整合 ChIP-seq 和转录组数据的荟萃分析揭示了雌激素受体 α 在乳腺癌中影响的基因组区域。
Meta-analysis of integrated ChIP-seq and transcriptome data revealed genomic regions affected by estrogen receptor alpha in breast cancer.
机构信息
Department of Bioinformatics, Kish International Campus University of Tehran, Kish, Iran.
Laboratory of Complex Biological Systems and Bioinformatics (CBB), Department of Bioinformatics, Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran.
出版信息
BMC Med Genomics. 2023 Sep 15;16(1):219. doi: 10.1186/s12920-023-01655-z.
BACKGROUND
The largest group of patients with breast cancer are estrogen receptor-positive (ER) type. The estrogen receptor acts as a transcription factor and triggers cell proliferation and differentiation. Hence, investigating ER-DNA interaction genomic regions can help identify genes directly regulated by ER and understand the mechanism of ER action in cancer progression.
METHODS
In the present study, we employed a workflow to do a meta-analysis of ChIP-seq data of ER cell lines stimulated with 10 nM and 100 nM of E2. All publicly available data sets were re-analyzed with the same platform. Then, the known and unknown batch effects were removed. Finally, the meta-analysis was performed to obtain meta-differentially bound sites in estrogen-treated MCF7 cell lines compared to vehicles (as control). Also, the meta-analysis results were compared with the results of T47D cell lines for more precision. Enrichment analyses were also employed to find the functional importance of common meta-differentially bound sites and associated genes among both cell lines.
RESULTS
Remarkably, POU5F1B, ZNF662, ZNF442, KIN, ZNF410, and SGSM2 transcription factors were recognized in the meta-analysis but not in individual studies. Enrichment of the meta-differentially bound sites resulted in the candidacy of pathways not previously reported in breast cancer. PCGF2, HNF1B, and ZBED6 transcription factors were also predicted through the enrichment analysis of associated genes. In addition, comparing the meta-analysis results of both ChIP-seq and RNA-seq data showed that many transcription factors affected by ER were up-regulated.
CONCLUSION
The meta-analysis of ChIP-seq data of estrogen-treated MCF7 cell line leads to the identification of new binding sites of ER that have not been previously reported. Also, enrichment of the meta-differentially bound sites and their associated genes revealed new terms and pathways involved in the development of breast cancer which should be examined in future in vitro and in vivo studies.
背景
最大的乳腺癌患者群体为雌激素受体阳性（ER）型。雌激素受体作为转录因子，触发细胞增殖和分化。因此，研究 ER-DNA 相互作用的基因组区域有助于识别受 ER 直接调控的基因，并了解 ER 在癌症进展中的作用机制。
方法
本研究采用工作流程对用 10 nM 和 100 nM 的 E2 刺激的 ER 细胞系的 ChIP-seq 数据进行荟萃分析。所有公开的数据集都在同一平台上重新进行了分析。然后，去除已知和未知的批次效应。最后，进行荟萃分析以获得与载体（作为对照）相比，在雌激素处理的 MCF7 细胞系中差异结合的元位。此外，还比较了 T47D 细胞系的荟萃分析结果，以提高精度。还进行了富集分析，以发现两种细胞系中常见的元差异结合位点和相关基因的功能重要性。
结果
值得注意的是，在荟萃分析中识别到了 POU5F1B、ZNF662、ZNF442、KIN、ZNF410 和 SGSM2 转录因子，但在个别研究中没有识别到。元差异结合位点的富集导致了以前未在乳腺癌中报道的途径的候选。通过相关基因的富集分析还预测了 PCGF2、HNF1B 和 ZBED6 转录因子。此外，比较 ChIP-seq 和 RNA-seq 数据的荟萃分析结果表明，许多受 ER 影响的转录因子被上调。
结论
雌激素处理的 MCF7 细胞系的 ChIP-seq 数据荟萃分析导致鉴定出以前未报道的 ER 的新结合位点。元差异结合位点及其相关基因的富集揭示了新的术语和途径，这些术语和途径可能涉及乳腺癌的发展，应该在未来的体外和体内研究中进行检验。
Zotero 插件