GEO DataSets

(Submitter supplied) In recent years, genome wide RNA expression analysis has become a routine tool that offers a great opportunity to study and understand the key role of genes that contribute to carcinogenesis. Various microarray platforms and statistical approaches are implemented to identify genes that might serve as prognostic bio-markers and used for anti-tumor therapies in future. Metastatic renal cell carcinoma (mRCC) is a serious life-threatening disease. more...

Organism:

Homo sapiens

Type:

Expression profiling by array

Platform:

GPL13497

6 Samples

Download data: TXT

(Submitter supplied) Recent advancement in cancer research has shown that tumours are highly heterogeneous and multiple phenotypically different cell populations are found in single nodule. Cancer development and tumour growth is driven by specific type of cells - cancer stem cells or tumour initiating cells (CSCs/TICs), which are to be responsible for tumour growth, metastatic spread and drug resistance. This research was designed to verify the presence of tumour initiating cells in renal cancer cell lines. more...

Organism:

Homo sapiens

Type:

Expression profiling by array

Platform:

GPL13497

9 Samples

Download data: TXT

(Submitter supplied) This SuperSeries is composed of the SubSeries listed below.

Organism:

Homo sapiens

Type:

Expression profiling by array

Platform:

GPL6244

32 Samples

Download data: CEL

(Submitter supplied) Background: Biological interpretation of gene expression data may differ depending on underlying assumptions and statistical tests used by the chosen bioinformatic tool. We used Gene Set Enrichment Analysis (GSEA) and Ingenuity Pathway Analysis (IPA) to analyze previously generated gene expression profiles induced in human monocytes by N. meningitidis and IL-10 (“the model system”), and by meningococcal sepsis plasma before and after immunodepletion of IL-10 (“the patient plasma system”). more...

Organism:

Homo sapiens

Type:

Expression profiling by array

Platform:

GPL6244

12 Samples

Download data: CEL

(Submitter supplied) Background: Biological interpretation of gene expression data may differ depending on underlying assumptions and statistical tests used by the chosen bioinformatic tool. We used Gene Set Enrichment Analysis (GSEA) and Ingenuity Pathway Analysis (IPA) to analyze previously generated gene expression profiles induced in human monocytes by N. meningitidis and IL-10 (“the model system”), and by meningococcal sepsis plasma before and after immunodepletion of IL-10 (“the patient plasma system”). more...

Organism:

Homo sapiens

Type:

Expression profiling by array

Platform:

GPL6244

20 Samples

Download data: CEL

(Submitter supplied) Each total RNA sample is hybridized to two different arrays: Affymetrix U133A (GPL96) and U133B (GPL97). For most of the normal tissue samples there is a renal clear cell carcinoma sample from the same patient. There is no matching tumor sample for normal sample N1. For most of the renal clear cell carcinoma samples there is a corresponding adjacent normal tissue sample from the same patient. There are no matching normal tissue samples for C011 or C032. Keywords = kidney Keywords = renal Keywords = RCC Keywords = carcinoma Keywords = cancer Keywords: parallel sample

Organism:

Homo sapiens

Type:

Expression profiling by array

Datasets:

GDS505 GDS507

Platforms:

GPL96 GPL97

34 Samples

Download data: CEL

Investigation into mechanisms of renal clear cell carcinogenesis (RCC). Comparison of renal clear cell tumor tissue and adjacent normal tissue isolated from the same surgical samples.

Organism:

Homo sapiens

Type:

Expression profiling by array, count, 2 disease state, 10 individual sets

Platform:

GPL97

Series:

GSE781

17 Samples

Download data: CEL

Investigation into mechanisms of renal clear cell carcinogenesis (RCC). Comparison of renal clear cell tumor tissue and adjacent normal tissue isolated from the same surgical samples.

Organism:

Homo sapiens

Type:

Expression profiling by array, count, 2 disease state, 10 individual sets

Platform:

GPL96

Series:

GSE781

17 Samples

Download data: CEL

(Submitter supplied) 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. more...

Organism:

Homo sapiens

Type:

Expression profiling by array

Platform:

GPL6259

12 Samples

Download data: TXT

(Submitter supplied) 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. more...

Organism:

Homo sapiens

Type:

Expression profiling by array

Platform:

GPL96

92 Samples

Download data: CEL, TXT

(Submitter supplied) In order to clarify the molecular mechanism involved in renal carcinogenesis, and identify molecular targets for diagnosis and treatment, we analyzed genome-wide gene expression profiles of 15 surgical specimens of clear cell renal cell carcinoma (RCC), compared to normal renal cortex, using a combination of laser microbeam microdissection (LMM) with a cDNA microarray representing 27,648 genes.

Organism:

Homo sapiens

Type:

Expression profiling by array

Platform:

GPL4747

15 Samples

Download data: TXT

(Submitter supplied) This study investigates the genes that promote clear cell renal cell carcimoma (ccRCC) metastasis using 4 primary metastatic and 5 non-metastatic tumor samples. U133 plus 2.0 array was used to identify the diffrently expressed genes between the primary metastatic and non metastatic ccRCC samples

Organism:

Homo sapiens

Type:

Expression profiling by array

Platform:

GPL570

9 Samples

Download data: CEL

(Submitter supplied) The understanding of metastatic spread is limited and molecular mechanisms causing particular characteristics of metastasis are largely unknown. This comprises the extremely varying dormancy periods of tumor cells in the secondary organ after metastatic spread, represented by the disease-free survival (DFS) of the patients, or differing numbers of metastases in different patients. Knowing the molecular fundamentals of these phenomena would support the individual prediction of patients´ outcome and facilitate the decision for an appropriate monitoring and therapy regime. more...

Organism:

Homo sapiens

Type:

Expression profiling by array

Platform:

GPL570

68 Samples

Download data: CEL

(Submitter supplied) Time Course of TGF-beta treatment of A549 lung adenocarcinoma cell line on Affymetrix HG_U133_plus_2 arrays; triplicate experiments. The goal of the experiment is to profile temporal gene expression changes during TGF-beta-induced epithelial-mesenchymal transition (EMT). During EMT cancer cells loose their epithelial specifc proteins and gain mesenchymal proteins to acquire migratory and invasive phenotype essential for metastasis. more...

Organism:

Homo sapiens

Type:

Expression profiling by array

Dataset:

GDS3710

Platform:

GPL570

26 Samples

Download data: CEL, XLS

Analysis of A549 epithelial cells treated for up to 72 hours with TGF-beta to induce epithelial-mesenchymal transition (EMT). EMT is a developmental process that facilitates the dispersion of cells. A similar process is reactivated in cancer cells as an early event during tumor metastasis.

Organism:

Homo sapiens

Type:

Expression profiling by array, transformed count, 2 agent, 9 time sets

Platform:

GPL570

Series:

GSE17708

26 Samples

Download data: CEL

(Submitter supplied) Smoking is the second leading cause of preventable death in the United States. Cohort epidemiological studies have demonstrated that women are more vulnerable to cigarette-smoking induced diseases than their male counterparts, however, the molecular basis of these differences has been remained unknown to date. In this study, we explored if there were differences in the gene expression patterns between male and female smokers, and how these patterns might reflect different gender-specific responses to the stress of smoking.

Organism:

Homo sapiens

Type:

Expression profiling by array

Platform:

GPL6480

48 Samples

Download data: TXT