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Homo sapiens
225 Downloadable Samples
Affymetrix Human Genome U133A Array (hgu133a)
Description
These data, combined with other cohorts (GSE6532, GSE12093, and qRT-PCR based cohorts), was used to construct the EP algorithm, which predicts the likelihood of developing of a distant recurrence of early stage breast cancer under endocrine treatment. In addition, EPclin, a combination of the EP score, the nodal status and the tumor size, was constructed.
Publication Title
A new molecular predictor of distant recurrence in ER-positive, HER2-negative breast cancer adds independent information to conventional clinical risk factors.
Sample Metadata Fields
No sample metadata fields
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GSE63862- Homo sapiens
- 6 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
In order to understand the transcriptional effects of CD44s expression in a cell line that does not express CD44 in its native form we transfected CD44s into HEK cells and measured the transcriptional chances compared to native HEK cells
Publication Title
CD44 Isoform Status Predicts Response to Treatment with Anti-CD44 Antibody in Cancer Patients.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 251 Downloadable Samples
- Affymetrix Human Gene 2.0 ST Array (hugene20st)
Description
593 FFPE colorectal cancer samples were used to generate three prediction models: Recurrence prediction, 5FU efficacy prediction, and FOLFOX efficacy prediction
Publication Title
Building personalized treatment plans for early-stage colorectal cancer patients.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 187 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
The tissue of origin form metastatic tumors is sometimes difficult to identify from clinical and histologic information. Gene expression signatures are one potential method for identifying the tissue of origin. In the development of algorithms to identify tissue of origin, a collection of human tumor metastatic specimens with known primary sites or primary tumors with poor differentiation are very useful in identifying gene expressions signatures that can classify unknown specimens as to the tissue of origin. Here we describe a series of 276 such tumor specimens used for this purpose. The specimens are poorly differentiated, undifferentiated and metastatic specimens from tumors of the following types/tissues of origin: breast, liver, non-Hodgkin's lymphoma, non-small cell lung cancer, ovary, testicular germ cell, thyroid, kidney, pancreas, colorectal cancer, soft tissue sarcoma, bladder, gastric cancer, prostate and melanoma. This data combined with other series (GSE2109) was used to validate a proprietary tumor classification algorithm of Pathwork Diagnostics. The results of this validation set (N = 545 CEL files) showed that the algorithm correctly identified the tissue of origin for 89.4% of the specimens.
Publication Title
Multicenter validation of a 1,550-gene expression profile for identification of tumor tissue of origin.
Sample Metadata Fields
Sex, Age
View Samples- Homo sapiens
- 80 Downloadable Samples
- Affymetrix Human Gene 2.0 ST Array (hugene20st)
Description
211 FFPE NSLC surgical samples were used to generate recurrence prediction models
Publication Title
Generating a robust prediction model for stage I lung adenocarcinoma recurrence after surgical resection.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 62 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Wiskott-Aldrich syndrome (WAS) predisposes patients to leukemia and lymphoma. WAS is caused by mutations in the protein WASP which impair its interaction with the WIPF1 protein. Here, we aim to identify a module of WIPF1-coexpressed genes and to assess its use as a prognostic signature for colorectal cancer, glioma, and breast cancer patients. Two public colorectal cancer microarray data sets were used for discovery and validation of the WIPF1 co-expression module. Based on expression of the WIPF1 signature, we classified more than 400 additional tumors with microarray data from our own experiments or from publicly available data sets according to their WIPF1 signature expression. This allowed us to separate patient populations for colorectal cancers, breast cancers, and gliomas for which clinical characteristics like survival times and times to relapse were analyzed. Groups of colorectal cancer, breast cancer, and glioma patients with low expression of the WIPF1 co-expression module generally had a favorable prognosis. In addition, the majority of WIPF1 signature genes are individually correlated with disease outcome in different studies. Literature gene network analysis revealed that among WIPF1 co-expressed genes known direct transcriptional targets of c-myc, ESR1 and p53 are enriched. The mean expression profile of WIPF1 signature genes is correlated with the profile of a proliferation signature. The WIPF1 signature is the first microarray-based prognostic expression signature primarily developed for colorectal cancer that is instrumental in other tumor types: low expression of the WIPF1 module is associated with better prognosis.
Publication Title
An expression module of WIPF1-coexpressed genes identifies patients with favorable prognosis in three tumor types.
Sample Metadata Fields
Sex, Age
View Samples- Homo sapiens
- 89 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Background: Antimalarials have anticancer potential. Results: We have systematically tested five distinct antimalaria drugs in a panel of cancer cell lines. Conclusion: Three antimalarial classes display potent antiproliferative activity, and their potency is correlated with cancer cell gene expression patterns. Significance: We confirm and extend anticancer potential of these antimalarials and we discuss their therapeutic potential based on clinical data.
Publication Title
Anticancer properties of distinct antimalarial drug classes.
Sample Metadata Fields
Sex, Age, Cell line
View Samples- Homo sapiens
- 62 Downloadable Samples
- Affymetrix Human Gene 2.1 ST Array (hugene21st)
Description
The main aim of this study was to assess the changes in blood gene expression in UCB patients and to identify genes serving as biomarkers for UCB diagnosis and progression.
Publication Title
A Specific Blood Signature Reveals Higher Levels of S100A12: A Potential Bladder Cancer Diagnostic Biomarker Along With Urinary Engrailed-2 Protein Detection.
Sample Metadata Fields
Age
View Samples- Homo sapiens
- 29 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Time course comparison to tissue origin and with control cell line HT29 derived from colorectal adenocarcinoma.
Publication Title
No associated publication
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 15 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Background: Isolation and characterization of tumourigenic colon cancer initiating cells may help to develop novel diagnostic and therapeutic procedures. Methods: We characterized a panel of fourteen human colon carcinoma cell lines and their corresponding xenografts for the surface expression of different potential stem cell markers: CD133, CD24, CD44, CDCP1 and CXCR4. In five cell lines and nine xenografts mRNA expression of the investigated markers was determined. Tumour growth behaviour of CD133+, CD133- and unsorted SW620 cells was evaluated in vivo. Results: All surface markers showed distinct expression patterns in the examined tumours. Analyses of the corresponding xenografts revealed a significant reduction of cell numbers expressing the investigated markers. CD44 and CXCR4 mRNA expression correlated within the cell line panel and CD44 and CDCP1 within the xenograft panel, respectively. Small subpopulations of double and triple positive cells could be described. SW620 showed significantly higher take rates and shorter doubling times in vivo when sorted for CD133 positivity. Conclusion: Our data support the hypothesis of a small subset of cells with stem cell-like properties characterized by a distinct surface marker profile. In vivo growth kinetics give strong relevance for an important role of CD133 within the mentioned surface marker profile.
Publication Title
Characterization of colon cancer cells: a functional approach characterizing CD133 as a potential stem cell marker.
Sample Metadata Fields
Sex, Age, Specimen part
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