bioRxivCancer BiologyPreprint
Targeting NOTCH2-JAG1 juxtacrine signaling reverses macrophage-mediated tumor resistance to taxol
Fazhi YuiD, Qin ZhouiD, Tong ZhouiD, Yijia XieiD, Peng ZhangiD, Wei He, Weiqiang YuiD, Aoxing ChengiD, Hanyuan LiuiD, Qingfa WuiD, Xiaopeng MaiD, Jing Song GuoiD, Ying ZhouiD, Jue ShiiD, Zhenye YangiD
Abstract
Taxanes are widely used in chemotherapy, but primary and acquired resistance limit the clinical efficacy. Studies have shown tumor interaction with macrophages in the tumor microenvironment (TME) plays a significant role in taxane resistance, yet therapeutic strategies that directly deplete or repolarize macrophages are challenging and with considerable risk of side effects. Here we uncovered that tumor-macrophage interaction can be selectively targeted by inhibiting post-mitotic NOTCH2-JAG1 juxtacrine signaling in the TME, which strongly sensitizes paclitaxel response. Using translatome profiling, we found significant NOTCH2 upregulation during paclitaxel-induced prolonged mitosis. NOTCH2 was subsequently activated in the post-mitotic G1 phase by JAG1 expressed on the neighboring macrophages and tumor cells, which promoted tumor cell survival and upregulated cytokines that recruited JAG1-expressing macrophages, thus generating a positive feedback loop that further enhanced the pro-tumor NOTCH2 activity. By targeting this NOTCH2-JAG1 axis using NOTCH2 shRNA or a pan-NOTCH inhibitor, macrophage recruitment and paclitaxel resistance were significantly attenuated in multiple mouse tumor models of ovarian cancer. Clinical samples from paired primary and recurrent ovarian cancer patients also showed significant correlation of higher NOTCH2 expression with worse prognosis. Our results thus point to combining NOTCH2 inhibitor with taxane as an effective therapeutic strategy to selectively disrupt tumor-macrophage interaction in the TME and overcome macrophage-mediated taxane resistance in NOTCH2-positive tumors.
- organism: mouse
- assay: bulk RNA-seq
- research focus: drug response / drug discovery
- approach: statistical model
- Citations
- 1
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