Combined analysis of transcriptome and proteome data as a tool for the identification of candidate biomarkers in renal cell carcinoma

Integrated multiomics analysis identifies molecular landscape perturbations during hyperammonemia in skeletal muscle and myotubes

Ammonia is a cytotoxic molecule generated during normal cellular functions. Dysregulated ammonia metabolism, which is evident in many chronic diseases such as liver cirrhosis, heart failure, and chronic obstructive pulmonary disease, initiates a hyperammonemic stress response in tissues including skeletal muscle and in myotubes. Perturbations in levels of specific regulatory molecules have been reported, but the global responses to hyperammonemia are unclear. In this study, we used a multiomics approach to vertically integrate unbiased data generated using an assay for transposase-accessible chromatin with high-throughput sequencing, RNA-Seq, and proteomics. We then horizontally integrated these data across different models of hyperammonemia, including myotubes and mouse and human muscle tissues. Changes in chromatin accessibility and/or expression of genes resulted in distinct clusters of temporal molecular changes including transient, persistent, and delayed responses during hyperammonemia in myotubes. Known responses to hyperammonemia, including mitochondrial and oxidative dysfunction, protein homeostasis disruption, and oxidative stress pathway activation, were enriched in our datasets. During hyperammonemia, pathways that impact skeletal muscle structure and function that were consistently enriched were those that contribute to mitochondrial dysfunction, oxidative stress, and senescence. We made several novel observations, including an enrichment in antiapoptotic B-cell leukemia/lymphoma 2 family protein expression, increased calcium flux, and increased protein glycosylation in myotubes and muscle tissue upon hyperammonemia. Critical molecules in these pathways were validated experimentally. Human skeletal muscle from patients with cirrhosis displayed similar responses, establishing translational relevance. These data demonstrate complex molecular interactions during adaptive and maladaptive responses during the cellular stress response to hyperammonemia.

Integrative proteomics and pharmacogenomics analysis of methylphenidate treatment response

Transcriptomics and candidate gene/protein expression studies have indicated several biological processes modulated by methylphenidate (MPH), widely used in attention-deficit/hyperactivity disorder (ADHD) treatment. However, the lack of a differential proteomic profiling of MPH treatment limits the understanding of the most relevant mechanisms by which MPH exerts its pharmacological effects at the molecular level. Therefore, our aim is to investigate the MPH-induced proteomic alterations using an experimental design integrated with a pharmacogenomic analysis in a translational perspective. Proteomic analysis was performed using the cortices of Wistar-Kyoto rats, which were treated by gavage with MPH (2 mg/kg) or saline for two weeks (n = 6/group). After functional enrichment analysis of the differentially expressed proteins (DEP) in rats, the significant biological pathways were tested for association with MPH response in adults with ADHD (n = 189) using genome-wide data. Following MPH treatment in rats, 98 DEPs were found (P < 0.05 and FC < -1.0 or > 1.0). The functional enrichment analysis of the DEPs revealed 18 significant biological pathways (gene-sets) modulated by MPH, including some with recognized biological plausibility, such as those related to synaptic transmission. The pharmacogenomic analysis in the clinical sample evaluating these pathways revealed nominal associations for gene-sets related to neurotransmitter release and GABA transmission. Our results, which integrate proteomics and pharmacogenomics, revealed putative molecular effects of MPH on several biological processes, including oxidative stress, cellular respiration, and metabolism, and extended the results involving synaptic transmission pathways to a clinical sample. These findings shed light on the molecular signatures of MPH effects and possible biological sources of treatment response variability.

The past, present, and future of coral heat stress studies

The global loss and degradation of coral reefs, as a result of intensified frequency and severity of bleaching events, is a major concern. Evidence of heat stress affecting corals through loss of symbionts and consequent coral bleaching was first reported in the 1930s. However, it was not until the 1998 major global bleaching event that the urgency for heat stress studies became internationally recognized. Current efforts focus not only on examining the consequences of heat stress on corals but also on finding strategies to potentially improve thermal tolerance and aid coral reefs survival in future climate scenarios. Although initial studies were limited in comparison with modern technological tools, they provided the foundation for many of today's research methods and hypotheses. Technological advancements are providing new research prospects at a rapid pace. Understanding how coral heat stress studies have evolved is important for the critical assessment of their progress. This review summarizes the development of the field to date and assesses avenues for future research.

Proteome profiling of clear cell renal cell carcinoma in von Hippel-Lindau patients highlights upregulation of Xaa-Pro aminopeptidase-1, an anti-proliferative and anti-migratory exoprotease

Patients of the von Hippel-Lindau (VHL) disease frequently develop clear cell renal cell carcinoma (ccRCC). Using archived, formalin-fixed, paraffin-embedded (FFPE) samples, we sought to determine global proteome alterations that distinguish ccRCC tissue from adjacent, non-malignant kidney tissue in VHL-patients. Our quantitative proteomic analysis clearly discriminated tumor and non-malignant tissue. Significantly dysregulated proteins were distinguished using the linear models for microarray data algorithm. In the ccRCC tissue, we noticed a predominant under-representation of proteins involved in the tricarboxylic acid cycle and an increase in proteins involved in glycolysis. This profile possibly represents a proteomic fingerprint of the "Warburg effect", which is a molecular hallmark of ccRCC. Furthermore, we observed an increase in proteins involved in extracellular matrix organization. We also noticed differential expression of many exoproteases in the ccRCC tissue. Of particular note were opposing alterations of Xaa-Pro Aminopeptidases-1 and -2 (XPNPEP-1 and -2): a strong decrease of XPNPEP-2 in ccRCC was accompanied by abundant presence of the related protease XPNPEP-1. In both cases, we corroborated the proteomic results by immunohistochemical analysis of ccRCC and adjacent, non-malignant kidney tissue of VHL patients. To functionally investigate the role of XPNPEP-1 in ccRCC, we performed small-hairpin RNA mediated XPNPEP-1 expression silencing in 786-O ccRCC cells harboring a mutated VHL gene. We found that XPNPEP-1 expression dampens cellular proliferation and migration. These results suggest that XPNPEP-1 is likely an anti-target in ccRCC. Methodologically, our work further validates the robustness of using FFPE material for quantitative proteomics.

Identification of genes associated with renal cell carcinoma using gene expression profiling analysis

Renal cell carcinoma (RCC) is the most common type of kidney cancer in adults and accounts for ~80% of all kidney cancer cases. However, the pathogenesis of RCC has not yet been fully elucidated. To interpret the pathogenesis of RCC at the molecular level, gene expression data and bio-informatics methods were used to identify RCC associated genes. Gene expression data was downloaded from Gene Expression Omnibus (GEO) database and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in RCC patients compared with controls. In addition, a regulatory network was constructed using the known regulatory data between transcription factors (TFs) and target genes in the University of California Santa Cruz (UCSC) Genome Browser (http://genome.ucsc.edu) and the regulatory impact factor of each TF was calculated. A total of 258,0427 pairs of DCGs were identified. The regulatory network contained 1,525 pairs of regulatory associations between 126 TFs and 1,259 target genes and these genes were mainly enriched in cancer pathways, ErbB and MAPK. In the regulatory network, the 10 most strongly associated TFs were FOXC1, GATA3, ESR1, FOXL1, PATZ1, MYB, STAT5A, EGR2, EGR3 and PELP1. GATA3, ERG and MYB serve important roles in RCC while FOXC1, ESR1, FOXL1, PATZ1, STAT5A and PELP1 may be potential genes associated with RCC. In conclusion, the present study constructed a regulatory network and screened out several TFs that may be used as molecular biomarkers of RCC. However, future studies are needed to confirm the findings of the present study.

Proteotranscriptomic Analysis Reveals Stage Specific Changes in the Molecular Landscape of Clear-Cell Renal Cell Carcinoma

Renal cell carcinoma comprises 2 to 3% of malignancies in adults with the most prevalent subtype being clear-cell RCC (ccRCC). This type of cancer is well characterized at the genomic and transcriptomic level and is associated with a loss of VHL that results in stabilization of HIF1. The current study focused on evaluating ccRCC stage dependent changes at the proteome level to provide insight into the molecular pathogenesis of ccRCC progression. To accomplish this, label-free proteomics was used to characterize matched tumor and normal-adjacent tissues from 84 patients with stage I to IV ccRCC. Using pooled samples 1551 proteins were identified, of which 290 were differentially abundant, while 783 proteins were identified using individual samples, with 344 being differentially abundant. These 344 differentially abundant proteins were enriched in metabolic pathways and further examination revealed metabolic dysfunction consistent with the Warburg effect. Additionally, the protein data indicated activation of ESRRA and ESRRG, and HIF1A, as well as inhibition of FOXA1, MAPK1 and WISP2. A subset analysis of complementary gene expression array data on 47 pairs of these same tissues indicated similar upstream changes, such as increased HIF1A activation with stage, though ESRRA and ESRRG activation and FOXA1 inhibition were not predicted from the transcriptomic data. The activation of ESRRA and ESRRG implied that HIF2A may also be activated during later stages of ccRCC, which was confirmed in the transcriptional analysis. This combined analysis highlights the importance of HIF1A and HIF2A in developing the ccRCC molecular phenotype as well as the potential involvement of ESRRA and ESRRG in driving these changes. In addition, cofilin-1, profilin-1, nicotinamide N-methyltransferase, and fructose-bisphosphate aldolase A were identified as candidate markers of late stage ccRCC. Utilization of data collected from heterogeneous biological domains strengthened the findings from each domain, demonstrating the complementary nature of such an analysis. Together these results highlight the importance of the VHL/HIF1A/HIF2A axis and provide a foundation and therapeutic targets for future studies. (Data are available via ProteomeXchange with identifier PXD003271 and MassIVE with identifier MSV000079511.)

Annexin A4 and cancer

Annexin A4 (Anxa4) is one of the Ca(2+)-regulated and phospholipid-binding annexin superfamily proteins. Anxa4 has a potential role in diagnosis, prognosis, and treatment of certain cancers. Studies indicate that Anxa4 up-regulation promotes the progression of tumor and chemoresistance of colorectal cancer (CRC), esophageal squamous cell carcinoma (ESCC), endometrial carcinoma (EC), gastric cancer (GC), chemoresistant lung cancer (LC), malignant mesothelioma (MM), renal cell carcinoma (RCC), ovarian clear cell carcinoma (OCCC), cholangiocarcinoma, hepatocellular carcinoma (HCC), breast cancer (BC), and laryngeal cancer. Interestingly, Anxa4 also might specifically function as a tumor suppressor for prostate cancer (PCa) and have a paradoxical role for pancreatic cancer (PCC). Differential expression of Anxa4 may distinguish major salivary gland tumor (MSGT) from thyroid cancer. In addition, its differential expression was linked to Sirt1-induced cisplatin resistance of oral squamous cell carcinoma (OSCC) and miR-7-induced migration and invasion inhibition of glioma. This current review summarizes and discusses the clinical significance of Anxa4 in cancer as well as its potential mechanisms of action. It may provide new integrative understanding for future studies on the exact role of Anxa4 in cancer.

Towards defining biomarkers indicating resistances to targeted therapies

An impressive, but often short objective response was obtained in many tumor patients treated with different targeted therapies, but most of the patients develop resistances against these drugs. So far, a number of distinct mechanisms leading to intrinsic as well as acquired resistances have been identified in tumors of distinct origin. These can arise from genetic alterations, like mutations, truncations, and amplifications or due to deregulated expression of various proteins and signal transduction pathways, but also from cellular heterogeneity within tumors after an initial response. Therefore, biomarkers are urgently needed for cancer prognosis and personalized cancer medicine. The application of "ome"-based technologies including cancer (epi)genomics, next generation sequencing, cDNA microarrays and proteomics might led to the predictive or prognostic stratification of patients to categorize resistance mechanisms and to postulate combinations of treatment strategies. This review discusses the implementation of proteome-based analysis to identify markers of pathway (in)activation in tumors and the resistance mechanisms, which represent major clinical problems as a tool to optimize individually tailored therapies based on targeted drugs. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

Proteomic identification of Reticulocalbin 1 as potential tumor marker in renal cell carcinoma

Renal cell carcinoma (RCC) biomarkers are necessary for diagnosis and prognosis. They serve to monitor therapy response and follow-up, as drug targets, and therapy predictors in personalized treatments. Proteomics is a suitable method for biomarker discovery. Here we investigate differential protein expression in RCC, and we evaluate Reticulocalbin 1 (RCN1) use as a new potential marker. Neoplastic and healthy tissue samples were collected from 24 RCC patients during radical nephrectomy. Seven specimens were firstly processed by proteomic analysis (2-DE and MALDI-TOF) and 18 differentially expressed proteins from neoplastic and healthy renal tissues were identified. Among them, RCN1 was over-expressed in all cancer specimens analyzed by proteomics. Consequently RCN1 use as a potential marker was further evaluated in all 24 donors. RCN1 expression was verified by Western blotting (WB) and immunohistochemistry (IHC). WB analysis confirmed RCN1 over-expression in 21 out of 24 tumor specimens, whereas IHC displayed focal or diffuse expression of RCN1 in all 24 RCC tissues. Thus RCN1 appears as a potential marker for clinical approaches. A larger histopathological trial will clarify the prognostic value of RCN1 in RCC.

BIOLOGICAL SIGNIFICANCE

The present work aimed at finding new biomarkers for RCC - a life-threatening disease characterized by high incidence in Western countries - by performing differential proteomic analysis of neoplastic and normal renal tissues obtained from a small cohort of RCC patients. Some of the identified proteins have been previously associated to renal cancer however data confirming the possible use of these proteins in clinical practice are not available to date. By IHC we demonstrated that RCN1 could be easily employed in clinical practice, confirming RCN1 over-expression in RCC tissues of all examined patients, and weak protein expression in healthy renal tissues only in correspondence to the renal tubule section. These data indicate a promising role of RCN1 as a possible marker in RCC and indicate the proximal convoluted renal tubule as a putative origin point for RCC. Since IHC staining displayed different grades of intensity in tested tissues, we hypothesized that RCN1 could also be employed as a prognostic marker or as a response predictor for RCC-targeted therapy. To test such a hypothesis, a larger retrospective trial on paraffin-embedded tissues obtained from radical or partial nephrectomy of RCC patients is planned to be performed by our group.

A decision theory paradigm for evaluating identifier mapping and filtering methods using data integration

Background

In bioinformatics, we pre-process raw data into a format ready for answering medical and biological questions. A key step in processing is labeling the measured features with the identities of the molecules purportedly assayed: “molecular identification” (MI). Biological meaning comes from identifying these molecular measurements correctly with actual molecular species. But MI can be incorrect. Identifier filtering (IDF) selects features with more trusted MI, leaving a smaller, but more correct dataset. Identifier mapping (IDM) is needed when an analyst is combining two high-throughput (HT) measurement platforms on the same samples. IDM produces ID pairs, one ID from each platform, where the mapping declares that the two analytes are associated through a causal path, direct or indirect (example: pairing an ID for an mRNA species with an ID for a protein species that is its putative translation). Many competing solutions for IDF and IDM exist. Analysts need a rigorous method for evaluating and comparing all these choices.

Results

We describe a paradigm for critically evaluating and comparing IDF and IDM methods, guided by data on biological samples. The requirements are: a large set of biological samples, measurements on those samples from at least two high-throughput platforms, a model family connecting features from the platforms, and an association measure. From these ingredients, one fits a mixture model coupled to a decision framework. We demonstrate this evaluation paradigm in three settings: comparing performance of several bioinformatics resources for IDM between transcripts and proteins, comparing several published microarray probeset IDF methods and their combinations, and selecting optimal quality thresholds for tandem mass spectrometry spectral events.

Conclusions

The paradigm outlined here provides a data-grounded approach for evaluating the quality not just of IDM and IDF, but of any pre-processing step or pipeline. The results will help researchers to semantically integrate or filter data optimally, and help bioinformatics database curators to track changes in quality over time and even to troubleshoot causes of MI errors.

Identification of a Novel Biomarker for Biliary Tract Cancer Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Early diagnosis of biliary tract cancer (BTC) is important for curative surgical resection. Current tumor markers of BTC are unsatisfactory in terms of sensitivity and specificity. In a search for novel biomarkers for BTC, serum samples obtained from 62 patients with BTC were compared with those from patients with benign biliary diseases and from healthy controls, using the MALDI-TOF/TOF ClinProt system. Initial screening and further validation identified a peak at 4204 Da with significantly greater intensity in the BTC samples. The 4204 Da peak was partially purified and identified as a fragment of prothrombin by amino acid sequencing. The sensitivity of the 4204 Da peptide for detection of stage I BTC cancer was greater than those for CEA and CA19-9. Also, serum levels of the 4204 Da peptide were above the cut-off level in 15 (79%) of 19 cases in which the CEA and CA19-9 levels were both within their cut-off values. Receiver operating characteristic analysis showed that the combination of the 4204 Da peptide and CA19-9 was significantly more sensitive for detection of stage I BTC cancer compared to CEA and CA19-9. These results suggest that this protein fragment may be a promising biomarker for biliary tract cancer.

MicroRNAs in liver disease

MicroRNAs are small noncoding RNA molecules that regulate gene expression posttranscriptionally through complementary base pairing with thousands of messenger RNAs. They regulate diverse physiological, developmental, and pathophysiological processes. Recent studies have uncovered the contribution of microRNAs to the pathogenesis of many human diseases, including liver diseases. Moreover, microRNAs have been identified as biomarkers that can often be detected in the systemic circulation. We review the role of microRNAs in liver physiology and pathophysiology, focusing on viral hepatitis, liver fibrosis, and cancer. We also discuss microRNAs as diagnostic and prognostic markers and microRNA-based therapeutic approaches for liver disease.

DIPSBC--data integration platform for systems biology collaborations

Background

Modern biomedical research is often organized in collaborations involving labs worldwide. In particular in systems biology, complex molecular systems are analyzed that require the generation and interpretation of heterogeneous data for their explanation, for example ranging from gene expression studies and mass spectrometry measurements to experimental techniques for detecting molecular interactions and functional assays. XML has become the most prominent format for representing and exchanging these data. However, besides the development of standards there is still a fundamental lack of data integration systems that are able to utilize these exchange formats, organize the data in an integrative way and link it with applications for data interpretation and analysis.

Results

We have developed DIPSBC, an interactive data integration platform supporting collaborative research projects, based on Foswiki, Solr/Lucene, and specific helper applications. We describe the main features of the implementation and highlight the performance of the system with several use cases. All components of the system are platform independent and open-source developments and thus can be easily adopted by researchers. An exemplary installation of the platform which also provides several helper applications and detailed instructions for system usage and setup is available at http://dipsbc.molgen.mpg.de.

Conclusions

DIPSBC is a data integration platform for medium-scale collaboration projects that has been tested already within several research collaborations. Because of its modular design and the incorporation of XML data formats it is highly flexible and easy to use.

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.

Proteomic analysis of tumor necrosis factor-alpha (TNF-α)-induced L6 myotube secretome reveals novel TNF-α-dependent myokines in diabetic skeletal muscle

There is a strong possibility that skeletal muscle can respond to irregular metabolic states by secreting specific cytokines. Obesity-related chronic inflammation, mediated by pro-inflammatory cytokines, is believed to be one of the causes of insulin resistance that results in type 2 diabetes. Here, we attempted to identify and characterize the members of the skeletal muscle secretome in response to tumor necrosis factor-alpha (TNF-α)-induced insulin resistance. To conduct this study, we comparatively analyzed the media levels of proteins released from L6 skeletal muscle cells. We found 28 TNF-α modulated secretory proteins by using separate filtering methods: Gene Ontology, SignalP, and SecretomeP, as well as the normalized Spectral Index for label-free quantification. Ten of these secretory proteins were increased and 18 secretory proteins were decreased by TNF-α treatment. Using microarray analysis of Zuker diabetic rat skeletal muscle combined with bioinformatics and Q-PCR, we found a correlation between TNF-α-mediated insulin resistance and type 2 diabetes. This novel approach combining analysis of the conditioned secretome and transcriptome has identified several previously unknown, TNF-α-dependent secretory proteins, which establish a foothold for research on the different causes of insulin resistance and their relationships with each other.

The application of a three-step proteome analysis for identification of new biomarkers of pancreatic cancer

We searched for novel tumor markers of pancreatic cancer by three-step serum proteome analysis. Twelve serum abundant proteins were depleted using immunoaffinity columns followed by fractionation by reverse-phase high-performance liquid chromatography. Proteins in each fraction were separated by two-dimensional gel electrophoresis. Then the gel was stained by Coomassie Brilliant Blue. Protein spots in which the expression levels were significantly different between cancer and normal control were identified by LC-MS/MS. One hundred and two spots were upregulated, and 84 spots were downregulated in serum samples obtained from patients with pancreatic cancers, and 58 proteins were identified by mass spectrometry. These candidate proteins were validated using western blot analysis and enzyme-linked immunosorbent assay (ELISA). As a result of these validation process, we could confirm that the serum levels of apolipoprotein A-IV, vitamin D-binding protein, plasma retinol-binding protein 4, and tetranectin were significantly decreased in patients with pancreatic cancer.

Analysis of proteomic changes induced upon cellular differentiation of the human intestinal cell line Caco-2

The human intestinal cell line Caco-2 is a well-established model system to study cellular differentiation of human enterocytes of intestinal origin, because these cells have the capability to differentiate spontaneously into polarized cells with morphological and biochemical features of small intestinal enterocytes. Therefore, the cells are widely used as an in vitro model for the human intestinal barrier. In this study, a proteomic approach was used to identify the molecular marker of intestinal cellular differentiation. The proteome of proliferating Caco-2 cells was compared with that of fully differentiated cells. Two-dimensional gel analysis yielded 53 proteins that were differently regulated during the differentiation process. Pathway analysis conducted with those 34 proteins that were identified by matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) analysis revealed subsets of proteins with common molecular and cellular function. It was shown that proteins involved in xenobiotic and drug metabolism as well as in lipid metabolism were upregulated upon cellular differentiation. In parallel, proteins associated with proliferation, cell growth and cancer were downregulated, reflecting the loss of the tumorigenic phenotype of the cells. Thus, the proteomic approach in combination with a literature-based pathway analysis yielded valuable information about the differentiation process of Caco-2 cells on the molecular level that contributes to the understanding of the development of colon cancer or inflammatory diseases such as ulcerative colitis--diseases associated with an imbalanced differentiation process of intestinal cells.

Stage-related alterations in renal cell carcinoma--comprehensive quantitative analysis by 2D-DIGE and protein network analysis

Renal cell carcinoma accounts for about 3% of adult malignancies and 85% of neoplasms arising from the kidney. To identify potential progression markers for kidney cancer we examined non-neoplastic and neoplastic kidney tissue from three groups of patients, which represent different tumor stages (pT1, pT2, pT3) by a fluorescence two-dimensional difference gel electrophoresis (2D-DIGE) approach combined with MALDI-ToF-MS/MS. Delta2D software package was used for gel image based quantification and statistical analysis. Thereby, a comprehensive Principal Component Analysis (PCA) could be performed and allowed a robust quality control of the experiment as well as a classification of the analyzed samples, which correlated with the predicted stages from the pathological examination. Additionally for selected candidate proteins we detected a correlation to the tumor grading as revealed by immunohistochemistry. On the 2D protein map 176 spots out of 989 were detected as at least 2-fold differentially expressed. These spots were analyzed by MALDI-ToF-MS/MS and 187 different proteins were identified. The functional clustering of the identified proteins revealed ten groups. Within these groups we found 86 enzymes, 63 proteins of unknown function, 14 transporter, 8 peptidases and 7 kinases. From the systems biology approach we could map many of these proteins in major pathways involved in remodelling of cytoskeleton, mitochondrial dysfunctions and changes in lipid metabolism. Due to complexity of the highly interconnected pathway network, further expression and functional validation of these proteins might provide new insights in kidney cancer progression to design novel diagnostic and therapeutic strategies.

Metabolic profiling reveals key metabolic features of renal cell carcinoma

Recent evidence suggests that metabolic changes play a pivotal role in the biology of cancer and in particular renal cell carcinoma (RCC). Here, a global metabolite profiling approach was applied to characterize the metabolite pool of RCC and normal renal tissue. Advanced decision tree models were applied to characterize the metabolic signature of RCC and to explore features of metastasized tumours. The findings were validated in a second independent dataset. Vitamin E derivates and metabolites of glucose, fatty acid, and inositol phosphate metabolism determined the metabolic profile of RCC. α-tocopherol, hippuric acid, myoinositol, fructose-1-phosphate and glucose-1-phosphate contributed most to the tumour/normal discrimination and all showed pronounced concentration changes in RCC. The identified metabolic profile was characterized by a low recognition error of only 5% for tumour versus normal samples. Data on metastasized tumours suggested a key role for metabolic pathways involving arachidonic acid, free fatty acids, proline, uracil and the tricarboxylic acid cycle. These results illustrate the potential of mass spectroscopy based metabolomics in conjunction with sophisticated data analysis methods to uncover the metabolic phenotype of cancer. Differentially regulated metabolites, such as vitamin E compounds, hippuric acid and myoinositol, provide leads for the characterization of novel pathways in RCC.

Identification and characterization of human leukocyte antigen class I ligands in renal cell carcinoma cells

The presentation of tumor antigen-derived peptides by human leukocyte antigen (HLA) class I surface antigens on tumor cells is a key prerequisite to trigger effective T-cell responses in cancer patients. Multiple complementary strategies like cDNA and serological expression cloning, reverse immunology and different 'ome'-based methods have been employed to identify potential T-cell targets. This report focuses on a ligandomic profiling approach leading to the identification of 49 naturally processed HLA class I peptide ligands presented on the cell surface of renal cell carcinoma (RCC) cells. The source proteins of the defined HLA ligands are classified according to their biological function and subcellular localization. Previously established cDNA microarray data of paired tissue specimen of RCC and renal epithelium assessed the transcriptional regulation for 28 source proteins. In addition, HLA-A2-restricted, peptide-specific T cells directed against a HLA ligand derived from sulfiredoxin-1 (SRXN1) were generated, which were able to recognize and lyse ligand-presenting target cells in a HLA class I-restricted manner. Furthermore, tumor-infiltrating T cells isolated from a RCC patient were also able to kill SRXN1 expressing tumor cells. Thus, this experimental strategy might be suited to define potential candidate biomarkers and novel targets for T-cell-based immunotherapies of this disease.

Linkage of microRNA and proteome-based profiling data sets: a perspective for the priorization of candidate biomarkers in renal cell carcinoma?

Despite recent advances in the understanding of the biology of renal cell carcinoma (RCC) and the implementation of novel targeted therapies, the overall 5 years' survival rate for RCC patients remains disappointing. Late presentation, tumor heterogeneity and in particular the lack of molecular biomarkers for early detection and classification represent major obstacles. Global, untargeted comparative analysis of RCC vs tumor adjacent renal epithelium (NN) samples by high throughput analyses both at the transcriptome and proteome level have identified signatures, which might further clarify the molecular differences of RCC subtypes and might allow the identification of suitable therapeutic targets and diagnostic/prognostic biomarkers, but none thereof has yet been implemented in routine clinical use. The increasing knowledge regarding the functional role of noncoding microRNA (miR) in physiological, developmental, and pathophysiological processes by shaping the protein expression profile might provide an important link to improve the definition of disease-relevant regulatory networks. Taking into account that miR profiling of RCC and NN provides robust signatures discriminating between malignant and normal tissues, the concept of evaluating and scoring miR/protein pairs might represent a strategy for the selection and prioritization of potential biomarkers and their translation into practical use.

GAP promoter library for fine-tuning of gene expression in Pichia pastoris

A library of engineered promoters of various strengths is a useful genetic tool that enables the fine-tuning and precise control of gene expression across a continuum of broad expression levels. The methylotrophic yeast Pichia pastoris is a well-established expression host with a large academic and industrial user base. To facilitate manipulation of gene expression spanning a wide dynamic range in P. pastoris, we created a functional promoter library through mutagenesis of the constitutive GAP promoter. Using yeast-enhanced green fluorescent protein (yEGFP) as the reporter, 33 mutants were chosen to form the functional promoter library. The 33 mutants spanned an activity range between ∼0.6% and 19.6-fold of the wild-type promoter activity with an almost linear fluorescence intensity distribution. After an extensive characterization of the library, the broader applicability of the results obtained with the yEGFP reporter was confirmed using two additional reporters (β-galactosidase and methionine adenosyltransferase [MAT]) at the transcription and enzyme activity levels. Furthermore, the utility of the promoter library was tested by investigating the influence of heterologous MAT gene expression levels on cell growth and S-adenosylmethionine (SAM) production. The extensive characterization of the promoter strength enabled identification of the optimal MAT activity (around 1.05 U/mg of protein) to obtain maximal volumetric SAM production. The promoter library permits precise control of gene expression and quantitative assessment that correlates gene expression level with physiologic parameters. Thus, it is a useful toolbox for both basic and applied research in P. pastoris.

LC-MS based serum metabonomic analysis for renal cell carcinoma diagnosis, staging, and biomarker discovery

A LC-MS based method, which utilizes both reversed-performance (RP) chromatography and hydrophilic interaction chromatography (HILIC) separations, has been carried out in conjunction with multivariate data analysis to discriminate the global serum profiles of renal cell carcinoma (RCC) patients and healthy controls. The HILIC was found necessary for a comprehensive serum metabonomic profiling as well as RP separation. The feasibility of using serum metabonomics for the diagnosis and staging of RCC has been evaluated. One-hundred percent sensitivity in detection has been achieved, and a satisfactory clustering between the early stage and advanced-stage patients is observed. The results suggest that the combination of LC-MS analysis with multivariate statistical analysis can be used for RCC diagnosis and has potential in the staging of RCC. The MS/MS experiments have been carried out to identify the biomarker patterns that made great contribution to the discrimination. As a result, 30 potential biomarkers for RCC are identified. It is possible that the current biomarker patterns are not unique to RCC but just the result of any malignancy disease. To further elucidate the pathophysiology of RCC, related metabolic pathways have been studied. RCC is found to be closely related to disturbed phospholipid catabolism, sphingolipid metabolism, phenylalanine metabolism, tryptophan metabolism, fatty acid beta-oxidation, cholesterol metabolism, and arachidonic acid metabolism.

Breaking through a plateau in renal cell carcinoma therapeutics: development and incorporation of biomarkers

With the Food and Drug Administration approval of 6 novel targeted agents since December 2005 and limited comparative trials to discern relative efficacy, the treatment of metastatic renal cell carcinoma (RCC) has become immensely complex. The research community must look to novel ways in which to identify appropriate candidates for selected targeted therapies; one potential strategy is the use of clinical and molecular biomarkers. A growing body of knowledge-related von Hippel Lindau-driven pathways in this disease has highlighted the potential role of hypoxia-inducible factor subtypes in distinguishing RCC patients clinically. Techniques applied in other malignancies, such as gene expression and proteomic profiling, may also ultimately allow for clinical stratification. An emerging understanding of immunologic phenomena that may affect cancer progression (i.e., tumor infiltration by CD68 lymphocytes, memory T-cells, etc.) has unveiled a number of other potential biomarkers of response. Several vascular endothelial growth factor receptor-directed therapies classically thought to function as antiangiogenics may also have complex effects upon the tumor microenvironment including the associated immune cell milieu. As such, immunologic parameters could potentially predict response to current therapies. Finally, clinical biomarkers, such as hypertension, may predict the efficacy of several currently available targeted agents, although implementation of such biomarkers remains challenging. Herein, the clinical relevance of putative RCC biomarkers is examined in detail.

Proteome analysis of schizophrenia brain tissue

OBJECTIVES

Proteome analysis has emerged as a promising strategy to the identification of potential biomarkers and to further confirm the importance of certain pathways in the schizophrenia (SCZ) pathophysiology. Reviewing the results of 13 proteome studies in SCZ brain tissue, we aimed to provide information regarding potential proteins biomarkers as well as information about the pathophysiology of the disease.

METHODS AND RESULTS

Using two-dimensional gel electrophoresis and shotgun mass spectrometry, 31 proteins were consistently found differentially expressed in the brains of SCZ patients. The most frequent protein alterations reported in SCZ were related to brain energy metabolism, brain plasticity, and synaptic function, processes that are thought to belong to the core of the biology of this disease. The recurrent identification and validation of inter-related protein clusters, determined in different samples and approaches, strongly reinforces the putative involvement of certain pathways in SCZ.

CONCLUSIONS

The availability of reliable markers not only paves the way to the development of new therapeutic strategies but also points out the possibility of their use as peripheral blood markers that may potentially contribute to the early SCZ detection and early therapeutic intervention, both of which can reduce the social and cognitive consequences of the disease.

Primary cell cultures from human renal cortex and renal-cell carcinoma evidence a differential expression of two spliced isoforms of Annexin A3

Primary cell cultures from renal cell carcinoma (RCC) and normal renal cortex tissue of 60 patients have been established, with high efficiency (more than 70%) and reproducibility, and extensively characterized. These cultures composed of more than 90% of normal or tumor tubular cells have been instrumental for molecular characterization of Annexin A3 (AnxA3), never extensively studied before in RCC cells although AnxA3 has a prognostic relevance in some cancer and it has been suggested to be involved in the hypoxia-inducible factor-1 pathway. Western blot analysis of 20 matched cortex/RCC culture lysates showed two AnxA3 protein bands of 36 and 33 kDa, and two-dimensional Western blot evidenced several specific protein spots. In RCC cultures the 36-kDa isoform was significantly down-regulated and the 33-kDa isoform up-regulated. Furthermore, the inversion of the quantitative expression pattern of two AnxA3 isoforms in tumor cultures correlate with hypoxia-inducible factor-1alpha expression. The total AnxA3 protein is down-regulated in RCC cultures as confirmed also in tissues by tissue microarray. Two AnxA3 transcripts that differ for alternative splicing of exon III have been also detected. Real-time PCR quantification in 19 matched cortex/RCC cultures confirms the down-regulation of longer isoform in RCC cells. The characteristic expression pattern of AnxA3 in normal and tumor renal cells, documented in our primary cultures, may open new insight in RCC management.

Systematic comparative protein expression profiling of clear cell renal cell carcinoma: a pilot study based on the separation of tissue specimens by two-dimensional gel electrophoresis

Proteome-based technologies represent powerful tools for the analysis of protein expression profiles, including the identification of potential cancer candidate biomarkers. Thus, here we provide a comprehensive protein expression map for clear cell renal cell carcinoma established by systematic comparative two-dimensional gel electrophoresis-based protein expression profiling of 16 paired tissue systems comprising clear cell renal cell carcinoma lesions and corresponding tumor-adjacent renal epithelium using overlapping narrow pH gradients. This approach led to the mapping of 348 distinct spots corresponding to 248 different protein identities. By implementing restriction criteria concerning their detection frequency and overall regulation mode, 28 up- and 56 down-regulated single target spots were considered as potential candidate biomarkers. Based on their gene ontology information, these differentially expressed proteins were classified into distinct functional groups and according to their cellular distribution. Moreover, three representative members of this group, namely calbindin, gelsolin, and heart fatty acid-binding protein, were selected, and their expression pattern was analyzed by immunohistochemistry using tissue microarrays. Thus, this pilot study provides a significant update of the current renal cell carcinoma map and defines a number of differentially expressed proteins, but both their potential as candidate biomarkers and clinical relevance has to be further explored in tissues and for body fluids like serum and urine.