Transcriptome analysis of normal kidney, primary and metastasis ccRCC
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE105261 | GEO | 2018/10/16
REPOSITORIES: GEO
Similar Datasets
Project description:In order to address the progression, metastasis, and clinical heterogeneity of renal cell cancer (RCC), transcriptional profiling with oligonucleotide microarrays (22,283 genes) was done on 49 RCC tumors, 20 non-RCC renal tumors, and 23 normal kidney samples. Samples were clustered based on gene expression profiles and specific gene sets for each renal tumor type were identified. Gene expression was correlated to disease progression and a metastasis gene signature was derived. Gene signatures were identified for each tumor type with 100% accuracy. Differentially expressed genes during early tumor formation and tumor progression to metastatic RCC were found. Subsets of these genes code for secreted proteins and membrane receptors and are both potential therapeutic or diagnostic targets. A gene pattern ("metastatic signature") derived from primary tumors was very accurate in classifying tumors with and without metastases at the time of surgery. A previously described "global" metastatic signature derived by another group from various non-RCC tumors was validated in RCC. Unlike previous studies, we describe highly accurate and externally validated gene signatures for RCC subtypes and other renal tumors. Interestingly, the gene expression of primary tumors provides us information about the metastatic status in the respective patients and has the potential, if prospectively validated, to enrich the armamentarium of diagnostic tests in RCC. We validated in RCC, for the first time, a previously described metastatic signature and further showed the feasibility of applying a gene signature across different microarray platforms. Transcriptional profiling allows a better appreciation of the molecular and clinical heterogeneity in RCC. We used the following tissue samples to obtain transcriptional profiling of kidney tumors using Affymetrix HGU-133A chips: 23 Normal, 32 clear cell RCC (cRCC), 11 papillary RCC (pRCC), 6 chromophobe RCC (chrRCC), 12 Oncocytoma (OC), and 8 transitional cell carcinoma (TCC). The supplementary file 'GSE15641_mas5_data.txt' contains MAS5 signal values for the Samples included in Series GSE15641. This dataset is part of the TransQST collection.
2009-04-28 | E-GEOD-15641 | biostudies-arrayexpress
Project description:In recent years, several approaches have been taken in the peptide-based immunotherapy of metastatic renal cell carcinoma (RCC), although little is known about HLA presentation on metastases compared to primary tumor and normal tissue of RCC. In this study we compared primary tumor, normal tissue and metastases with the aim of identifying similarities and differences between these tissues. We performed this comparison for two RCC patients on the level of the HLA ligandome using mass spectrometry and for three patients on the level of the transcriptome using oligonucleotide microarrays. The quantitative results show that primary tumor is more similar to metastasis than to normal tissue, both on the level of HLA ligand presentation and mRNA. We were able to characterize a total of 142 peptides in the qualitative analysis of HLA-presented peptides. Six of them were significantly overpresented on metastasis, among them a peptide derived from CD151; fourteen were overpresented on both primary tumor and metastasis compared to normal tissue, among them an HLA ligand derived from tumor protein p53. Thus, we could demonstrate that peptide-based immunotherapy might affect tumor as well as metastasis of RCC, but not healthy kidney tissue. Furthermore we were able to identify several peptides derived from tumor-associated antigens that are suitable for vaccination of metastatic RCC. Three clear cell renal cell carcinomas including autologous normal tissue and autologous metastasis were analyzed. This dataset is part of the TransQST collection.
2008-09-03 | E-GEOD-12606 | biostudies-arrayexpress
Project description:In order to address the progression, metastasis, and clinical heterogeneity of renal cell cancer (RCC), transcriptional profiling with oligonucleotide microarrays (22,283 genes) was done on 49 RCC tumors, 20 non-RCC renal tumors, and 23 normal kidney samples. Samples were clustered based on gene expression profiles and specific gene sets for each renal tumor type were identified. Gene expression was correlated to disease progression and a metastasis gene signature was derived. Gene signatures were identified for each tumor type with 100% accuracy. Differentially expressed genes during early tumor formation and tumor progression to metastatic RCC were found. Subsets of these genes code for secreted proteins and membrane receptors and are both potential therapeutic or diagnostic targets. A gene pattern ("metastatic signature") derived from primary tumors was very accurate in classifying tumors with and without metastases at the time of surgery. A previously described "global" metastatic signature derived by another group from various non-RCC tumors was validated in RCC. Unlike previous studies, we describe highly accurate and externally validated gene signatures for RCC subtypes and other renal tumors. Interestingly, the gene expression of primary tumors provides us information about the metastatic status in the respective patients and has the potential, if prospectively validated, to enrich the armamentarium of diagnostic tests in RCC. We validated in RCC, for the first time, a previously described metastatic signature and further showed the feasibility of applying a gene signature across different microarray platforms. Transcriptional profiling allows a better appreciation of the molecular and clinical heterogeneity in RCC.
2009-04-28 | GSE15641 | GEO
Project description:In recent years, several approaches have been taken in the peptide-based immunotherapy of metastatic renal cell carcinoma (RCC), although little is known about HLA presentation on metastases compared to primary tumor and normal tissue of RCC. In this study we compared primary tumor, normal tissue and metastases with the aim of identifying similarities and differences between these tissues. We performed this comparison for two RCC patients on the level of the HLA ligandome using mass spectrometry and for three patients on the level of the transcriptome using oligonucleotide microarrays. The quantitative results show that primary tumor is more similar to metastasis than to normal tissue, both on the level of HLA ligand presentation and mRNA. We were able to characterize a total of 142 peptides in the qualitative analysis of HLA-presented peptides. Six of them were significantly overpresented on metastasis, among them a peptide derived from CD151; fourteen were overpresented on both primary tumor and metastasis compared to normal tissue, among them an HLA ligand derived from tumor protein p53. Thus, we could demonstrate that peptide-based immunotherapy might affect tumor as well as metastasis of RCC, but not healthy kidney tissue. Furthermore we were able to identify several peptides derived from tumor-associated antigens that are suitable for vaccination of metastatic RCC.
2008-09-03 | GSE12606 | GEO
Project description:Transcriptome analysis of normal kidney, primary and metastasis ccRCC
| PRJNA415083 | ENA
Project description:Renal cell carcinoma (RCC) is among the ten most common malignancies. By far, the most common histology is clear cell (ccRCC). The Cancer Genome Atlas and other large scale sequencing studies of ccRCC have been integral to the current understanding of molecular events underlying RCC and its biology. However, these data sets have focused on primary RCC which often demonstrates indolent behavior. In contrast, metastatic disease is the major cause of mortality associated with ccRCC. However, data sets examining metastatic tumor are sparse. We therefore undertook an integrative analysis of gene expression and DNA methylome profiling of metastatic ccRCC in addition to primary RCC and normal kidney. Integrative analysis of the methylome and transcriptome identified over 30 RCC specific genes whose mRNA expression inversely correlated with promoter methylation including several known targets of hypoxia inducible factors (HIFs). Notably, genes encoding several metabolism-related proteins were identified as differentially regulated via methylation. Collectively, our data provide novel insight into biology of aggressive RCC. Furthermore, they demonstrate a clear role for epigenetics in the promotion of HIF signaling and invasive phenotypes in renal cancer.
2018-10-16 | GSE105288 | GEO
Project description:Background/Objective: MicroRNAs (miRNAs) play a pivotal role in cancerogenesis and cancer progression, but their specific role in metastasis of clear cell renal cell carcinomas (ccRCCs) as so-called metastamirs is still limited. Based on microRNA microarray analyses from normal (n=12) and cancerous (n=12) samples of ccRCC specimens and from bone metastases (n=9) of ccRCC patients, we identified a set of 57 differentially expressed microRNAs between those three sample groups of ccRCC. A selected panel of 33 miRNAs, including miRNAs reported in the literature as differentially expressed in non-metastatic RCC, was validated by RT-qPCR on 57 clinical samples. 30 of the 33 examined miRNAs were confirmed to be deregulated. A stepwise down-regulated miRNA expression from normal over primary tumor to metastatic tissue samples was found to be typical. 23 miRNAs (miR-10b/-19a/-19b/-20a/-29a/-29b/-29c/-100/-101/-126/-127/-130/-141/-143/-145/-148a/-192/-194/-200c/-210/-215/-370/-514) were down-regulated in metastatic tissue samples in comparison to normal tissue. This down-regulated expression in metastatic tissue was also present in 21 miRNAs except for miR-127 and miR-370. The altered miRNA profiles including the newly identified metastasis-associated miRNAs, the compiled predicted miRNA-target interactions, and the significant correlations of miRNAs which were either lost or newly appeared in the studied sample groups afford a solid basis for further functional analyses of individual miRNAs. In this study, microarray-based profiling was performed from 9 bone metastatic tissue samples from 9 patients with clear cell renal cell carcinoma (ccRCC). For controls, 2 bone metastatic samples from two patients with prostate carcinoma and 5 total RNA pools (2 different pools of total RNAs isolated from malignant renal tissue samples derived from different ccRCC patients; 1 pool from non-malignant renal tissue of ccRCC patients; 2 pools of total RNA both from malignant and non-malignant prostate cancer tissue) were used. In addition, matched malignant (e.g., malignant NC2) and non-malignant (e.g., non-malignant NN1) samples from two independent 12 ccRCC sets were profiled (these samples were previously analyzed on a different Platform in GSE12105). The 2002 TNM System and the 2004 WHO classification was used for staging and grading.
2013-02-26 | E-GEOD-37989 | biostudies-arrayexpress
Project description:This study investigates the molecular signatures that drive Renal Cell Carcinoma (RCC) metastatic conversion using the metastatic (LM2) and non-metastatic (SN12C) RCC cell lines. Two-condition experiment, RCC Cell lines vs. Reference human genome DNA from normal male.
2010-08-17 | E-GEOD-23633 | biostudies-arrayexpress
Project description:Metastatic clear cell renal cell carcinoma (ccRCC) has a poor prognosis and unpredictable course and there are no molecular markers that reliably predict ccRCC metastasis. In this study, specimens from 84 patients with ccRCC were directly cultured in vitro. The primary cultures from 38 of 94 specimens contained more than 90% tumor cells at 4th passages. After identified by immunostaining, the primary cultures of metastatic- and nonmetastatic ccRCC specimens from the age-, gender-matched patients were subjected to cDNA microrray assays. A total of 842 differentially expressed genes with FDR (false discovery rate) = 4.79% were identified by using SAM (Significance Analysis of Microarray) software. Pathway enrichment and co-occurrence with “cancer”, “metastasis” and “invasion” in the literature annotations enriched the functions of the 842 genes and indicated the reliability of our microarray assays. Novel genes associated with metastasis were selected based on intra-molecular interaction between 205 differentially expressed genes co-occurred with “metastasis” and those not appeared with “metastasis” on Medline, as well as co-expression analysis between 205 differentially expressed genes co-occurred with “metastasis” and those not appeared on Medline in 12 microarray data. FSTL1, AV722783, SLC15A1, DDX17, ORC2L and PKMYT1 were proved to be potential ccRCC metastasis-associated novel genes, based on its expression patterns in the cultures and tumor tissues. Interestingly, the up-regulated genes (CAV1, PKMYT1 and ORC2L) were up-regulated and the down-regulated genes (FSTL1, GSTM3, CYR61, SLC15A1 and AV722783) were down-regulated, in the primary ccRCC specimens as compared with its adjacent normal kidney in 37 patients (determined by semi-quantitative RT-PCR). This study provides potential biomarkers and novel molecular targets for the early diagnosis and treatment of ccRCC metastasis. Keywords: Homo sapiens Because of limited cell number of primary cultures, total RNA of the primary cultures from 2 age and gender matched patients was pooled for each microarray assay. Each assay was technically repeated once. Cy3-labeled 1st cDNA synthesized from total RNA of the metastatic ccRCC pool was mixed with Cy5-labeled 1st cDNA synthesized from total RNA of the non-metastatic ccRCC pool, and hybridized to 16K cDNA chips (GEO Platform ID: GPL6259; SBC-R-HC-100-22, National Engineering Center for Biochip, Shanghai, China) that included 14784 unigenes, 241 negative controls and 527 positive controls. In our study we used a co-expression analysis for the relationship between genes; three gastric cancer Samples were only introduced to this analysis methods.
2008-08-27 | E-GEOD-11072 | biostudies-arrayexpress
Project description:Renal cell carcinoma (RCC) is the most common and lethal cancer of the adult kidney. Its incidence is increasing and outcomes remain poor. Accurate discrimination of RCC patients with poor prognosis was very important for the appropriate and effective patient management. ccRCC originated from dysregulation of different gene expression. To screen novel prognosis markers, a dysregulated mRNA expression profile was identified by microarray in some pairs of different stages ccRCC.
2017-12-31 | GSE100666 | GEO