Transcriptomics

Dataset Information

0

Mechanisms and pathways of bone metastasis: challenges and pitfalls of performing molecular research on patient samples


ABSTRACT: The molecular mechanisms underlying the development of bone metastases in breast cancer remain unclear. Disseminated tumour cells (DTCs) in the bone marrow of breast cancer patients are commonly identified, even in early stage disease, but their potential to initiate metastases is not known. The mechanism whereby DTCs become overt metastatic tumour cells (MTCs) is therefore, an area of considerable interest. This study explored the analysable yield of genetic material from human biopsy samples in order to describe differences in gene expression between DTCs and bone MTCs. Thirteen breast cancer patients with bone metastases underwent a CT-guided bone metastasis biopsy and a bone marrow biopsy. Tumour cells were enriched and gene expression profiling was conducted to identify differentially expressed genes. The analysable yield of sufficient RNA for microarray analysis was 60% from bone metastasis biopsies and 80% from bone marrow biopsies. A signature of 133 candidate genes differentially expressed between DTCs and MTCs was identified. Several genes relevant to breast cancer metastasis to bone (osteopontin, CTGF, parathyroid hormone receptor, EGFR) were significantly overexpressed in MTCs as compared to DTCs. Biopsies of bone metastases and bone marrow rarely yield enough tissue for robust molecular biology studies using clinical samples. The findings obtained however are interesting and seem to overlap with the bone metastasis gene expression signature described in murine xenograft models. Larger biopsy specimens or improved RNA extraction techniques may improve analysable yield and feasibility of these techniques.

ORGANISM(S): Homo sapiens

PROVIDER: GSE14776 | GEO | 2012/07/06

SECONDARY ACCESSION(S): PRJNA112323

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2012-07-05 | E-GEOD-14776 | biostudies-arrayexpress
2019-04-23 | GSE119153 | GEO
2015-12-16 | E-GEOD-71258 | biostudies-arrayexpress
2015-12-16 | GSE71258 | GEO
2020-06-29 | GSE146661 | GEO
2021-09-07 | GSE172184 | GEO
2020-06-29 | GSE149038 | GEO
2022-07-13 | GSE196936 | GEO
2016-01-30 | GSE77379 | GEO
2024-09-02 | BIOMD0000000793 | BioModels