Kotipalli Aneesh, Banerjee Ruma, Kasibhatla Sunitha Manjari, Joshi Rajendra
HPC-Medical and Bioinformatics Applications Group, Centre for Development of Advanced Computing, Pune 411008, India.
Genomics Inform. 2021 Jun;19(2):e17. doi: 10.5808/gi.21020. Epub 2021 Jun 30.
Breast cancer is one of the leading causes of cancer in women all over the world and accounts for ~25% of newly observed cancers in women. Epigenetic modifications influence differential expression of genes through non-coding RNA and play a crucial role in cancer regulation. In the present study, epigenetic regulation of gene expression by in-silico analysis of histone modifications using chromatin immunoprecipitation sequencing (ChIP-Seq) has been carried out. Histone modification data of H3K4me3 from one normal-like and four breast cancer cell lines were used to predict miRNA expression at the promoter level. Predicted miRNA promoters (based on ChIP-Seq) were used as a probe to identify gene targets. Five triple-negative breast cancer (TNBC)-specific miRNAs (miR153-1, miR4767, miR4487, miR6720, and miR-LET7I) were identified and corresponding 13 gene targets were predicted. Eight miRNA promoter peaks were predicted to be differentially expressed in at least three breast cancer cell lines (miR4512, miR6791, miR330, miR3180-3, miR6080, miR5787, miR6733, and miR3613). A total of 44 gene targets were identified based on the 3'-untranslated regions of downregulated mRNA genes that contain putative binding targets to these eight miRNAs. These include 17 and 15 genes in luminal-A type and TNBC respectively, that have been reported to be associated with breast cancer regulation. Of the remaining 12 genes, seven (A4GALT, C2ORF74, HRCT1, ZC4H2, ZNF512, ZNF655, and ZNF608) show similar relative expression profiles in large patient samples and other breast cancer cell lines thereby giving insight into predicted role of H3K4me3 mediated gene regulation via the miRNA-mRNA axis.
乳腺癌是全球女性癌症的主要病因之一,约占女性新确诊癌症的25%。表观遗传修饰通过非编码RNA影响基因的差异表达,并在癌症调控中发挥关键作用。在本研究中,利用染色质免疫沉淀测序(ChIP-Seq)对组蛋白修饰进行计算机分析,开展了基因表达的表观遗传调控研究。来自一个类正常细胞系和四个乳腺癌细胞系的H3K4me3组蛋白修饰数据用于预测启动子水平的miRNA表达。基于ChIP-Seq预测的miRNA启动子用作探针来识别基因靶点。鉴定出五个三阴性乳腺癌(TNBC)特异性miRNA(miR153-1、miR4767、miR4487、miR6720和miR-LET7I),并预测了相应的13个基因靶点。预测有八个miRNA启动子峰在至少三个乳腺癌细胞系中差异表达(miR4512、miR6791、miR330、miR3180-3、miR6080、miR5787、miR6733和miR3613)。基于下调的mRNA基因的3'-非翻译区(其包含与这八个miRNA的推定结合靶点),共鉴定出44个基因靶点。其中分别有17个和15个基因在腔面A型和TNBC中,据报道与乳腺癌调控相关。在其余12个基因中,有七个(A4GALT、C2ORF74、HRCT1、ZC4H2、ZNF512、ZNF655和ZNF608)在大量患者样本和其他乳腺癌细胞系中显示出相似的相对表达谱,从而深入了解了H3K4me3通过miRNA-mRNA轴介导的基因调控的预测作用。