Targeting pancreatic cancer by TAK-981: a SUMOylation inhibitor that activates the immune system and blocks cancer cell cycle progression in a preclinical model
Objective: Pancreatic ductal adenocarcinoma (PDAC) has the characteristics of high-density desmoplastic stroma, a distinctive immunosuppressive microenvironment and is profoundly resistant to all forms of chemotherapy and immunotherapy, leading to a 5-year survival rate of 9%. Our study aims to add novel small molecule therapeutics for the treatment of PDAC. Design: We have studied whether TAK-981, a novel highly selective and potent small molecule inhibitor of the small ubiquitin like modifier (SUMO) activating enzyme E1 could be used to treat a preclinical syngeneic PDAC mouse model and we have studied the mode of action of TAK-981. Results: We found that SUMOylation, a reversible post-translational modification required for cell cycle progression, is increased in PDAC patient samples compared with normal pancreatic tissue. TAK-981 decreased SUMOylation in PDAC cells at the nanomolar range, thereby causing a G2/M cell cycle arrest, mitotic failure and chromosomal segregation defects. TAK-981 efficiently limited tumour burden in the KPC3 syngeneic mouse model without evidence of systemic toxicity. In vivo treatment with TAK-981 enhanced the proportions of activated CD8 T cells and natural killer (NK) cells but transiently decreased B cell numbers in tumour, peripheral blood, spleen and lymph nodes. Single cell RNA sequencing revealed activation of the interferon response on TAK-981 treatment in lymphocytes including T, B and NK cells. TAK-981 treatment of CD8 T cells ex vivo induced activation of STAT1 and interferon target genes. Conclusion: Our findings indicate that pharmacological inhibition of the SUMO pathway represents a potential strategy to target PDAC via a dual mechanism: inhibiting cancer cell cycle progression and activating anti-tumour immunity by inducing interferon signalling. Keywords: T lymphocytes; immune response; interferon; pancreatic cancer; signal transduction.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
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细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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