Detection of renal cell carcinoma-associated markers via proteome- and other 'ome'-based analyses

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.

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.

Gene expression profile of renal cell carcinoma clear cell type

PURPOSE

The determination of prognosis in patients with renal cell carcinoma (RCC) is based, classically, on stage and histopathological aspects. The metastatic disease develops in one third of patients after surgery, even in localized tumors. There are few options for treating those patients, and even the new target designed drugs have shown low rates of success in controlling disease progression. Few studies used high throughput genomic analysis in renal cell carcinoma for determination of prognosis. This study is focused on the identification of gene expression signatures in tissues of low-risk, high-risk and metastatic RCC clear cell type (RCC-CCT).

MATERIALS AND METHODS

We analyzed the expression of approximately 55,000 distinct transcripts using the Whole Genome microarray platform hybridized with RNA extracted from 19 patients submitted to surgery to treat RCC-CCT with different clinical outcomes. They were divided into three groups (1) low risk, characterized by pT1, Fuhrman grade 1 or 2, no microvascular invasion RCC; (2) high risk, pT2-3, Fuhrman grade 3 or 4 with, necrosis and microvascular invasion present and (3) metastatic RCC-CCT. Normal renal tissue was used as control.

RESULTS

After comparison of differentially expressed genes among low-risk, high-risk and metastatic groups, we identified a group of common genes characterizing metastatic disease. Among them Interleukin-8 and Heat shock protein 70 were over-expressed in metastasis and validated by real-time polymerase chain reaction.

CONCLUSION

These findings can be used as a starting point to generate molecular markers of RCC-CCT as well as a target for the development of innovative therapies.

Analysis of differentially expressed proteins in oral squamous cell carcinoma by MALDI-TOF MS

PURPOSE

To explore the presence of differentially expressed proteins in OSCC for discrimination of tumour and normal mucosa to establish potential biomarkers and therapeutic targets.

EXPERIMENTAL DESIGN

Paired protein samples of 12 individuals (tongue cancer and non-cancerous mucosa) were separated by two-dimensional polyacrylamid gel electrophoresis. The protein patterns were compared pairwise and protein spots were quantified. We identified about 70 regulated proteins which we subsequently identified by MALDI-TOF mass spectrometry.

RESULTS

Cancerous and non-cancerous tissues could be most precisely distinguished by a panel of proteins. They include the heat shock proteins (hsp)70 and 90, keratins (ck) 5, 6, 13, 14, 16, 17 and 19, beta globin, alpha-2-actin, stratifin, tropomyosin, calreticulin precursor, beta-2-tubulin, galectin7, thioredoxin, involucrin, adenylyl-cyclase-associated protein, disulfide isomerase-associated protein, thyrosine 3-monooxygenase, MYL2 and the s100 calcium binding protein. MYL3, cardiac muscle alpha actin 1 proprotein and transferrin were under-represented in OSCC. Six biomarkers, ck6 und ck13, beta globin, alpha-2-actin, hsp70 and hsp90 discriminated best between cancerous and non-cancerous oral tissues. All over-expressed proteins were analysed by STRING-analysis to highlight experimentally determined and computationally predicted interactions between the proteins. Especially involucrin, hsp70, calreticulin precursor, stratifin, (ck) 5, 6, 14, 19, tyrosine 3-monooxygenase, beta-2-tubulin and disulfide isomerase associated protein showed multiple relations.

CONCLUSION

We identified six proteins which are differentially expressed in most OSCC compared to healthy tissues. Of those, by string analysis, multiple interaction partners are assumed for hsp70. This protein is supposed to be the most promising candidate as marker molecule and target for OSCC therapy.

Molecular analysis of tumor margins by MALDI mass spectrometry in renal carcinoma

The rate of tumor recurrence post resection suggests that there are underlying molecular changes in nearby histologically normal tissue that go undetected by conventional diagnostic methods that utilize contrast agents and immunohistochemistry. MALDI MS is a molecular technology that has the specificity and sensitivity to monitor and identify molecular species indicative of these changes. The current study utilizes this technology to assess molecular distributions within a tumor and adjacent normal tissue in clear cell renal cell carcinoma biopsies. Results indicate that the histologically normal tissue adjacent to the tumor expresses many of the molecular characteristics of the tumor. Proteins of the mitochondrial electron transport system are examples of such distributions. This work demonstrates the utility of MALDI MS for the analysis of tumor tissue in the elucidation of aberrant molecular changes in the tumor microenvironment.

Epigenetic control of the ubiquitin carboxyl terminal hydrolase 1 in renal cell carcinoma

Background

The ubiquitin carboxyl-terminal hydrolase 1 (UCHL1) gene involved in the regulation of cellular ubiquitin levels plays an important role in different cellular processes including cell growth and differentiation. Aberrant expression of UCHL1 has been found in a number of human solid tumors including renal cell carcinoma (RCC). In RCC, UCHL1 overexpression is associated with tumor progression and an altered von Hippel Lindau gene expression.

Methods

To determine the underlying mechanisms for the heterogeneous UCHL1 expression pattern in RCC the UCHL1 promoter DNA methylation status was determined in 17 RCC cell lines as well as in 32 RCC lesions and corresponding tumor adjacent kidney epithelium using combined bisulfite restriction analysis as well as bisulfite DNA sequencing.

Results

UCHL1 expression was found in all 32 tumor adjacent kidney epithelium samples. However, the lack of or reduced UCHL1 mRNA and/or protein expression was detected in 13/32 RCC biopsies and 7/17 RCC cell lines and due to either a total or partial methylation of the UCHL1 promoter DNA. Upon 2'-deoxy-5-azacytidine treatment an induction of UCHL1 mRNA and protein expression was found in 9/17 RCC cell lines, which was linked to the demethylation degree of the UCHL1 promoter DNA.

Conclusion

Promoter hypermethylation represents a mechanism for the silencing of the UCHL1 gene expression in RCC and supports the concept of an epigenetic control for the expression of UCHL1 during disease progression.

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.

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

Results obtained from expression profilings of renal cell carcinoma using different "ome"-based approaches and comprehensive data analysis demonstrated that proteome-based technologies and cDNA microarray analyses complement each other during the discovery phase for disease-related candidate biomarkers. The integration of the respective data revealed the uniqueness and complementarities of the different technologies. While comparative cDNA microarray analyses though restricted to up-regulated targets largely revealed genes involved in controlling gene/protein expression (19%) and signal transduction processes (13%), proteomics/PROTEOMEX-defined candidate biomarkers include enzymes of the cellular metabolism (36%), transport proteins (12%), and cell motility/structural molecules (10%). Candidate biomarkers defined by proteomics and PROTEOMEX are frequently shared, whereas the sharing rate between cDNA microarray and proteome-based profilings is limited. Putative candidate biomarkers provide insights into their cellular (dys)function and their diagnostic/prognostic value but still warrant further validation in larger patient numbers. Based on the fact that merely three candidate biomarkers were shared by all applied technologies, namely annexin A4, tubulin alpha-1A chain, and ubiquitin carboxyl-terminal hydrolase L1, the analysis at a single hierarchical level of biological regulation seems to provide only limited results thus emphasizing the importance and benefit of performing rather combinatorial screenings which can complement the standard clinical predictors.

Exploring the pathogenesis of renal cell carcinoma: pathway and bioinformatics analysis of dysregulated genes and proteins

We recently identified a group of proteins which are dysregulated in renal cell carcinoma (RCC). In this study, we performed bioinformatics and pathway analysis of these proteins. Proteins were mapped to gene ontology biological processes. The upregulated proteins tend to cluster in processes, such as cancer initiation and progression. In addition, we identified a number of pathways that are significantly enriched in RCC. Some of these are 'common' pathways which are dysregulated in many cancers, but we also identified a number of pathways which were not previously linked to RCC. In addition to their potential prognostic values, many of these pathways have a potential as therapeutic targets for RCC. To verify our findings, we compared our proteins to a pool of datasets from published reports. Although there were only a minimal number of common proteins, there was a significant overlap between the identified pathways in the two groups. Moreover, out of 16 individually discovered genes identified by a literature search, 10 were found to be related to our dysregulated pathways. We also verified the upregulation of the mammalian target of rapamycin signaling pathway in RCC by immunohistochemistry. Finally, we highlight the potential clinical applications of pathway analysis in kidney cancer.

Cancer immunomics: from serological proteome analysis to multiple affinity protein profiling

Cancer remains one of the leading causes of death worldwide. Thus, to identify any useful biomarkers is still a need. We performed "cancer immunomics" to identify autoantibody signatures produced in response to the presence of either breast or colorectal cancer. SERological proteome analysis (SERPA) was performed by two-dimensional (2-D) electrophoresis separation, immunoblotting, image analysis, and mass spectrometry. Alternatively, to identify the antigens recognized by the autoantibodies of cancer patients, we developed an approach combining 2-D immunoaffinity chromatography, enzymatic digestion of the isolated antigens, nano flow separation of the resulting peptides, and identification: MAPPing (multiple affinity protein profiling). By these approaches we identified both proteins recognized by autoantibodies independently of a cancer status, and a limited number of proteins reacting preferentially with cancer sera.

WHO grade associated downregulation of MHC class I antigen-processing machinery components in human astrocytomas: does it reflect a potential immune escape mechanism?

Defects of major histocompatibility complex (MHC) class I antigen-processing machinery (APM) components have been shown to contribute to immune escape of malignant cells. We investigated the expression of APM components in astrocytomas without detectable defects in HLA class I antigen expression and correlated it with grade of malignancy. Quantitative immunohistochemical analysis of astrocytomas revealed reduced expression of the cytosolic proteasome subunit low molecular weight protein 2 (LMP2), the endoplasmatic reticulum (ER) transporter associated with antigen processing-1 (TAP1), and the ER chaperone beta2-microglobulin (beta2m) in astrocytoma cells when compared to astrocytes from nonpathological brain. Among human WHO grade II-IV astrocytomas, downregulation of LMP2, TAP1 and beta2m correlated with grade of malignancy. Furthermore, astrocytoma cell lines (n = 12) expressed all APM components analyzed at levels comparable to dendritic cells (DC), which were used for comparative purposes. However, upregulation of beta2m after stimulation with inflammatory cytokines was significantly lower in astrocytoma cell lines than in control cells. Our results support the hypothesis that coordinated downregulation or impaired upregulation of certain HLA class I APM components may serve as a mechanism for astrocytoma cells to evade the host's immune response, even if HLA class I antigen surface expression is not altered.

Cancer immunomics using autoantibody signatures for biomarker discovery

The increased incidence of autoantibodies in malignancies has been described since the 1970s. Thus the ability to determine molecular fingerprinting of autoantibodies (antibody signatures) may provide useful clinical diagnostic and prognostic information. This review describes the use of several proteomics approaches for the identification of antigens recognized by these autoantibodies. Serological proteome analysis combines separation of tumor cell proteins on two-dimensional gel electrophoresis gels, Western blotting with sera of patients and healthy subjects, and identification of the detected antigens by MS. Alternatively multiple affinity protein profiling combines isolation of the antigens recognized by patient antibodies by two-dimensional immunoaffinity chromatography and identification by MS/MS. The use and limitations of reverse phase protein microarrays for testing patient serum containing autoantibodies are also considered. Lastly the most important difficulty of any proteomically identified autoantibody signature is validation in patient cohorts or clinical samples.

Ubiquitin COOH-Terminal Hydrolase 1: A Biomarker of Renal Cell Carcinoma Associated with Enhanced Tumor Cell Proliferation and Migration[?Q1: Running head: UCHL1, a Biomarker of RCC. Short title OK?Q1]

PURPOSE

Renal cell carcinoma (RCC) accounts for 2% to 3% of all malignancies. It represents one of the most radiation- and chemotherapy-resistant tumors and surgical resections are only effective in organ-defined disease. However, RCC is an immunogenic tumor with response rates to immunotherapies between 10% and 20% of the treated patients. Due to the currently inefficient therapies and the low 5-year survival rates of RCC patients, novel diagnostic, prognostic, and therapeutic markers are urgently needed for this disease.

EXPERIMENTAL DESIGN

Proteome-based approaches were used to identify (a) differentially expressed proteins in RCC compared with normal kidney epithelium and (b) proteins that are able to induce an antibody response in RCC patients. Based on these experiments, a promising candidate was subsequently validated by reverse transcription-PCR, Western blot analyses, and immunohistochemistry. In addition, functional assays were done in generated transfectants.

RESULTS

The ubiquitin COOH-terminal hydrolase L1 (UCHL1) was found to be differentially expressed in both RCC lesions and RCC cell lines and immunoreactive using patients' sera. UCHL1 expression was often down-regulated in primary RCC when compared with normal kidney epithelium but dependent on the RCC subtype, the von Hippel-Lindau phenotype, and the tumor grading. Moreover, the frequency and the level of UCHL1 expression were higher in metastases when compared with primary RCC lesions. Gain-of-function transfectants exhibited a significant higher proliferation and migration rate than UCHL1-negative RCC cells.

CONCLUSIONS

UCHL1 expression seems to be associated with the metastatic phenotype of RCC and therefore might serve as potential biomarker for the diagnosis and prognosis of RCC patients.

Identification of fatty acid binding proteins as markers associated with the initiation and/or progression of renal cell carcinoma

Renal cell carcinoma (RCC) representing the most common neoplasia of the kidney in Western countries is a histologic diverse disease with an often unpredictable course. The prognosis of RCC is worsened with the onset of metastasis, and the therapies currently available are of limited success for the treatment of metastatic RCC. Although gene expression analyses and other methods are promising tools clarifying and standardizing the pathological classification of RCC, novel innovative molecular markers for the diagnosis, prognosis, and for the monitoring of this disease during therapy as well as potential therapeutic targets are urgently needed. Using proteome-based strategies, a number of RCC-associated markers either over-expressed or down-regulated in tumor lesions in comparison to the normal epithelium have been identified which have been implicated in tumorigenesis, but never linked to the initiation and/or progression of RCC. These include members of the fatty acid binding protein family, which have the potential to serve as diagnostic or prognostic markers for the screening of RCC patients.

From proteomics to biomarker discovery in Alzheimer's disease

Alzheimer's disease (AD) is the most common form of dementia in the elderly. AD is an invariably fatal neurodegenerative disorder with no effective treatment or definitive antemortem diagnostic test. Little is known about the changes in the brain preceding or accompanying initiation of the disease. Understanding the biological processes, which occur during AD onset and/or progression, will improve the diagnosis and treatment of the disease. As we will discuss in this review article, using high-throughput cDNA microarray we identified candidate genes whose expression is altered in the brain of cases at risk for AD dementia. However, it is possible that the use of the cDNA microarray technology alone may underestimate post-transcriptional modifications and therefore provides only a partial view of the biological problem of interest. As such, the combination of cDNA and protein arrays may provide a more global picture of the biological processes being studied. Based on this hypothesis, we initiated a series of high-throughput proteomic studies and found that the expressions of proteins involved in synaptic plasticity are selectively altered in the brain of cases at high risk to develop AD dementia (mild cognitive impairment; MCI). This is consistent with our cDNA microarray evidence showing that the expression of a-type synapsins is selectively altered in the brain of MCI cases. Collectively, these studies support the feasibility and usefulness of high-throughput cDNA microarray and proteomics techniques to study the sequential changes of distinctive gene expression patterns in the brain as a function of the progression of AD dementia.