Unknown,Transcriptomics,Genomics,Proteomics

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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 BurrowsM-bM-^@M-^SWheeler 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 M-bM-^IM-% 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 M-bM-^IM-% 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. DNA methylation and mRNA expression profiles from tamoxifen sensitive parental cell line MCF-7/S0.5 and 4 high dosage of tamoxifen selected resistant offspring sublines (MCF-7/TAMR-1, MCF-7/TAMR-4, MCF-7/TAMR-7 and MCF-7/TAMR-8) were analyzed by MMSDK and DGE methods, respectively, in combination of massively parallel sequencing, using Illumina HiSeq 2000

ORGANISM(S): Homo sapiens

SUBMITTER: Jian Li

PROVIDER: E-GEOD-40665 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Integrative analyses of gene expression and DNA methylation profiles in breast cancer cell line models of tamoxifen-resistance indicate a potential role of cells with stem-like properties.

Lin Xue X Li Jian J Yin Guangliang G Zhao Qian Q Elias Daniel D Lykkesfeldt Anne E AE Stenvang Jan J Brünner Nils N Wang Jun J Wang Jun J Yang Huanming H Bolund Lars L Ditzel Henrik J HJ

Breast cancer research : BCR 20131219 6

<h4>Introduction</h4>Development of resistance to tamoxifen is an important clinical issue in the treatment of breast cancer. Tamoxifen resistance may be the result of acquisition of epigenetic regulation within breast cancer cells, such as DNA methylation, resulting in changed mRNA expression of genes pivotal for estrogen-dependent growth. Alternatively, tamoxifen resistance may be due to selection of pre-existing resistant cells, or a combination of the two mechanisms.<h4>Methods</h4>To evalua ...[more]

PMID: 24355041

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Project description: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.

Project description:Purpose: Tamoxifen is the most commonly used antiestrogen drug for breast cancer treatment, however, acquired resistance is a considerable challenge in clinic. Complexity and redundancy in biological system implies tamoxifen resistance is associated with complex biological processes. The aim of this study is to attempt to reveal the mechanism of tamoxifen resistance using high-throughput sequencing technique. Methods: We applied digital gene expression (DGE), RNA-seq, Small RNA-seq, bisulifte-seq (reduced representation bisuflite sequencing (RRBS)) with Illumina sequencing platforms, and Array CGH to analyze two well-established tamoxifen resistant cell line models: one is the LCC cell line model that was derived from MCF-7 breast cancer cell line and developed tamoxifen resistance following a step-wise strategy. This cell line model includes LCC0 (estrogen-dependent and tamoxifen sensitive), LCC1 (estrogen-independent and tamoxifen sensitive), LCC2 (derived from LCC1 with increased small-dosage tamoxifen treatment, estrogen-independent, and tamoxifen-resistant), and LCC9 (derived from LCC1 with increased small-dosage fluvestrant treatment, estrogen-independent, and cross-resistance to both fluvestrant and tamoxifen). The other is the TAMR cell line model that was derived from MCF-7 breast cancer cell line and developed four tamoxifen-resistant sublines following the strategy of high-dosage of tamoxifen treatment. Each subline was developed from the survived single cell after the tamoxifen treatment. Results: The DGE and RNA-seq results showed characteristic expression features for the both cell line models, for instance, high expression of SOX2 and alterations of other SOX gene family members, decreased expression of PGR, PTEN, TP53, EZH2, SMAD3, TGF-β1, DNMT1, APOBEC3B, FOXO3 and FOXO4, and increased expression of CDH1, APOBEC3H, FOXA1, TET2, TET3, TDG, MBD4, DNMT3a and DNMT3b between the tamoxifen-resistant cell lines with their matched parental cell lines. Small RNA seq showed the decreased expressions of miR-1, miR-196-3p, miR-18a-5p, miR-125b-5p, and the increased expression of miR-23a-3p, miR-26b-5p, miR-320d, miR-141-3p, miR-23a-3p, miR-30a-5p, miR-9-5p, miR-200c, miR-129-5p, miR-125b-5p, miR-1285-3p and miR-30b-5p between the tamoxifen-resistant cell lines and their matched parental cell lines. Additionally, let-7a and let-7c have been found to present high expression levels in the tamoxifen resistant cells in the both cell line models, even it showed significantly decreased in some TAMR cells compared with their parental cell line. The RRBS showed similar DNA methylation levels between the LCC cell lines. Array CGH showed a small number of copy number variants between the LCC cell lines. Conclusion: Our present study suggests the development of tamoxifen resistance is associated with a dynamic process of cell fate changing. Therefore, new therapeutic method that targets whole cell system and cell fate dynamics, will be a promising strategy.

Project description:Genome-wide expression signatures detect specific perturbations in developmental programs and contribute to functional resolution of key regulatory networks. In maize (Zea mays) inflorescences, mutations in the RAMOSA (RA) genes affect determinacy of axillary meristems and thus alter branching patterns, an important agronomic trait. In this work, we developed and tested a framework for analysis of tag-based, digital gene expression (DGE) profiles using Illumina’s high-throughput sequencing technology and the newly-assembled B73 maize reference genome. We also used a mutation in the RA3 gene to identify putative expression signatures specific to stem cell fate in determinacy of axillary meristems. The RA3 gene encodes a trehalose-6-phosphate-phosphatase and may act at the interface between developmental and metabolic processes. Deep sequencing of DGE libraries, representing three biological replicate ear samples from wild-type and ra3 plants, generated 27 million 20-21nt reads with frequencies spanning four orders of magnitude. Unique sequence tags were anchored to 3´-ends of individual transcripts by DpnII and NlaIII digests, which were multiplexed during sequencing. We mapped 86% of non-redundant signature tags to the maize genome, which associated with 37,117 working gene models and un-annotated regions of expression. 66% of maize genes were detected at ? nine reads in immature maize ears. We used comparative genomics to leverage existing information from Arabidopsis and rice in functional analyses of differentially expressed maize genes. Results from this study provide a basis for analysis of short-read expression data in maize and resolved specific expression signatures that will help define mechanisms of action for the RA3 gene. 3' tag-based DGE libraries were generated using Illumina 1G technology. Libraries were prepared from 2mm ear samples and represent: 3 biological replicates of wild-type B73, 3 biological replicates of ramosa3 (ra3) mutants, and 1 technical replicate of a ra3 sample. Each sample was sequenced in a single lane of a flow cell. Each lane includes library preparations from both DpnII and NlaIII digests for that sample. Sequences from DpnII digests start with GATC and those from NlaIII digests start with ATG.

Dataset Information

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

Publications

Integrative analyses of gene expression and DNA methylation profiles in breast cancer cell line models of tamoxifen-resistance indicate a potential role of cells with stem-like properties.

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