also annotated 23 genes reported to be differentially regulated under IL-11 stimulation. We have enabled the data availability in standard exchange formats from 'NetPath', a repository for signaling pathways. We believe that this will help in the identification of potential therapeutic targets in IL-11-associated disorders.

Proteomic analysis of human follicular fluid: a new perspective towards understanding folliculogenesis.

Human follicular fluid is a complex body fluid that constitutes the microenvironment of developing follicles in the ovary. Follicular fluid contains a number of proteins that modulate oocyte maturation and ovulation. Information about the protein constituents of follicular fluid may provide a better understanding of ovarian physiology in addition to opening new avenues for investigating ovarian disorders. However, the composition of follicular fluid proteome remains poorly defined. In this study, we carried out SDS-PAGE, OFFGEL and SCX-based separation followed by LC-MS/MS analysis to characterize the proteome of human follicular fluid. We report high confidence identification of 480 proteins, of which 320 have not been described previously in the follicular fluid. The identified proteins belong to diverse functional categories including growth factor and hormones, receptor signaling, enzyme catalysis, defense/immunity and complement activity. Our dataset should serve as a resource for future studies aimed at developing biomarkers for monitoring oocyte and embryo quality, pregnancy outcomes and ovarian disorders. BIOLOGICAL SIGNIFICANCE: Proteome analysis of human follicular fluid by multi-pronged approach of protein peptide fractionation revealed 480 proteins with high confidence. The identified protein may facilitate the understanding of folliculogenesis. This protein dataset should serve as a useful resource for development of biomarkers for oocyte quality, in vitro fertilization techniques and female infertility.

Proteomic strategies to characterize signaling pathways.

Cells respond to external stimuli by transducing signals through a series of intracellular molecules and eliciting an appropriate response. The cascade of events through which the signals are transduced include post-translational modifications such as phosphorylation and ubiquitylation in addition to formation of multi-protein complexes. Improvements in biological mass spectrometry and protein/peptide microarray technology have tremendously improved our ability to probe proteins, protein complexes, and signaling pathways in a high-throughput fashion. Today, a single mass spectrometry-based investigation of a signaling pathway has the potential to uncover the large majority of known signaling intermediates painstakingly characterized over decades in addition to discovering a number of novel ones. Here, we discuss various proteomic strategies to characterize signaling pathways and provide protocols for phosphoproteomic analysis.

SILAC-based quantitative proteomic analysis of gastric cancer secretome.

PURPOSE: Gastric cancer is a commonly occurring cancer in Asia and one of the leading causes of cancer deaths. However, there is no reliable blood-based screening test for this cancer. Identifying proteins secreted from tumor cells could lead to the discovery of clinically useful biomarkers for early detection of gastric cancer. EXPERIMENTAL DESIGN: A SILAC-based quantitative proteomic approach was employed to identify secreted proteins that were differentially expressed between neoplastic and non-neoplastic gastric epithelial cells. Proteins from the secretome were subjected to SDS-PAGE and SCX-based fractionation, followed by mass spectrometric analysis on an LTQ-Orbitrap Velos mass spectrometer. Immunohistochemical labeling was employed to validate a subset of candidates using tissue microarrays. RESULTS: We identified 2205 proteins in the gastric cancer secretome of which 263 proteins were overexpressed greater than fourfold in gastric cancer-derived cell lines as compared to non-neoplastic gastric epithelial cells. Three candidate proteins, proprotein convertase subtilisin/kexin type 9 (PCSK9), lectin mannose binding 2 (LMAN2), and PDGFA-associated protein 1 (PDAP1) were validated by immunohistochemical labeling. CONCLUSIONS AND CLINICAL RELEVANCE: We report here the largest cancer secretome described to date. The novel biomarkers identified in the current study are excellent candidates for further testing as early detection biomarkers for gastric adenocarcinoma.

Vesiclepedia: a compendium for extracellular vesicles with continuous community annotation.

Extracellular vesicles (EVs) are membraneous vesicles released by a variety of cells into their microenvironment. Recent studies have elucidated the role of EVs in intercellular communication, pathogenesis, drug, vaccine and gene-vector delivery, and as possible reservoirs of biomarkers. These findings have generated immense interest, along with an exponential increase in molecular data pertaining to EVs. Here, we describe Vesiclepedia, a manually curated compendium of molecular data (lipid, RNA, and protein) identified in different classes of EVs from more than 300 independent studies published over the past several years. Even though databases are indispensable resources for the scientific community, recent studies have shown that more than 50% of the databases are not regularly updated. In addition, more than 20% of the database links are inactive. To prevent such database and link decay, we have initiated a continuous community annotation project with the active involvement of EV researchers. The EV research community can set a gold standard in data sharing with Vesiclepedia, which could evolve as a primary resource for the field.

Quantitative proteomics for identifying biomarkers for tuberculous meningitis.

INTRODUCTION: Tuberculous meningitis is a frequent extrapulmonary disease caused by Mycobacterium tuberculosis and is associated with high mortality rates and severe neurological sequelae. In an earlier study employing DNA microarrays, we had identified genes that were differentially expressed at the transcript level in human brain tissue from cases of tuberculous meningitis. In the current study, we used a quantitative proteomics approach to discover protein biomarkers for tuberculous meningitis. METHODS: To compare brain tissues from confirmed cased of tuberculous meningitis with uninfected brain tissue, we carried out quantitative protein expression profiling using iTRAQ labeling and LC-MS/MS analysis of SCX fractionated peptides on Agilent's accurate mass QTOF mass spectrometer. RESULTS AND CONCLUSIONS: Through this approach, we identified both known and novel differentially regulated molecules. Those described previously included signal-regulatory protein alpha (SIRPA) and protein disulfide isomerase family A, member 6 (PDIA6), which have been shown to be overexpressed at the mRNA level in tuberculous meningitis. The novel overexpressed proteins identified in our study included amphiphysin (AMPH) and neurofascin (NFASC) while ferritin light chain (FTL) was found to be downregulated in TBM. We validated amphiphysin, neurofascin and ferritin light chain using immunohistochemistry which confirmed their differential expression in tuberculous meningitis. Overall, our data provides insights into the host response in tuberculous meningitis at the molecular level in addition to providing candidate diagnostic biomarkers for tuberculous meningitis.

Proteins with altered levels in plasma from glioblastoma patients as revealed by iTRAQ-based quantitative proteomic analysis.

Glioblastomas (GBMs) are the most common and lethal primary tumors of the central nervous system with high level of recurrence despite aggressive therapy. Tumor-associated proteins/peptides may appear in the plasma of these patients as a result of disruption of the blood-brain barrier in them, raising the scope for development of plasma-based tests for diagnosis and monitoring the disease. With this objective, we analyzed the levels of proteins present in the plasma from GBM patients using an iTRAQ based LC-MS/MS approach. Analysis with pooled plasma specimens from the patient and healthy control samples revealed high confidence identification of 296 proteins, of which 61 exhibited a fold-change ≥1.5 in the patient group. Forty-eight of them contained signal sequence. A majority have been reported in the differentially expressed transcript or protein profile of GBM tissues; 6 have been previously studied as plasma biomarkers for GBM and 16 for other types of cancers. Altered levels of three representative proteins-ferritin light chain (FTL), S100A9, and carnosinase 1 (CNDP1)-were verified by ELISA in a test set of ten individual plasma specimens. FTL is an inflammation marker also implicated in cancer, S100A9 is an important member of the Ca(2+) signaling cascade reported to be altered in GBM tissue, and CNDP1 has been reported for its role in the regulation of the levels of carnosine, implicated as a potential drug for GBM. These and other proteins in the dataset may form useful starting points for further clinical investigations for the development of plasma-based biomarker panels for GBM.

Rapid characterization of candidate biomarkers for pancreatic cancer using cell microarrays (CMAs).

Tissue microarrays have become a valuable tool for high-throughput analysis using immunohistochemical labeling. However, the large majority of biochemical studies are carried out in cell lines to further characterize candidate biomarkers or therapeutic targets with subsequent studies in animals or using primary tissues. Thus, cell line-based microarrays could be a useful screening tool in some situations. Here, we constructed a cell microarray (CMA) containing a panel of 40 pancreatic cancer cell lines available from American Type Culture Collection in addition to those locally available at Johns Hopkins. As proof of principle, we performed immunocytochemical labeling of an epithelial cell adhesion molecule (Ep-CAM), a molecule generally expressed in the epithelium, on this pancreatic cancer CMA. In addition, selected molecules that have been previously shown to be differentially expressed in pancreatic cancer in the literature were validated. For example, we observed strong labeling of CA19-9 antigen, a prognostic and predictive marker for pancreatic cancer. We also carried out a bioinformatics analysis of a literature curated catalog of pancreatic cancer biomarkers developed previously by our group and identified two candidate biomarkers, HLA class I and transmembrane protease, serine 4 (TMPRSS4), and examined their expression in the cell lines represented on the pancreatic cancer CMAs. Our results demonstrate the utility of CMAs as a useful resource for rapid screening of molecules of interest and suggest that CMAs can become a universal standard platform in cancer research.