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，抗TGF-β抗体正处于治疗晚期癌症的早期临床试验中（NCI-06-C-0200）。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。 我们在2011财年的主要重点是建立一组可移植的转移性乳腺癌同基因小鼠模型，评估抗TGF-β抗体在不同模型中的治疗效果，然后使用该模型开发对抗TGF-β治疗反应的预测性生物标志物。我们已经组装了一组11个转移性乳腺模型，这些模型来自自发或基因工程小鼠乳腺肿瘤，可以移植到免疫活性小鼠宿主中。 代表了一系列肿瘤组织学和小鼠品系背景。我们已经成功地评估了泛TGF-β中和小鼠单克隆抗体对9种模型中转移的影响（1D 11），我们发现，虽然1D 11在某些模型中抑制转移，但在其他模型中没有影响，甚至可以刺激转移。使用这个面板，我们已经评估了许多合理的候选生物标志物的预测能力。我们已经发现，对TGF-β拮抗作用的治疗反应不能通过（a）肿瘤细胞中TGF-β表达水平，（B）肿瘤细胞对TGF-β的生长抑制反应的丧失，（c）Six-1表达水平，（d）紧密连接蛋白低状态，（e）非经典TGF-β信号传导途径的激活成功预测。 我们现在正在进行基于发现的方法来鉴定预测性生物标志物，包括测试我们在相关项目ZIA BC 005785中鉴定的TGF-β介导的肿瘤抑制的基因特征。我们还研究了在某些模型中1D 11对转移的不良刺激的潜在机制，并且我们已经表明，与治疗效果不同，这种刺激作用不依赖于适应性免疫应答的存在。

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, an anti-TGF-beta antibody is in early phase clinical trials for the treatment of advanced cancer (NCI-06-C-0200). 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. Our major focus in FY11 has been to establish a panel of transplantable syngeneic mouse models of metastatic breast cancer, assess the therapeutic effects of anti-TGF-beta antibodies in the different models and then use the panel to develop predictive biomarkers of response to anti-TGF-beta therapy. We have assembled a panel of 11 metastatic mammary models derived from spontaneous or genetically engineered mouse mammary tumors that can be transplanted into immunocompetent mouse hosts. A range of tumor histologies and mouse strain background are represented. We have successfully assessed the effect of a pan-TGF-beta neutralizing mouse monoclonal antibody on metastasis (1D11) in 9 of the models, and we find that while 1D11 inhibits metastasis in some models, it has no effect or can even stimulate metastasis in other models. Using this panel, we have assessed the predictive power of a number of plausible candidate biomarkers. We have found that therapeutic response to TGF-beta antagonism is not successfully predicted by (a) TGF-beta expression levels in the tumor cells, (b) loss of growth inhibitory response of the tumor cells to TGF-beta, (c) Six-1 expression levels, (d) Claudin-low status, (e) activation of non-canonical TGF-beta signaling pathways. We are now proceeding with discovery-based approaches to the identification of predictive biomarkers, including testing gene signatures of TGF-beta-mediated tumor suppression that we identified in the related project ZIA BC 005785. We have also examined mechanisms underlying the undesirable stimulation of metastasis by 1D11 in some models, and we have shown that unlike the therapeutic effect, this stimulatory effect is not dependent on the presence of an adaptive immune response.