BMC Medical Genomics · 2019 · 20 citations · 17 references
MedicineMolecular BiologyOncologyGene ExpressionMolecular OncologyTranscriptional RegulationCancer EpigeneticsCancer GenomicsCancer TranscriptomicsChromatinEnhancer ArchitectureEnhancer FunctionCancer BioinformaticsCis-acting Regulatory ElementsForkhead Box ProteinsSmall Cell Lung Cancer AssociationSuper-enhancer InteractionsSuper-enhancer RegulationSuper-enhancersTumor Evolution Analysis
BACKGROUND: Chemoresistance is a primary clinical challenge for the management of small cell lung cancer. Additionally, transcriptional regulation by super enhancer (SE) has an important role in tumor evolution. The functions of SEs, a key class of noncoding DNA cis-regulatory elements, have been the subject of many recent studies in the field of cancer research. METHODS: In this study, using chromatin immunoprecipitation-sequencing and RNA-sequencing (RNA-seq), we aimed to identify SEs associated with chemoresistance from H69AR cells. Through integrated bioinformatics analysis of the MEME chip, we predicted the master transcriptional factors (TFs) binding to SE sites and verified the relationships between TFs of SEs and drug resistance by RNA interference, cell counting kit 8 assays, quantitative real-time reverse transcription polymerase chain reaction. RESULTS: In total, 108 SEs were screened from H69AR cells. When combining this analysis with RNA-seq data, 45 SEs were suggested to be closely related to drug resistance. Then, 12 master TFs were predicted to localize to regions of those SEs. Subsequently, we selected forkhead box P1 (FOXP1), interferon regulatory factor 1 (IRF1), and specificity protein 1 (SP1) to authenticate the functional relationships of master TFs with chemoresistance via SEs. CONCLUSIONS: We screened out SEs involved with drug resistance and evaluated the functions of FOXP1, IRF1, and SP1 in chemoresistance. Our findings established a large group of SEs associated with drug resistance in small cell lung cancer, revealed the drug resistance mechanisms of SEs, and provided insights into the clinical applications of SEs.
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