Therapeutically targeting oncogenic CRCs facilitates induced differentiation of NB by RA and the BET bromodomain inhibitor

Abstract

Retinoic acids (RAs) are the most successful therapeutics for cancer differentiation therapy used in high-risk neuroblastoma (NB) maintenance therapy but are limited in effectiveness. This study identifies a strategy for improving efficacy through disruption of cancer cell identity via BET inhibitors. Mutations that block development are theorized to cause NB through retention of immature cell identities contributing to oncogenesis. NB has two interchangeable cell identities, maintained by two different core transcriptional regulatory circuitries (CRCs): a therapy-resistant mesenchymal/stem cell state and a proliferative adrenergic cell state. MYCN amplification is a common mutation of high-risk NB and recently found to block differentiation by driving high expression of the adrenergic CRC transcription factor ASCL1. We investigated whether disruption of immature CRCs can promote RA-induced differentiation since only a subset of NB patients responds to RA. We found that silencing ASCL1, a critical member of the adrenergic CRC, or global disruption of CRCs with the BET inhibitor JQ1, suppresses gene expression of multiple CRC factors, improving RA-mediated differentiation. Further, JQ1 and RA synergistically decrease proliferation and induce differentiation in NB cell lines. Our findings support preclinical studies of RA and BET inhibitors as a combination therapy in treating NB.

Keywords: ASCL1; BET inhibitor JQ1; MYCN, SOX10; neuroblastoma; retinoic acid.

Graphical abstract

Figure 1

Evaluation of the ASCL1 knockdown and its effects on CRC factors by Sh6 and Sh8 in Kelly Sh6 and Sh8 induced knockdown of ASCL1 in the presence of doxycycline (Dox) at day 4, as assessed by (A and B) RT-PCR and (C and D) western blot analysis. (E and F) Gene expression of ASCL1, SOX10, and GATA3 in Sh6- and Sh8-inducible Kelly cells by RT-PCR analysis. (G and H) Protein expression of CRC transcription factors in Sh6 and Sh8 cells. (All statistical data presented as mean ± SEM with n = 3, ∗∗p < 0.01 or ∗p < 0.05.)

Figure 2

Effect of ASCL1 knockdown and treatment of ATRA on proliferation and differentiation (A and B) The gene expression of ASCL1 and TH in day-3 treatments of Dox versus Dox + ATRA in Sh6- and Sh8-inducible cells by RT-PCR assay. (C) Protein expression of ASCL1 and TH as assessed by western blots. (D) Proliferation percentage in Sh6- and Sh8-inducible cells at day-4 treatment of Dox and Dox + ATRA combination as measured by CyQuant (n = 3, ∗∗p < 0.01 or ∗p < 0.05).

Figure 3

Effect of JQ1 and ATRA combinations on gene expression of CRC in NB cells (A−C). Gene expression by RT-PCR of ASCL1, GATA3, and SOX10 in (A) Kelly, (B) SY5Y, and (C) SKNAS cells under the treatment of independent and combinations of JQ1 + ATRA. (All data presented as mean ± SEM with n = 3, ∗∗p < 0.01 or ∗p < 0.05.)

Figure 4

Evaluation of differentiation markers under JQ1 and ATRA combinatorial treatments in NB cells (A and B) Gene expression by RT-PCR of TH and MBP in Kelly, SY5Y, and SKNAS cells under the treatment of independent and combinations of JQ1 + ATRA. (C−E) Protein expression analyzed by western blots of TH and ASCL1 in the three cell lines under the treatment of independent and combinations of JQ1 + ATRA. (Data presented as mean ± SEM with n = 3, ∗∗p < 0.01.)

Figure 5

Determination of dose versus response effect of JQ1 + ATRA combinatorial treatments on NB cells (A−C) Combinatorial treatment of JQ1 and ATRA on Kelly, SKNAS, and SY5Y on percent proliferation by CyQuant assay data. (D and E) Dose versus response curves in the treatments of JQ1 with ATRA combinations on Kelly and SKNAS cells. x axis represents the concentration of drugs used; y axis represents the percent inhibition of cells as fraction affected (Fa). (F and G) The combinatorial treatment of JQ1 + ATRA in Kelly and SKNAS on the quantitative outcomes of combination index (CI) values. x axis represents percent inhibition of cells as Fa; y axis represents CI, which generates drug-effect values with a differing ratio of drug combinations. Representative data were analyzed by CompuSyn software. (Data presented as mean ± SEM with n = 3, ∗∗p < 0.01 or ∗p < 0.05; ∗significant difference between JQ1 versus JQ1 + ATRA.)

Figure 6

Effect of JQ1 and ATRA combinatorial treatments on tumor-sphere formation (A) Tumor-sphere formation in 25 days after treating cells with JQ1, ATRA, and combinations from 10 nM to 1 μM. (B) Proliferation inhibition measured by CyQuant assay of Kelly with JQ1 and ATRA combinatorial treatments for 10 days. Representative images of tumor spheres and proliferating colony of Kelly cells. Cells were imaged after adding crystal violet dye and the washing procedure.