Vareli Aimilia, Narayanan Haripriya Vaidehi, Clark Heather, Jayawant Eleanor, Zhou Hui, Liu Yi, Stott Lauren, Simoes Fabio, Hoffmann Alexander, Pepper Andrea, Pepper Chris, Mitchell Simon
bioRxiv. 2025 Feb 1:2024.11.30.626166. doi: 10.1101/2024.11.30.626166.
In Diffuse Large B-cell Lymphoma (DLBCL), elevated anti-apoptotic BCL2-family proteins (e.g., MCL1, BCL2, BCLXL) and NF-κB subunits (RelA, RelB, cRel) confer poor prognosis. Heterogeneous expression, regulatory complexity, and redundancy offsetting the inhibition of individual proteins, complicate the assignment of targeted therapy. We combined flow cytometry "fingerprinting", immunofluorescence imaging, and computational modeling to identify therapeutic vulnerabilities in DLBCL. The combined workflow predicted selective responses to BCL2 inhibition (venetoclax) and non-canonical NF-κB inhibition (Amgen16). Within the U2932 cell line we identified distinct resistance mechanisms to BCL2 inhibition in cellular sub-populations recapitulating intratumoral heterogeneity. Co-cultures with CD40L-expressing stromal cells, mimicking the tumor microenvironment (TME), induced resistance to BCL2 and BCLXL targeting BH3-mimetics via cell-type specific upregulation of BCLXL or MCL1. Computational models, validated experimentally, showed that basal NF-κB activation determined whether CD40 activation drove BH3-mimetic resistance through upregulation of RelB and BCLXL, or cRel and MCL1. High basal NF-κB activity could be overcome by inhibiting BTK to resensitize cells to BH3-mimetics in CD40L co-culture. Importantly, non-canonical NF-κB inhibition overcame heterogeneous compensatory BCL2 upregulation, restoring sensitivity to both BCL2- and BCLXL-targeting BH3-mimetics. Combined molecular fingerprinting and computational modelling provides a strategy for the precision use of BH3-mimetics and NF-κB inhibitors in DLBCL.
在弥漫性大B细胞淋巴瘤(DLBCL)中,抗凋亡BCL2家族蛋白(如MCL1、BCL2、BCLXL)和NF-κB亚基(RelA、RelB、cRel)水平升高预示着预后不良。其表达的异质性、调控的复杂性以及单个蛋白抑制作用的冗余性相互抵消,使得靶向治疗的应用变得复杂。我们结合流式细胞术“指纹识别”、免疫荧光成像和计算模型,以确定DLBCL中的治疗脆弱点。该联合工作流程预测了对BCL2抑制(维奈托克)和非经典NF-κB抑制(安进16)的选择性反应。在U2932细胞系中,我们在重现肿瘤内异质性的细胞亚群中鉴定出对BCL2抑制的不同耐药机制。与表达CD40L的基质细胞共培养,模拟肿瘤微环境(TME),通过BCLXL或MCL1的细胞类型特异性上调,诱导对靶向BCL2和BCLXL的BH3模拟物产生耐药性。经实验验证的计算模型表明,基础NF-κB激活决定了CD40激活是否通过RelB和BCLXL或cRel和MCL1的上调驱动BH3模拟物耐药。在CD40L共培养中,抑制BTK可克服高基础NF-κB活性,使细胞对BH3模拟物重新敏感。重要的是,非经典NF-κB抑制克服了BCL2异质性代偿性上调,恢复了对靶向BCL2和BCLXL的BH3模拟物的敏感性。联合分子指纹识别和计算建模为在DLBCL中精准使用BH3模拟物和NF-κB抑制剂提供了一种策略。