Differential protein expressions in renal cell carcinoma: new biomarker discovery by mass spectrometry

Absolute quantitative proteomics using the total protein approach to identify novel clinical immunohistochemical markers in renal neoplasms

BACKGROUND

Renal neoplasms encompass a variety of malignant and benign tumors, including many with shared characteristics. The diagnosis of these renal neoplasms remains challenging with currently available tools. In this work, we demonstrate the total protein approach (TPA) based on high-resolution mass spectrometry (MS) as a tool to improve the accuracy of renal neoplasm diagnosis.

METHODS

Frozen tissue biopsies of human renal tissues [clear cell renal cell carcinoma (n = 7), papillary renal cell carcinoma (n = 5), chromophobe renal cell carcinoma (n = 5), and renal oncocytoma (n = 5)] were collected for proteome analysis. Normal adjacent renal tissue (NAT, n = 5) was used as a control. Proteins were extracted and digested using trypsin, and the digested proteomes were analyzed by label-free high-resolution MS (nanoLC-ESI-HR-MS/MS). Quantitative analysis was performed by comparison between protein abundances of tumors and NAT specimens, and the label-free and standard-free TPA was used to obtain absolute protein concentrations.

RESULTS

A total of 205 differentially expressed proteins with the potential to distinguish the renal neoplasms were found. Of these proteins, a TPA-based panel of 24, including known and new biomarkers, was selected as the best candidates to differentiate the neoplasms. As proof of concept, the diagnostic potential of PLIN2, TUBB3, LAMP1, and HK1 was validated using semi-quantitative immunohistochemistry with a total of 128 samples assessed on tissue micro-arrays.

CONCLUSIONS

We demonstrate the utility of combining high-resolution MS and the TPA as potential new diagnostic tool in the pathology of renal neoplasms. A similar TPA approach may be implemented in any cancer study with solid biopsies.

Identification of Prognostic Genes in Neuroblastoma in Children by Weighted Gene Coexpression Network Analysis

Background

Neuroblastoma is a malignant neuroendocrine tumor from the sympathetic nervous system, the most common extracranial tumor in children. Identifying potential prognostic markers of neuroblastoma can provide clues for early diagnosis, recurrence, and treatment.

Methods

RNA sequence data and clinical features of 147 neuroblastomas were obtained from the TARGET (Therapeutically Applicable Research to Generate Effective Treatments project) database. Application weighted gene coexpression network analysis (WGCNA) was used to construct a free-scale gene coexpression network, to study the interrelationship between its potential modules and clinical features, and to identify hub genes in the module. We performed Lasso regression and Cox regression analyses to identify the three most important genes and develop a new prognostic model. Data from the GSE85047 cohort verified the predictive accuracy of the prognostic model.

Results

14 coexpression modules were constructed using WGCNA. Brown coexpression modules were found to be significantly associated with disease survival status. Multivariate Cox analysis was performed on genes from univariate Cox regression and Lasso regression analyses using the Cox proportional hazards regression model. Finally, we constructed a three-gene prognostic model: risk score = (0.003812659∗CKB) + (−0.152376975∗expDST) + (0.032032815∗expDUT). The prognosis of samples in the high-risk group was significantly poorer than that of samples in the low-risk group (P=1.225e − 06). The risk model was also regarded as an independent predictor of prognosis (HR = 1.632; 95% CI = 1.391–1.934; P < 0.001).

Conclusion

Our study constructed a neuroblastoma coexpressing gene module and identified a prognostic potential risk model for prognosis in neuroblastoma.

Exploiting the HSP60/10 chaperonin system as a chemotherapeutic target for colorectal cancer

Over the past few decades, an increasing variety of molecular chaperones have been investigated for their role in tumorigenesis and as potential chemotherapeutic targets; however, the 60 kDa Heat Shock Protein (HSP60), along with its HSP10 co-chaperone, have received little attention in this regard. In the present study, we investigated two series of our previously developed inhibitors of the bacterial homolog of HSP60/10, called GroEL/ES, for their selective cytotoxicity to cancerous over non-cancerous colorectal cells. We further developed a third "hybrid" series of analogs to identify new candidates with superior properties than the two parent scaffolds. Using a series of well-established HSP60/10 biochemical screens and cell-viability assays, we identified 24 inhibitors (14%) that exhibited > 3-fold selectivity for targeting colorectal cancer over non-cancerous cells. Notably, cell viability EC₅₀ results correlated with the relative expression of HSP60 in the mitochondria, suggesting a potential for this HSP60-targeting chemotherapeutic strategy as emerging evidence indicates that HSP60 is up-regulated in colorectal cancer tumors. Further examination of five lead candidates indicated their ability to inhibit the clonogenicity and migration of colorectal cancer cells. These promising results are the most thorough analysis and first reported instance of HSP60/10 inhibitors being able to selectively target colorectal cancer cells and highlight the potential of the HSP60/10 chaperonin system as a viable chemotherapeutic target.

Quantitative Proteomics Analysis for the Identification of Differential Protein Expression in Calf Muscles between Young and Old SD Rats Using Mass Spectrometry

Aging is associated with loss of muscle mass and strength that leads to a condition termed sarcopenia. Impaired conditions, morbidity, and malnutrition are the factors of devaluation of muscle fibers in aged animals. Satellite cells play an important role in maintaining muscle homeostasis during tissue regeneration and repair. Proteomic profiling on the skeletal muscle tissues of different age group rats helps to determine the differentially expressed (DE) proteins, which may eventually lead to the development of biomarkers in treating the conditions of sarcopenia. In this study, nanoscale liquid chromatography coupled to tandem mass spectrometry (nano-LC-MS/MS) analysis was implemented in the calf tissues of young and old groups of rats. The mass spectrometry (MS) analysis revealed the presence of 335 differentially expressed proteins between the two different age conditions, among which those based on log-fold change 25 proteins were upregulated and 77 were downregulated. The protein-protein interaction network analysis revealed 18 upregulated proteins with three distinct interconnected networks and 57 downregulated proteins with two networks. Further, gene ontology (GO) enrichment analysis showed the biological process, cellular component, and molecular function of the differential proteins. Pathway enrichment analysis of the DE proteins identified nine significantly enriched pathways with a list of eight significant genes (Cryab, Hspb2, Acat1, Ak1, Adssl1, Anxa5, Gys1, Ogdh, Gc, and Adssl1). Quantification of significant genes by quantitative real-time polymerase chain reaction (qRT-PCR) confirmed the downregulation at the mRNA level. Western blot analysis of their protein expression showed concordant results on two candidate proteins (Ogdh and annexin 5) confirming their differential regulation between the two age groups of rats. Thus, these proteomic approaches on young and aged rats provide insights into the development of protein targets in the treatment of sarcopenia (muscle loss).

Proteomic approaches for characterizing renal cell carcinoma

Renal cell carcinoma is among the top 15 most commonly diagnosed cancers worldwide, comprising multiple sub-histologies with distinct genomic, proteomic, and clinicopathological features. Proteomic methodologies enable the detection and quantitation of protein profiles associated with the disease state and have been explored to delineate the dysregulated cellular processes associated with renal cell carcinoma. In this review we highlight the reports that employed proteomic technologies to characterize tissue, blood, and urine samples obtained from renal cell carcinoma patients. We describe the proteomic approaches utilized and relate the results of studies in the larger context of renal cell carcinoma biology. Moreover, we discuss some unmet clinical needs and how emerging proteomic approaches can seek to address them. There has been significant progress to characterize the molecular features of renal cell carcinoma; however, despite the large-scale studies that have characterized the genomic and transcriptomic profiles, curative treatments are still elusive. Proteomics facilitates a direct evaluation of the functional modules that drive pathobiology, and the resulting protein profiles would have applications in diagnostics, patient stratification, and identification of novel therapeutic interventions.

LC-MS-Based Plasma Metabolomics and Lipidomics Analyses for Differential Diagnosis of Bladder Cancer and Renal Cell Carcinoma

Bladder cancer (BC) and Renal cell carcinoma(RCC) are the two most frequent genitourinary cancers in China. In this study, a comprehensive liquid chromatography-mass spectrometry (LC-MS) based method, which utilizes both plasma metabolomics and lipidomics platform, has been carried out to discriminate the global plasma profiles of 64 patients with BC, 74 patients with RCC, and 141 healthy controls. Apparent separation was observed between cancer (BC and RCC) plasma samples and controls. The area under the receiving operator characteristic curve (AUC) was 0.985 and 0.993 by plasma metabolomics and lipidomics, respectively (external validation group: AUC was 0.944 and 0.976, respectively). Combined plasma metabolomics and lipidomics showed good predictive ability with an AUC of 1 (external validation group: AUC = 0.99). Then, separation was observed between the BC and RCC samples. The AUC was 0.862, 0.853 and 0.939, respectively, by plasma metabolomics, lipidomics and combined metabolomics and lipidomics (external validation group: AUC was 0.802, 0.898, and 0.942, respectively). Furthermore, we also found eight metabolites that showed good predictive ability for BC, RCC and control discrimination. This study indicated that plasma metabolomics and lipidomics may be effective for BC, RCC and control discrimination, and combined plasma metabolomics and lipidomics showed better predictive performance. This study would provide a reference for BC and RCC biomarker discovery, not only for early detection and screening, but also for differential diagnosis.

Circulating Retinol-Binding Protein 4 as a Possible Biomarker of Treatment Response for Ankylosing Spondylitis: An Array-Based Comparative Study

Objective

To explore proteins associated with ankylosing spondylitis (AS) and to investigate potential proteins that may predict treatment response of adalimumab (ADA) in AS patients.

Methods

In the discovery cohort, 39 AS patients and 20 healthy controls (HCs) were included, and 16 AS patients received ADA treatment for 24 weeks after included. In the validation cohort, 43 AS patients and 39 HCs were enrolled, and all 43 patients received ADA treatment after enrollment. Blood samples and clinical information were collected from two cohorts at baseline from all participants and week 24 from patients received ADA treatment. A human antibody array containing 1,000 proteins was used in the discovery phase, and Elisa kits were used for protein validation.

Results

Compared with HCs, we identified 53 differentially expressed proteins (DEPs) in AS patients. Bioinformatics analysis revealed they were mostly enriched in coagulation function-related pathways, acute response signaling, and LXR/RXR activation. Bone metabolism pathways were also associated. Comparison between samples of pre- and post-ADA treatment revealed 42 DEPs. They were mostly associated with bone metabolism and inflammation response pathways. Significant enrichment was also found in LXR/RXR activation but not the coagulation function-related pathways. Upstream regulator analysis suggested that most regulators also significantly functioned under usage of ADA. Precisely, seven proteins were abnormally expressed in AS and restored after ADA treatment. Retinol-binding protein 4 (RBP4), one of the seven proteins, was validated that its baseline levels were inversely correlated with improvements in Ankylosing Spondylitis Disease Activity Score-C-reactive protein (ASDAS-CRP). Likewise, percentage changes in RBP4 levels were inversely correlated with changes in ASDAS-CRP score.

Conclusion

A dysregulated serum protein profile existed in AS. ADA exerted a considerable but not entire alteration toward the dysregulation. RBP4 could be a biomarker for predicting and monitoring ADA treatment response.

UPLC-MS based urine untargeted metabolomic analyses to differentiate bladder cancer from renal cell carcinoma

Background

To discover biomarker panels that could distinguish cancers (BC and RCC) from healthy controls (HCs) and bladder cancers (BC) from renal cell carcinoma (RCC), regardless of whether the patients have haematuria. In addition, we also explored the altered metabolomic pathways of BC and RCC.

Methods

In total, 403 participants were enrolled in our study, which included 146 BC patients (77 without haematuria and 69 with haematuria), 115 RCC patients (94 without haematuria and 21 with haematuria) and 142 sex- and age-matched HCs. Their midstream urine samples were collected and analysed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarker panels and altered metabolic pathways.

Results

The panel of α-CEHC, β-cortolone, deoxyinosine, flunisolide, 11b,17a,21-trihydroxypreg-nenolone and glycerol tripropanoate could distinguish the patients with cancer from the HCs (the AUC was 0.950) and the external validation also displayed a good predictive ability (the AUC was 0.867). The panel of 4-ethoxymethylphenol, prostaglandin F2b, thromboxane B3, hydroxybutyrylcarnitine, 3-hydroxyphloretin and N′-formylkynurenine could differentiate BC from RCC without haematuria. The AUC was 0.829 in the discovering group and 0.76 in the external validation. The metabolite panel comprising 1-hydroxy-2-oxopropyl tetrahydropterin, 1-acetoxy-2-hydroxy-16-heptadecyn-4-one, 1,2-dehydrosalsolinol and L-tyrosine could significantly discriminate BC from RCC with haematuria (AUC was 0.913). Pathway analyses revealed altered lipid and purine metabolisms between cancer patients and HCs, together with disordered amino acid and purine metabolisms between BC and RCC with haematuria.

Conclusions

UPLC-MS urine metabolomic analyses could not only differentiate cancers from HCs but also discriminate BC from RCC. In addition, pathway analyses demonstrated a deeper metabolic mechanism of BC and RCC.

FARP1 Facilitates Cell Proliferation Through Modulating MAPK Signaling Pathway in Cutaneous Melanoma

PURPOSE

The purpose of our study was to investigate the biological functions of FARP1 gene in cutaneous melanoma.

METHODS

The mRNA expression level of FARP1 in cutaneous melanoma was analyzed based on the data obtained from ONCOMINE and The Cancer Genome Atlas database. Kaplan-Meier analysis was conducted to explore the association between FARP1 expression and the overall survival time of patients with cutaneous melanoma. The mRNA expression of FARP1 in melanoma cells was determined by qRT-PCR. A-375 cell line with silenced FARP1 was constructed to explore its biological functions. Cell proliferation, migration, and invasion abilities were determined by CCK8 assay, wound-healing assay, and transwell assays, respectively. Western blot was performed to explore the protein expression of FARP1, pMEK, MEK, pERK, and ERK.

RESULTS

Our results showed that the expression level of FARP1 was upregulated in cutaneous melanoma tissues and cells. Kaplan-Meier analysis revealed that high expression of FARP1 is predictive of shorter overall survival time in patients with cutaneous melanoma. Through CCK8 assay, we found that knockdown of FARP1 in A-375 cells exhibited dramatically inhibitory effect on cell proliferation. The results of wound-healing and transwell assays revealed that the motility of A-375 cells was notably suppressed after silencing FARP1. Moreover, the relative expression levels of pMEK/MEK and pERK/ERK decreased remarkably in A-375 cells following being transfected with si-FARP1.

CONCLUSIONS

Our present results preliminary proofed that FARP1 possibly acts as a promoter in cutaneous melanoma development and possesses the potential to be a therapeutic target in patients with cutaneous melanoma.

Translational research: Empowering the role of pathologists and cytopathologists

Research activity is in the core essence of pathology. Advancing our understanding of disease pathogenesis translates into better patient care. Because of their unique position, laboratorians are the best to accurately identify, annotate, and classify research specimens. They also are essential for the accurate interpretation of genomic testing. Currently, cytopathologists are moving to the center of patient care through active communication with clinicians and patients. There are certain research areas in which cytopathologists can be pioneers, such as image analysis, morphology research, and genotype-phenotype association studies integrating morphologic and molecular features. Health service utilization research is another domain in which cytopathologists can excel. Successful research is a journey that necessitates multiple steps. It also involves building expertise in how to overcome obstacles and handle challenges.

Downregulation of HSP60 disrupts mitochondrial proteostasis to promote tumorigenesis and progression in clear cell renal cell carcinoma

In the present study, we demonstrate that HSP60 is unequivocally downregulated in clear cell renal cell carcinoma (ccRCC) tissues compared to pericarcinous tissues. Overexpression of HSP60 in ccRCC cancer cells suppresses cell growth. HSP60 knockdown increases cell growth and proliferation in both cell culture and nude mice xenografts, and drives cells to undergo epithelial to mesenchymal transition (EMT). Our results propose that HSP60 silencing disrupts the integrity of the respiratory complex I and triggers the excessive ROS production, which promotes tumor progression in the following aspects: (1) ROS activates the AMPK pathway that promotes acquisition of the Warburg phenotype in HSP60-KN cells; (2) ROS generated by HSP60 knockdown or by rotenone inhibition drives cells to undergo EMT; and (3) the high level of ROS may also fragment the Fe-S clusters that up regulates ADHFe1 expression and the 2-hydroxygluterate (2-HG) production leading to changes in DNA methylation. These results suggest that the high level of ROS is needed for tumorigenesis and progression in tumors with the low HSP60 expression and HSP60 is a potential diagnostic biomarker as well as a therapeutic target in ccRCC.

Proteomic profiling of human HepG2 cells treated with hesperidin using antibody array

Protein array technology not only identifies a large number of proteins but also determines their expression levels. In the present study, antibody array analysis is used to decipher the proteins involved in hesperidin-induced cell death in HepG2 cells. Altered proteins in hesperidin treated cells were compared with that of untreated control cells by using a RayBio® Label‑based (L series) human antibody array kit. The identified proteins were further confirmed using western blot analysis. STRING software based analysis was used to determine the protein‑protein interactions. Many proteins related to signal transduction, cellular mechanisms, cell growth and proliferation regulatory proteins were identified. Among the proteins identified Hsp90, Smac/DIABLO, Prdx6 and FRK were significantly reduced in hesperidin treated cells. To the best of the authors' knowledge, the present study is the first to use antibody array for identifying proteins marker in hesperidin‑induced cell death in HepG2 cells. The present study provides a novel insight into the anticancer mechanism of hesperidin.

MAPK-mediated auxin signal transduction pathways regulate the malic acid secretion under aluminum stress in wheat (Triticum aestivum L.)

An isobaric tags for relative and absolute quantitative (iTRAQ)-based quantitative proteomic approach was used to screen the differentially expressed proteins during control treatment (CK), aluminum (Al) and Al⁺ indole-3-acetic acid (IAA) treatment of wheat lines ET8 (Al-tolerant). Further, the the expression levels of auxin response factor (ARF), Aux/IAA, Mitogen activated protein kinase (MAPK) 2c, and MAPK1a were analyzed. Results showed that 16 proteins were determined to be differentially expressed in response to Al and IAA co-treatment compared with Al alone. Among them, MAPK2c and MAPK1a proteins displayed markedly differential expression during the processes. The expression of ARF2 was upregulated and Aux/IAA was downregulated by Al, while both in concentration- and time-dependent manners. Western-blot detection of MAPK2c and MAPK1a indicated that Al upregulated MAPK2c and downregulated MAPK1a in both concentration- and time-dependent manners. Exogenous IAA could promote the expression of MAPK2c, but inhibit the expression of MAPK1a in the presence/absence of Al. These findings indicated that IAA acted as one of the key signaling molecule controls the response mechanism of wheat malic acid efflux to Al stress through the suppression/activation of Aux/IAA and ARFs, and the activity of MAPK2c and MAPK1a were positively or negatively regulated.

PGRMC1 Is a Novel Potential Tumor Biomarker of Human Renal Cell Carcinoma Based on Quantitative Proteomic and Integrative Biological Assessments

Progesterone receptor membrane component 1 (PGRMC1) is widely observed with an elevated level in multiple human cancers. However, the roles of PGRMC1 in renal cancer are not clear and merit further study. In this report, we made a systematic, integrative biological assessment for PGRMC1 in renal cell carcinoma (RCC) by a quantitative proteomic identification, immunohistochemical detection, and its clinic pathologic significance analysis. We found that PGRMC1 abundance is increased by 3.91-fold in RCC tissues compared with its autologous para-cancerous tissues by a quantitative proteome identification. To validate the proteomic result with more confidence, 135 clinic RCC tissues were recruited to measure PGRMC1 abundance by immunohistochemical staining, and 63.7% RCC samples (n = 86) showed a higher abundance of PGRMC1 than the noncancerous counterparts. And the elevated PGRMC1 level was related to the tumor malignancy degree and overall survival of RCC patients. Meanwhile the average serum PGRMC1 concentration for RCC patients (n = 18) was significantly increased by 1.67 fold compared with healthy persons. Moreover an exogenous elevated abundance of PGRMC1 by plasmid transfections significantly enhanced cell proliferation of renal cancer cells in vitro. Our findings demonstrate PGRMC1, which promotes RCC progression phenotypes in vitro and in vivo, is a novel potential biomarker and therapeutic target for RCC.

Integrated transcriptomic and metabolomic analysis shows that disturbances in metabolism of tumor cells contribute to poor survival of RCC patients

PURPOSE

Cellular metabolism of renal cell carcinoma (RCC) tumors is disturbed. The clinical significance of these alterations is weakly understood. We aimed to find if changes in metabolic pathways contribute to survival of RCC patients.

MATERIAL AND METHODS

35 RCC tumors and matched controls were used for metabolite profiling using gas chromatography-mass spectrometry and transcriptomic analysis with qPCR-arrays targeting the expression of 93 metabolic genes. The clinical significance of obtained data was validated on independent cohort of 468 RCC patients with median follow-up of 43.22months.

RESULTS

The levels of 31 metabolites were statistically significantly changed in RCC tumors compared with controls. The top altered metabolites included beta-alanine (+4.2-fold), glucose (+3.4-fold), succinate (-11.0-fold), myo-inositol (-4.6-fold), adenine (-4.2-fold), uracil (-3.7-fold), and hypoxanthine (-3.0-fold). These disturbances were associated with altered expression of 53 metabolic genes. ROC curve analysis revealed that the top metabolites discriminating between tumor and control samples included succinate (AUC=0.91), adenine (AUC=0.89), myo-inositol (AUC=0.87), hypoxanthine (AUC=0.85), urea (AUC=0.85), and beta-alanine (AUC=0.85). Poor survival of RCC patients correlated (p<0.0001) with altered expression of genes involved in metabolism of succinate (HR=2.7), purines (HR=2.4), glucose (HR=2.4), beta-alanine (HR=2.5), and myo-inositol (HR=1.9).

CONCLUSIONS

We found that changes in metabolism of succinate, beta-alanine, purines, glucose and myo-inositol correlate with poor survival of RCC patients.

The proteomic landscape of renal tumors

INTRODUCTION

Renal cell carcinoma (RCC) is the most fatal of the common urologic cancers, with approximately 35% of patients dying within 5 years following diagnosis. Therefore, there is a need for non-invasive markers that are capable of detecting and determining the severity of small renal masses at an early stage in order to tailor treatment and follow-up. Proteomic studies have proved to be very useful in the study of tumors. Areas covered: In this review, we will detail the current knowledge obtained by the different proteomic approaches, focusing on MS-based strategies, used to investigate RCC biology in order to identify diagnostic, prognostic and predictive biomarkers on tissue, cultured cells and biological fluids. Expert commentary: Currently, no reliable biomarkers or targets for RCC have been translated into the clinical setting. Moreover, despite the efforts of proteomics and other -omics disciplines, only a small number of them have been observed as shared targets between the different analytical platforms and biological specimens. The difficulty to define a specific molecular pattern for RCC and its subtypes highlights a peculiar profile and a heterogeneity that must be taken into account in future studies.

Comparative proteomic profiling identifies potential prognostic factors for human clear cell renal cell carcinoma

The identification of markers for disease diagnostic, prognostic, or predictive purposes will have a great effect in improving patient management. Proteomic‑based approaches for biomarker discovery are promising strategies used in cancer research. In this study, we performed quantitative proteomic analysis on four patients including clear cell renal cell carcinoma (ccRCC) and paired adjacent non‑cancerous renal tissues using label‑free quantitative proteomics and liquid chromatography‑tandem mass spectrometry (LC‑MS/MS) to identify differentially expressed proteins. Among 3,061 identified non‑redundant proteins, we found that 210 proteins were differentially expressed (83 overexpressed and 127 underexpressed) in ccRCC tissue when compared with normal kidney tissues. Two most significantly dysregulated proteins (PCK1 and SNRPF) were chosen to be confirmed by western blotting. Pathway analysis of 210 differentially expressed proteins showed that dysregulated proteins are related to many cancer‑related biological processes such as oxidative phosphorylation, glycolysis and amino acid synthetic pathways. Online survival analysis indicated the prognostic value of these dysregulated proteins. In conclusion, we identified some potential diagnostic biomarkers for ccRCC and an in‑depth understanding of their involved biological pathways may help pave the way to discover new therapeutic strategies for ccRCC.

Establishment and characterization of a highly immunogenic human renal carcinoma cell line

Renal cell carcinoma (RCC) is the most common kidney cancer, and accounts for ~3% of all adult malignancies. RCC has proven refractory to conventional treatment modalities but appears to be the only histological form that shows any consistent response to immunotherapeutic approaches. The development of a clinically effective vaccine remains a major strategic target for devising active specific immunotherapy in RCC. We aimed to identify a highly immunogenic antigenic format for immunotherapeutic approaches, so as to boost immune responses in RCC patients. We established and cloned an immunogenic cell line, RCC85#21 named Elthem, which was derived from a non-aggressive and non-metastatic clear cell carcinoma. The cell line characterization was performed by genomics (real-time PCR, genome instability), proteomics (two dimensional electrophoresis, mass spectro-metry) and immunological analysis (mixed lymphocytes tumor cell cultures). Real-time PCR confirmed the RCC85#21 cell expression of tumor antigens and cytokine genes. No difference in microsatellite instability (MSI) in RCC85#21 cell line was found as compared to control, loss of heterozygosity was observed in the RCC85#21 clone, but not in the renal cancer cell lines from which it was generated. The image analysis of RCC85#21 by two-dimensional gels showed 700±26 spots and 119 spots were identified by mass spectrometry analysis. RCC85#21 promoted a significant RCC-specific T cells activation by exhibiting a cytotoxic phenotype after mixed lymphocyte and tumor cell cultures. CD8+ T cells isolated from RCC patients displayed an elevated reactivity against RCC85#21 and efficiently lysed the RCC85#21 clone. The RCC85#21 immunogenic cell line will be suitable for immune stimulation. The identification of novel tumor associated antigens will allow the evaluation of the immune response in vitro and, subsequently, in vivo paving the way for new immunotherapeutic strategies in the RCC setting.

iTRAQ-based quantitative proteomic analysis reveals potential early diagnostic markers of clear-cell Renal cell carcinoma

Early detection is the key to improve the prognosis of kidney cancer. This study profiled and identified differentially expressed serum proteins in stage T1a renal cell carcinoma (RCC) using isobaric tags for relative and absolute quantification (iTRAQ)-based mass spectrometry. A total amount of 99 serum samples including 29 patients with ccRCC, 24 patients with a benign kidney mass, 28 patients with another type of urological tumor (20 cases of transitional cell carcinoma and 8 cases of prostate cancer or a male genital tumor), and 18 healthy controls were subjected to iTRAQ-based mass spectrometry. ProteinPilot software was used to identify the differentially expressed serum proteins in RCC compared to the other three populations. Hierarchical clustering analysis according to The Cancer Genome Atlas (TCGA) RCC database was then performed as the cross-platform validation. Immunohistochemistry was performed to verify the expression of selected proteins in tissue samples from these subjects. iTRAQ identified 27 differentially expressed serum proteins in the RCC patients, and 11 of these proteins were cross validated in RCC tissues from the TCGA database. The expression of C1QC, C1QB, S100A8, S100A9, ceruplasmin, and lumican was verified and associated with the tumor stage and/or grade. There were 27 differentially expressed proteins in early-stage RCC identified by iTRAQ; among them, the expression of C1QC, C1QB, S100A8, S100A9, ceruplasmin, and lumican were associated with the tumor stage and/or grade. Further studies are needed to confirm these data for their use as biomarkers for the early detection of RCC.

Cdc42 and Rac1 activity is reduced in human pheochromocytoma and correlates with FARP1 and ARHGEF1 expression

Among small GTPases from the Rho family, Cdc42, RAC, and Rho are well known to mediate a large variety of cellular processes linked with cancer biology through their ability to cycle between an inactive (GDP-bound) and an active (GTP-bound) state. Guanine nucleotide exchange factors (GEFs) stimulate the exchange of GDP for GTP to generate the activated form, whereas the GTPase-activating proteins (GAPs) catalyze GTP hydrolysis, leading to the inactivated form. Modulation of Rho GTPase activity following altered expression of RHO-GEFs and/or RHO-GAPs has already been reported in various human tumors. However, nothing is known about the Rho GTPase activity or the expression of their regulators in human pheochromocytomas, a neuroendocrine tumor (NET) arising from chromaffin cells of the adrenal medulla. In this study, we demonstrate, through an ELISA-based activity assay, that Rac1 and Cdc42 activities decrease in human pheochromocytomas (PCCs) compared with the matched adjacent non-tumor tissue. Furthermore, through quantitative mass spectrometry (MS) approaches, we show that the expression of two RHO-GEF proteins, namely ARHGEF1 and FARP1, is significantly reduced in tumors compared with matched non-tumor tissue, whereas ARHGAP36 expression is increased. Moreover, siRNA-based knockdown of ARHGEF1 and FARP1 in PC12 cells leads to a significant inhibition of Rac1 and Cdc42 activities, respectively. Finally, a principal component analysis (PCA) of our dataset was able to discriminate PCC from non-tumor tissue and indicates a close correlation between Cdc42/Rac1 activity and FARP1/ARHGEF1 expression. Altogether, our findings reveal for the first time the importance of modulation of Rho GTPase activities and expression of their regulators in human PCCs.

Quantitative proteomic profiling of renal tissue in human chronic rejection biopsy samples after renal transplantation

INTRODUCTION

Chronic rejection (CR) is the leading cause of late renal transplant failure and is characterized by a relatively slow but progressive loss of renal function in combination with proteinuria and hypertension >3 months after transplantation. To identify and quantify the protein profiles in renal tissues of CR patients, we used isotope tagging for relative and absolute quantification (iTRAQ)-based proteomic technology to perform global protein expression analyses in CR patients and control subjects.

MATERIALS AND METHODS

After protein extraction, quantitation, and digestion, samples were labeled with iTRAQ reagents and then separated by strong cation exchange and high-performance liquid chromatography. The fractions were further analyzed by tandem mass spectrometry. ProteinPilot version 4.0 software and the Swiss-Prot human database were applied for statistical analysis and database searching, respectively. Differentially expressed proteins were subjected to bioinformatic analysis by using the Gene Ontology database and the Kyoto Encyclopedia of Genes and Genomes database to further characterize their potential functional roles and related pathways in CR.

RESULTS

In total, 1857 distinct proteins (confidence >95%, ρ < .05) were identified and quantified. Using a strict cutoff value of 1.5-fold for expressed variation, 87 proteins showed significant differences in expression between the CR and control groups; 53 were up-regulated and 34 were down-regulated. The differentially expressed proteins were mainly involved in protein binding, structural molecule activity, and extracellular matrix structural constituent. Several proteins, such as the alpha-1 chain of collagen type IV and integrin alpha-1, may play roles in the pathogenesis of CR and were implicated in the extracellular matrix-receptor interaction pathway.

CONCLUSIONS

This study is the first to focus on iTRAQ-based quantitative proteomic characterization of renal tissue in CR. These insights may broaden our understanding of the molecular mechanisms underlying CR and provide potential biomarker candidates for future diagnostics.

Proteomic analysis reveals differentially secreted proteins in the urine from patients with clear cell renal cell carcinoma

OBJECTIVE

The aim of this study was to evaluate the differentially secreted protein profile in the urine from patients with clear cell renal cell carcinoma (ccRCC) using mass spectrometry-based methods. Urine composition can reflect kidney physiology and can be used to detect markers for renal diseases. Moreover, characterization of the secretome is likely to assist in the investigation of new drugs for biological targets and diagnose the ccRCC at an early stage.

METHODS AND MATERIALS

Urine samples from patients were divided according to Fuhrman degree (FI-IV), which was associated with the cellular differentiation as good prognosis (GP) and poor prognosis (PP). Healthy individuals were used as the control group (CG). We used both qualitative and quantitative mass spectrometry-based analyses that involved the following approaches: 1-dimensional gel electrophoresis combined with liquid chromatography mass spectrometry in tandem (1DE LC-MS/MS), in-solution digestion combined with label-free 1-dimensional LC-MS(E) (1D LC-MS(E)), and bidimensional gel electrophoresis combined with matrix-assisted laser desorption/ionization time of flight in tandem (2DE MALDI-TOF/TOF) or combined with LC-MS/MS.

RESULTS

All the strategies allowed the identification of 354 proteins from the CG, GP, and PP groups. Qualitative experiments using 1DE LC-MS/MS analysis detected different protein profiles, and 224 proteins were identified in all groups. The label-free MS(E) quantitative analysis identified 113 proteins and generated novel information on secreted protein profiles, including 49 up-secreted proteins in the urine from patients with ccRCC and 40 down-secreted proteins related to the CG. Proteins such as kininogen-1, uromodulin, apolipoprotein D, polyubiquitin, and CD59 glycoprotein were down secreted according to the groups CG>GP>PP. In contrast, apolipoprotein A, fibrinogen, and haptoglobin were up secreted in patient groups. The same expression profile observed for kininogen-1, apolipoprotein D, fibrinogen, and haptoglobin was corroborated by 2DE LC-MS/MS or 2DE MALDI-TOF/TOF analyses. These 2 strategies also showed 13 differentially secreted proteins among the 3 groups.

CONCLUSIONS

The proteins kininogen-1, apolipoprotein D, fibrinogen, and haptoglobin presented similar quantitative protein profiles according to MS(E) and 2DE approaches. The latter proteins were up secreted and the former ones were down-regulated. The strategies used proved to be valuable in identifying proteins that were differentially secreted in urine from patients with RCC.

Identification of Protein Markers Specific for Papillary Renal Cell Carcinoma Using Imaging Mass Spectrometry

Since the emergence of proteomics methods, many proteins specific for renal cell carcinoma (RCC) have been identified. Despite their usefulness for the specific diagnosis of RCC, such proteins do not provide spatial information on the diseased tissue. Therefore, the identification of cancer-specific proteins that include information on their specific location is needed. Recently, matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS) based imaging mass spectrometry (IMS) has emerged as a new tool for the analysis of spatial distribution as well as identification of either proteins or small molecules in tissues. In this report, surgical tissue sections of papillary RCC were analyzed using MALDI-IMS. Statistical analysis revealed several discriminative cancer-specific m/z-species between normal and diseased tissues. Among these m/z-species, two particular proteins, S100A11 and ferritin light chain, which are specific for papillary RCC cancer regions, were successfully identified using LC-MS/MS following protein extraction from independent RCC samples. The expressions of S100A11 and ferritin light chain were further validated by immunohistochemistry of human tissues and tissue microarrays (TMAs) of RCC. In conclusion, MALDI-IMS followed by LC-MS/MS analysis in human tissue identified that S100A11 and ferritin light chain are differentially expressed proteins in papillary RCC cancer regions.

Quantitative proteomic analysis reveals potential diagnostic markers and pathways involved in pathogenesis of renal cell carcinoma

There are no serum biomarkers for the accurate diagnosis of clear cell renal cell carcinoma (ccRCC). Diagnosis and decision of nephrectomy rely on imaging which is not always accurate. Non-invasive diagnostic biomarkers are urgently required. In this study, we preformed quantitative proteomics analysis on a total of 199 patients including 30 matched pairs of normal kidney and ccRCC using isobaric tags for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to identify differentially expressed proteins. We found 55 proteins significantly dysregulated in ccRCC compared to normal kidney tissue. 54 were previously reported to play a role in carcinogenesis, and 39 are secreted proteins. Dysregulation of alpha-enolase (ENO1), L-lactate dehydrogenase A chain (LDHA), heat shock protein beta-1 (HSPB1/Hsp27), and 10 kDa heat shock protein, mitochondrial (HSPE1) was confirmed in two independent sets of patients by western blot and immunohistochemistry. Pathway analysis, validated by PCR, showed glucose metabolism is altered in ccRCC compared to normal kidney tissue. In addition, we examined the utility of Hsp27 as biomarker in serum and urine. In ccRCC patients, Hsp27 was elevated in the urine and serum and high serum Hsp27 was associated with high grade (Grade 3-4) tumors. These data together identify potential diagnostic biomarkers for ccRCC and shed new light on the molecular mechanisms that are dysregulated and contribute to the pathogenesis of ccRCC. Hsp27 is a promising diagnostic marker for ccRCC although further large-scale studies are required. Also, molecular profiling may help pave the road to the discovery of new therapies.

Liquid chromatography-mass spectrometry based serum peptidomic approach for renal clear cell carcinoma diagnosis

Serum peptidomic approach was applied to investigate the peptidomic signature and discover the clinical biomarkers and biomarker patterns for RCC patients. The holistic orthogonal partial least-squares-discriminant analysis (OPLS-DA) based on qualified profile data successfully classified RCC patients from healthy controls, showing 100% sensitivity and specificity. Following critical criteria, several peptides presenting significant differences in serum level were picked out. The unsupervised hierarchical cluster analysis on those peptides was performed, showing 100% sensitivity and 93.3% specificity for RCC diagnosis regarding the present samples. Besides, receiver-operating characteristic (ROC) analysis was applied on single peptide biomarkers, with four peptides showing excellent predictive power. Among them, IYQLNSKLV and AGISMRSGDSPQD are reported for the first time for cancer detection.

Identification and validation of TGFBI as a promising prognosis marker of clear cell renal cell carcinoma

OBJECTIVE

To identify prognostic biomarkers in clear cell renal cell carcinoma (ccRCC) using a proteomic approach.

MATERIAL AND METHODS

We performed a comparative proteomic profiling of ccRCC and normal renal tissues from 9 different human specimens. We assessed differential protein expression by iTRAQ (isobaric tagging reagent for absolute quantify) labeling with regard to tumor aggressiveness according to the stage, size, grade, and necrosis (SSIGN) score and confirmed our results using Western blot (9 patients) and immunohistochemistry (135 patients) analysis.

RESULTS

After proteomic analysis, 928 constitutive proteins were identified. Among these proteins, 346 had a modified expression in tumor compared with that of normal tissue. Pathway and integrated analyses indicated the presence of an up-regulation of the pentose phosphate pathway in aggressive tumors. In total, 14 proteins were excreted and could potentially become biomarkers. Overexpression of transforming growth factor, beta-induced (TGFBI) in ccRCC was confirmed using Western blot and immunohistochemistry analysis. A significant association was found between the presence of TGFBI expression with tumor category T3-4 (P<0.0001), Fuhrman grades III and IV (P<0.0001), tumor size>4cm (P<0.0001), presence of tumor necrosis (P<0.0001), nodal involvement (n = 0.009), metastasis (P = 0.012), SSIGN score≥5 (P<0.0001), cancer progression (P<0.0001), and cancer-specific death (P<0.0001). Cancer-specific survival was significantly better for patients with no cytoplasmic TGFBI expression (1-, 3-, 5-y cancer-specific survival of 94.7%, 87.8%, and 73.4% vs. 92.9%, 71.2%, and 49.8%, respectively; P<0.0001).

CONCLUSION

We identified 346 proteins involved in renal carcinogenesis and confirmed the presence of a metabolic shift in aggressive tumors. TGFBI was overexpressed in tumors with high SSIGN scores and was significantly associated with oncologic outcomes.

Representing kidney development using the gene ontology

Gene Ontology (GO) provides dynamic controlled vocabularies to aid in the description of the functional biological attributes and subcellular locations of gene products from all taxonomic groups (www.geneontology.org). Here we describe collaboration between the renal biomedical research community and the GO Consortium to improve the quality and quantity of GO terms describing renal development. In the associated annotation activity, the new and revised terms were associated with gene products involved in renal development and function. This project resulted in a total of 522 GO terms being added to the ontology and the creation of approximately 9,600 kidney-related GO term associations to 940 UniProt Knowledgebase (UniProtKB) entries, covering 66 taxonomic groups. We demonstrate the impact of these improvements on the interpretation of GO term analyses performed on genes differentially expressed in kidney glomeruli affected by diabetic nephropathy. In summary, we have produced a resource that can be utilized in the interpretation of data from small- and large-scale experiments investigating molecular mechanisms of kidney function and development and thereby help towards alleviating renal disease.

Lactate dehydrogenase A is a potential prognostic marker in clear cell renal cell carcinoma

Background

Over 90% of cancer-related deaths in clear cell renal cell carcinoma (RCC) are caused by tumor relapse and metastasis. Thus, there is an urgent need for new molecular markers that can potentiate the efficacy of the current clinical-based models of prognosis assessment. The objective of this study is to evaluate the potential significance of lactate dehydrogenase A (LDHA), assessed by immunohistochemical staining, as a prognostic marker in clear cell renal cell carcinoma in relation to clinicopathological features and clinical outcome.

Methods

We assessed the expression of LDHA at the protein level, by immunohistochemistry, and correlated its expression with multiple clinicopathological features including tumor size, clinical stage, histological grade, disease-free and overall survival in 385 patients with primary clear cell renal cell carcinoma. We also correlated the LDHA expression with overall survival, at mRNA level, in an independent data set of 170 clear cell renal cell carcinoma cases from The Cancer Genome Atlas databases. Cox proportional hazards models adjusted for the potential clinicopathological factors were used to test for associations between the LDHA expression and both disease-free survival and overall survival.

Results

There is statistically significant positive correlation between LDHA level of expression and tumor size, clinical stage and histological grade. Moreover, LDHA expression shows significantly inverse correlation with both disease-free survival and overall survival in patients with clear cell renal cell carcinoma. Our results are validated by examining LDHA expression, at the mRNA level, in the independent data set of clear cell renal cell carcinoma cases from The Cancer Genome Atlas databases which also shows that higher lactate dehydrogenase A expression is associated with significantly shorter overall survival.

Conclusion

Our results indicate that LDHA up-regulation can be a predictor of poor prognosis in clear cell renal cell carcinoma. Thus, it represents a potential prognostic biomarker that can boost the accuracy of other prognostic models in patients with clear cell renal cell carcinoma.

Identification and validation of dysregulated metabolic pathways in metastatic renal cell carcinoma

Metastatic renal cell carcinoma (mRCC) is a devastating disease with a 5-year survival rate of approximately 9 % and low response to chemotherapy and radiotherapy. Targeted therapies have slightly improved patient survival, but are only effective in a small subset of patients, who eventually develop resistance. A better understanding of pathways contributing to tumor progression and metastasis will allow for the development of novel targeted therapies and accurate prognostic markers. We performed extensive bioinformatics coupled with experimental validation on proteins dysregulated in mRCC. Gene ontology analysis showed that many proteins are involved in oxidation reduction, metabolic processes, and signal transduction. Pathway analysis showed metabolic pathways are altered in mRCC including glycolysis and pyruvate metabolism, the citric acid cycle, and the pentose phosphate pathway. RT-qPCR analysis showed that genes involved in the citric acid cycle were downregulated in metastatic RCC while genes of the pentose phosphate pathway were overexpressed. Protein-protein interaction analysis showed that most of the 198 proteins altered in mRCC clustered together and many were involved in glycolysis and pyruvate metabolism. We identified 29 reported regions of chromosomal aberrations in metastatic disease that correlate with the direction of protein dysregulation in mRCC. Furthermore, 36 proteins dysregulated in mRCC are predicted to be targets of metastasis-related miRNAs. A more comprehensive understanding of the pathways dysregulated in metastasis can be useful for the development of new therapies and novel prognostic markers. Also, multileveled analyses provide a unique "snapshot" of the molecular "environment" in RCC with prognostic and therapeutic implications.

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.

Role of moesin in hyaluronan induced cell migration in glioblastoma multiforme

Background

A major barrier to effective treatment of glioblastoma multiforme (GBM) is the invasion of glioma cells into the brain parenchyma rendering local therapies such as surgery and radiation therapy ineffective. GBM patients with such highly invasive and infiltrative tumors have poor prognosis with a median survival time of only about a year. However, the mechanisms leading to increased cell migration, invasion and diffused behavior of glioma cells are still poorly understood.

Methods

In the current study, we applied quantitative proteomics for the identification of differentially expressed proteins in GBMs as compared to non-malignant brain tissues.

Results

Our study led to the identification of 23 proteins showing overexpression in GBM; these include membrane proteins, moesin and CD44. The results were verified using Western blotting and immunohistochemistry in independent set of GBM and non-malignant brain tissues. Both GBM tissues and glioma cell lines (U87 / U373) demonstrated membranous expression of moesin and CD44, as revealed by immunohistochemistry and immunofluorescence, respectively. Notably, glioma cells transfected with moesin siRNA displayed reduced migration and invasion on treatment with hyaluronan (HA), an important component of the extracellular matrix in GBM. CD44, a transmembrane glycoprotein, acts as a major receptor for hyaluronan (HA). Using co-immunoprecipitation assays, we further demonstrated that moesin interacts with CD44 in glioma cells only after treatment with HA; this implicates a novel role of moesin in HA-CD44 signaling in gliomas.

Conclusions

Our results suggest that development of inhibitors which interfere with CD44-moesin interactions may open a new avenue in the future to mitigate cellular migration in gliomas.

Protein composition of bronchoalveolar lavage fluid and airway surface liquid from newborn pigs

The airway mucosa and the alveolar surface form dynamic interfaces between the lung and the external environment. The epithelial cells lining these barriers elaborate a thin liquid layer containing secreted peptides and proteins that contribute to host defense and other functions. The goal of this study was to develop and apply methods to define the proteome of porcine lung lining liquid, in part, by leveraging the wealth of information in the Sus scrofa database of Ensembl gene, transcript, and protein model predictions. We developed an optimized workflow for detection of secreted proteins in porcine bronchoalveolar lavage (BAL) fluid and in methacholine-induced tracheal secretions [airway surface liquid (ASL)]. We detected 674 and 3,858 unique porcine-specific proteins in BAL and ASL, respectively. This proteome was composed of proteins representing a diverse range of molecular classes and biological processes, including host defense, molecular transport, cell communication, cytoskeletal, and metabolic functions. Specifically, we detected a significant number of secreted proteins with known or predicted roles in innate and adaptive immunity, microbial killing, or other aspects of host defense. In greatly expanding the known proteome of the lung lining fluid in the pig, this study provides a valuable resource for future studies using this important animal model of pulmonary physiology and disease.

Genomic medicine: new frontiers and new challenges

BACKGROUND

The practice of personalized medicine has made large strides since the introduction of high-throughput technologies and the vast improvements in computational biotechnology. The personalized-medicine approach to cancer management holds promise for earlier disease detection, accurate prediction of prognosis, and better treatment options; however, the early experience with personalized medicine has revealed important concerns that need to be addressed before research findings can be translated to the bedside.

CONTENT

We discuss several emerging "practical" or "focused" applications of personalized medicine. Molecular testing can have an important positive impact on health and disease management in a number of ways, and the list of specific applications is evolving. This list includes improvements in risk assessment, disease prevention, identification of new disease-related mutations, accurate disease classification based on molecular signatures, selection of patients for enrollment in clinical trials, and development of new targeted therapies, especially for metastatic tumors that are refractory to treatment. Several challenges remain to be addressed before genomics information can be applied successfully in the routine clinical management of cancers. Further improvements and investigations are needed in data interpretation, extraction of actionable items, cost-effectiveness, how to account for patient heterogeneity and ethnic variation, and how to handle the risk of "incidental findings" in genetic testing.

SUMMARY

It is now clear that personalized medicine will not immediately provide a permanent solution for patient management and that further refinement in the applications of personalized medicine will be needed to address and focus on specific issues.

Quantitative proteomic analysis in metastatic renal cell carcinoma reveals a unique set of proteins with potential prognostic significance

Metastatic renal cell carcinoma (RCC) is one of the most treatment-resistant malignancies, and patients have a dismal prognosis, with a <10% five-year survival rate. The identification of markers that can predict the potential for metastases will have a great effect in improving patient outcomes. In this study, we used differential proteomics with isobaric tags for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to identify proteins that are differentially expressed in metastatic and primary RCC. We identified 1256 non-redundant proteins, and 456 of these were quantified. Further analysis identified 29 proteins that were differentially expressed (12 overexpressed and 17 underexpressed) in metastatic and primary RCC. Dysregulated protein expressions of profilin-1 (Pfn1), 14-3-3 zeta/delta (14-3-3ζ), and galectin-1 (Gal-1) were verified on two independent sets of tissues by means of Western blot and immunohistochemical analysis. Hierarchical clustering analysis showed that the protein expression profile specific for metastatic RCC can distinguish between aggressive and non-aggressive RCC. Pathway analysis showed that dysregulated proteins are involved in cellular processes related to tumor progression and metastasis. Furthermore, preliminary analysis using a small set of tumors showed that increased expression of Pfn1 is associated with poor outcome and is a potential prognostic marker in RCC. In addition, 14-3-3ζ and Gal-1 also showed higher expression in tumors with poor prognosis than in those with good prognosis. Dysregulated proteins in metastatic RCC represent potential prognostic markers for kidney cancer patients, and a greater understanding of their involved biological pathways can serve as the foundation of the development of novel targeted therapies for metastatic RCC.

Imaging the clear cell renal cell carcinoma proteome

PURPOSE

A key barrier to identifying tissue biomarkers of clear cell renal cell carcinoma is the heterogeneity of protein expression in tissue. However, by providing spectra for every 0.05 mm(2) area of tissue, imaging mass spectrometry reveals the spatial distribution of peptides. We determined whether this approach could be used to identify and map protein signatures of clear cell renal cell carcinoma.

MATERIALS AND METHODS

We constructed 2 tissue microarrays with 2 cores each of matched tumor and normal tissue from the nephrectomy specimens of 70 patients with clear cell renal cell carcinoma. Samples were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. In each tissue microarray peptide signatures were identified that differentiated cancer from normal tissue. The signatures were then cross validated. Mass spectrometry/mass spectrometry sequencing was performed to determine the identity of select, differentially expressed peptides. Immunohistochemistry was used for validation.

RESULTS

In each tissue microarray peptide signatures were identified that had 94.7% to 98.5% classification accuracy for each 0.05 mm(2) spot (spectrum) and 96.9% to 100% accuracy for each tissue core. Cross validation across tissue microarrays revealed a classification accuracy of 82.6% to 84.7% for each spot and 88.9% to 92.4% for each core. We identified vimentin, histone 2A.X and α-enolase as proteins with greater expression in cancer tissue. This was validated by immunohistochemistry.

CONCLUSIONS

Imaging mass spectrometry identified and mapped specific peptides that accurately distinguished malignant from normal renal tissue. This demonstrates its potential as a novel, high throughput approach to clear cell renal cell carcinoma biomarker discovery. Given the multiple pathways and known heterogeneity involved in tumors such as clear cell renal cell carcinoma, multiple peptide signatures that maintain their spatial relationships may outperform traditional protein biomarkers.

Multilevel whole-genome analysis reveals candidate biomarkers in clear cell renal cell carcinoma

Renal cell carcinoma (RCC) is the most common neoplasm of the kidney. We conducted an integrated analysis of copy number, gene expression (mRNA and miRNA), protein expression, and methylation changes in clear cell renal cell carcinoma (ccRCC). We used a stepwise approach to identify the most significant copy number aberrations (CNA) and identified regions of peak and broad copy number gain and loss, including peak gains (3q21, 5q32, 5q34-q35, 7p11, 7q21, 8q24, 11q13, and 12q14) and deletions (1p36, 2q34-q37, 3p25, 4q33-q35, 6q23-q27, and 9p21). These regions harbor novel tumor-related genes and miRNAs not previously reported in renal carcinoma. Integration of genome-wide expression data and gene set enrichment analysis revealed 75 gene sets significantly altered in tumors with CNAs compared with tumors without aberration. We also identified genes located in peak CNAs with concordant methylation changes (hypomethylated in copy number gains such as STC2 and CCND1 and hypermethylated in deletions such as CLCNKB, VHL, and CDKN2A/2B). For other genes, such as CA9, expression represents the net outcome of opposing forces (deletion and hypomethylation) that also significantly influences patient survival. We also validated the prognostic value of miRNA let-7i in RCCs. miR-138, located in chromosome 3p deletion, was also found to have suppressive effects on tumor proliferation and migration abilities. Our findings provide a significant advance in the delineation of the ccRCC genome by better defining the impact of CNAs in conjunction with methylation changes on the expression of cancer-related genes, miRNAs, and proteins and their influence on patient survival.

The Renal Gene Ontology Annotation Initiative

The gene ontology (go) resource provides dynamic controlled vocabularies to aid in the description of the functional attributes and subcellular locations of gene products from all taxonomic groups (www.geneontology.org). A renal-focused curation initiative, funded by Kidney Research UK and supported by the GO Consortium, has started at the European Bioinformatics Institute and aims to provide a detailed GO resource for mammalian proteins implicated in renal development and function. This report outlines the aims of this initiative and explains how the renal community can become involved to help improve the availability, quality and quantity of GO terms and their association to specific proteins.

Differential proteomic analysis of noncardia gastric cancer from individuals of northern Brazil

Gastric cancer is the second leading cause of cancer-related death worldwide. The identification of new cancer biomarkers is necessary to reduce the mortality rates through the development of new screening assays and early diagnosis, as well as new target therapies. In this study, we performed a proteomic analysis of noncardia gastric neoplasias of individuals from Northern Brazil. The proteins were analyzed by two-dimensional electrophoresis and mass spectrometry. For the identification of differentially expressed proteins, we used statistical tests with bootstrapping resampling to control the type I error in the multiple comparison analyses. We identified 111 proteins involved in gastric carcinogenesis. The computational analysis revealed several proteins involved in the energy production processes and reinforced the Warburg effect in gastric cancer. ENO1 and HSPB1 expression were further evaluated. ENO1 was selected due to its role in aerobic glycolysis that may contribute to the Warburg effect. Although we observed two up-regulated spots of ENO1 in the proteomic analysis, the mean expression of ENO1 was reduced in gastric tumors by western blot. However, mean ENO1 expression seems to increase in more invasive tumors. This lack of correlation between proteomic and western blot analyses may be due to the presence of other ENO1 spots that present a slightly reduced expression, but with a high impact in the mean protein expression. In neoplasias, HSPB1 is induced by cellular stress to protect cells against apoptosis. In the present study, HSPB1 presented an elevated protein and mRNA expression in a subset of gastric cancer samples. However, no association was observed between HSPB1 expression and clinicopathological characteristics. Here, we identified several possible biomarkers of gastric cancer in individuals from Northern Brazil. These biomarkers may be useful for the assessment of prognosis and stratification for therapy if validated in larger clinical study sets.

Expression, circulation, and excretion profile of microRNA-21, -155, and -18a following acute kidney injury

MicroRNAs (miRNAs) are endogenous noncoding RNA molecules that are involved in post-transcriptional gene silencing. Using global miRNA expression profiling, we found miR-21, -155, and 18a to be highly upregulated in rat kidneys following tubular injury induced by ischemia/reperfusion (I/R) or gentamicin administration. Mir-21 and -155 also showed decreased expression patterns in blood and urinary supernatants in both models of kidney injury. Furthermore, urinary levels of miR-21 increased 1.2-fold in patients with clinical diagnosis of acute kidney injury (AKI) (n = 22) as compared with healthy volunteers (n = 25) (p < 0.05), and miR-155 decreased 1.5-fold in patients with AKI (p < 0.01). We identified 29 messenger RNA core targets of these 3 miRNAs using the context likelihood of relatedness algorithm and found these predicted gene targets to be highly enriched for genes associated with apoptosis or cell proliferation. Taken together, these results suggest that miRNA-21 and -155 could potentially serve as translational biomarkers for detection of AKI and may play a critical role in the pathogenesis of kidney injury and tissue repair process.

Quantitative proteomic study of human lung squamous carcinoma and normal bronchial epithelial acquired by laser capture microdissection

Objective. To investigate the differential protein profile of human lung squamous carcinoma (HLSC) and normal bronchial epithelium (NBE) and provide preliminary results for further study to explore the carcinogenic mechanism of HLSC. Methods. Laser capture microdissection (LCM) was used to purify the target cells from 10 pairs of HLSC tissues and their matched NHBE, respectively. A stable-isotope labeled strategy using iTRAQ, followed by 2D-LC/Q-STAR mass spectrometry, was performed to separate and identify the differential expression proteins. Results. A total of 96 differential expression proteins in the LCM-purified HLSC and NBE were identified. Compared with NBE, 49 proteins were upregulated and 47 proteins were downregulated in HLSC. Furthermore, the expression levels of the differential proteins including HSPB1, CKB, SCCA1, S100A8, as well as S100A9 were confirmed by western blot and tissue microarray and were consistent with the results of quantitative proteomics. Conclusion. The different expression proteins in HLSC will provide scientific foundation for further study to explore the carcinogenic mechanism of HLSC.

Discovery and verification of gelsolin as a potential biomarker of colorectal adenocarcinoma in the Chinese population: Examining differential protein expression using an iTRAQ labelling-based proteomics approach

OBJECTIVE

To identify and validate potential biomarkers of colorectal adenocarcinoma using a proteomic approach.

METHODS

Multidimensional liquid chromatography⁄mass spectrometry was used to analyze biological samples labelled with isobaric mass tags for relative and absolute quantitation to identify differentially expressed proteins in human colorectal adenocarcinoma and paired normal mucosa for the discovery of cancerous biomarkers. Cancerous and noncancerous samples were compared using online and offline separation. Protein identification was performed using mass spectrometry. The downregulation of gelsolin protein in colorectal adenocarcinoma samples was confirmed by Western blot analysis and validated using immunohistochemistry.

RESULTS

A total of 802 nonredundant proteins were identified in colorectal adenocarcinoma samples, 82 of which fell outside the expression range of 0.8 to 1.2, and were considered to be potential cancer-specific proteins. Immunohistochemistry revealed a complete absence of gelsolin expression in 86.89% of samples and a reduction of expression in 13.11% of samples, yielding a sensitivity of 86.89% and a specificity of 100% for distinguishing colorectal adenocarcinoma from normal tissue.

CONCLUSIONS

These findings suggest that decreased expression of gelsolin is a potential biomarker of colorectal adenocarcinoma.

DIGE and iTRAQ as biomarker discovery tools in aquatic toxicology

Molecular approaches in ecotoxicology have greatly enhanced mechanistic understanding of the impact of aquatic pollutants in organisms. These methods have included high throughput Omics technologies, including quantitative proteomics methods such as 2D differential in-gel electrophoresis (DIGE) and isobaric tagging for relative and absolute quantitation (iTRAQ). These methods are becoming more widely used in ecotoxicology studies to identify and characterize protein bioindicators of adverse effect. In teleost fish, iTRAQ has been used successfully in different fish species (e.g. fathead minnow, goldfish, largemouth bass) and tissues (e.g. hypothalamus and liver) to quantify relative protein abundance. Of interest for ecotoxicology is that many proteins commonly utilized as bioindicators of toxicity or stress are quantifiable using iTRAQ on a larger scale, providing a global baseline of biological effect from which to assess changes in the proteome. This review highlights the successes to date for high throughput quantitative proteomics using DIGE and iTRAQ in aquatic toxicology. Current challenges for the iTRAQ method for biomarker discovery in fish are the high cost and the lack of complete annotated genomes for teleosts. However, the use of protein homology from teleost fishes in protein databases and the introduction of hybrid LTQ-FT (Linear ion trap-Fourier transform) mass spectrometers with high resolution, increased sensitivity, and high mass accuracy are able to improve significantly the protein identification rates. Despite these challenges, initial studies utilizing iTRAQ for ecotoxicoproteomics have exceeded expectations and it is anticipated that the use of non-gel based quantitative proteomics will increase for protein biomarker discovery and for characterization of chemical mode of action.

Microvascular density as an independent predictor of clinical outcome in renal cell carcinoma: an automated image analysis study

Tumor microvascular density (MVD) has been shown to correlate with the aggressiveness of several cancers. With the introduction of targeted anti-angiogenic therapy, assessment of MVD has the potential not only as a prognostic but also as a therapeutic marker. The significance of tumor vascularity in clear cell renal cell carcinoma (ccRCC) has been debated, with studies showing contradictory results. Previous studies were limited by manual quantification of MVD within a small area of tumor. Since then, the validity of this method has been questioned. To avoid the inaccuracies of manual quantification, we employed a computerized image analysis, which allowed assessment of large areas of tumor and adjacent normal tissue. The latter was used as an internal reference for normalization. MVD and vascular endothelial growth factor (VEGF) were assessed in 57 cases of ccRCC. Sections were immunostained for CD34 and VEGF. Areas of ccRCC and normal kidney medulla were analyzed within scanned images using software that counted CD34-positive vessels and measured the intensity of VEGF staining. We obtained unadjusted values from tumoral areas and calculated adjusted values as tumor/normal ratios. Unadjusted MVD had no association with clinical outcome. However, similarly to tumor stage, higher adjusted MVD was associated with shorter disease-free survival (log-rank P=0.037, Cox P=0.02). This was significant in univariate and multivariate analyses. MVD did not correlate with tumor stage, pointing to its independent prognostic value. As expected due to the known molecular abnormalities in ccRCC, most tumors showed higher VEGF expression than normal tissue. Higher adjusted VEGF was associated with high tumor grade (P=0.049). The finding of increased MVD as an independent marker of tumor aggressiveness may prove useful in the development of new tests for prognostic and therapeutic guidance. Digital techniques can provide more accurate assessment of immunomarkers and may reveal less obvious associations.