The mechanisms of adaptive resistance to genetic-based targeted therapies of solid malignancies have been the subject of intense research. These studies hold great promise for finding co-targetable hub/pathways which in turn would control the downstream non-genetic mechanisms of adaptive resistance. Many such mechanisms have been described in the paradigmatic BRAF-mutated melanoma model of adaptive response to BRAF inhibition. Currently, a major challenge for these mechanistic studies is to confirm in vivo, at the single-cell proteomic level, the existence of dependencies between the co-targeted hub/pathways and their downstream effectors. Moreover, the drug-induced in vivo modulation of these dependencies needs to be demonstrated. Here, we implement such single-cell-based in vivo expression dependency quantification using immunohistochemistry (IHC)-based analyses of sequential biopsies in two xenograft models. These mimic phase 2 and 3 trials in our own therapeutic strategy to prevent the adaptive response to BRAF inhibition. In this mechanistic model, the dependencies between the targeted Li₂CO₃-inducible hub HuR and the resistance effectors are more likely time-shifted and transient since the minority of HuR^Low cells, which act as a reservoir of adaptive plasticity, switch to a HuR^High state as they paradoxically proliferate under BRAF inhibition. Nevertheless, we show that a copula/kernel density estimator (KDE)-based quantification of mutual information (MI) efficiently captures, at the individual level, the dependencies between HuR and two relevant resistance markers pERK and EGFR, and outperforms classic expression correlation coefficients. Ultimately, the validation of MI as a predictive IHC-based metric of response to our therapeutic strategy will be carried in clinical trials.

实体恶性肿瘤的基于基因的靶向治疗的适应性耐药机制一直是深入研究的主题。这些研究为寻找可共同靶向的枢纽/途径带来了巨大的希望，这些枢纽/途径反过来将控制适应性抗性的下游非遗传机制。许多此类机制已在对 BRAF 抑制的适应性反应的典型 BRAF 突变黑色素瘤模型中进行了描述。目前，这些机制研究的一个主要挑战是在体内，在单细胞蛋白质组水平上，共同靶向枢纽/通路及其下游效应器之间存在依赖性。此外，需要证明药物诱导的这些依赖性的体内调节。在这里，我们实现了这种基于单细胞的在两个异种移植模型中，使用基于免疫组织化学 (IHC) 的连续活检分析进行体内表达依赖性量化。这些模拟了我们自己的治疗策略中的 2 期和 3 期试验，以防止对 BRAF 抑制的适应性反应。在这个机械模型中，目标 Li ₂ CO ₃诱导型枢纽 HuR 和电阻效应器之间的依赖关系更可能是时移和瞬态的，因为作为适应性可塑性储存器的少数 HuR ^Low细胞切换到高呼^_状态，因为它们在 BRAF 抑制下矛盾地增殖。尽管如此，我们表明基于 copula/内核密度估计器 (KDE) 的互信息 (MI) 量化在个体水平上有效地捕获了 HuR 与两个相关抗性标记 pERK 和 EGFR 之间的依赖关系，并且优于经典的表达相关系数. 最终，将在临床试验中验证 MI 作为基于 IHC 的对我们治疗策略反应的预测指标。