Deciphering Urogenital Cancers through Proteomic Biomarkers: A Systematic Review and Meta-Analysis

Urogenital cancers, which include prostate, bladder, and kidney malignancies, exert a substantial impact on global cancer-related morbidity and mortality. Proteomic biomarkers, emerging as valuable tools, aim to enhance early detection, prognostic accuracy, and the development of personalized therapeutic strategies. This study undertook a comprehensive systematic review and meta-analysis of the existing literature investigating the role and potential of proteomic biomarkers in plasma, tissue, and urine samples in urogenital cancers. Our extensive search across several databases identified 1879 differentially expressed proteins from 37 studies, signifying their potential as unique biomarkers for these cancers. A meta-analysis of the significantly differentially expressed proteins was executed, accentuating the findings through visually intuitive volcano plots. A functional enrichment analysis unveiled their significant involvement in diverse biological processes, including signal transduction, immune response, cell communication, and cell growth. A pathway analysis highlighted the participation of key pathways such as the nectin adhesion pathway, TRAIL signaling pathway, and integrin signaling pathways. These findings not only pave the way for future investigations into early detection and targeted therapeutic approaches but also underscore the fundamental role of proteomics in advancing our understanding of the molecular mechanisms underpinning urogenital cancer pathogenesis. Ultimately, these findings hold remarkable potential to significantly enhance patient care and improve clinical outcomes.

Carnosine dipeptidase II (CNDP2) protects cells under cysteine insufficiency by hydrolyzing glutathione-related peptides

The knockout (KO) of the cystine transporter xCT causes ferroptosis, a type of iron-dependent necrotic cell death, in mouse embryonic fibroblasts, but this does not occur in macrophages. In this study, we explored the gene that supports cell survival under a xCT deficiency using a proteomics approach. Analysis of macrophage-derived peptides that were tagged with iTRAQ by liquid chromatography-mass spectrometry revealed a robust elevation in the levels of carnosine dipeptidase II (CNDP2) in xCT KO macrophages. The elevation in the CNDP2 protein levels was confirmed by immunoblot analyses and this elevation was accompanied by an increase in hydrolytic activity towards cysteinylglycine, the intermediate degradation product of glutathione after the removal of the γ-glutamyl group, in xCT KO macrophages. Supplementation of the cystine-free media of Hepa1-6 cells with glutathione or cysteinylglycine extended their survival, whereas the inclusion of bestatin, an inhibitor of CNDP2, counteracted the effects of these compounds. We established CNDP2 KO mice by means of the CRISPR/Cas9 system and found a decrease in dipeptidase activity in the liver, kidney, and brain. An acetaminophen overdose (350 mg/kg) showed not only aggravated hepatic damage but also renal injury in the CNDP2 KO mice, which was not evident in the wild-type mice that were receiving the same dose. The aggravated renal damage in the CNDP2 KO mice was consistent with the presence of abundant levels of CNDP2 in the kidney, the organ prone to developing ferroptosis. These collective data imply that cytosolic CNDP2, in conjugation with the removal of the γ-glutamyl group, recruits Cys from extracellular GSH and supports redox homeostasis of cells, particularly in epithelial cells of proximal tubules that are continuously exposed to oxidative insult from metabolic wastes that are produced in the body.

Quantitative global proteome and phosphorylome analyses reveal potential biomarkers in kidney cancer

Currently, high‑throughput quantitative proteomic and transcriptomic approaches have been widely used for exploring the molecular mechanisms and acquiring biomarkers for cancers. Our study aimed to illuminate the multi-dimensional molecular mechanisms underlying renal cell carcinoma (RCC) via investigating the quantitative global proteome and the profile of phosphorylation. A total of 5,428 proteins and 8,632 phosphorylation sites were quantified in RCC tissues, with 709 proteins and 649 phosphorylation sites found to be altered in expression compared with the matched adjacent non‑tumor tissues. These differentially expressed proteins were mainly involved in metabolic process terms involving the glycolysis pathway, oxidative phosphorylation and fatty acid metabolism which have been considered to be a potential mechanism of RCC progression. Moreover, phosphorylation analysis indicated that these upregulated phosphorylated proteins are implicated in the glucagon signaling pathway and cholesterol metabolism, while the downregulated phosphorylated proteins were found to be predominantly involved in glycolysis, the pentose phosphate pathway, carbon metabolism and biosynthesis of amino acids. In addition, several new candidate proteins, CD14, MPO, NCF2, SOD2, PARP1, were found to be upregulated and MUT, ACADM, PCK1 were downregulated in RCC. These proteins may be recognized as new biomarkers for RCC. These findings could broaden our insight into the underlying molecular mechanisms of RCC and identify candidate biomarkers for the treatment of RCC.

CNDP2 Acts as an Activator for Human Ovarian Cancer Growth and Metastasis via the PI3K/AKT Pathway

Introduction:

The mechanism of tumorigenesis and metastasis of ovarian cancer has not yet been elucidated. This study aimed to investigate the role and molecular mechanism of cytosolic nonspecific dipeptidase 2 in tumorigenesis and metastasis.

Methods:

Cytosolic nonspecific dipeptidase 2 expression in human ovarian cancer tissues and cell lines was assessed with methyl thiazolyl tetrazolium (MTT), clone formation, and transwell assays performed to evaluate the ability of ovarian cancer cells to proliferate and migrate. Nude mice tumor formation experiments were also performed by subcutaneously injecting cells with stable cytosolic nonspecific dipeptidase 2 knockdown and control SKOV3 cells into BALB/c female nude mice to detect changes in PI3K/AKT pathway-related proteins by Western blotting.

Results:

Cytosolic nonspecific dipeptidase 2 was highly expressed in human ovarian cancer tissues, with its expression associated with pathological data, including ovarian cancer metastasis. A cytosolic nonspecific dipeptidase 2 stable knockdown or ectopic expression ovarian cancer cell model was established and demonstrated that cytosolic nonspecific dipeptidase 2 could promote the proliferation of ovarian cancer cells. Transwell cell migration and invasion assays confirmed that cytosolic nonspecific dipeptidase 2 enhanced cell metastasis in ovarian cancer. Furthermore, in vivo xenograft experiments demonstrated that cytosolic nonspecific dipeptidase 2 can promote the development and progression of ovarian cancer, increasing the expression of phosphorylated PI3K and AKT.

Conclusions:

Cytosolic nonspecific dipeptidase 2 promotes the occurrence and development of ovarian cancer through the PI3K/AKT signaling pathway.

Searching for prognostic biomarkers for small renal masses in the urinary proteome

Renal cell carcinoma (RCC) is frequently diagnosed incidentally as an early-stage small renal mass (SRM; pT1a, ≤4 cm). Overtreatment of patients with benign or clinically indolent SRMs is increasingly common and has resulted in a recent shift in treatment recommendations. There are currently no available biomarkers that can accurately predict clinical behavior. Therefore, we set out to identify early biomarkers of RCC progression. We employed a quantitative label-free liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) proteomics approach and targeted parallel-reaction monitoring to identify and validate early, noninvasive urinary biomarkers for RCC-SRMs. In total, we evaluated 115 urine samples, including 33 renal oncocytoma (≤4 cm) cases, 30 progressive and 26 nonprogressive clear cell RCC (ccRCC)-SRM cases, in addition to 26 healthy controls. We identified six proteins, which displayed significantly elevated expression in clear cell RCC-SRMs (ccRCC-SRMs) relative to healthy controls. Proteins C12ORF49 and EHD4 showed significantly elevated expression in ccRCC-SRMs compared to renal oncocytoma (≤4 cm). Additionally, proteins EPS8L2, CHMP2A, PDCD6IP, CNDP2 and CEACAM1 displayed significantly elevated expression in progressive relative to nonprogressive ccRCC-SRMs. A two-protein signature (EPS8L2 and CCT6A) showed significant discriminatory ability (areas under the curve: 0.81, 95% CI: 0.70-0.93) in distinguishing progressive from nonprogressive ccRCC-SRMs. Patients (Stage I-IV) with EPS8L2 and CCT6A mRNA alterations showed significantly shorter overall survival (p = 1.407 × 10^-6 ) compared to patients with no alterations. Our in-depth proteomic analysis identified novel biomarkers for early-stage RCC-SRMs. Pretreatment characterization of urinary proteins may provide insight into early RCC progression and could potentially help assign patients to appropriate management strategies.

A toolset to study functions of Cytosolic non-specific dipeptidase 2 (CNDP2) using Drosophila as a model organism

Background

Expression of the CNDP2 gene is frequently up- or down-regulated in different types of human cancers. However, how the product of this gene is involved in cell growth and proliferation is poorly understood. Moreover, our knowledge of the functions of the CNDP2 orthologs in well-established model organisms is scarce. In particular, the function of the D. melanogaster ortholog of CNDP2, encoded by the CG17337 gene (hereafter referred to as dCNDP2), is still unknown.

Results

This study was aimed at developing a set of genetic and molecular tools to study the roles of dCNDP2. We generated a dCNDP2 null mutation (hereafter ∆dCNDP2) using CRISPR/Cas9-mediated homologous recombination (HR) and found that the ∆dCNDP2 mutants are homozygous viable, morphologically normal and fertile. We also generated transgenic fly lines expressing eGFP-tagged and non-tagged dCNDP2 protein, all under the control of the UAS promoter, as well as polyclonal antibodies specific to dCNDP2. Using these tools, we demonstrate that only one of the two predicted dCNDP2 isoforms is expressed throughout the different tissues tested. dCNDP2 was detected in both the cytoplasm and the nucleus, and was found to be associated with multiple sites in the salivary gland polytene chromosomes.

Conclusions

The dCNDP2 gene is not essential for fly viability under standard laboratory conditions. The subcellular localization pattern of dCNDP2 suggests that this protein might have roles in both the cytoplasm and the nucleus. The genetic and molecular tools developed in this study will allow further functional characterization of the conserved CNDP2 protein using D. melanogaster as a model system.

Electronic supplementary material

The online version of this article (10.1186/s12863-019-0726-z) contains supplementary material, which is available to authorized users.

Identification of Coiled-Coil Domain-Containing Protein 180 and Leucine-Rich Repeat-Containing Protein 4 as Potential Immunohistochemical Markers for Liposarcoma Based on Proteomic Analysis Using Formalin-Fixed, Paraffin-Embedded Tissue

Recent technical improvements in both mass spectrometry and protein extraction have made it possible to use formalin-fixed, paraffin-embedded (FFPE) tissues for proteome analysis. In this study, comparable proteome analysis of FFPE tissues revealed multiple candidate marker molecules for differentiating atypical lipomatous tumor/well-differentiated liposarcoma (ALT/WDL) from lipoma. A total of 181 unique proteins were identified for ALT/WDL. Of the identified proteins, coiled-coil domain-containing protein 180 (CCDC180) and leucine-rich repeat-containing protein 4 (LRRC4) were studied as candidate markers of ALT/WDL. CCDC180 and LRRC4 immunohistochemistry clearly stained tumor cells of ALT/WDL and dedifferentiated liposarcoma and could differentiate them from lipoma with high accuracy. Cell biological methods were used to further examine the expression of the candidate marker molecules in liposarcoma cells. In liposarcoma cells, knockdown of CCDC180 and LRRC4 inhibited cell proliferation. CCDC180 inhibited cell migration, invasion, and apoptosis resistance in WDL cells. Adipogenic differentiation suppressed the expression of CCDC180 and LRRC4 in WDL cells. These results indicated that LRRC4 and CCDC180 are novel immunohistochemical markers for differentiating ALT/WDLs. Their expression was associated with adipocyte differentiation and contributed to malignant potentials of WDL cells. Proteome analysis using a standard stock of FFPE tissues can reveal novel biomarkers for various diseases, which contributes to the progress of molecular pathology.

Urinary RKIP/p-RKIP is a potential diagnostic and prognostic marker of clear cell renal cell carcinoma

Clear cell Renal Cell Carcinoma (ccRCC) causes over 13,000 deaths each year, and about 20,000 new cases/year in Europe. In most cases, the causes are unknown and, most importantly, there are no reliable biomarkers for the diagnosis and prognosis of this disease. The search for sensitive biomarkers for early diagnosis and prognosis of clear cell Renal Cell Carcinoma (ccRCC) is currently a fast growing field. We carried out proteomics analysis of 93 urinary samples of healthy subjects (HS) and patients affected by ccRCC, prostate cancer (PCa) and chronic kidney disease (CKD), that was able to successfully distinguish each group.

The most significant candidate biomarker was identified by mass spectrometry as Raf Kinase Inhibitor Protein (RKIP), a key regulator of cell signaling, already described in several cancer types as a metastasis suppressor. By combining ELISA, immunoblotting and tissue microarray, we demonstrated that, in ccRCC, urinary excretion of RKIP and its phosphorylated form (p-RKIP) reflected the tissue expression of these putative biomarkers. Baseline urinary RKIP, evaluated in an independent cohort of 56 ccRCC patients and 28 HS, successfully distinguished both groups and, most importantly, a cut-off value of 10 ng/mg/g Pr/uCr enabled a highly accurate prediction of Cancer-specific survival and Progression-free survival. Furthermore, p-RKIP was totally undetectable in both tissue and urine samples of ccRCC, showing a great potential for diagnostics purposes.

Our data indicate that urinary RKIP encompasses both the unphosphorylated and the phosphorylated form and that their combined evaluation can help in the diagnosis and prognosis of ccRCC.

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.

In vivo pharmacokinetics, biodistribution and the anti-tumor effect of cyclic RGD-modified doxorubicin-loaded polymers in tumor-bearing mice

In our previous study, we successfully produced and characterized a multifunctional drug delivery system with doxorubicin (RC/GO/DOX), which was based on graphene oxide (GO) and cyclic RGD-modified chitosan (RC). Its characteristics include: pH-responsiveness, active targeting of hepatocarcinoma cells, and efficient loading with controlled drug release. Here, we report the pharmacokinetics, biodistribution, and anti-tumor efficacy of RC/GO/DOX polymers in tumor-bearing nude mice. The objective of this study is to assess its targeting potential for tumors. Pharmacokinetic and biodistribution profiles demonstrated that tumor accumulation of RC/GO/DOX polymers was almost three times higher than the others, highlighting the efficacy of the active targeting strategy. Furthermore, the tumor inhibition rate of RC/GO/DOX polymers was 56.64%, 2.09 and 2.93 times higher than that of CS/GO/DOX polymers (without modification) and the DOX solution, respectively. Anti-tumor efficacy results indicated that the tumor growth was better controlled by RC/GO/DOX polymers than the others. Hematoxylin and eosin (H&E) staining showed remarkable changes in tumor histology. Compared with the saline group, the tumor section from the RC/GO/DOX group revealed a marked increase in the quantity of apoptotic and necrotic cells, and a reduction in the quantity of the blood vessels. Together, these studies show that this new system could be regarded as a suitable form of DOX-based treatment of the hepatocellular carcinoma.

Up-regulation of CNDP2 facilitates the proliferation of colon cancer

BACKGROUND

Cytosolic nonspecific dipetidase (CN2) belongs to the family of M20 metallopeptidases. It was stated in previous articles that higher expression levels of CN2 were observed in renal cell carcinoma and breast cancer. Our study explored the correlation between CN2 and colon carcinogenesis.

METHODS

We analysed the relationship between 183 patients clinicopathological characteristics and its CN2 expression. To detect the levels of CN2 in colon cancer cell lines and colon cancer tissues by western blot. To verify cell proliferation in colon cancer cells with knockdown of CNDP2 and explore the causes of these phenomena.

RESULTS

The expression levels of CN2 in clinical colon tumors and colon cancer cell lines were significantly higher than that in normal colon mucosa and colon cell lines. The difference in CN2 levels was associated with tumor location (right- and left-sided colon cancer), but there was no significant association with age, gender, tumor size, tumor grade, tumor stage or serum carcinoembryonic antigen (CEA). Knockdown of CNDP2 inhibited cell proliferation, blocked cell cycle progression and retarded carcinogenesis in an animal model. The signaling pathway through which knockdown of CNDP2 inhibited cell proliferation and tumorigenesis involved in EGFR, cyclin B1 and cyclin E.

CONCLUSIONS

Knockdown of CNDP2 can inhibit the proliferation of colon cancer in vitro and retarded carcinogenesis in vivo.

Underexpressed CNDP2 participates in gastric cancer growth inhibition through activating the MAPK signaling pathway

Increasing evidence suggests that cytosolic non-specific dipeptidase 2 (CNDP2) appears to do more than just perform an enzymatic activity; it is functionally important in cancers as well. Here, we show that the expression of CNDP2 is commonly down-regulated in gastric cancer tissues. The ectopic expression of CNDP2 resulted in significant inhibition of cell proliferation, induction of cell apoptosis and cell cycle arrest, and suppressed gastric tumor growth in nude mice. We further revealed that the reintroduction of CNDP2 transcriptionally upregulated p38 and activated c-Jun NH2-terminal kinase (JNK), whereas the loss of CNDP2 increased the phosphorylation of extracellular signal-related kinase (ERK). These results suggest that CNDP2 acts as a functional tumor suppressor in gastric cancer via activation of the mitogen-activated protein kinase (MAPK) pathway.

Quantitative proteomics approach to screening of potential diagnostic and therapeutic targets for laryngeal carcinoma

To discover candidate biomarkers for diagnosis and detection of human laryngeal carcinoma and explore possible mechanisms of this cancer carcinogenesis, two-dimensional strong cation-exchange/reversed-phase nano-scale liquid chromatography/mass spectrometry analysis was used to identify differentially expressed proteins between the laryngeal carcinoma tissue and the adjacent normal tissue. As a result, 281 proteins with significant difference in expression were identified, and four differential proteins, Profilin-1 (PFN1), Nucleolin (NCL), Cytosolic non-specific dipeptidase (CNDP2) and Mimecan (OGN) with different subcellular localization were selectively validated. Semiquantitative RT-PCR and Western blotting were performed to detect the expression of the four proteins employing a large collection of human laryngeal carcinoma tissues, and the results validated the differentially expressed proteins identified by the proteomics. Furthermore, we knocked down PFN1 in immortalized human laryngeal squamous cell line Hep-2 cells and then the proliferation and metastasis of these transfected cells were measured. The results showed that PFN1 silencing inhibited the proliferation and affected the migration ability of Hep-2 cells, providing some new insights into the pathogenesis of PFN1 in laryngeal carcinoma. Altogether, our present data first time show that PFN1, NCL, CNDP2 and OGN are novel potential biomarkers for diagnosis and therapeutic targets for laryngeal carcinoma, and PFN1 is involved in the metastasis of laryngeal carcinoma.

Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling

Background:

Proteomics-based approaches for biomarker discovery are promising strategies used in cancer research. We present state-of-art label-free quantitative proteomics method to assess proteome of renal cell carcinoma (RCC) compared with noncancer renal tissues.

Methods:

Fresh frozen tissue samples from eight primary RCC lesions and autologous adjacent normal renal tissues were obtained from surgically resected tumour-bearing kidneys. Proteins were extracted by complete solubilisation of tissues using filter-aided sample preparation (FASP) method. Trypsin digested proteins were analysed using quantitative label-free proteomics approach followed by data interpretation and pathways analysis.

Results:

A total of 1761 proteins were identified and quantified with high confidence (MASCOT ion score threshold of 35 and P-value <0.05). Of these, 596 proteins were identified as differentially expressed between cancer and noncancer tissues. Two upregulated proteins in tumour samples (adipose differentiation-related protein and Coronin 1A) were further validated by immunohistochemistry. Pathway analysis using IPA, KOBAS 2.0, DAVID functional annotation and FLink tools showed enrichment of many cancer-related biological processes and pathways such as oxidative phosphorylation, glycolysis and amino acid synthetic pathways.

Conclusions:

Our study identified a number of differentially expressed proteins and pathways using label-free proteomics approach in RCC compared with normal tissue samples. Two proteins validated in this study are the focus of on-going research in a large cohort of patients.

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.

Mining protein lists from proteomics studies: applications for drug discovery

IMPORTANCE OF THE FIELD

In recent years, proteomics has become a common technique applied to a wide spectrum of scientific problems, including the identification of diagnostic biomarkers, monitoring the effects of drug treatments or identification of chemical properties of a protein or a drug. Although being significantly different in scientific essence, the ultimate result of the majority of proteomics studies is a protein list. Thousands of independent proteomics studies have reported protein lists in various functional contexts.

AREAS COVERED IN THIS REVIEW

We review here the spectrum of scientific problems where proteomics technology was applied recently to deliver protein lists. The available bioinformatics methods commonly used to understand the properties of the protein lists are compared.

WHAT THE READER WILL GAIN

The types and common functional properties of the reported protein lists are discussed. The range of scientific problems where this knowledge could be potentially helpful with a focus on drug discovery issues is explored.

TAKE HOME MESSAGE

Reported protein lists represent a valuable resource which can be used for a variety of goals, ranging from biomarkers discovery to identification of novel therapeutic implications of known drugs.

PGRN is a key adipokine mediating high fat diet-induced insulin resistance and obesity through IL-6 in adipose tissue

Adipose tissue secretes adipokines that mediate insulin resistance, a characteristic feature of obesity and type 2 diabetes. By differential proteome analysis of cellular models of insulin resistance, we identified progranulin (PGRN) as an adipokine induced by TNF-α and dexamethasone. PGRN in blood and adipose tissues was markedly increased in obese mouse models and was normalized with treatment of pioglitazone, an insulin-sensitizing agent. Ablation of PGRN (Grn(-/-)) prevented mice from high fat diet (HFD)-induced insulin resistance, adipocyte hypertrophy, and obesity. Grn deficiency blocked elevation of IL-6, an inflammatory cytokine, induced by HFD in blood and adipose tissues. Insulin resistance induced by chronic administration of PGRN was suppressed by neutralizing IL-6 in vivo. Thus, PGRN is a key adipokine that mediates HFD-induced insulin resistance and obesity through production of IL-6 in adipose tissue, and may be a promising therapeutic target for obesity.

Classification of unknown primary tumors with a data-driven method based on a large microarray reference database

We present a new method to analyze cancer of unknown primary origin (CUP) samples. Our method achieves good results with classification accuracy (88% leave-one-out cross validation for primary tumors from 56 categories, 78% for CUP samples), and can also be used to study CUP samples on a gene-by-gene basis. It is not tied to any a priori defined gene set as many previous methods, and is adaptable to emerging new information.

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.

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.

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.

KEGG spider: interpretation of genomics data in the context of the global gene metabolic network

KEGG spider is a web-based tool for interpretation of experimentally derived gene lists in order to gain understanding of metabolism variations at a genomic level. KEGG spider implements a 'pathway-free' framework that overcomes a major bottleneck of enrichment analyses: it provides global models uniting genes from different metabolic pathways. Analyzing a number of experimentally derived gene lists, we demonstrate that KEGG spider provides deeper insights into metabolism variations in comparison to existing methods.