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GSE137310
Homo sapiens
24 Downloadable Samples
Illumina HumanHT-12 V4.0 expression beadchip
Description
Genome-wide analysis of GBM-derived brain tumor stem cells-like (BTSCs) collected at the Freiburg Medical Center and UAB (JX6)
Publication Title
NF1 regulates mesenchymal glioblastoma plasticity and aggressiveness through the AP-1 transcription factor FOSL1.
Sample Metadata Fields
Specimen part, Disease, Disease stage
View Samples- Homo sapiens
- 118 Downloadable Samples
- Illumina human-6 v2.0 expression beadchip
Description
Despite continual efforts to rationalize a prognostic stratification of patients with esophageal adenocarcinoma (EAC) before treatment, current staging system only shows limited success owing to the lack of molecular and genetic markers that reflect prognostic features of the tumor. To develop molecular predictors of prognosis, we used systems-level characterization of tumor transcriptome. Using DNA microarray, genome-wide gene expression profiling was performed on 75 biopsy samples from patients with untreated EAC. Various statistical and informatical methods were applied to gene expression data to identify potential biomarkers associated with prognosis. Potential marker genes were validated in an independent cohort using quantitiative RT-PCR to measure gene expression. Distinct subgroups of EAC were uncovered by systems-level characterization of tumor transcriptome. We also identified a six-gene expression signature that could be used to predict overall survival (OS) of EAC patients. In particular, expression of SPARC and SPP1 was a strong independent predictor of OS, and a combined gene expression signature with these two genes was associated with prognosis (P < 0.024), even when all relevant pathological variables were considered together in multivariate Cox hazard regression analysis. Our findings suggest that molecular features reflected in gene expression signatures may dictate the prognosis of EAC patients, and these gene expression signatures can be used to predict the likelihood of prognosis at the time of diagnosis and before treatment.
Publication Title
Prognostic biomarkers for esophageal adenocarcinoma identified by analysis of tumor transcriptome.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 21 Downloadable Samples
Illumina HiSeq 2500
Description
Somatic cancer driver mutations may result in distinctly diverging phenotypic outputs. Thus, a common driver lesion may result in cancer subtypes with distinct clinical presentations and outcomes. The diverging phenotypic outputs of mutations result from the superimposition of the mutations with distinct progenitor cell populations that have differing lineage potential. However, our ability to test this hypothesis has been challenged by currently available tools. For example, flow cytometry is limited in its inability to resolve lineage commitment of early progenitors. Single-cell RNA sequencing (scRNA-seq) may provide higher resolution mapping of the early progenitor populations as long as high throughput technology is available to sequence thousands of single cells. Nevertheless, high throughput scRNA-seq is limited in its inability to jointly and robustly detect the mutational status and the transcriptional profile from the same cell. To overcome these limitations, we propose the use of scRNA-seq combined with targeted mutation sequencing from transcrptional read-outs. Overall design: We apply this method to study myeloid neopasms, in which the comlex process of hematopoiesis is corrupted by mutated stem and progenitor cells.
Publication Title
Somatic mutations and cell identity linked by Genotyping of Transcriptomes.
Sample Metadata Fields
Sex, Age, Disease, Treatment, Subject
View Samples