Aufgrund ihres sehr hohen Metastasierungsrisikos weisen Patienten mit klarzelligem Nierenzellkarzinom (kzNZK) eine sehr hohe Sterblichkeit auf. Mit den zurzeit zur Verfügung stehenden klinischen Parametern kann der Krankheitsverlauf der Patienten nach der operativen Entfernung des Primärtumors nur unzureichend vorhergesagt werden. Um das Nachsorge- und Therapieregime der Patienten zu optimieren, muss die Vorhersagegenauigkeit der bestehenden Prognosemodelle durch molekulare Marker erhöht werden. Um geeignete Gene für eine Abschätzung von Metastasierungsrisiko und krankheitsfreiem Überleben (DFS) zu identifizieren, wurden genomweite Expressionsanalysen sowohl an Lungenmetastasen (n = 24) als auch an Primärtumoren (n = 24) des kzNZK vorgenommen. Durch Vergleich von Metastasensubgruppen, die sich nach unterschiedlich langen DFS entwickelt hatten bzw. Primärtumoren, die nach unterschiedlich langen DFS Metastasen bedingten, wurden tumorintrinsische DFS-assoziierte Expressionsmuster identifiziert. Weiterhin wurden Gene identifiziert, deren Expression sich zwischen Primärtumoren unterschied, die im Krankheitsverlauf manifeste Metastasen bedingten und solchen, die dies nicht taten. Die differenzielle Expression funktionell interessanter, teilweise auch in anderen publizierten Microarraystudien an kzNZK bestätigter Gene wurde im Folgenden mittels quantitativer Polymerasekettenreaktion (qPCR) validiert. Anschließend wurde die Assoziation ausgewählter Gene mit klinischen Parametern und dem Überleben der Patienten untersucht. Ein von klinischen Parametern unabhängiger Einfluss auf den Krankheitsverlauf der Patienten wurde dabei für EDNRB und PECAM1 auf Expressionsebene (qPCR; n = 86) sowie für TSPAN7 auf Proteinebene (Immunhistochemie an „Tissue Microarrays“; n = 106) belegt. EDNRB und PECAM1 waren signifikant höher exprimiert in Primärtumoren mit günstigen klinischen Parametern (TNMI/II, G1/2, V0, N0/M0). TSPAN7 war vorwiegend in den Gefäßen der primären kzNZK nachweisbar; eine signifikant höhere Zahl TSPAN7-positiver Gefäße war ebenfalls in Tumoren mit günstigen klinischen Parametern zu verzeichnen (pT1/2, TNMI/II, N0). Überlebensanalysen zeigten ein signifikant längeres DFS für Patienten mit einer hohen im Vergleich zu solchen mit einer geringen EDNRB-Expression und für Patienten, die in beiden untersuchten Gewebestanzen der „Tissue Microarrays“ TSPAN7-positive Gefäße aufwiesen im Vergleich zu Patienten mit nur einer oder keiner TSPAN7-gefäßpositiven Stanze. Für Patienten mit einer hohen im Vergleich zu solchen mit einer geringen EDNRB- bzw. PECAM1-Expression oder mit zwei im Vergleich zu keiner oder einer TSPAN7-gefäßpositiven Gewebestanze war zudem ein signifikant längeres tumorspezifisches Überleben (TSS) zu verzeichnen. Mit Hilfe multivariater Cox-Regressionsanalysen wurde eine unabhängige günstige prognostische Relevanz für EDNRB auf das DFS sowie für EDNRB, PECAM1 und TSPAN7 auf das TSS nachgewiesen. Somit sind diese molekularen Faktoren geeignet, um die Genauigkeit der bestehenden und ausschließlich auf klinischen Parametern basierenden Prognosemodelle zu erhöhen. Für eine Abschätzung von DFS und Metastasierungsrisiko erscheint dabei insbesondere EDNRB geeignet. / Patients with clear cell renal cell carcinoma (ccRCC) have an extremely poor prognosis due to their high risk of metastases. Currently used clinico-patological parameters are insufficient for reliable prediction of metastatic risk and disease free survival (DFS) after surgical resection of the primary tumor. Molecular markers are strongly needed to improve outcome prediction, and thus to optimize the follow up and treatment schedule for patients with ccRCC. To identify genes which are suitable for the prediction of metastatic risk and DFS, genome-wide expression analyses were performed on pulmonary metastases (n = 24) and primary tumors (n = 24) obtained from patients with ccRCC. Tumor-intrinsic DFS-associated expression patterns were observed by comparing subgroups of metastases, which had developed within different DFS as well as primary tumors, which had caused metastases after different DFS. Furthermore, genes differentially expressed in primary tumors, which caused macroscopic metastases and tumors, which did not were identified. The differential expression of genes with a potential function in metastatic spread, which has in part been identified in independent published microarray studies as well, were validated by quantitative polymerase chain reaction (qPCR). Moreover, an independent prognostic impact on the survival of ccRCC patients was observed for the EDNRB und the PECAM1 gene expression (qPCR; n = 86) as well as for the TSPAN7 protein level (immunohistochemistry on tissue microarrays; n = 106). Primary tumors of patients with favourable clinico-pathological parameters (TNMI/II, G1/2, V0, N0/M0) showed a significantly higher EDNRB und PECAM1 gene expression than those with unfavorable parameters. TSPAN7 was predominantly detected in blood vessels of ccRCC tissues. In patients with favourable clinico-pathological parameters (pT1/2, TNMI/II, N0) a significantly higher number of TSPAN7-positive vessels was observed. Using survival analyses, a significantly longer DFS was observed for patients with a high compared to those with a low EDNRB expression as well as for patients with TSPAN7-positive vessels in both cores compared to no or one of the both cores investigated on tissue microarrays. A significantly longer TSS was observed for patients with a high EDNRB or PECAM1 expression as well as for patients with TSPAN7-positive vessles in both tissue cores investigated. Furthermore, EDNRB was an independent prognostic factor for the DFS of the patients; EDNRB, PECAM and TSPAN7 had an independent prognostic impact on the TSS. Therefore, these molecular markers are suitable to improve the accuracy of outcome prediction based on clinico-pathological parameters in ccRCC. For the prediction of DFS and metastatic risk EDNRB is particularly interesting.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Theory predicts that sexually antagonistic mutations will be over- or under-represented on the X and Z chromosomes, depending on the average dominance coefficient of the mutations. However, as little is known about the dominance coefficients for new mutations, the effect of sexually antagonistic selection is difficult to predict. To elucidate the role of sexually antagonistic selection in the evolution of Z chromosome gene content in chicken, we analyzed publicly available microarray data from several somatic tissues as well as somatic and germ cells of the ovary. We found that the Z chromosome is enriched for genes showing preferential expression in ovarian somatic cells, but not for genes with preferential expression in primary oocytes or non-sex-specific somatic tissues. Our results suggest that sexual antagonism leads to higher abundance of female-benefit alleles on the Z chromosome. No bias towards Z-linkage of oocyte-enriched genes can be explained by lower intensity of sexually antagonistic selection in ovarian germ cells compared to ovarian somatic cells. An alternative explanation would be that meiotic Z chromosome inactivation hinders accumulation of oocyte-expressed genes on the Z chromosome. Our results are consistent with findings in mammals and indicate that recessive rather than dominant...

La technologie des microarrays demeure à ce jour un outil important pour la mesure de l'expression génique. Au-delà de la technologie elle-même, l'analyse des données provenant des microarrays constitue un problème statistique complexe, ce qui explique la myriade de méthodes proposées pour le pré-traitement et en particulier, l'analyse de l'expression différentielle. Toutefois, l'absence de données de calibration ou de méthodologie de comparaison appropriée a empêché l'émergence d'un consensus quant aux méthodes d'analyse optimales. En conséquence, la décision de l'analyste de choisir telle méthode plutôt qu'une autre se fera la plupart du temps de façon subjective, en se basant par exemple sur la facilité d'utilisation, l'accès au logiciel ou la popularité. Ce mémoire présente une approche nouvelle au problème de la comparaison des méthodes d'analyse de l'expression différentielle. Plus de 800 pipelines d'analyse sont appliqués à plus d'une centaine d'expériences sur deux plateformes Affymetrix différentes. La performance de chacun des pipelines est évaluée en calculant le niveau moyen de co-régulation par l'entremise de scores d'enrichissements pour différentes collections de signatures moléculaires. L'approche comparative proposée repose donc sur un ensemble varié de données biologiques pertinentes, ne confond pas la reproductibilité avec l'exactitude et peut facilement être appliquée à de nouvelles méthodes. Parmi les méthodes testées, la supériorité de la sommarisation FARMS et de la statistique de l'expression différentielle TREAT est sans équivoque. De plus, les résultats obtenus quant à la statistique d'expression différentielle corroborent les conclusions d'autres études récentes à propos de l'importance de prendre en compte la grandeur du changement en plus de sa significativité statistique. / Microarrays remain an important tool for the measurement of gene expression, and a myriad of methods for their pre-processing or statistical testing of differential expression has been proposed in the past. However, insufficient and sometimes contradictory evidence has prevented the emergence of a strong consensus over a preferred methodology. This leaves microarray practitioners to somewhat arbitrarily decide which method should be used to analyze their data. Here we present a novel approach to the problem of comparing methods for the identification of differentially expressed genes. Over eight hundred analytic pipelines were applied to more than a hundred independent microarray experiments. The accuracy of each analytic pipeline was assessed by measuring the average level of co-regulation uncovered across all data sets. This analysis thus relies on a varied set of biologically relevant data, does not confound reproducibility for accuracy and can easily be extended to future analytic pipelines. This procedure identified FARMS summarization and the TREAT gene ordering statistic as algorithms significantly more accurate than other alternatives. Most interestingly, our results corroborate recent findings about the importance of taking the magnitude of change into account along with an assessment of statistical significance.

La technologie des microarrays demeure à ce jour un outil important pour la mesure de l'expression génique. Au-delà de la technologie elle-même, l'analyse des données provenant des microarrays constitue un problème statistique complexe, ce qui explique la myriade de méthodes proposées pour le pré-traitement et en particulier, l'analyse de l'expression différentielle. Toutefois, l'absence de données de calibration ou de méthodologie de comparaison appropriée a empêché l'émergence d'un consensus quant aux méthodes d'analyse optimales. En conséquence, la décision de l'analyste de choisir telle méthode plutôt qu'une autre se fera la plupart du temps de façon subjective, en se basant par exemple sur la facilité d'utilisation, l'accès au logiciel ou la popularité. Ce mémoire présente une approche nouvelle au problème de la comparaison des méthodes d'analyse de l'expression différentielle. Plus de 800 pipelines d'analyse sont appliqués à plus d'une centaine d'expériences sur deux plateformes Affymetrix différentes. La performance de chacun des pipelines est évaluée en calculant le niveau moyen de co-régulation par l'entremise de scores d'enrichissements pour différentes collections de signatures moléculaires. L'approche comparative proposée repose donc sur un ensemble varié de données biologiques pertinentes, ne confond pas la reproductibilité avec l'exactitude et peut facilement être appliquée à de nouvelles méthodes. Parmi les méthodes testées, la supériorité de la sommarisation FARMS et de la statistique de l'expression différentielle TREAT est sans équivoque. De plus, les résultats obtenus quant à la statistique d'expression différentielle corroborent les conclusions d'autres études récentes à propos de l'importance de prendre en compte la grandeur du changement en plus de sa significativité statistique. / Microarrays remain an important tool for the measurement of gene expression, and a myriad of methods for their pre-processing or statistical testing of differential expression has been proposed in the past. However, insufficient and sometimes contradictory evidence has prevented the emergence of a strong consensus over a preferred methodology. This leaves microarray practitioners to somewhat arbitrarily decide which method should be used to analyze their data. Here we present a novel approach to the problem of comparing methods for the identification of differentially expressed genes. Over eight hundred analytic pipelines were applied to more than a hundred independent microarray experiments. The accuracy of each analytic pipeline was assessed by measuring the average level of co-regulation uncovered across all data sets. This analysis thus relies on a varied set of biologically relevant data, does not confound reproducibility for accuracy and can easily be extended to future analytic pipelines. This procedure identified FARMS summarization and the TREAT gene ordering statistic as algorithms significantly more accurate than other alternatives. Most interestingly, our results corroborate recent findings about the importance of taking the magnitude of change into account along with an assessment of statistical significance.

The endocrine heart synthesises and secretes two polypeptide hormones: the natriuretic peptides (NP) atrial natriuretic factor (ANF) and B-type natriuretic peptide (BNP). The biological actions of these hormones serve both acutely and chronically to reduce systemic blood pressure and hemodynamic load to the heart, thus contributing to the maintenance of cardiorenal homeostasis. Considerable effort has been focused on the elucidation of the mechanistic underlying ANF and BNP gene expression and secretion but much remains to be determined regarding specific molecular events involved in the cardiocyte secretory function. These hormones are produced by the atrial muscle cells (cardiocytes), which display a dual secretory/muscle phenotype. In contrast, ventricular cardiocytes display mainly a muscle phenotype. Comparatively little information is available regarding the genetic background for this important phenotypic difference with particular reference to the endocrine function of the heart. We postulated that comparison of gene expression profiles between atrial and ventricular muscles would help identify transcripts that underlie the phenotypic differences associated with the endocrine function of the heart as well as identify signaling pathways involved in its regulation. The cardiac atrial and ventricular transcriptomes were analyzed using oligonucleotide microarrays under normal or chronically induced aortocaval shunt volume-overload conditions. Transcriptional differences were validated by RT-PCR and transcripts of interest were knocked-down by RNAi. Comparison of gene expression profiles in the rat heart revealed a total of 1415 differentially expressed genes between normal atrial and ventricular tissues. Functional classification and pathway analysis identified numerous transcripts involved in mechanosensing, vesicle trafficking, hormone secretion, and G protein signaling. Volume-overloaded animals exhibited a progressive increase in cardiac mass over the four-week time course, an increase in expression of known hypertrophic genes, as well as the differential expression of 700 genes within the atria. Volume-overload specifically downregulated the accessory protein for heterotrimeric G protein signaling RASD1 in the atria. In vitro, knockdown of RASD1 in the atrial-derived HL-1 cells, significantly increased ANF secretion, demonstrating a previously unknown negative modulator role for RASD1. The data developed in this investigation provides insight into the expression profiles of genes particularly centered on the secretory function of the heart under normal and chronic hemodynamic overload conditions. Genome-wide expression profile analysis identified RASD1 as being differentially expressed between cardiac tissues as well as being modulated by chronic volume overload. RASD1 emerges as a tonic inhibitor of ANF secretion. The novel function identified herein for RASD1 in the atria is of considerable interest given the fact that secretory impairment of the cardiac natriuretic hormones can negatively impact cardiovascular homeostasis.

The endocrine heart synthesises and secretes two polypeptide hormones: the natriuretic peptides (NP) atrial natriuretic factor (ANF) and B-type natriuretic peptide (BNP). The biological actions of these hormones serve both acutely and chronically to reduce systemic blood pressure and hemodynamic load to the heart, thus contributing to the maintenance of cardiorenal homeostasis. Considerable effort has been focused on the elucidation of the mechanistic underlying ANF and BNP gene expression and secretion but much remains to be determined regarding specific molecular events involved in the cardiocyte secretory function. These hormones are produced by the atrial muscle cells (cardiocytes), which display a dual secretory/muscle phenotype. In contrast, ventricular cardiocytes display mainly a muscle phenotype. Comparatively little information is available regarding the genetic background for this important phenotypic difference with particular reference to the endocrine function of the heart. We postulated that comparison of gene expression profiles between atrial and ventricular muscles would help identify transcripts that underlie the phenotypic differences associated with the endocrine function of the heart as well as identify signaling pathways involved in its regulation. The cardiac atrial and ventricular transcriptomes were analyzed using oligonucleotide microarrays under normal or chronically induced aortocaval shunt volume-overload conditions. Transcriptional differences were validated by RT-PCR and transcripts of interest were knocked-down by RNAi. Comparison of gene expression profiles in the rat heart revealed a total of 1415 differentially expressed genes between normal atrial and ventricular tissues. Functional classification and pathway analysis identified numerous transcripts involved in mechanosensing, vesicle trafficking, hormone secretion, and G protein signaling. Volume-overloaded animals exhibited a progressive increase in cardiac mass over the four-week time course, an increase in expression of known hypertrophic genes, as well as the differential expression of 700 genes within the atria. Volume-overload specifically downregulated the accessory protein for heterotrimeric G protein signaling RASD1 in the atria. In vitro, knockdown of RASD1 in the atrial-derived HL-1 cells, significantly increased ANF secretion, demonstrating a previously unknown negative modulator role for RASD1. The data developed in this investigation provides insight into the expression profiles of genes particularly centered on the secretory function of the heart under normal and chronic hemodynamic overload conditions. Genome-wide expression profile analysis identified RASD1 as being differentially expressed between cardiac tissues as well as being modulated by chronic volume overload. RASD1 emerges as a tonic inhibitor of ANF secretion. The novel function identified herein for RASD1 in the atria is of considerable interest given the fact that secretory impairment of the cardiac natriuretic hormones can negatively impact cardiovascular homeostasis.

The endocrine heart synthesises and secretes two polypeptide hormones: the natriuretic peptides (NP) atrial natriuretic factor (ANF) and B-type natriuretic peptide (BNP). The biological actions of these hormones serve both acutely and chronically to reduce systemic blood pressure and hemodynamic load to the heart, thus contributing to the maintenance of cardiorenal homeostasis. Considerable effort has been focused on the elucidation of the mechanistic underlying ANF and BNP gene expression and secretion but much remains to be determined regarding specific molecular events involved in the cardiocyte secretory function. These hormones are produced by the atrial muscle cells (cardiocytes), which display a dual secretory/muscle phenotype. In contrast, ventricular cardiocytes display mainly a muscle phenotype. Comparatively little information is available regarding the genetic background for this important phenotypic difference with particular reference to the endocrine function of the heart. We postulated that comparison of gene expression profiles between atrial and ventricular muscles would help identify transcripts that underlie the phenotypic differences associated with the endocrine function of the heart as well as identify signaling pathways involved in its regulation. The cardiac atrial and ventricular transcriptomes were analyzed using oligonucleotide microarrays under normal or chronically induced aortocaval shunt volume-overload conditions. Transcriptional differences were validated by RT-PCR and transcripts of interest were knocked-down by RNAi. Comparison of gene expression profiles in the rat heart revealed a total of 1415 differentially expressed genes between normal atrial and ventricular tissues. Functional classification and pathway analysis identified numerous transcripts involved in mechanosensing, vesicle trafficking, hormone secretion, and G protein signaling. Volume-overloaded animals exhibited a progressive increase in cardiac mass over the four-week time course, an increase in expression of known hypertrophic genes, as well as the differential expression of 700 genes within the atria. Volume-overload specifically downregulated the accessory protein for heterotrimeric G protein signaling RASD1 in the atria. In vitro, knockdown of RASD1 in the atrial-derived HL-1 cells, significantly increased ANF secretion, demonstrating a previously unknown negative modulator role for RASD1. The data developed in this investigation provides insight into the expression profiles of genes particularly centered on the secretory function of the heart under normal and chronic hemodynamic overload conditions. Genome-wide expression profile analysis identified RASD1 as being differentially expressed between cardiac tissues as well as being modulated by chronic volume overload. RASD1 emerges as a tonic inhibitor of ANF secretion. The novel function identified herein for RASD1 in the atria is of considerable interest given the fact that secretory impairment of the cardiac natriuretic hormones can negatively impact cardiovascular homeostasis.

The endocrine heart synthesises and secretes two polypeptide hormones: the natriuretic peptides (NP) atrial natriuretic factor (ANF) and B-type natriuretic peptide (BNP). The biological actions of these hormones serve both acutely and chronically to reduce systemic blood pressure and hemodynamic load to the heart, thus contributing to the maintenance of cardiorenal homeostasis. Considerable effort has been focused on the elucidation of the mechanistic underlying ANF and BNP gene expression and secretion but much remains to be determined regarding specific molecular events involved in the cardiocyte secretory function. These hormones are produced by the atrial muscle cells (cardiocytes), which display a dual secretory/muscle phenotype. In contrast, ventricular cardiocytes display mainly a muscle phenotype. Comparatively little information is available regarding the genetic background for this important phenotypic difference with particular reference to the endocrine function of the heart. We postulated that comparison of gene expression profiles between atrial and ventricular muscles would help identify transcripts that underlie the phenotypic differences associated with the endocrine function of the heart as well as identify signaling pathways involved in its regulation. The cardiac atrial and ventricular transcriptomes were analyzed using oligonucleotide microarrays under normal or chronically induced aortocaval shunt volume-overload conditions. Transcriptional differences were validated by RT-PCR and transcripts of interest were knocked-down by RNAi. Comparison of gene expression profiles in the rat heart revealed a total of 1415 differentially expressed genes between normal atrial and ventricular tissues. Functional classification and pathway analysis identified numerous transcripts involved in mechanosensing, vesicle trafficking, hormone secretion, and G protein signaling. Volume-overloaded animals exhibited a progressive increase in cardiac mass over the four-week time course, an increase in expression of known hypertrophic genes, as well as the differential expression of 700 genes within the atria. Volume-overload specifically downregulated the accessory protein for heterotrimeric G protein signaling RASD1 in the atria. In vitro, knockdown of RASD1 in the atrial-derived HL-1 cells, significantly increased ANF secretion, demonstrating a previously unknown negative modulator role for RASD1. The data developed in this investigation provides insight into the expression profiles of genes particularly centered on the secretory function of the heart under normal and chronic hemodynamic overload conditions. Genome-wide expression profile analysis identified RASD1 as being differentially expressed between cardiac tissues as well as being modulated by chronic volume overload. RASD1 emerges as a tonic inhibitor of ANF secretion. The novel function identified herein for RASD1 in the atria is of considerable interest given the fact that secretory impairment of the cardiac natriuretic hormones can negatively impact cardiovascular homeostasis.

Aufgrund ihres sehr hohen Metastasierungsrisikos weisen Patienten mit klarzelligem Nierenzellkarzinom (kzNZK) eine sehr hohe Sterblichkeit auf. Mit den zurzeit zur Verfügung stehenden klinischen Parametern kann der Krankheitsverlauf der Patienten nach der operativen Entfernung des Primärtumors nur unzureichend vorhergesagt werden. Um das Nachsorge- und Therapieregime der Patienten zu optimieren, muss die Vorhersagegenauigkeit der bestehenden Prognosemodelle durch molekulare Marker erhöht werden. Um geeignete Gene für eine Abschätzung von Metastasierungsrisiko und krankheitsfreiem Überleben (DFS) zu identifizieren, wurden genomweite Expressionsanalysen sowohl an Lungenmetastasen (n = 24) als auch an Primärtumoren (n = 24) des kzNZK vorgenommen. Durch Vergleich von Metastasensubgruppen, die sich nach unterschiedlich langen DFS entwickelt hatten bzw. Primärtumoren, die nach unterschiedlich langen DFS Metastasen bedingten, wurden tumorintrinsische DFS-assoziierte Expressionsmuster identifiziert. Weiterhin wurden Gene identifiziert, deren Expression sich zwischen Primärtumoren unterschied, die im Krankheitsverlauf manifeste Metastasen bedingten und solchen, die dies nicht taten. Die differenzielle Expression funktionell interessanter, teilweise auch in anderen publizierten Microarraystudien an kzNZK bestätigter Gene wurde im Folgenden mittels quantitativer Polymerasekettenreaktion (qPCR) validiert. Anschließend wurde die Assoziation ausgewählter Gene mit klinischen Parametern und dem Überleben der Patienten untersucht. Ein von klinischen Parametern unabhängiger Einfluss auf den Krankheitsverlauf der Patienten wurde dabei für EDNRB und PECAM1 auf Expressionsebene (qPCR; n = 86) sowie für TSPAN7 auf Proteinebene (Immunhistochemie an „Tissue Microarrays“; n = 106) belegt. EDNRB und PECAM1 waren signifikant höher exprimiert in Primärtumoren mit günstigen klinischen Parametern (TNMI/II, G1/2, V0, N0/M0). TSPAN7 war vorwiegend in den Gefäßen der primären kzNZK nachweisbar; eine signifikant höhere Zahl TSPAN7-positiver Gefäße war ebenfalls in Tumoren mit günstigen klinischen Parametern zu verzeichnen (pT1/2, TNMI/II, N0). Überlebensanalysen zeigten ein signifikant längeres DFS für Patienten mit einer hohen im Vergleich zu solchen mit einer geringen EDNRB-Expression und für Patienten, die in beiden untersuchten Gewebestanzen der „Tissue Microarrays“ TSPAN7-positive Gefäße aufwiesen im Vergleich zu Patienten mit nur einer oder keiner TSPAN7-gefäßpositiven Stanze. Für Patienten mit einer hohen im Vergleich zu solchen mit einer geringen EDNRB- bzw. PECAM1-Expression oder mit zwei im Vergleich zu keiner oder einer TSPAN7-gefäßpositiven Gewebestanze war zudem ein signifikant längeres tumorspezifisches Überleben (TSS) zu verzeichnen. Mit Hilfe multivariater Cox-Regressionsanalysen wurde eine unabhängige günstige prognostische Relevanz für EDNRB auf das DFS sowie für EDNRB, PECAM1 und TSPAN7 auf das TSS nachgewiesen. Somit sind diese molekularen Faktoren geeignet, um die Genauigkeit der bestehenden und ausschließlich auf klinischen Parametern basierenden Prognosemodelle zu erhöhen. Für eine Abschätzung von DFS und Metastasierungsrisiko erscheint dabei insbesondere EDNRB geeignet. / Patients with clear cell renal cell carcinoma (ccRCC) have an extremely poor prognosis due to their high risk of metastases. Currently used clinico-patological parameters are insufficient for reliable prediction of metastatic risk and disease free survival (DFS) after surgical resection of the primary tumor. Molecular markers are strongly needed to improve outcome prediction, and thus to optimize the follow up and treatment schedule for patients with ccRCC. To identify genes which are suitable for the prediction of metastatic risk and DFS, genome-wide expression analyses were performed on pulmonary metastases (n = 24) and primary tumors (n = 24) obtained from patients with ccRCC. Tumor-intrinsic DFS-associated expression patterns were observed by comparing subgroups of metastases, which had developed within different DFS as well as primary tumors, which had caused metastases after different DFS. Furthermore, genes differentially expressed in primary tumors, which caused macroscopic metastases and tumors, which did not were identified. The differential expression of genes with a potential function in metastatic spread, which has in part been identified in independent published microarray studies as well, were validated by quantitative polymerase chain reaction (qPCR). Moreover, an independent prognostic impact on the survival of ccRCC patients was observed for the EDNRB und the PECAM1 gene expression (qPCR; n = 86) as well as for the TSPAN7 protein level (immunohistochemistry on tissue microarrays; n = 106). Primary tumors of patients with favourable clinico-pathological parameters (TNMI/II, G1/2, V0, N0/M0) showed a significantly higher EDNRB und PECAM1 gene expression than those with unfavorable parameters. TSPAN7 was predominantly detected in blood vessels of ccRCC tissues. In patients with favourable clinico-pathological parameters (pT1/2, TNMI/II, N0) a significantly higher number of TSPAN7-positive vessels was observed. Using survival analyses, a significantly longer DFS was observed for patients with a high compared to those with a low EDNRB expression as well as for patients with TSPAN7-positive vessels in both cores compared to no or one of the both cores investigated on tissue microarrays. A significantly longer TSS was observed for patients with a high EDNRB or PECAM1 expression as well as for patients with TSPAN7-positive vessles in both tissue cores investigated. Furthermore, EDNRB was an independent prognostic factor for the DFS of the patients; EDNRB, PECAM and TSPAN7 had an independent prognostic impact on the TSS. Therefore, these molecular markers are suitable to improve the accuracy of outcome prediction based on clinico-pathological parameters in ccRCC. For the prediction of DFS and metastatic risk EDNRB is particularly interesting.