Regulatory Crosstalk of Doxorubicin, Estradiol and TNFα Combined Treatment in Breast Cancer-derived Cell Lines

Abstract

We present a new model of ESR1 network regulation based on analysis of Doxorubicin, Estradiol, and TNFα combination treatment in MCF-7. We used Doxorubicin as a therapeutic agent, TNFα as marker and mediator of an inflammatory microenvironment and 17β-Estradiol (E2) as an agonist of Estrogen Receptors, known predisposing factor for hormone-driven breast cancer, whose pharmacological inhibition reduces the risk of breast cancer recurrence. Based on the results of transcriptomics analysis, we found 71 differentially expressed genes that are specific for the combination treatment with Doxorubicin + Estradiol + TNFα in comparison with single or double treatments. The responsiveness to the triple treatment was examined for seven genes by qPCR, of which six were validated, and then extended to four additional cell lines differing for p53 and/or ER status. The results of differential regulation enrichment analysis highlight the role of the ESR1 network that included 36 of 71 specific differentially expressed genes. We propose that the combined activation of p53 and NF-kB transcription factors significantly influences ligand-dependent, ER-driven transcriptional responses, also of the ESR1 gene itself. These results provide a model of coordinated interaction of TFs to explain the Doxorubicin, E2 and TNFα induced repression mechanisms.

TranSNPs: A class of functional SNPs affecting mRNA translation potential revealed by fraction-based allelic imbalance

“…We used both a commonly used chemotherapeutic drug that activates the DNA damage response, and a selective MDM2 inhibitor that results in acute p53 activation without apparent genotoxic response ( Rizzotto et al., 2020 ; Tovar et al., 2006 ). Doses and treatment time points were selected based on previous characterization of both p53 activation pathway and cell outcome ( Lion et al., 2013 ; Nassiri et al., 2019 ). Furthermore, for both treatments, we have previously shown a global as well as a specific impact on translation ( Zaccara et al., 2014 ).…”

Elucidating the pharmacological mechanism by which Si-Wu-Tang induces cellular senescence in breast cancer via multilevel data integration

“…The fragments per kilobase million (FPKM) values of the TCGA cohort were then transformed into transcripts per million (TPM) values before further analysis. The GSE23610 (GSM578941, GSM578942, GSM578943, GSM578956, GSM578957, and GSM578958) [ 11 ], GSE39870 (GSM980568, GSM980569, GSM980570, GSM980571, GSM980572, and GSM980573) [ 59 ], GSE50650 (GSM1225765, GSM1225766, GSM1225767, GSM1225768, GSM1225769, GSM1225770, GSM1225771, GSM1225772, and GSM1225773) [ 60 ], and GSE68026 (GSM1661360, GSM1661361, GSM1661362, GSM1661363, GSM1661364, and GSM1661365) datasets were downloaded from the GEO ( https://www.ncbi.nlm.nih.gov/geo ) database.…”