Development of TGF-beta antagonists for cancer therapy

基于有希望的临床前结果，几种不同的tgf - β途径拮抗剂正处于治疗晚期癌症的早期临床试验中。然而，鉴于tgf - β的复杂生物学特性，用于癌症治疗的tgf - β拮抗剂的成功开发将取决于对这些药物如何起作用的清晰理解，以及如何选择将从这种治疗中受益的患者的相关问题。采用12只转移性乳腺癌小鼠同种异体移植模型，以转移负荷为主要终点，我们发现了对tgf - β拮抗剂的异质性反应。tgf - β通路阻断在某些模型中抑制转移，而在其他模型中对转移没有影响或刺激。我们正在继续应用靶向和基于发现的方法来解决治疗反应异质性的分子和生物学机制，并产生有用的预测性生物标志物。出乎意料的是，原发肿瘤中tgf - β表达水平和tgf - β通路激活程度都不能预测抗tgf - β治疗的反应。然而，来自模型的肿瘤对tgf - β拮抗剂表现出理想的反应，其特征是tgf - β途径在未治疗状态下激活的转录组学证据。因此，在体内，tgf - β信号的输出可能比任何输入参数（如配体水平和信号转导组分的状态）更敏感地指示tgf - β通路的激活状态。我们正在生成可能预测抗tgf -治疗反应的基因表达特征，并将在其他临床前模型中进行测试。我们还确定了tgf - β治疗反应的候选分子决定因素，并通过敲低和过表达方法在肿瘤模型中进行测试。我们也在继续研究提高tgf - β拮抗剂治疗效果的方法。相关临床数据和文献证据表明，尽管tgf - β 1主要与许多癌症的不良预后相关，但tgf - β 3实际上可能与tgf - β 1相反，并与良好预后相关。我们优化了一种准确定量tgf - β蛋白异构体表达的方法，并表明乳腺是少数表达tgf - β 3显著水平的成人器官之一。我们发现，与正常乳腺相比，tgf - β 1持续上调，tgf - β 3持续下调。我们关于tgf - β亚型选择性抗体的初步数据表明，就治疗效果而言，保留tgf - β 3没有优势，但这种方法可能有积极的代谢后果。我们的整合基因组方法也提示了可以与tgf - β拮抗剂联合使用的药物，以提高治疗效果，我们正在积极寻求临床前模型的领先优势。

Based on promising preclinical results, several different TGF-beta pathway antagonists are in early phase clinical trials for the treatment of advanced cancer. However, given the complex biology of TGF-beta, the successful development of TGF-beta antagonists for cancer therapy will depend on a clear understanding of how these agents work, and the related question of how to select patients who will benefit from this type of treatment. Using a panel of 12 mouse syngeneic allograft models of metastatic breast cancer, with metastatic burden as the primary endpoint, we uncovered heterogeneous responses to TGF-beta antagonism. TGF-beta pathway blockade inhibited metastasis in some models, while having no effect on or stimulating metastasis in other models. We are continuing to apply targeted and discovery-based approaches to address molecular and biological mechanisms underlying the heterogeneity of therapeutic response and to generate useful predictive biomarkers. Unexpectedly, neither TGF-beta expression levels nor extent of TGF-beta pathway activation in the primary tumor predict response to anti-TGF-beta therapy. However, tumors from models showing a desirable response to TGF-beta antagonism are characterized by transcriptomic evidence of TGF-beta pathway activation in the untreated state. Thus in vivo, the output of TGF-beta signaling may be a more sensitive indicator of the activation status of the TGF-beta pathway than any of the input parameters such as ligand levels and status of signal transduction components. We are generating gene expression signatures that might predict response to anti-TGF-beta therapy and will test these in additional preclinical models. We have also identified candidate molecular determinants of the therapeutic response to TGF-beta and are testing these by knockdown and overexpression approaches in the tumor models. We are also continuing to address ways of improving the therapeutic efficacy of TGF-beta antagonism. Correlative clinical data and literature evidence suggest that whereas TGF-beta1 is primarily associated with poor outcome in many cancers, TGF-beta3 may actually oppose TGF-beta1 and be associated with good outcome. We have optimized a method for accurate quantitation of TGF-beta protein isoform expression and have shown that the mammary gland is one of the few adult organs to express significant levels of TGF-beta3. We find TGF-beta1 to be consistently upregulated and TGF-beta3 to be downregulated when compared with the normal mammary gland. Our preliminary data with TGF-beta isoform-selective antibodies suggests that there is no advantage to sparing TGF-beta3 in terms of therapeutic efficacy, but that there may be positive metabolic consequences of this approach. Our integrated genomic approaches are also suggesting drugs that could be combined with TGF-beta antagonists to improve therapeutic efficacy, and we are actively pursuing the top leads in our preclinical models.