Mouse Organ-Specific Proteins and Functions.

Organ-specific proteins (OSPs) possess great medical potential both in clinics and in biomedical research. Applications of them-such as alanine transaminase, aspartate transaminase, and troponins-in clinics have raised certain concerns of their organ specificity. The dynamics and diversity of protein expression in heterogeneous human populations are well known, yet their effects on OSPs are less addressed. Here, we used mice as a model and implemented a breadth study to examine the panorgan proteome for potential variations in organ specificity in different genetic backgrounds. Using reasonable resources, we generated panorgan proteomes of four in-bred mouse strains. The results revealed a large diversity that was more profound among OSPs than among proteomes overall. We defined a robustness score to quantify such variation and derived three sets of OSPs with different stringencies. In the meantime, we found that the enriched biological functions of OSPs are also organ-specific and are sensitive and useful to assess the quality of OSPs. We hope our breadth study can open doors to explore the molecular diversity and dynamics of organ specificity at the protein level.

Glycocapture-assisted global quantitative proteomics (gagQP) reveals multiorgan responses in serum toxicoproteome.

Blood is an ideal window for viewing our health and disease status. Because blood circulates throughout the entire body and carries secreted, shed, and excreted signature proteins from every organ and tissue type, it is thus possible to use the blood proteome to achieve a comprehensive assessment of multiple-organ physiology and pathology. To date, the blood proteome has been frequently examined for diseases of individual organs; studies on compound insults impacting multiple organs are, however, elusive. We believe that a characterization of peripheral blood for organ-specific proteins affords a powerful strategy to allow early detection, staging, and monitoring of diseases and their treatments at a whole-body level. In this paper we test this hypothesis by examining a mouse model of acetaminophen (APAP)-induced hepatic and extra-hepatic toxicity. We used a glycocapture-assisted global quantitative proteomics (gagQP) approach to study serum proteins and validated our results using Western blot. We discovered in mouse sera both hepatic and extra-hepatic organ-specific proteins. From our validation, it was determined that selected organ-specific proteins had changed their blood concentration during the course of toxicity development and recovery. Interestingly, the peak responding time of proteins specific to different organs varied in a time-course study. The collected molecular information shed light on a complex, dynamic, yet interweaving, multiorgan-enrolled APAP toxicity. The developed technique as well as the identified protein markers is translational to human studies. We hope our work can broaden the utility of blood proteomics in diagnosis and research of the whole-body response to pathogenic cues.

Integrated expression profiling and ChIP-seq analyses of the growth inhibition response program of the androgen receptor.

BACKGROUND: The androgen receptor (AR) plays important roles in the development of male phenotype and in different human diseases including prostate cancers. The AR can act either as a promoter or a tumor suppressor depending on cell types. The AR proliferative response program has been well studied, but its prohibitive response program has not yet been thoroughly studied. METHODOLOGY/PRINCIPAL FINDINGS: Previous studies found that PC3 cells expressing the wild-type AR inhibit growth and suppress invasion. We applied expression profiling to identify the response program of PC3 cells expressing the AR (PC3-AR) under different growth conditions (i.e. with or without androgens and at different concentration of androgens) and then applied the newly developed ChIP-seq technology to identify the AR binding regions in the PC3 cancer genome. A surprising finding was that the comparison of MOCK-transfected PC3 cells with AR-transfected cells identified 3,452 differentially expressed genes (two fold cutoff) even without the addition of androgens (i.e. in ethanol control), suggesting that a ligand independent activation or extremely low-level androgen activation of the AR. ChIP-Seq analysis revealed 6,629 AR binding regions in the cancer genome of PC3 cells with an FDR (false discovery rate) cut off of 0.05. About 22.4% (638 of 2,849) can be mapped to within 2 kb of the transcription start site (TSS). Three novel AR binding motifs were identified in the AR binding regions of PC3-AR cells, and two of them share a core consensus sequence CGAGCTCTTC, which together mapped to 27.3% of AR binding regions (1,808/6,629). In contrast, only about 2.9% (190/6,629) of AR binding sites contains the canonical AR matrix M00481, M00447 and M00962 (from the Transfac database), which is derived mostly from AR proliferative responsive genes in androgen dependent cells. In addition, we identified four top ranking co-occupancy transcription factors in the AR binding regions, which include TEF1 (Transcriptional enhancer factor), GATA (GATA transcription factors), OCT (octamer transcription factors) and PU1 (PU.1 transcription factor). CONCLUSIONS/SIGNIFICANCE: Our data provide a valuable data set in understanding the molecular basis for growth inhibition response program of the AR in prostate cancer cells, which can be exploited for developing novel prostate cancer therapeutic strategies.

Quantitative proteomics analysis integrated with microarray data reveals that extracellular matrix proteins, catenins, and p53 binding protein 1 are important for chemotherapy response in ovarian cancers.

Chemotherapy with carboplatin and paclitaxel is the standard treatment for ovarian cancer patients. Although most patients initially respond to this treatment, few are cured. Resistance to chemotherapy is the major cause of treatment failure. We applied a quantitative proteomic approach based on ICAT/MS/MS technology to analyze tissues harvested at primary debulking surgery before the initiation of combination chemotherapy in order to identify potential naive or intrinsic chemotherapy response proteins in ovarian cancers. We identified 44 proteins that are overexpressed, and 34 proteins that are underexpressed in the chemosensitive tissue compared to the chemoresistant tissue. The overexpressed proteins identified in the chemoresistant tissue include 10 proteins (25.6%) belonging to the extracellular matrix (ECM), including decorin, versican, basigin (CD147), fibulin-1, extracellular matrix protein 1, biglycan, fibronectin 1, dermatopontin, alpha-cardiac actin (smooth muscle actin), and an EGF-containing fibulin-like extracellular matrix protein 1. Interesting proteins identified as overexpressed in the chemosensitive tissue include gamma-catenin (junction plakoglobin) and delta-catenin, tumor suppressor p53-binding protein 1 (53BP1), insulin-like growth factor-binding protein 2 (IGFBP2), proliferating cell nuclear antigen (PCNA), annexin A11, and 53 kDa selenium binding protein 1. Integrative analysis with expression profiling data of eight chemoresistant tissues and 13 chemosensitive tissues revealed that 16 proteins showed consistent changes at both the protein and the RNA levels. These include P53 binding protein 1, catenin delta 1 and plakoglobin, EGF-containing fibulin-like extracellular matrix protein 1 and voltage-dependent anion-selective channel protein 1. Our results suggest that chemotherapy response may be determined by multiple and complex system properties involving extracellular-matrix, cell adhesion and junction proteins.

WDR19 expression is increased in prostate cancer compared with normal cells, but low-intensity expression in cancers is associated with shorter time to biochemical failures and local recurrence.

PURPOSE: Prostate cancer is the third leading cause of cancer death in the United States, following lung and colorectal cancer. We previously identified WDR19 as a prostate-specific, androgen-regulated gene. Here, we evaluate its utility as a prostate cancer tissue marker for diagnosis and prognostic evaluation. EXPERIMENTAL DESIGN: Real-time quantitative PCR was done on a panel of prostate tissue isolated by laser capture microdissection. After generating antibodies against WDR19, tissue microarrays (TMA) were employed to compare WDR19 expression between normal, benign prostatic hyperplasia, and prostate cancer tissue. RESULTS: Using microarrays and real-time quantitative PCR, we showed that WDR19 mRNA expression was increased in cancer. We further showed that WDR19 protein is localized to cytoplasmic subcellular granules and is expressed exclusively in prostate epithelia. Large-scale immunohistochemical staining using TMAs reveals a significant percentage of increase in intensely staining tissue cores in cancer tissue when compared with normal or benign prostatic hyperplastic tissue. Based on the analysis of a separate TMA for which clinical follow-up information was available, low-intensity WDR19 staining was significantly associated with decreased time to biochemical failure (P = 0.006) and with decreased time to locoregional recurrence (P = 0.050). CONCLUSIONS: WDR19 should be added to the list of prostate cancer tissue markers. The continued expansion of a multiple-marker panel will conceivably increase the sensitivity and specificity of prostate cancer diagnosis and prognosis.

Proteomics cataloging analysis of human expressed prostatic secretions reveals rich source of biomarker candidates.

Expressed prostatic secretions (EPS) contain proteins of prostate origin that may reflect the health status of the prostate and be used as diagnostic markers for prostate diseases including prostatitis, benign prostatic hyperplasia, and prostate cancer. Despite their importance and potential applications, a complete catalog of EPS proteins is not yet available. We, therefore, undertook a comprehensive analysis of the EPS proteome using 2-D micro-LC combined with MS/MS. Using stringent filtering criteria, we identified a list of 114 proteins with at least two unique-peptide hits and an additional 75 proteins with only a single unique-peptide hit. The proteins identified include kallikrein 2 (KLK2), KLK3 (prostate-specific antigen), KLK11, and nine cluster of differentiation (CD) molecules including CD10, CD13, CD14, CD26, CD66a, CD66c, CD 143, CD177, and CD224. To our knowledge, this list represents the first comprehensive characterization of the EPS proteome, and it provides a candidate biomarker list for targeted quantitative proteomics analysis using a multiple reaction monitoring (MRM) approach. To help prioritize candidate biomarkers, we constructed a protein-protein interaction network of the EPS proteins using Cytoscape (www.cytoscape.org), and overlaid the expression level changes from the Oncomine database onto the network.

Shotgun glycopeptide capture approach coupled with mass spectrometry for comprehensive glycoproteomics.

We present a robust and general shotgun glycoproteomics approach to comprehensively profile glycoproteins in complex biological mixtures. In this approach, glycopeptides derived from glycoproteins are enriched by selective capture onto a solid support using hydrazide chemistry followed by enzymatic release of the peptides and subsequent analysis by tandem mass spectrometry. The approach was validated using standard protein mixtures that resulted in a close to 100% capture efficiency. Our capture approach was then applied to microsomal fractions of the cisplatin-resistant ovarian cancer cell line IGROV-1/CP. With a Protein Prophet probability value greater than 0.9, we identified a total of 302 proteins with an average protein identification rate of 136 +/- 19 (n = 4) in a single linear quadrupole ion trap (LTQ) mass spectrometer nano-LC-MS experiment and a selectivity of 91 +/- 1.6% (n = 4) for the N-linked glycoconsensus sequence. Our method has several advantages. 1) Digestion of proteins initially into peptides improves the solubility of large membrane proteins and exposes all of the glycosylation sites to ensure equal accessibility to capture reagents. 2) Capturing glycosylated peptides can effectively reduce sample complexity and at the same time increase the confidence of MS-based protein identifications (more potential peptide identifications per protein). 3) The utility of sodium sulfite as a quencher in our capture approach to replace the solid phase extraction step in an earlier glycoprotein chemical capture approach for removing excess sodium periodate allows the overall capture procedure to be completed in a single vessel. This improvement minimizes sample loss, increases sensitivity, and makes our protocol amenable for high throughput implementation, a feature that is essential for biomarker identification and validation of a large number of clinical samples. 4) The approach is demonstrated here on the analysis of N-linked glycopeptides; however, it can be applied equally well to O-glycoprotein analysis.

KLK31P is a novel androgen regulated and transcribed pseudogene of kallikreins that is expressed at lower levels in prostate cancer cells than in normal prostate cells.

BACKGROUND: Fifteen human tissue kallikrein (KLK) genes have been identified as a cluster on chromosome 19. KLK expression is associated with various human diseases including cancers. Noncoding RNAs such as PCA3/DD3 and PCGEM1 have been identified in prostate cancer cells. METHODS: Using massively parallel signature sequencing (MPSS) technology, RT-PCR, and 5' rapid amplification of cDNA ends (RACE), we identified and cloned a novel gene that maps to the KLK locus. RESULTS: We have characterized this gene, named as KLK31P by the HUGO Gene Nomenclature Committee, as an unprocessed KLK pseudogene. It contains five exons, two of which are KLK-derived while the rest are "exonized" interspersed repeats. KLK31P is expressed abundantly in prostate tissues and is androgen regulated. KLK31P is expressed at lower levels in localized and metastatic prostate cancer cells than in normal prostate cells. CONCLUSIONS: KLK31P is a novel androgen regulated and transcribed pseudogene of kallikreins that may play a role in prostate carcinogenesis or maintenance.

Evidence for the presence of disease-perturbed networks in prostate cancer cells by genomic and proteomic analyses: a systems approach to disease.

Prostate cancer is initially responsive to androgen ablation therapy and progresses to androgen-unresponsive states that are refractory to treatment. The mechanism of this transition is unknown. A systems approach to disease begins with the quantitative delineation of the informational elements (mRNAs and proteins) in various disease states. We employed two recently developed high-throughput technologies, massively parallel signature sequencing (MPSS) and isotope-coded affinity tag, to gain a comprehensive picture of the changes in mRNA levels and more restricted analysis of protein levels, respectively, during the transition from androgen-dependent LNCaP (model for early-stage prostate cancer) to androgen-independent CL1 cells (model for late-stage prostate cancer). We sequenced >5 million MPSS signatures, obtained >142,000 tandem mass spectra, and built comprehensive MPSS and proteomic databases. The integrated mRNA and protein expression data revealed underlying functional differences between androgen-dependent and androgen-independent prostate cancer cells. The high sensitivity of MPSS enabled us to identify virtually all of the expressed transcripts and to quantify the changes in gene expression between these two cell states, including functionally important low-abundance mRNAs, such as those encoding transcription factors and signal transduction molecules. These data enable us to map the differences onto extant physiologic networks, creating perturbation networks that reflect prostate cancer progression. We found 37 BioCarta and 14 Kyoto Encyclopedia of Genes and Genomes pathways that are up-regulated and 23 BioCarta and 22 Kyoto Encyclopedia of Genes and Genomes pathways that are down-regulated in LNCaP cells versus CL1 cells. Our efforts represent a significant step toward a systems approach to understanding prostate cancer progression.

Isolation and characterization of human and mouse WDR19,a novel WD-repeat protein exhibiting androgen-regulated expression in prostate epithelium.

Androgens regulate important processes involved in the normal development and function of the human and rodent prostate glands. Here we report the isolation and characterization of a new androgen-regulated gene, designated WDR19, that encodes repeating sequence motifs found in the WD-repeat family of proteins. The WD repeat is a conserved domain of approximately 40 amino acids that is typically bracketed by glycine-histidine and tryptophan-aspartic acid (WD) dipeptides. WD-repeat proteins are a large group of structurally related proteins that participate in a wide range of cellular functions, including transmembrane signaling, mRNA modification, vesicle formation, and vesicular trafficking. The WDR19 gene comprises 36 exons and is located on chromosome 4p15-4p11. The predicted protein contains six WD repeats, a clathrin heavy-chain repeat, and three transmembrane domains. Sequence analysis reveals that the WDR19 gene is conserved from Caenorhabditis elegans to human. WDR19 is expressed in normal and neoplastic prostate epithelium as demonstrated by RNA in situ hybridization and is regulated by androgenic hormones. WDR19 transcripts exhibit alternative splicing in which two isoforms appear to be prostate restricted, a property that could be exploited for designing diagnostic or therapeutic strategies for prostate carcinoma.

Proteomic analysis of human prostasomes.

BACKGROUND: Prostasomes are secretory particles in human seminal fluid. Other than a microscopic description of these secretory particles and an incomplete two-dimensional gel electrophoresis (2DE) study, little is known about the composition of proteins in prostasomes. METHODS: We employed a direct iterative approach using Gas phase fractionation and microcapillary HPLC-tandem mass spectrometry (microLC-MS/MS) to catalogue the prostasome proteome. RESULTS: We identified 139 proteins that can be divided into the following categories: (1). enzymes (33.8% of total), (2). transport/structural (19.4% of total), (3). GTP proteins (14.4% of total), (4). chaperone proteins (5.8% of total), (5). signal transduction proteins (17.3% of total), and (6). unannotated proteins (9.4% of total). A total of 128 of the 139 proteins have not previously been described as prostasomal. CONCLUSIONS: The proteins identified can be used as reference dataset in future work comparing prostasome proteins between normal and pathological states such as prostate cancer, benign prostatic hyperplasia, prostatitis, and infertility.