Pax-5 Inhibits NF-κB Activity in Breast Cancer Cells Through IKKε and miRNA-155 Effectors

Jason Harquail, Nicolas LeBlanc, Carine Landry, Nicolas Crapoulet, Gilles A. Robichaud

Pax-5, an essential transcription factor in B cell development, is aberrantly expressed in various B cell cancer lesions and solid tumors such as breast carcinoma. We have recently shown that Pax-5 regulates NF-κB activity which lead to the modulation of breast cancer phenotypic features (EMT-MET). NF-κB is known as a central mediator in inflammation, stress response as well as being a gatekeeper of pro-tumorigenic activity. However, little is known as to how Pax-5 affects this modulation. We thus turned our attention to microRNAs as potential regulatory effectors. In this study, we set out to elucidate the regulatory network between differential Pax-5 expression and NF-κB activity which dictate breast cancer malignancy. Through next-generation sequencing (NGS) of breast cancer cells conditionally expressing Pax-5, we profile significantly upregulated microRNAs; including microRNA-155, a known regulator of pathological processes and suppressor of malignant growth. Through the conditional expression of microRNA-155 in breast cancer models, we identify and validate IKKε (IKBKE) as a downstream target and an essential effector of Pax-5-mediated suppression of NF-κB signaling. Using rescue experiments, we also confirm that Pax-5 modulates NF-κB activity via IKKε downregulation. Interestingly, we also show that microRNA-155, in turn, supresses Pax-5 expression, indicative of an auto-regulatory feedback loop. Altogether, we demonstrate that Pax-5 inhibits NF-κB signalling through the regulation of microRNA-155 and its downstream target IKKε. The elucidation of this signaling network is relevant as Pax-5 and NF-κB are potent transcriptional regulators of breast cancer aggressivity. In addition, IKKε is relevant oncogene aberrantly expressed in 30% of breast carcinomas. Further insight into the regulatory pathways of breast cancer progression will eventually identify strategic therapeutic and prognostic targets to improve cancer patient outcome.