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Gene-expression profile of breast cancer cell lines and sorted breast cancer epithelial cells

ABSTRACT: Most of the breast cancer samples used in clinical research contain multiple cell types other than epithelial cells alone. The non-epithelial cell types have have a substantial effect on the gene expression-profile, which is used to define molecular subtypes of the tumours. The purpose of this data set is to retrieve gene-expression profile within tumour epithelial cells. We collected 9 breast cancer epithelial cell lines and 5 tumour sampes from which epithelial cells were sorted and enriched using BerEp4 antibody coated beads. We profiled the mRNA expression level of these samples and classified probe sets into epithelial genes which were those genes with present calls in at least 50% of the samples. Then we derived an 23-gene signature based on only the epithelial genes to stratify breast cancer.

ORGANISM(S): Homo sapiens

PROVIDER: GSE23640 | GEO | 2010/08/17

SECONDARY ACCESSION(S): PRJNA130949

REPOSITORIES: GEO

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Project description:Purpose: There is a quest for novel non-invasive diagnostic markers for the detection of breast cancer. The goal of this study is to identify circulating microRNA signatures using a cohort of Asian Chinese breast cancer patients, and to compare microRNA profiles between tumour and serum samples. Experimental design: MicroRNAs from paired breast cancer tumours, normal tissue and serum samples derived from 32 patients were comprehensively profiled using microarrays (1300 microRNAs against tumour and normal tissues) or LNA RT-PCR panels (742 microRNAs against serum samples). Serum samples from healthy individuals (n=22) were also employed as normal controls. Significant serum microRNAs, identified by logistic regression, were validated in an independent set of serum samples from patients (n=82) and healthy controls (n=53). Results: The 20 most significant microRNAs differentially expressed in breast cancer tumours included miR-21, miR-10b, and miR-145, previously shown to be dysregulated in breast cancer. Interestingly, 16 of the 20 most significant microRNAs differentially expressed in serum samples were novel. MiR-1, miR-92a, miR-133a and miR-133b were identified as the most important diagnostic markers, and were successfully validated; receiver operating characteristic curves derived from combinations of these microRNAs exhibited areas under the curves of 0.944-0.946. Only seven microRNAs were overexpressed in both tumours and serum, suggesting that microRNAs may be released into the serum selectively. Conclusion: The clinical employment of microRNA signatures as a non-invasive diagnostic strategy is promising, but should be further validated for different subtypes of breast cancers. "_A" and "_B" are two tissue sections of the same sample; "_1" and "_2" represents 2 runs of the same sample; na = not available All tissue samples were histologically confirmed by a pathologist using hematoxylin and eosin staining of cryosectioned specimens. One tumour sample was rejected due to failure to detect any tumour cells. Except for two samples (with 30% and 40% tumour cells), all tumour tissues employed had a minimum of 60% tumour cells, as estimated microscopically. Overall, the breast cancer tumour samples had an average of 71% tumour cells. The criteria for adjacent normal tissue were absence of tumour cells and presence of epithelial cells. Hence, after histological confirmation, 31 breast cancer tumours and 23 matched normal tissues were employed for microRNA extraction and profiling using microarray.

Project description:Breast cancers contain a minority population of cancer cells characterized by CD44 expression but low or undetectable levels of CD24 (CD44+CD24-/low) that have higher tumorigenic capacity than other subtypes of cancer cells. METHODS: We compared the gene-expression profile of CD44+CD24-/low tumorigenic breast-cancer cells with that of normal breast epithelium. Differentially expressed genes were used to generate a 186-gene invasiveness gene signature (IGS), which was evaluated for its association with overall survival and metastasis-free survival in patients with breast cancer or other types of cancer. RESULTS: There was a significant association between the IGS and both overall and metastasis-free survival (P<0.001, for both) in patients with breast cancer, which was independent of established clinical and pathological variables. When combined with the prognostic criteria of the National Institutes of Health, the IGS was used to stratify patients with high-risk early breast cancer into prognostic categories (good or poor); among patients with a good prognosis, the 10-year rate of metastasis-free survival was 81%, and among those with a poor prognosis, it was 57%. The IGS was also associated with the prognosis in medulloblastoma (P=0.004), lung cancer (P=0.03), and prostate cancer (P=0.01). The prognostic power of the IGS was increased when combined with the wound-response (WR) signature. CONCLUSIONS: The IGS is strongly associated with metastasis-free survival and overall survival for four different types of tumors. This genetic signature of tumorigenic breast-cancer cells was even more strongly associated with clinical outcomes when combined with the WR signature in breast cancer. Expression profling was performed on 6 tumorigenic, 3 non tumorigenic samples of breast tumors and 3 normal breast samples on two different platforms GPL96 and GPL97. A gene signature was derived by comparing the gene expressions of 6 tumorigenic samples with 3 normal breast samples.

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Gene-expression profile of breast cancer cell lines and sorted breast cancer epithelial cells

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