ΔNp63-driven recruitment of myeloid-derived suppressor cells promotes metastasis in triple-negative breast cancer
Sushil Kumar, David W. Wilkes, Nina Samuel, Mario Andres Blanco, Anupma Nayak, Kevin Alicea-Torres, Christian Gluck, Satrajit Sinha, Dmitry Gabrilovich, Rumela Chakrabarti
Sushil Kumar, David W. Wilkes, Nina Samuel, Mario Andres Blanco, Anupma Nayak, Kevin Alicea-Torres, Christian Gluck, Satrajit Sinha, Dmitry Gabrilovich, Rumela Chakrabarti
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Research Article Oncology

ΔNp63-driven recruitment of myeloid-derived suppressor cells promotes metastasis in triple-negative breast cancer

Abstract

Triple-negative breast cancer (TNBC) is particularly aggressive, with enhanced incidence of tumor relapse, resistance to chemotherapy, and metastases. As the mechanistic basis for this aggressive phenotype is unclear, treatment options are limited. Here, we showed an increased population of myeloid-derived immunosuppressor cells (MDSCs) in TNBC patients compared with non-TNBC patients. We found that high levels of the transcription factor ΔNp63 correlate with an increased number of MDSCs in basal TNBC patients, and that ΔNp63 promotes tumor growth, progression, and metastasis in human and mouse TNBC cells. Furthermore, we showed that MDSC recruitment to the primary tumor and metastatic sites occurs via direct ΔNp63-dependent activation of the chemokines CXCL2 and CCL22. CXCR2/CCR4 inhibitors reduced MDSC recruitment, angiogenesis, and metastasis, highlighting a novel treatment option for this subset of TNBC patients. Finally, we found that MDSCs secrete prometastatic factors such as MMP9 and chitinase 3–like 1 to promote TNBC cancer stem cell function, thereby identifying a nonimmunologic role for MDSCs in promoting TNBC progression. These findings identify a unique crosstalk between ΔNp63+ TNBC cells and MDSCs that promotes tumor progression and metastasis, which could be exploited in future combined immunotherapy/chemotherapy strategies for TNBC patients.

Authors

Sushil Kumar, David W. Wilkes, Nina Samuel, Mario Andres Blanco, Anupma Nayak, Kevin Alicea-Torres, Christian Gluck, Satrajit Sinha, Dmitry Gabrilovich, Rumela Chakrabarti

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Figure 5

ΔNp63 directly regulates CXCL2 and CCL22, promoting MDSC recruitment in TNBC tumors.

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ΔNp63 directly regulates CXCL2 and CCL22, promoting MDSC recruitment in ...
(A–C) Gene set enrichment analysis demonstrating enriched basal signature compared with luminal signatures (A), enriched IFN signaling gene signature (B), and enriched chemokine signature (C) in control compared with ΔNp63-KD HCC1806 cells. NES, normalized enrichment score. (D) Heatmaps depicting relative expression of ΔNp63-dependent chemokines in control and ΔNp63-KD of HCC1806 and SUM159 cells. (E–G) Quantitative reverse transcriptase PCR (RT-qPCR) analysis of indicated chemokines in control and ΔNp63-KD HCC1806 (E), SUM159 (F), and EpRas cells (G). The relative expression of control was considered fold change 1, depicted by the dotted lines. (H) ChIP-Seq analysis shows the putative ΔNp63-binding site (peaks) in the human CXCL2 and CCL22 gene loci using ΔNp63 antibody. (I) Representative images of chemokine antibody arrays from control and ΔNp63-KD HCC1806 cells. (J) The box plot shows the quantification of protein level of CXCL2 by ELISA in conditioned media of control and ΔNp63-KD HCC1806 cells. (K–M) Quantification of migrated MDSCs toward conditioned media of indicated cell lines compared with control (plain medium was added). (N and O) Quantification of migrated MDSCs toward conditioned media of control and ΔNp63-KD cells (HCC1806 and EpRas). (P) Quantification of migrated MDSCs toward indicated chemokine ligand or chemokine receptor inhibitor. (Q) RT-qPCR analysis shows the quantification of mRNA expression levels of indicated chemokine receptors in MDSCs compared with TNBC cells. SUM159 tumor cells were used for analysis. (A–Q) n = 3 independent experiments performed in technical duplicate. Real-time PCR values were normalized to the housekeeping gene GAPDH (mouse and human), and data are presented as the mean ± SD. (E–G, J–O, and Q) P values were calculated using Student’s t test. (P) P value was calculated using 1-way ANOVA with Tukey’s multiple-comparisons post hoc test. *P < 0.05, **P < 0.01, ***P < 0.001.