Research Project 1: Development of PI3K Inhibitors as Single Agents or in Combination with MEK Inhibitors for Breast Cancer

研究项目 1：开发 PI3K 抑制剂作为单一药物或与 MEK 抑制剂联合治疗乳腺癌

• 批准号: 10005320
• 负责人: Cynthia X Ma
• 金额: $ 0.92万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10005320
• 关键词: AKT1 gene; Aftercare; Bioinformatics; Biological Markers; Biopsy; Breast Cancer Model; Breast Cancer Patient; Candidate Disease Gene; Catalytic Domain; Categories; Characteristics; Classification; Clinical; Clinical Trials; Combined Modality Therapy; Data; Data Collection; Data Discovery; Dependence; Development; Dose; Dose-Limiting; Drug Combinations; Drug effect disorder; Drug resistance; ERBB2 gene; Endocrine; Estrogen receptor positive; Evaluation; Event; FRAP1 gene; Feedback; Future; Gene Proteins; Genetic; Genome Stability; Goals; Immune; Individual; Infrastructure; Interruption; Investigation; Lipids; Literature; MEK inhibition; MEKs; Mass Spectrum Analysis; Mediating; Modeling; Molecular; Mus; Mutation; PIK3CA gene; PIK3CB gene; PTEN gene; Pathway interactions; Patient-derived xenograft models of breast cancer; Patients; Pharmaceutical Preparations; Pharmacotherapy; Phenotype; Phosphatidylinositide 3-Kinase Inhibitor; Phosphotransferases; Play; Population; Prediction of Response to Therapy; Progression-Free Survivals; Protein Isoforms; Proteomics; Proto-Oncogene Proteins c-akt; Publishing; Randomized; Research; Research Project Grants; Resistance; Resources; Role; SDZ RAD; Sampling; Signal Transduction; Standardization; Target Populations; Therapeutic Agents; Time; Tissues; Toxic effect; Treatment-related toxicity; Tumor Volume; Tumor-Derived; Universities; Validation; Washington; Xenograft Model; Xenograft procedure; antitumor effect; base; biomarker development; biomarker discovery; cancer subtypes; candidate marker; clinical development; differential expression; early phase trial; exome sequencing; genetic signature; genomic data; hormone receptor-positive; improved; inhibitor/antagonist; interest; malignant breast neoplasm; member; mutant; novel; predicting response; predictive marker; primary endpoint; research clinical testing; resistance mechanism; response; secondary endpoint; success; targeted agent; therapeutic target; therapy resistant; transcriptome sequencing; treatment group; triple-negative invasive breast carcinoma; tumor; tumor growth; tumorigenesis

Research project 1 focuses on identifying response predictors and resistance mechanisms for phosphatidylinositide 3-kinase (PI3K) inhibitors through the conduct of a PDX trial using a broad selection of breast cancer models of hormone receptor positive (HR+)/HER2- and triple negative breast cancer (TNBC) subtypes. PI3K inhibitors are attractive therapeutic agents for breast cancer because of the frequent occurrence of PIK3CA mutations in hormone receptor positive (HR+) and PTEN loss in TNBC. However single agent PI3K inhibitors have yielded only modest anti-tumor activity and the efficacy of pan-PI3K inhibitors are often limited by dose limiting toxicities in clinical trials. Isoform-specific PI3K inhibitors are therefore of great interest to maximize target inhibition with improved tolerability. A major challenge in the development of PI3K inhibitors have been the identification of patients who may benefit the most from these agents and for whom isoform specific inhibitors are appropriate. Clinical trials have focused on limited markers including PIK3CA mutation and PTEN status, which do not consistently predict response. In-depth biomarker research is needed, but is often difficult in the clinical trial setting due to the quantity and quality of the study material and the inability to obtain serial tumor biopsies from patients. In contrast, patient-derived xenograft (PDX) models provide nearly unlimited tumor resources for pre- and post-treatment in-depth genoproteomic analysis for biomarker development and determination of resistance mechanisms for rational drug combinations. We hypothesize that a breast cancer PDX trial of pan- and isoform-specific PI3K inhibitors, will discern isoform dependency of individual tumors to derive predictive biomarkers. We will use copanlisib, a potent pan-PI3K inhibitor with activity against predominantly PI3Kα versus PI3Kβ, and AZD8186, a specific PI3Kβ inhibitor, both agents are in the NCI-IND portfolio. In addition, based on literature evidence and our preliminary data from a PDX trial of buparlisib, we hypothesize that adding the MEK inhibitor selumetinib, also an NCI IND agent, will improve response to copanlisib and/or AZD8186 based on literature evidence and the synergistic anti-tumor effects we observed when combining a pan-PI3K inhibitor with a MEK inhibitor in our PDX models of breast cancer. Aim 1 will conduct the PDX trial. 100 breast cancer PDX models comprised of ER+HER2- and TNBC subtypes available from the PDX core will be selected based on passage number, genomic stability and tumor characteristics. To enrich for the target population, at least 30 PDX models with PIK3CA mutation and at least 30 PDX models with PTEN null phenotype will be included in this PDX trial. Each PDX model will be passaged to 12 immune-deficient mice and randomly assigned to 6 treatment groups (n=2 each treatment group) to receive either vehicle, copanlisib, AZD8186, selumatinib, copanlisib + selumetinib or AZD8186 + selumetinib. Several tumor response criteria will be used for classification of sensitive vs resistant to drug(s) therapy. These include the recently published mRECIST criteria and the traditional % tumor growth inhibition which includes a vehicle treated group. Aim 2 will identify candidate and novel genoproteomic predictors of response for each single agent or combination therapy by analyzing global genomic data (whole exome and RNA Seq) and proteomic data generated by multi-kinase inhibitor bead mass spectrometry (MIB-MS) for unbiased discovery of candidate biomarkers. The analysis will include a focus on identifying outlying, differentially expressed biomarkers between sensitive and resistant tumors. Aim 3 will perform kinome profiling (MIB-MS) of post treatment samples to assess drug-induced signaling changes in order to discern mechanisms of action of the study treatments and to identify intrinsic and treatment-induced adaptive survival mechanisms. This project will be supported by the infrastructure established by the WU-PDTC for data collection, including drug treatment, mice tolerability and tumor volumes changes over time. In addition, the bioinformatics capability provided by the WU-PDTC for trial interpretation and genoproteomic analysis will be leveraged to derive predictors of response and resistance mechanisms to PI3K inhibitors. In addition, team members of Project 1 will interact regularly with team members of Project 2 for information exchange to improve research approach and results sharing. The long term goal of this research is to set up a standardized PDX trial platform to identify promising drug(s) and biomarker pairs for clinical testing.

研究项目1侧重于确定反应预测因素和抵抗机制 磷脂酰肌醇3-激酶(PI3K)抑制剂通过使用广泛的选择进行的PDX试验 激素受体阳性(HR+/HER2-)和三阴性乳腺癌(TNBC)模型的建立 子类型。PI3K抑制剂因其频繁出现而成为治疗乳腺癌的有吸引力的药物 TBC中激素受体阳性(HR+)和PTEN缺失的PIK3CA突变。然而，单一代理PI3K 抑制剂只产生了适度的抗肿瘤活性，而PAN-PI3K抑制剂的疗效往往受到以下因素的限制 临床试验中的剂量限制毒性。因此，异构体特异性的PI3K抑制剂具有极大的兴趣 靶向抑制，耐受性提高。开发PI3K抑制剂的一个主要挑战是 确定哪些患者可能从这些药物中获益最多，以及哪些患者使用同工型特异性抑制剂 都是合适的。临床试验主要集中在有限的标志物上，包括PIK3CA突变和PTEN状态， 这并不能始终如一地预测反应。深入的生物标记物研究是必要的，但在 由于研究材料的数量和质量以及无法获得连续肿瘤而导致的临床试验安排 病人的活组织检查。相比之下，患者来源的异种移植(PDX)模型提供了几乎无限的肿瘤 用于生物标记物开发和治疗前后深入基因蛋白质组学分析的资源 合理用药组合耐药机制的确定。我们假设乳腺癌 PAN和异构体特异性PI3K抑制剂的PDX试验，将区分个体肿瘤对异构体的依赖 得出预测性生物标记物。我们将使用Copanlisib，一种有效的PAN-PI3K抑制剂，具有抗肿瘤活性 主要是PI3Kα与PI3Kβ，以及特定的PI3Kβ抑制剂AZD8186，这两种药物都在NCI-IND中 公文包。此外，基于文献证据和我们对丁帕利西布的PDX试验的初步数据，我们 假设加入MEK抑制剂selumetinib，也是NCI Ind药剂，将改善对 基于文献证据的Copanlisib和/或AZD8186以及我们观察到的协同抗肿瘤作用 当在我们的乳腺癌PDX模型中联合使用PAN-PI3K抑制剂和MEK抑制剂时。 AIM 1将进行PDX试验。100个ER+HER2-和TNBC亚型组成的乳腺癌PDX模型 将根据传代次数、基因组稳定性和肿瘤来选择来自PDX核心的可用药 特点。为了丰富目标人群，至少30个携带PIK3CA突变的PDX模型和至少 这项PDX试验将包括30个PTEN缺失表型的PDX模型。每个PDX型号都将通过 将12只免疫缺陷小鼠随机分为6个治疗组(每组2只)，分别接受 任何一种赋形剂、科帕利西布、AZD8186、赛鲁马替尼、科帕利西布+赛鲁米替尼或AZD8186+赛鲁米替尼。几个 肿瘤反应标准将用于对S治疗敏感和耐药的分类。这些措施包括 最近发表的mRECIST标准和传统的肿瘤生长抑制%，包括一种载体 治疗组。目标2将确定候选的和新的基因蛋白质组对每个单独的药物的反应预测因子 或通过分析全球基因组数据(整个外显子组和RNA序列)和蛋白质组数据进行联合治疗 由多激酶抑制物珠质谱(MIB-MS)生成，用于无偏见地发现候选 生物标志物。分析将包括重点识别不同的、差异表达的生物标志物 敏感和耐药肿瘤。AIM 3将对治疗后样本进行动态组分析(MIB-MS)以评估 药物诱导的信号变化，以辨别研究治疗的作用机制并确定 内在的和治疗诱导的适应性生存机制。 该项目将得到数据收集委员会为收集数据而建立的基础设施的支持，包括 药物治疗后，小鼠的耐受性和肿瘤体积会随时间发生变化。此外，生物信息学能力 将利用WU-PDTC提供的试译和基因蛋白质组分析来推导出 预测对PI3K抑制剂的反应和耐药机制。此外，项目1的团队成员 将定期与项目2的团队成员进行信息交流，以改进研究方法 和成果分享。本研究的长期目标是建立一个标准化的PDX试验平台，以确定 有希望的药物(S)和生物标志物对用于临床试验。