Therapeutic targeting of autophagy-dependent cancer

 描述(由申请人提供)：自噬在癌症的发展、进展和治疗反应中很重要。虽然我们已经在临床上尝试以自噬为靶点，但目前还没有办法确定哪些肿瘤将受益于或将不受益于自噬抑制。我们最近报道，一些乳腺肿瘤细胞比其他细胞更依赖自噬，我们的数据表明，只有在真正依赖自噬的肿瘤细胞(我们定义的是那些需要自噬才能在没有额外压力的情况下存活的细胞)中，自噬抑制才会单独或与其他药物联合有效。事实上，我们的数据表明，将自噬抑制与肿瘤细胞中不依赖自噬的另一种药物相结合可能会适得其反。我们还发现了一种解释自噬依赖性乳腺癌的潜在机制--自噬仅控制某些肿瘤细胞中的STAT3活性，这是解释自噬依赖性生存的必要条件和充分条件；此外，最近的研究也表明，肿瘤干细胞的活性需要在这些细胞中进行自噬。这些数据让我们提出假设：自噬依赖定义了一种特定的肿瘤亚型，其细胞存活和干细胞样特征依赖于自噬：这些肿瘤对自噬抑制反应最好。为了检验我们的假设，我们有三个具体目标。目的1.鉴定依赖自噬的肿瘤并确定对自噬抑制的反应。我们假设我们可以识别自噬依赖的肿瘤，并将测试我们认为可以做到这一点的初步基因表达特征。我们认为自噬抑制将是有效的，但仅对依赖自噬的肿瘤有效，并将在原发肿瘤和手术切除的转移瘤的新辅助和辅助治疗中测试这一点。目的2.检测自噬抑制是否对自噬依赖型乳腺癌的其他治疗敏感。为了验证自噬依赖型肿瘤将从自噬抑制剂联合治疗中受益最大的假设，使用大规模shRNA分析的实验以及使用Coxen原理的新生物信息学方法将找出如何最好地结合其他药物来靶向自噬。目的3.确定乳腺肿瘤自噬依赖的机制。我们假设自噬信号的自噬调节解释了STAT3的激活、存活和干细胞样的自噬依赖的肿瘤细胞。我们将通过分析自噬通过白介素6等细胞因子发出信号的能力来测试这一点，我们已经证明，自噬仅在依赖自噬的肿瘤细胞中受到自噬的特异性控制。如果我们的想法是正确的，我们的工作将有助于定义一种新的自噬依赖型乳腺癌亚型，并提供一种新的方法来识别、治疗和改进这些肿瘤的联合治疗，同时为自噬在癌症治疗和癌症生物学中的作用提供新的见解。

 DESCRIPTION (provided by applicant): Autophagy is important in cancer development, progression and response to therapy. Although we are already trying to target autophagy in the clinic, there is currently no way to identify the tumors that will or will not benefit from autophay inhibition. We recently reported that some breast tumor cells are much more dependent on autophagy than others and our data suggest that it is only in the truly autophagy-dependent tumor cells (which we define as those that require autophagy to survive even in the absence of additional stress) where autophagy inhibition will be effective on its own or in combination with other agents. Indeed, our data suggest that combining autophagy inhibition with another agent in tumor cells that are not autophagy-dependent can be counterproductive. We also identified a potential mechanism to explain autophagy-dependent breast cancer- autophagy controls STAT3 activity in only some tumor cells and this is necessary and sufficient to explain autophagy-dependent survival; moreover recent studies have also indicated that tumor stem-like cell activity requires autophagy in these cells. These data led us to hypothesize: autophagy-dependency defines a specific tumor subtype whose cell survival and stem cell-like characteristics depend on autophagy: these are the tumors that will respond best to autophagy inhibition. To test our hypothesis, we have three specific aims. Aim 1. Identify autophagy-dependent tumors and determine response to autophagy inhibition. We hypothesize that we can identify autophagy-dependent tumors and will test a preliminary gene expression signature that we think can do this. We propose that autophagy inhibition will be effective but only for autophagy-dependent tumors and will test this in primary tumors and by neoadjuvant and adjuvant treatment of surgically resected metastatic tumors. Aim 2. Test if autophagy inhibition sensitizes to other treatments in autophagy-dependent breast cancer. To test the hypothesis that autophagy-dependent tumors will benefit most from combination treatment with autophagy inhibitors, experiments using large scale shRNA analysis well as a novel bioinformatics approach using the COXEN principle will work out how best to target autophagy in combination with other drugs. Aim 3. Determine the mechanism underlying autophagy-dependency in breast tumors. We hypothesize that autophagy regulation of autocrine signaling explains STAT3 activation, survival and stem cell like of autophagy-dependent tumor cells. We will test this by analyzing autophagy's ability to signal through cytokines like IL6, which we have shown is specifically controlled by autophagy only in the autophagy-dependent tumor cells. If our ideas are correct, our work will help define a novel subtype of autophagy-dependent breast cancer and provide a new way to identify, treat and improve combination treatments for these tumors while providing new insights into the roles of autophagy in cancer therapy and cancer biology.