Phenotypic marker-guided development of selective antimetastasis therapeutic leads

缺乏针对癌症转移的有效治疗在很大程度上是由于转移性肿瘤的复杂性。 转型过程和对关键基本机制的不完全理解。基因列表和 与致癌作用相关的途径正在增长，靶向单基因活性的抗癌剂已经 到达诊所并显示原发性肿瘤生长抑制。然而，这些药物在有效治疗 转移，导致患者长期存活率差，并加强了癌症复杂性的挑战。它有 根据肿瘤细胞的形态学变化对恶性程度进行分级的临床实践由来已久 和组织，其中高级别癌症通常与患者预后不良相关， 特定的病理特征可用作癌组织恶性潜能的读出。这里我们 利用"自上而下"的方法，其中特定的亚细胞特异性结构独特的转移 电位被用作恶性肿瘤的替代标志物。我们推断，这种细胞亚结构应该 比任何单一基因或基因产物更好地反映复杂和独特的恶性性质。这些 结构不仅提供了一个体外实验平台（细胞系），以研究重要的关键因素， 用于癌症转移（以及随后的体内验证），而且还用作抗癌的表型标志物 药物开发为此，我们已经验证了核仁周围区室（PNC），一个核体， 这种癌细胞恶性行为的标志物。 PNC在转移性肿瘤中高度流行，并且PNC患病率与疾病正相关 在几种癌症中与患者预后呈负相关。使用PNC降低流行率 作为高含量筛选中转移的表型标志物，我们开发了I期临床候选物 metarrestin，一种用于大量癌细胞系的有效PNC抑制剂。Metarrestin抑制体外侵袭， 在三种人类癌症小鼠模型中阻断转移性发展，并延长了小鼠在 转移性胰腺癌异种移植模型，没有可辨别的副作用。 该提案描述了开发新的抗转移治疗先导物的双管齐下的方法。 我们已经确定eEF1A2作为metarrestin的分子靶点，并将使用跨学科的互补方法， 利用与eEF1A2的相互作用来开发更有效的PNC流行抑制剂的方法， 一代治疗铅。同时，我们将使用PNC患病率作为表型读数， 额外的结构上不同的高通量筛选命中。这些袭击都经过了国家民警活动的审查 对细胞毒性和DNA结合进行了复筛，并证实其在体外迁移和 入侵实验这两种互补的方法都利用了从 开发metarrestin，并促进新的治疗先导物和化学工具的开发， 研究eEF1A2和PNC在转移中的作用。

The lack of effective treatment against cancer metastasis is in large part due to the complexity of the metastatic transformation process and incomplete understanding of the key underlying mechanisms. The list of genes and pathways associated with carcinogenesis is growing and anti-cancer agents targeting single gene activities have reached clinics and shown primary tumor growth inhibition. However, these agents fall short in effectively treating metastasis, leading to poor long-term patient survival and reinforcing the challenge of cancer complexity. It has long been a clinical practice to grade the levels of malignancy based on morphological changes of tumor cells and tissues, where a high-grade cancer generally correlates with poor patient outcomes, suggesting cancer specific pathognomonic features can be used as readouts for the malignant potential of cancer tissues. Here we utilize a “top-down” approach, in which specific subcellular pathognomonic structures unique to metastatic potential are used as surrogate markers for malignancy. We reason that such cellular substructures should reflect the complex and unique malignant properties better than any single gene or gene product. These structures not only provide an in vitro experimental platform (cell lines) to investigate the key factors important for cancer metastasis (and subsequent in vivo validations), but also serve as a phenotypic marker for anti-cancer drug development. To this end, we have validated the perinucleolar compartment (PNC), a nuclear body, as such a marker for cancer cell malignant behavior. PNCs are highly prevalent in metastatic tumors and PNC prevalence positively correlates with disease progression and inversely correlates with patient outcomes in several cancers. Using PNC prevalence reduction as a phenotypic marker for metastasis in a high-content screen, we developed the phase I clinical candidate metarrestin, a potent PNC inhibitor for a large array of cancer cell lines. Metarrestin inhibits invasion in vitro, blocks metastatic development in three mouse models of human cancers, and extends survival of mice in a metastatic pancreatic cancer xenograft model without discernable adverse effects. This proposal describes a two-pronged approach for the development new anti-metastasis therapeutic leads. We have identified eEF1A2 as a molecular target for metarrestin and will use inter-disciplinary, complementary approaches to leverage interactions with eEF1A2 to develop more potent PNC prevalence inhibitors as next generation therapeutic leads. In parallel, we will use PNC prevalence as a phenotypic readout to interrogate additional structurally distinct high-throughput screening hits. These hits have been vetted for PNC activity, counterscreened for cytoxicity and DNA binding, and confirmed to possess efficacy in in vitro migration and invasion experiments. Both complementary approaches capitalize on the knowledge gained from the development of metarrestin and facilitate the development of new therapeutic leads and chemical tools for investigating the role of eEF1A2 and PNCs in metastasis.