PO.ET02.12 · 实验与分子治疗
基于网络的肿瘤检查点反转药物发现:靶向胰腺导管腺癌细胞状态与巨噬细胞重编程
Network-based discovery of tumor-checkpoint inverter drugs targeting pancreatic ductal adenocarcinoma cell states and macrophage reprogramming
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
胰腺导管腺癌(PDAC)仍然是最致命的恶性肿瘤之一,由极端的肿瘤异质性和高度免疫抑制性的肿瘤微环境(TME)所驱动。不同的PDAC细胞状态——胃肠样型(GLS)、形态发生型(MOS)和原始型(PLS)——共存于单个肿瘤内,并进一步按MAPK活性(M⁺/M⁻)进行分层,反映出由主调控因子(MR)蛋白维持的动态转录程序。据推测,这些细胞状态可差异化地调节TME中的肿瘤相关巨噬细胞。为研究这一点,我们建立了THP-1来源的巨噬细胞与代表各状态的PDAC细胞系的共培养系统,并分析了巨噬细胞的转录重编程。与不同PDAC状态共培养的巨噬细胞表现出M2样和TREM2⁺/APOE⁺/C1Q⁺免疫抑制表型的差异化激活,提示PDAC细胞状态可能独特地影响巨噬细胞表型和免疫逃逸。为鉴定能够重编程这些恶性状态的化合物,我们应用了一个基于网络的系统生物学框架,整合ARACNe和VIPER来推断PDAC各状态中的MR活性,OncoMatch来鉴定代表性细胞系模型,以及OncoTreat来预测能够反转肿瘤检查点模块活性的小分子。跨模型验证鉴定出状态特异性候选药物,包括用于GLS的亮丙瑞林(Leuprolide)、长春碱(Vinblastine)和巯嘌呤(Mercaptopurine);用于MOS的长春地辛(Vindesine)、棉酚(Gossypol)和比美替尼(Binimetinib);以及用于PLS的AT9283、克唑替尼(Crizotinib)和阿法替尼(Afatinib)。预测的MR反转评分与经OncoMatch选定的细胞系中的实验性剂量反应曲线相关。总之,这些结果建立了肿瘤内在转录状态与巨噬细胞免疫抑制之间的机制联系,同时鉴定出不依赖突变、状态特异性的药物,能够重编程肿瘤和免疫两个区室。这项工作提供了一个可推广的基于网络的药物重定位框架,以克服PDAC中的转录可塑性和免疫耐药。
查看英文原文 English abstract
Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, driven by extreme tumor heterogeneity and a profoundly immunosuppressive tumor microenvironment (TME). Distinct PDAC cell states-Gastrointestinal-like (GLS), Morphogenic (MOS), and Primitive (PLS)-coexist within individual tumors and are further stratified by MAPK activity (M⁺/M⁻), reflecting dynamic transcriptional programs sustained by Master Regulator (MR) proteins. These cell states are hypothesized to differentially modulate the tumor-associated macrophages in the TME. To investigate this, we established a co-culture system of THP-1-derived macrophages with PDAC cell lines representing each state and profiled macrophage transcriptional reprogramming. Macrophages co-cultured with distinct PDAC states exhibited differential activation of M2-like and TREM2⁺/APOE⁺/C1Q⁺ immunosuppressive phenotype, suggesting that PDAC cell states may uniquely influence macrophage phenotypes and immune evasion.To identify compounds capable of reprogramming these malignant states, we applied a network-based systems biology framework integrating ARACNe and VIPER to infer MR activity across PDAC states, OncoMatch to identify representative cell line models, and OncoTreat to predict small molecules capable of inverting tumor checkpoint-module activity. Cross-model validation identified state-specific candidate drugs, including Leuprolide, Vinblastine, and Mercaptopurine for GLS; Vindesine, Gossypol, and Binimetinib for MOS; and AT9283, Crizotinib, and Afatinib for PLS. Predicted MR-inversion scores correlated with experimental dose-response profiles in cell lines selected via OncoMatch.Together, these results establish a mechanistic link between tumor-intrinsic transcriptional states and macrophage immunosuppression, while identifying mutation-agnostic, state-specific drugs capable of reprogramming both tumor and immune compartments. This work provides a generalizable framework for network-based drug repurposing to overcome transcriptional plasticity and immune resistance in PDAC.
利益披露 Disclosure
Y. Chen, None..
A. Curiel-Garcia, None..
A. Piacentini, None..
Z. Liu, None..
T. Olsen, None.
R. Yau,
Cellanome Employment.
P. Sharma,
Cellanome Employment.
L. Murray,
Cellanome Employment.
G. Viscido, None..
K. Olive, None.
A. Califano,
DarwinHealth Independent Contractor, Stock, Other Business Ownership, Other, Dr. Califano is founder, equity holder, and consultant of DarwinHealth Inc., a company that has licensed some of the algorithms used in this manuscript from Columbia University. Columbia University is also an equity holder in DarwinHealth Inc.