CC_LRI_BC
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB43655 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR5462930.fastq.gz | Fastqsanger.gz | |||
| ERR5462940.fastq.gz | Fastqsanger.gz | |||
| ERR5462950.fastq.gz | Fastqsanger.gz | |||
| ERR5462960.fastq.gz | Fastqsanger.gz | |||
| ERR5462970.fastq.gz | Fastqsanger.gz |
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Project description:Recently, expression profiling of breast carcinomas has revealed gene signatures that predict clinical outcome, and discerned prognostically relevant breast cancer subtypes. Measurement of the degree of genomic instability provides a very similar stratification of prognostic groups. We therefore hypothesized that these features are linked. We used gene expression profiling of 48 breast cancer specimens that profoundly differed in their degree of genomic instability and identified a set of 12 genes that defines the two groups. The biological and prognostic significance of this gene set was established through survival prediction in published datasets from patients with breast cancer. Of note, the gene expression signatures that define specific prognostic subtypes in other breast cancer datasets predicted genomic instability in our samples. This remarkable congruence suggests a biological dependency of poor-prognosis gene signatures, breast cancer subtypes, genomic instability, and clinical outcome. Keywords: disease state analysis 44 samples
2009-11-30 | E-GEOD-11901 | biostudies-arrayexpress
Project description:Recently, expression profiling of breast carcinomas has revealed gene signatures that predict clinical outcome, and discerned prognostically relevant breast cancer subtypes. Measurement of the degree of genomic instability provides a very similar stratification of prognostic groups. We therefore hypothesized that these features are linked. We used gene expression profiling of 48 breast cancer specimens that profoundly differed in their degree of genomic instability and identified a set of 12 genes that defines the two groups. The biological and prognostic significance of this gene set was established through survival prediction in published datasets from patients with breast cancer. Of note, the gene expression signatures that define specific prognostic subtypes in other breast cancer datasets predicted genomic instability in our samples. This remarkable congruence suggests a biological dependency of poor-prognosis gene signatures, breast cancer subtypes, genomic instability, and clinical outcome. Keywords: disease state analysis
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Project description:We performed Chip-Seq analyses of several DNA binding transcription factors predicted to function as "master transcriptional regulators" (MTRs) of breast cancer prognostic gene signatures in primary human mammary epithelial cells (HMECs). These analyses demonstrated that these factors frequently co–bind the promoters of genes, the expression of which is associated with a proliferative phenotype and poor patient outcome. These data suggest that these predicted MTRs do indeed drive the expression of gene signatures associated with poor patient outcome in breast cancer.
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Project description:Triple-Negative Breast Cancer (TNBC) is a poorly targetable cancer subtype that exhibits a high metastatic potential. To develop new intervention strategies, it is crucial to understand the mechanisms governing migratory and invasive features of TNBC cells. Previously it was shown that high expression of the non-receptor tyrosine kinase FER is an independent prognostic factor that correlates with poor survival in high grade and basal breast cancer. Here, we show that FER controls proliferation and invasion of TNBC cells through the direct substrates MAPK1 and Dynactin 2 (DCTN2; Dynamitin). Our data demonstrate that FER regulates tumor cell proliferation through phosphorylation of MAPK1 on tyrosine 187, and recycling endosome function and subsequent invasion of breast cancer cells through tyrosine 6 residue (Y6) of DCTN2. We show that DCTN2-Y6 is essential for Dynein complex formation and the development of tubular recycling domains at the early endosome. By controlling this crucial step in endosomal recycling, FER drives and sustains adhesion and invasion of (triple negative) breast cancer cells. Our data provide clinical ramification by demonstrating that high grade and basal breast cancers expressing elevated FER levels are more susceptible to taxane-based chemotherapy interventions. In conclusion, our study links FER to kinase-dependent control of intracellular vesicular transport and tumor progression in breast cancer. Importantly, our results indicate that FER represents a predictive and functional biomarker in high grade basal breast cancers.
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