Expression profiling of human renal carcinomas with functional taxonomic analysis

BACKGROUND: Molecular characterization has contributed to the understanding of the inception, progression, treatment and prognosis of cancer. Nucleic acid array-based technologies extend molecular characterization of tumors to thousands of gene products. To effectively discriminate between tumor sub-types, reliable laboratory techniques and analytic methods are required. RESULTS: We derived mRNA expression profiles from 21 human tissue samples (eight normal kidneys and 13 kidney tumors) and two pooled samples using the Affymetrix GeneChip platform. A panel of ten clustering algorithms combined with four data pre-processing methods identified a consensus cluster dendrogram in 18 of 40 analyses and of these 16 used a logarithmic transformation. Within the consensus dendrogram the expression profiles of the samples grouped according to tissue type; clear cell and chromophobe carcinomas displayed distinctly different gene expression patterns. By using a rigorous statistical selection based method we identified 355 genes that showed significant (p < 0.001) gene expression changes in clear cell renal carcinomas compared to normal kidney. These genes were classified with a tool to conceptualize expression patterns called "Functional Taxonomy". Each tumor type had a distinct "signature," with a high number of genes in the categories of Metabolism, Signal Transduction, and Cellular and Matrix Organization and Adhesion. CONCLUSIONS: Affymetrix GeneChip profiling differentiated clear cell and chromophobe carcinomas from one another and from normal kidney cortex. Clustering methods that used logarithmic transformation of data sets produced dendrograms consistent with the sample biology. Functional taxonomy provided a practical approach to the interpretation of gene expression data

SPARC: a matricellular regulator of tumorigenesis

Although many clinical studies have found a correlation of SPARC expression with malignant progression and patient survival, the mechanisms for SPARC function in tumorigenesis and metastasis remain elusive. The activity of SPARC is context- and cell-type-dependent, which is highlighted by the fact that SPARC has shown seemingly contradictory effects on tumor progression in both clinical correlative studies and in animal models. The capacity of SPARC to dictate tumorigenic phenotype has been attributed to its effects on the bioavailability and signaling of integrins and growth factors/chemokines. These molecular pathways contribute to many physiological events affecting malignant progression, including extracellular matrix remodeling, angiogenesis, immune modulation and metastasis. Given that SPARC is credited with such varied activities, this review presents a comprehensive account of the divergent effects of SPARC in human cancers and mouse models, as well as a description of the potential mechanisms by which SPARC mediates these effects. We aim to provide insight into how a matricellular protein such as SPARC might generate paradoxical, yet relevant, tumor outcomes in order to unify an apparently incongruent collection of scientific literature

Molecular stratification and characterization of clear cell renal cell carcinoma

It is estimated that there will be 58,240 new diagnoses of kidney cancer in 2010. Most cases will be clear cell renal cell carcinoma (ccRCC) and have little information as to how their disease will progress. This diversity of disease natural history is especially noteworthy in a disease so well characterized by the inactivation of the von Hippel Lindau (VHL) tumor suppressor and resulting stabilization of Hypoxia Inducible Factors (HIF). Previous studies had suggested the presence of two or more clusters in ccRCC. Based on the nonuniformity within the disease's natural progression and previous research, we hypothesized that distinct inherent molecular subclasses of ccRCC must exist and, therefore, sought to define and characterize them. In fact, two robust subtypes of ccRCC were identified, designated ccA and ccB. These subtypes are associated with survival by multivariate analysis, conferring a median survival of 8.6 years versus 2 years, respectively. We postulated that the underlying molecular pathways within the data would explain the survival difference. ccA tumors overexpress angiogenesis, hypoxia, and metabolism pathways, common pathways characterizing ccRCC tumors. In contrast, ccB tumors overexpress more aggressive genes related to epithelial to mesenchymal transition, cell cycle, and Wnt targets. VHL analysis and HIF immunohistochemistry suggests that neither appear to be driving subtype differences. To understand what is causing the differences, underlying genetic changes were analyzed. Both subtypes show deletion of chromosome 3p, location of VHL, in greater than 75% of tumors, corresponding with previous research and suggesting a common initiating tumorigenic event. Overall, copy number patterns look very similar between the subtypes; however, more ccB tumors show deletion of chromosomes 9 and 14, which previous studies have shown to correlate with decreased survival. Additionally, ccA tumors have mutations in a number of histone modification genes, suggesting that epigenetic modification may play a role in subtype differences. Finally, a biomarker panel of 120 probes was defined to distinguish ccA and ccB tumors. This panel is the basis of an assay using FFPE tissue for clinical use. This assay will classify tumors into the inherent subtypes identified by this study, with prognostic impact and potentially predictive import.Doctor of Philosoph

Funktion des zellspezifischen Transkriptionsfaktors HNF4alpha bei der Zellproliferation und Identifizierung von HNF4-alpha-regulierten Genen in Nierenzellen

Der zellspezifische Transkriptionsfaktor HNF4alpha ist für die transkriptionelle Kontrolle von Genen wichtig, die in der Leber, der Niere, dem Magen-Darmtrakt und den b-Zellen des Pankreas exprimiert werden. Obwohl HNF4alpha in den proximalen Tubuli der Niere reichlich exprimiert wird, sind die Funktion und die Zielgene von HNF4alpha in diesem Organ noch unbekannt. Da ein Funktionsausfall von HNF4alpha bei Nierenzellkarzinomen beschrieben worden ist, besteht die Möglichkeit, dass HNF4alpha als Tumorsuppressor in Nierenzellen agiert. Die Erforschung der HNF4alpha-Funktion und der HNF4alpha-Zielgene in Nierenzellen ist daher ein wichtiges Ziel, um aufzuklären, ob HNF4alpha eine Tumorsuppressorfunktion im Nierenzellkarzinom ausübt. Unter Verwendung der Zelllinie Flp-In T-REx 293 wurden zunächst humane embryonale Nierenzellen (HEK293) etabliert, die HNF4alpha wt in einer induzierbaren Form exprimieren. Es zeigte sich, dass die Expression von HNF4alpha wt in HEK293 Zellen zu einer verzögerten Zellproliferation führte. Die Verringerung der Proliferation nach HNF4alpha-Expression war von einer Veränderung der Zellmorphologie begleitet. Um die Gene zu erfassen, deren Aktivität durch HNF4alpha in den HEK293 Zellen spezifisch verändert wird, wurde eine Mikroarray-Analyse durchgeführt. Eine Vielzahl neuer HNF4alpha-regulierter Gene wurde identifiziert. Die verwendeten Filterbedingungen zur Datenanalyse ergaben 65 Gene, die nach 24 Stunden HNF4alpha-Induktion in den HEK293 Zellen reguliert waren. Die differentielle Expression ausgewählter Kandidatengene wurde mittels Real-time PCR und Western Blot bestätigt. Die Analyse der gewebespezifischen Expression der identifizierten HNF4alpha-Zielgene belegte, dass eine hohe Anzahl der identifizierten Gene in der Niere exprimiert werden. Weiterhin wurden die identifizierten HNF4alpha-Zielgene mit den Genen, die im Nierenzellkarzinom differentiell exprimiert werden, verglichen. Dabei zeigte es sich, dass 13 von den 65 HNF4alpha-Zielgenen im Nierenzellkarzinom genau in der umgekehrten Richtung wie in den HEK293 Zellen reguliert sind. Man kann folglich spekulieren, dass diese 13 Gene (ACY1, WT1, SELENBP1, COBL, EFHD1, AGXT2L1, ALDH5A1, THEM2, ABCB1, FLJ14146, CSPG2, TRIM9 und HEY1) im Nierenzellkarzinom aufgrund der verminderten Expression von HNF4alpha dereguliert sind. Sowohl die antiproliferative Wirkung von HNF4alpha in Nierenzellen als auch die Deregulation vieler HNF4alpha-Zielgene im Nierenzellkarzinom stellen Hinweise auf eine Beteiligung von HNF4alpha an der Entstehung des Nierenzellkarzinoms dar

INTEGRATED GENOMICS ANALYSIS OF GENE AND MICRORNA EXPRESSION PROFILES IN CLEAR CELL RENAL CARCINOMA CELL LINES

Renal cell carcinoma (RCC) is the most common neoplasm of the adult kidney, accounting for a total of 2-3% of adult neoplasias, and it arises from the renal epithelium. Clear cell renal cell carcinoma (ccRCC) is the most common, invasive and metastatic among RCC subtypes, representing 75-80% of kidney primary malignancies. The von Hippel-Lindau (VHL) gene, which is the main tumor suppressor gene involved in early steps of RCC tumorigenesis, undergoes complete inactivation by mutation, deletion, and promoter methylation in the majority of sporadic ccRCCs and in all inherited forms. Defining the prognosis for RCC cases is important for both decision-making and counseling patients, but sometimes the diagnosis is difficult because tumor subtypes have overlapping histo-pathological features, thus resulting undistinguishable by microscopy investigation. In recent years, in several human cancers, microarray gene expression profiling proved to be a powerful tool to better classify tumor subtypes and to identify novel molecular biomarkers potentially useful for clinical applications. In fact, tumor transcriptomic profiling may identify patterns of genes that are functionally related to patients\u2019 prognosis, response to therapy and overall survival. Recent evidences have shown that microRNA (miRNA) molecules are involved in tumorigenesis, indicating that miRNAs might function as both tumor suppressors and oncogenes, and their role in RCC pathogenesis is now emerging. miRNAs are small single-stranded non-protein-coding RNA molecules, that function as negative post-transcriptional gene regulators in animals, plants and viruses, and are involved in many biological processes, also including haematopoietic cell differentiation, apoptosis, cell proliferation and organ development. miRNA and gene expression patterns are closely related, since they cooperatively work to create gene regulatory networks. Therefore, integrative genomics approach might be a useful tool to elucidate the complex relationships underlying these networks. The aim of my PhD fellowship work was to reconstruct miRNA-gene post-transcriptional regulatory networks involved in RCC biology, using miRNA and gene expression profiles of three RCC cell lines compared to a normal one, obtained by Affymetrix high-density microarray technology. We calculated differentially expressed genes and miRNAs, and, by functional enrichment analysis, we identified genes and miRNAs that were already known to be associated with RCC and involved in relevant pathways for this pathology, such as hypoxia, p53 signaling, focal adhesion, angiogenesis and mTOR signaling. Through integrated analysis of miRNA-gene expression profiles, we reconstructed potentially active regulatory networks involving miRNAs and their predicted target genes. We validated some miRNA-gene pairs by quantitative PCR, thus confirming their anti-correlated expression levels. Our results demonstrated that RCC cell lines can be an useful in vitro model for RCC pathology, since they showed gene and miRNA expression profiles similar to renal tumoral tissues, as obtained by comparing our results with published data. The analysis of the correlations between gene and miRNA expression profiles using a genome-wide integrative approach could help the identification of both post-transcriptional regulatory networks and novel candidate markers functionally relevant for RCC pathology. However, further investigations are necessary to elucidate the actual role of miRNA-gene networks in the context of RCC progression and outcome

Microarray-based expression profiling : improving data mining and the links to biological knowledge pools

Having identified differentially regulated genes, the final and most labour intensive part of the analysis process is drawing biological conclusions and hypothesises about the data. A novel solution is presented which combines experimental data with a curated annotation sources along with analysis tools to assist the researcher in exploring the information contained within their dataset.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Microarray-based expression profiling: improving data mining and the links to biological knowledge pools

Having identified differentially regulated genes, the final and most labour intensive part of the analysis process is drawing biological conclusions and hypothesises about the data. A novel solution is presented which combines experimental data with a curated annotation sources along with analysis tools to assist the researcher in exploring the information contained within their dataset