Transcriptomics

Dataset Information

0

Integrative Analyses of Gene Expression and DNA Methylation Profiles in a Breast Cancer Cell Line Model of Tamoxifen-Resistance Indicate a Crucial Role of Cells with Stem-like Properties


ABSTRACT: Purpose: Development of resistance to tamoxifen is an important clinical issue in the treatment of patients with breast cancer. Tamoxifen resistance may be the result of the acquisition of epigenetic regulation such as DNA methylation within breast cancer cells resulting in changed mRNA expression of genes being pivotal for estrogen dependent growth. Alternatively, tamoxifen resistance may be due to selection of preexisting resistant cells, which may exhibit cancer stem-like characteristics or a combination of the two mechanisms. Methods: To evaluate the contribution of these possible mechanisms to tamoxifen resistance, we applied modified DNA methylation-specific digital karyotyping (MMSDK) and digital gene expression (DGE) in combination with massively parallel sequencing to analyze a well-established tamoxifen resistant cell line model: MCF-7/S0.5 (tamoxifen sensitive parental cell line) and 4 high-dosage tamoxifen selected resistant offspring sublines (MCF-7/TAMR-1, MCF-7/TAMR-4, MCF-7/TAMR-7 and MCF-7/TAMR-8). MMSDK uses BssHII as mapping enzyme (DNA methylation sensitive enzyme). Both MMSDK and DGE use NlaIII and MmeI to produce 20-21 bp tag. The indexed single-end sequencing was performed by Illumina HiSeq 2000 in BGI-Shenzhen. A dynamic programming algorithm-FASTX-Toolkit implemented in Perl was used to trim the adaptor sequence. The trimmed tags were subjected to quality filtering, so that only tags with sequencing quality higher than 30 for more than 80% of the nucleotides were used for subsequent analysis. For MMSDK tag mapping, we generated a simulated reference library, i.e., BssHII reference library, by in silico enzyme digestion of the human genome (hg19, UCSC) regardless of the methylation state. This library was used as reference for subsequent mapping of the tags in the MMSDK analysis. In the DGE analysis, refMrna (hg19, UCSC) was used as reference for mapping cDNA tags. Subsequently, the Burrows–Wheeler Aligner (BWA) procedure for aligning the MMSDK and DGE tags to the simulated BssHII reference library and refMrna reference library, respectively, was applied. Results: MMSDK libraries using BssHII/NlaIII were generated from the parental tamoxifen sensitive subline MCF-7/S0.5 and the 4 TAMR cell lines: TAMR-1, TAMR-4, TAMR-7 and TAMR-8. The 5 indexed MMSDK libraries were sequenced in one lane and 1.38 Gb clean tag data for all 5 cell lines were obtained, with an average sequencing amount of ~270 Mb per library. On average, 59.5 % of the tags with mapping quality ≥ 20 were mapped back to the simulated BssHII/NlaIII reference library. DGE libraries were also generated from MCF-7/S0.5 and the 4 TAMR cell lines. The 5 indexed DGE libraries were sequenced in one lane and obtained 1.71 Gb clean tag data for all 5 cell lines with an average sequencing amount of ~340 Mb per library. On average, 40.8 % with mapping quality ≥ 20 were mapped back to the simulated NlaIII human transcriptome (refMrna reference library). Our present study demonstrates large differences in global gene expression and DNA methylation profiles between parental tamoxifen-sensitive cell line and 4 high-dosage tamoxifen treatment selected resistant sublines. The tamoxifen resistant cell lines exhibited globally higher methylation level than the parental cell line and an inverse relationship between gene expression and DNA methylation in the promoter regions were noticed. High expression of SOX2 and alterations of other SOX gene family members, E2F gene family members and RB-related pocket protein genes as well as highlighted stem cell pathways imply that cancer initiating cells/stem cells are involved in the resistance to tamoxifen.

ORGANISM(S): Homo sapiens

PROVIDER: GSE40665 | GEO | 2014/02/03

SECONDARY ACCESSION(S): PRJNA174525

REPOSITORIES: GEO

Dataset's files

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

Similar Datasets

2014-02-03 | E-GEOD-40665 | biostudies-arrayexpress
2017-07-12 | GSE95208 | GEO
2015-08-01 | E-GEOD-56411 | biostudies-arrayexpress
2023-06-14 | GSE234546 | GEO
2010-11-03 | E-GEOD-21618 | biostudies-arrayexpress
2017-12-01 | GSE92316 | GEO
2010-10-19 | E-GEOD-24788 | biostudies-arrayexpress
2018-06-01 | GSE55380 | GEO
2018-06-01 | GSE55343 | GEO
2015-12-31 | GSE54620 | GEO