Small RNAs subcellular distribution in breast cancer and normal cell lines
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Chen Runsheng
PROVIDER: S-ECPF-GEOD-15937 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:We detect the small RNAs subcellular distribution in breast cancer cell lines MCF-7 and MDA-MB-231, and normal cell line MCF-10A.
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Project description:We detect the small RNAs subcellular distribution in breast cancer cell lines MCF-7 and MDA-MB-231, and normal cell line MCF-10A. Each cell line, we detected the nuclear and cytoplasmic small RNAs expression intensity; and then we could get the nuclear-cytoplasmic-ratio.
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Project description:Background: Gefitinib is a tyrosine kinase inhibitor (TKI) of epidermal growth factor receptor (EGFR) used to treat EGFR mutation-positive patients with non-small cell lung cancer (NSCLC). However, the efficacy of gefitinib is limited by the development of acquired resistance. Studies have shown that circular RNAs (circRNAs) are involved in the acquired resistance to many anticancer agents. However, the expression profiles and functions of circRNAs in gefitinib resistance in NSCLC are poorly understood so far. Methods: In this study, circRNA expression profiling was explored in two gefitinib-resistant NSCLC cell lines (HCC827/GR and PC9/GR) and their parental sensitive cells (HCC827 and PC9) using high-throughput RNA sequencing. Quantitative real-time PCR (qRT-PCR) was used to confirm the expression of selected differentially expressed circRNAs. Bioinformatic tools including gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), network analysis, and Kaplan-Meier plotter database were used to predict the functions and pathways of these differentially expressed circRNAs. Results: We identified 46 and 56 differentially expressed circRNAs in HCC827/GR and PC9/GR cell lines, respectively, compared with those in their parental cell lines. Gene ontology and KEGG pathway analysis identified that the host linear transcripts of these differentially expressed circRNAs were involved in many critical biological pathways and molecular functions. We found that hsa_circ_0000567 was consistently up-regulated, and hsa_circ_0006867 was consistently down-regulated in two resistant cell lines. We further used hsa_circ_0000567 and hsa_circ_0006867 as key circRNAs to construct circRNA-miRNA-mRNA networks. Several target mRNAs of these two circRNAs had been shown to significantly associate with the overall survival of patients with lung cancer. Conclusions: In this study, we generated the comprehensive expression and functional profiles of the differentially expressed circRNAs between gefitinib-resistant and -sensitive NSCLC cells, and showed that dysregulation of circRNAs might play an important role in the development of acquired resistance to gefitinib in NSCLC.
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