Differential proteomic analysis of renal cell carcinoma tissue interstitial fluid

Renal cell carcinoma (RCC), the most common type of kidney cancer, currently has no biomarker of clinical utility. The present study utilized a mass spectrometry-based proteomics workflow for identifying differentially abundant proteins in RCC by harvesting shed and secreted proteins from the tumor microenvironment through sampling tissue interstitial fluid (TIF) from radical nephrectomies. Matched tumor and adjacent normal kidney (ANK) tissues were collected from 10 patients diagnosed with clear cell RCC. One-hundred thirty-eight proteins were identified with statistically significant differential abundances derived by spectral counting in tumor TIF when compared to ANK TIF. Among those proteins with elevated abundance in tumor TIF, nicotinamide n-methyltransferase (NNMT) and enolase 2 (ENO2) were verified by Western blot and selected reaction monitoring (SRM). The presence of ENO2 and thrombospondin-1 (TSP1) were verified as present and at elevated abundance in RCC patient serum samples as compared to a pooled standard control by enzyme-linked immunosorbent assay (ELISA), recapitulating the relative abundance increase in RCC as compared with ANK TIF.     

Proteomic analysis in clear cell renal cell carcinoma: identification of differentially expressed protein by 2-D DIGE

Renal cell carcinoma (RCC), the most common neoplasm affecting the adult kidney, is characterised by heterogeneity of histological subtypes, drug resistance, and absence of molecular markers. Two-dimensional difference gel electrophoresis (2-D DIGE) technology in combination with mass spectrometry (MS) was applied to detect differentially expressed proteins in 20 pairs of RCC tissues and matched adjacent normal kidney cortex (ANK), in order to search for RCC markers. After gel analysis by DeCyder 6.5 and EDA software, differentially expressed protein spots were excised from Deep Purple stained preparative 2DE gel. A total of 100 proteins were identified by MS out of 2500 spots, 23 and 77 of these were, respectively, over- and down-expressed in RCC. The Principal Component Analysis applied to gels and protein spots exactly separated the two sample classes in two groups: RCC and ANK. Moreover, some spots, including ANXA2, PPIA, FABP7 and LEG1, resulted highly differential. The DIGE data were also confirmed by immunoblotting analysis for these proteins. In conclusion, we suggest that applying 2-D DIGE to RCC may provide the basis for a better molecular characterization and for the discovery of candidate biomarkers.     

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.     

Subcellular fractionation enhances proteome coverage of pancreatic duct cells

ObjectivesSubcellular fractionation of whole cell lysates offers a means of simplifying protein mixtures, potentially permitting greater depth of proteomic analysis. Here we compare proteins identified from pancreatic duct cells (PaDC) following organelle enrichment to those identified from PaDC whole cell lysates to determine if the additional procedures of subcellular fractionation increase proteome coverage.MethodsWe used differential centrifugation to enrich for nuclear, mitochondrial, membrane, and cytosolic proteins. We then compared – via mass spectrometry-based analysis – the number of proteins identified from these four fractions with four biological replicates of PaDC whole cell lysates.ResultsWe identified similar numbers of proteins among all samples investigated. In total, 1658 non-redundant proteins were identified in the replicate samples, while 2196 were identified in the subcellular fractionation samples, corresponding to a 30% increase. Additionally, we noted that each organelle fraction was in fact enriched with proteins specific to the targeted organelle.ConclusionsSubcellular fractionation of PaDC resulted in greater proteome coverage compared to PaDC whole cell lysate analysis. Although more labor intensive and time consuming, subcellular fractionation provides greater proteome coverage, and enriches for compartmentalized sub-populations of proteins. Application of this subcellular fractionation strategy allows for a greater depth of proteomic analysis and thus a better understanding of the cellular mechanisms of pancreatic disease.     

Integrated Proteomic Analysis of Human Cancer Cells and Plasma from Tumor Bearing Mice for Ovarian Cancer Biomarker Discovery

Background

The complexity of the human plasma proteome represents a substantial challenge for biomarker discovery. Proteomic analysis of genetically engineered mouse models of cancer and isolated cancer cells and cell lines provide alternative methods for identification of potential cancer markers that would be detectable in human blood using sensitive assays. The goal of this work is to evaluate the utility of an integrative strategy using these two approaches for biomarker discovery.

Methodology/Principal Findings

We investigated a strategy that combined quantitative plasma proteomics of an ovarian cancer mouse model with analysis of proteins secreted or shed by human ovarian cancer cells. Of 106 plasma proteins identified with increased levels in tumor bearing mice, 58 were also secreted or shed from ovarian cancer cells. The remainder consisted primarily of host-response proteins. Of 25 proteins identified in the study that were assayed, 8 mostly secreted proteins common to mouse plasma and human cancer cells were significantly upregulated in a set of plasmas from ovarian cancer patients. Five of the eight proteins were confirmed to be upregulated in a second independent set of ovarian cancer plasmas, including in early stage disease.

Conclusions/Significance

Integrated proteomic analysis of cancer mouse models and human cancer cell populations provides an effective approach to identify potential circulating protein biomarkers.     

Immunochemical characterization of myosin-specific phosphatase 1 regulatory subunits in bovine endothelium

We have previously shown that myosin-specific phosphatase 1 (PPase 1) activity is critical for maintaining endothelial cell barrier function (Verin et al. [1995] Am. J. Physiol. 269:L99-L108). To further characterize myosin-specific PPase 1 in endothelium, we generated antibodies specific to published sequences of the myosin-associated PPase 1 regulatory subunit (M110) from smooth muscle. Peptide antigens were designed based upon consensus sequences for a single ankyrin repeat (ANK 110) and a leucine zipper motif region (LZ 110), which represents putative sites for binding the PPase 1 catalytic subunit (CS1) and myosin, respectively. Our initial study demonstrated that each antibody immunoprecipitated 2 proteins with an apparent Mr of 110 and 70 kD on SDS-PAGE. The CS1delta isoform, which appeared to be characteristic for the myosin-specific phosphatase, was co-immunoprecipitated under non-denaturing conditions with ANK110 and LZ110 as was actin, myosin, and myosin light chain kinase (MLCK). Similarly, immunoprecipitation with specific anti-myosin or anti-MLCK antibodies under the same conditions, followed by immunostaining with either LZ110 or ANK110 revealed the same 110 and 70 kD protein bands. The 70 kD protein (p70) was immunoreactive with ANK 110 and LZ 110, was complexed with myosin and MLCK, and was detected in non-denaturing M110 immunoprecipitates. Consistent with these results, endothelial cell fractionation demonstrates the presence of p70 in both cytoskeletal and myosin-enriched fractions, but not in the myosin-depleted (cytosolic) fractions. These data suggest that endothelial cells may exhibit two distinct myosin-specific PPase 1 regulatory subunits which share certain structural features with the M110 regulatory subunit from smooth muscle and which are tightly associated with myosin and MLCK in a functional complex.     

Subcellular localization of aldosterone-induced proteins in toad urinary bladders

Paired toad urinary hemibladders were incubated with [35S]methionine in the presence (experimental) or absence (control) of aldosterone. Short-circuit current was used to monitor aldosterone-induced Na+ transport. Protein synthesis in epithelial cell subcellular fractions (cytosolic, microsomal, mitochondrial) was evaluated by gradient polyacrylamide gel electrophoresis and autoradiography. Aldosterone-induced proteins were identified in the cytosolic and microsomal fractions (70 000 and 15 000 daltons, respectively). These results represent the first demonstration of aldosterone-induced proteins in subcellular fractions of epithelial cells derived from single toad urinary hemibladders.     

Uridine phosphorylase activity of isolated plasma membranes of rat liver.

Plasma membranes were isolated from rat liver homogenates either by differential centrifugation or by fractionation in discontinuous sucrose density gradients. Both membrane preparations contained about 17% of the total uridine phosphorylase (EC 2.4.2.3) activity and 44% of the total 5'-nucleotidase (EC 3.1.3.5). The enrichment factor for uridine phosphorylase in the fractions prepared by differential centrifugation was about 2.8 and by the gradient method, as much as 11.0; the respective enrichment factors for 5'-nucleotidase were 1.8 and 9.5. Uridine phosphorylase activity of isolated plasma membrane fractions was stimulated 2.5-fold by 0.1% Triton X-100. Unlike the cytosol enzyme, uridine phosphorylase of plasma membranes showed little or no deoxyuridine-cleaving activity. Contamination of the membrane fractions by thymidine phosphorylase (EC 2.4.2.4) of the cytosol was negligible. The other subcellular organelles obtained by either procedure and characterized by marker enzyme activities were found not to contain significant uridine phosphorylase activity; the cytosol fractions contained just over 70% of the total uridine phosphorylase activity with an enrichment of only about 2.8-fold. The activity of the cytosol enzyme was not stimulated by Triton X-100.     

Comparative proteomic analysis for the insoluble fractions of colorectal cancer patients

We used label-free quantitative proteomics with the insoluble fractions from colorectal cancer (CRC) patients to gain further insight into the utility of profiling altered protein expression as a potential biomarker for cancer. The insoluble fractions were prepared from paired tumor/normal biopsies from 13 patients diagnosed with CRC (stages I to IV). Fifty-six proteins identified in data pooled from the 13 cases were differentially expressed between the tumor and adjacent normal tissue. The connections between these proteins are involved in reciprocal networks related to tumorigenesis, cancer incidence based on genetic disorder, and skeletal and muscular disorders. To assess their potential utility as biomarkers, the relative expression levels of the proteins were validated using personal proteomics and a heat map to compare five individual CRC samples with five normal tissue samples. Further validation of a panel of proteins (KRT5, JUP, TUBB, and COL6A1) using western blotting confirmed the differential expression. These proteins gave specific network information for CRC, and yielded a panel of novel markers and potential targets for treatment. It is anticipated that the experimental approach described here will increase our understanding of the membrane environment in CRC, which may provide direction for making diagnoses and prognoses through molecular biomarker targeting.     

Reduced plasma APOA1 level is associated with Gastric Tumor Growth in MKN45 mouse xenograft model

There is no suitable diagnostic and prognostic biomarker for gastric cancer. The biggest hurdles in biomarker discovery are (i) the low abundance of cancer cell-specific proteins that limits their detection and (ii) complex inter-patient variations that complicate the discovery process. To circumvent these issues, we conducted proteomics on the plasma of gastric cancer mouse xenograft and attempted to identify proteins released by cancer cells. MKN45 gastric cancer cells were subcutaneously implanted into immune-incompetent nude mice. Plasma samples collected from mice with different tumor sizes (low, mid and high tumor loads) were subjected to iTRAQ and mass spectrometric analyses. Detection of human APOA1 in mouse plasma was verified and its expression level was shown to be lower in mice with large tumors compared to those with small tumors. Studies on a panel of about 14 gastric cancer cell lines supported the notion that APOA1 in mouse plasma was of human gastric cancer cell origin. While the clinical utility of APOA1 remains to be ascertained with a larger scale study, the current work supported the feasibility of using mouse xenograft model for gastric cancer biomarker discovery.     

Expression and localisation of the pyrophosphate transporter, ANK, in murine kidney cells.

BACKGROUND/AIMS: Mutation of the pyrophosphate transporter, ANK, results in progressive arthritis in mice. ANK is expressed in non-skeletal tissues including kidney. The aim was therefore to investigate ANK location at the cellular and subcellular level in renal cells. METHODS: RT-PCR identified a murine cell-line, mIMCD3, expressing ANK. The intra-renal distribution of ANK was determined by immunohistochemistry and the subcellular distribution in mIMCD3 cells by transfection of an ANK-NT-GFP fusion protein. Furthermore, an inactivating mutation of murine ank, Glu440X, and a gain of function mutation, Met48Thr, were tested to determine whether membrane traffic contributed to a transport defect. RESULTS: ANK is expressed in cells of the cortical collecting duct, as assessed by colocalisation with aquaporin 2 and at the lateral and apical plasma membranes of mIMCD-3 epithelial cells, as assessed by colocalisation with wheat germ agglutinin lectin (WGA). ANK-NT-GFP was also present in endoplasmic reticulum, Golgi, acidic endosomes and mitochondria. mIMCD3 expression of Glu440X ANK-NT-GFP shows evidence of Golgi retention whereas Met48Thr ANK-NT-GFP is unaltered at the plasma membrane compared to wild type. CONCLUSION: The intra-renal and subcellular localisation of ANK is consistent with pyrophosphate export from collecting duct cells and supports a role for ANK in limiting intra-renal calcium-crystal formation.     

Differential induction of peroxisomal populations in subcellular fractions of rat liver

In rat liver, peroxisome proliferators induce profound changes in the number and protein composition of peroxisomes, which upon subcellular fractionation is reflected in heterogeneity in sedimentation properties of peroxisome populations. In this study we have investigated the time course of induction of the peroxisomal proteins catalase, acyl-CoA oxidase (ACO) and the 70 kDa peroxisomal membrane protein (PMP70) in different subcellular fractions. Rats were fed a di(2-ethylhexyl)phthalate (DEHP) containing diet for 8 days and livers were removed at different time-points, fractionated by differential centrifugation into nuclear, heavy and light mitochondrial, microsomal and soluble fractions, and organelle marker enzymes were measured. Catalase was enriched mainly in the light mitochondrial and soluble fractions, while ACO was enriched in the nuclear fraction (about 30%) and in the soluble fraction. PMP70 was found in all fractions except the soluble fraction. DEHP treatment induced ACO, catalase and PMP70 activity and immunoreactive protein, but the time course and extent of induction was markedly different in the various subcellular fractions. All three proteins were induced more rapidly in the nuclear fraction than in the light mitochondrial or microsomal fractions, with catalase and PMP70 being maximally induced in the nuclear fraction already at 2 days of treatment. Refeeding a normal diet quickly normalized most parameters. These results suggest that induction of a heavy peroxisomal compartment is an early event and that induction of 'small peroxisomes', containing PMP70 and ACO, is a late event. These data are compatible with a model where peroxisomes initially proliferate by growth of a heavy, possibly reticular-like, structure rather than formation of peroxisomes by division of pre-existing organelles into small peroxisomes that subsequently grow. The various peroxisome populations that can be separated by subcellular fractionation may represent peroxisomes at different stages of biogenesis.     

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.     

An electron microscope comparison of plasma membrane vesicles from meristematic and mature soybean root tissue

Plasma membrane vesicles were isolated from homogenates of meristematic and mature soybean root tissue by differential sucrose gradient centrifugation. Vesicles were positively identified by the phosphotungstic acid-chromic acid procedure (PACP). The two preparations were comparable in size class distribution, mitochondrial contamination, and per cent plasma membrane vesicles present. Purity levels were estimated to be greater than 75%. The specificity of PACP was observed for a variety of cell types from both regions. Some variability in PACP staining was offset by careful modulation of the stain protocol and was found to be independent of developmental stage in subcellular fractions. Patchy or discontinuous staining, observed in both intact tissue and in subcellular fractions from both regions, was found to be a function of stain time.     

Candidate biomarkers in renal cell carcinoma

Although the human genome has been decoded, the knowledge about the pathogenesis of diseases including cancer is still limited. By focusing on renal cell carcinoma (RCC) we here summarize the data of various research groups analyzing the protein/peptide expression profiles of tumor lesions/cell lines or serum obtained from patients and respective controls. Different powerful approaches such as 2-DE, PROTEOMEX/SERPA/SPEARS, and T cell epitope discovery upon elution of MHC class I-bound peptides in combination with MS/LC-MS/MS revealed 500 differentially expressed proteins. The overlap in target recognition limits the pool to 299 unique protein identities, but only few thereof (12%) have been validated. The management, analysis, and interpretation of the distinct data sets derived from 27 publications required bioinformatic restructuring of the results. However, the comprehensive analysis of the results expands the knowledge about the pathophysiology of RCC in particular of the most prominent clear cell subtype by providing information on the differentially expressed proteins, their regulation status in RCC compared to normal kidney epithelium next to additional information on MHC-presented T cell epitopes and on serological targets. Despite the low number of validated differentially expressed proteins some of them might serve as candidate biomarkers for the diagnosis and/or as therapeutic targets.     

A systematic analysis of eluted fraction of plasma post immunoaffinity depletion: implications in biomarker discovery

Plasma is the most easily accessible source for biomarker discovery in clinical proteomics. However, identifying potential biomarkers from plasma is a challenge given the large dynamic range of proteins. The potential biomarkers in plasma are generally present at very low abundance levels and hence identification of these low abundance proteins necessitates the depletion of highly abundant proteins. Sample pre-fractionation using immuno-depletion of high abundance proteins using multi-affinity removal system (MARS) has been a popular method to deplete multiple high abundance proteins. However, depletion of these abundant proteins can result in concomitant removal of low abundant proteins. Although there are some reports suggesting the removal of non-targeted proteins, the predominant view is that number of such proteins is small. In this study, we identified proteins that are removed along with the targeted high abundant proteins. Three plasma samples were depleted using each of the three MARS (Hu-6, Hu-14 and Proteoprep 20) cartridges. The affinity bound fractions were subjected to gelC-MS using an LTQ-Orbitrap instrument. Using four database search algorithms including MassWiz (developed in house), we selected the peptides identified at <1% FDR. Peptides identified by at least two algorithms were selected for protein identification. After this rigorous bioinformatics analysis, we identified 101 proteins with high confidence. Thus, we believe that for biomarker discovery and proper quantitation of proteins, it might be better to study both bound and depleted fractions from any MARS depleted plasma sample.     

Identification of alphaB-crystallin, a biomarker of renal cell carcinoma by SELDI-TOF MS

Spectrometric-based surface-enhanced laser desorption/ionization ProteinChip (SELDI-TOF) facilitates rapid and easy analysis of protein mixtures and is often exploited to define potential diagnostic markers from sera. However, SELDI- TOF is a relatively insensitive technique and unable to detect circulating proteins at low levels even if they are differentially expressed in cancer patients. Therefore, we applied this technology to study tissues from renal cell carcinomas (RCC) in comparison to healthy controls. We found that different biomarkers are identified from tissues than those previously identified in serum, and that serum markers are often not produced by the tumors themselves at detectable levels, reflecting the nonspecific nature of many circulating biomarkers. We detected and characterized áB-crystallin as an overexpressed protein in RCC tissues and showed differential expression by immunohistochemistry. We conclude that SELDI-TOF is more useful for the identification of biomarkers that are synthesized by diseased tissues than for the identification of serum biomarkers and identifies a separate set of markers. We suggest that SELDI-TOF should be used to screen human cancer tissues to identify potential tissue-specific proteins and simpler and more sensitive techniques can then be applied to determine their validity as biomarkers in biological fluids.