Development of TGF-beta antagonists for cancer therapy

尽管TGF-β在肿瘤发生中具有肿瘤抑制和肿瘤促进的双重作用，但我们实验室和其他实验室的临床前数据先前表明，拮抗TGF-β的策略可以选择性地减少这种生长因子的不良肿瘤促进作用，同时保留对肿瘤抑制和正常体内平衡的理想作用。基于这些有希望的临床前结果，几种不同的TGF-β途径拮抗剂正在进行治疗晚期癌症的早期临床试验。然而，鉴于TGF-β的复杂生物学特性，成功开发用于癌症治疗的TGF-β拮抗剂将取决于对这些药物如何工作的清楚理解，以及如何选择将从这种治疗中受益的患者的相关问题。在我们之前的工作中，我们对广泛使用的转移性乳腺癌4 T1可移植小鼠模型中抗TGF-β中和抗体的作用模式进行了详细的机制分析。使用一组12个可移植的转移性乳腺癌同基因小鼠模型，以转移负荷作为主要治疗终点，我们以前发现了对TGF-β拮抗作用的异质性反应，在某些模型中抑制了转移，在其他模型中对转移没有影响或刺激。我们应用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，并产生有用的预测生物标志物。肿瘤细胞系的全外显子组DNA测序表明，乳腺癌中常见的突变都与治疗反应无关。该组中未治疗的原发性肿瘤的转录组学分析通过对抗TGF-β治疗的反应分离肿瘤，表明治疗反应由肿瘤的突出的、容易识别的分子和生物学特征决定。来自显示对TGF-β拮抗作用的期望应答的模型的肿瘤的特征在于免疫功能降低、血管生成增强、肿瘤细胞增殖和存活率较高以及在未治疗状态下TGF-β途径活化的转录组学证据。已经产生了预测抗TGF-β治疗反应的基因表达特征，并正在其他临床前模型中进行测试。在我们寻找TGF-β拮抗作用的有用的预测性和药效学生物标志物的过程中，我们开发了用于定量和更复杂地监测肿瘤中TGF-β途径活化的方法，采用ProteinSimple SimpleWestern技术精确定量肿瘤样品中的Smad活化，并开发了一种用于检测非典型“混合Smad”的定量明场邻近连接测定法，与病理性TGF-β信号传导相关的信号传导复合物。我们还开始研究是否有可能通过选择性中和不同的TGF-β亚型来改善对TGF-β拮抗作用的治疗反应。相关临床数据和文献证据表明，虽然TGF-β 1主要与不良结局相关，但TGF-β 3实际上可能与TGF-β 1相反，并与良好结局相关，这为选择性中和TGF-β 1和TGF-β 2，同时保留TGF-β 3提供了理论基础。作为该计划的一部分，我们已经开发了准确定量肿瘤提取物中TGF-β的方法，因为我们已经证明TGF-β mRNA水平与TGF-β 1和TGF-β 3的蛋白质水平没有很好的相关性。我们评估了转移性肿瘤组中TGF-β亚型蛋白水平，发现TGF-β 1：TGF-β 3的比例在20倍范围内变化。将在代表性模型中比较具有不同亚型选择性的治疗性抗TGF-β抗体的功效。通过这种方法，我们希望产生改进的TGF-β靶向疗法。

Despite the dual role for TGF-beta as both tumor suppressor and tumor promoter in carcinogenesis, preclinical data from our lab and others has previously suggested that strategies to antagonize TGF-beta may selectively reduce the undesirable tumor promoting effects of this growth factor while sparing the desirable effects on tumor suppression and normal homeostasis. Based on these 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. In our previous work, we performed detailed mechanistic analysis of the mode of action of anti-TGF-beta neutralizing antibodies in the widely used 4T1 transplantable mouse model of metastatic breast cancer. Using a panel of 12 transplantable syngeneic mouse models of metastatic breast cancer, with metastatic burden as the primary therapeutic endpoint, we had previously uncovered heterogeneous responses to TGF-beta antagonism, with inhibition of metastasis in some models, and no effect on or stimulation of metastasis in other models. We have applied discovery-based approaches to address molecular and biological mechanisms underlying the heterogeneity of therapeutic response and to generate useful predictive biomarkers. Whole exome DNA sequencing of the tumor cell lines has shown that none of the commonly occurring mutations in breast cancer are correlated with response to therapy. Transcriptomic analysis of untreated primary tumors in the panel segregates tumors by response to anti-TGF-beta therapy, suggesting that the therapeutic response is dictated by prominent, readily identifiable molecular and biological features of the tumor. Tumors from models showing a desirable response to TGF-beta antagonism are characterized by reduced immune function, enhanced angiogenesis, higher tumor cell proliferation and survival, and transcriptomic evidence of TGF-beta pathway activation in the untreated state. Gene expression signatures that are predictive of response to anti-TGF-beta therapy have been generated and are being tested in additional preclinical models. In our search for useful predictive and pharmacodynamic biomarkers of TGF-beta antagonism, we have developed approaches for quantitative and more sophisticated monitoring of TGF-beta pathway activation in tumors, adapting the ProteinSimple SimpleWestern technology for accurate quantitation of Smad activation in tumor samples, and developing a quantitative brightfield proximity ligation assay for detection of the non-canonical "mixed Smad" signaling complexes that are associated with pathological TGF-beta signaling. We have also begun to address whether it might be possible to improve the therapeutic response to TGF-beta antagonism by selective neutralization of different TGF-beta isoforms. Correlative clinical data and literature evidence suggests that whereas TGF-beta1 is primarily associated with poor outcome, TGF-beta3 may actually oppose TGF-beta1 and be associated with good outcome, providing a rationale for selective neutralization of TGF-beta1 and TGF-beta2, while sparing TGF-beta3. As part of this initiative, we have developed methods for accurate quantitation of TGF-betas in tumor extracts since we have shown that TGF-beta mRNA levels do not correlate well with protein levels for TGF-beta1 and TGF-beta3. We have assessed TGF-beta isoform protein levels across the metastatic tumor panel and find that TGF-beta1:TGF-beta3 ratios vary over a 20-fold range. Therapeutic anti-TGF-beta antibodies with different isoform selectivity will be compared for efficacy in representative models. Through this approach, we hope to generate improved TGF-beta-targeted therapeutics.