Determinants of signaling network regulation in combinatorial targeted therapies

组合靶向治疗中信号网络调节的决定因素

• 批准号: 7780328
• 负责人: PRAHLAD T RAM
• 金额: $ 34.93万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-16 至 2012-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7780328
• 关键词: Address; Breast Cancer Cell; Bypass; Cell Death Inhibition; Cell Line; Cell Proliferation; Complex; Computer Simulation; Coupled; Cues; Data; Development; Disease Management; Drug Combinations; Drug Delivery Systems; Epidermal Growth Factor Receptor; Failure; Feedback; Future; Goals; Growth; In Vitro; Individual; Knowledge; MAP Kinase Gene; MEKs; Malignant Neoplasms; Mediating; Molecular; Mus; Outcome; Pathway interactions; Patient Rights; Patients; Pharmaceutical Preparations; Proliferating; Proteins; Proteomics; Proto-Oncogene Proteins c-akt; Publishing; Regulation; Resistance; Route; Signal Transduction; Signal Transduction Pathway; Signaling Molecule; Site; System; Systems Biology; Technology; Testing; Work; base; cancer cell; cancer therapy; clinical application; combinatorial; design; improved; in vivo; lapatinib; malignant breast neoplasm; neoplastic cell; network models; novel strategies; patient population; public health relevance; response; therapeutic target; tumor; tumor growth; tumor xenograft

DESCRIPTION (provided by applicant): Clinical application of molecular therapeutics targeting signaling molecules holds tremendous promise for the management of patients with cancer. Within the cell, signals are routed through specific signal transduction pathways, many of which can interact to form networks. Targeting a node or molecule within this network can be challenging since signals can bypass the inhibition and continue to propagate. One of the challenges in the use of targeted therapeutics to inhibit cancer cell proliferation is to understand how signal flows through the network and what combination of molecules have to be blocked in order to effectively inhibit proliferation. My long-term goal is to understand the systems function of signaling networks in cancer and utilize this knowledge to develop and implement novel approaches to patient management. The objectives of this application are to determine the regulators of the EGFR signaling network in breast cancer to identify optimal combinations of targets for therapy, and to determine how differences in activity of regulatory molecules and homeostatic loops alters response to targeted therapies. We will integrate existing proteomic and computational modeling technology to address these important issues in the use of combination targeted therapy for cancer. Aim 1. Determine rational approaches to targeting the EGFR signaling network in lapatinib resistant breast cancer cells. Aim 2. Determine approaches to target regulatory molecules defining EGFR/AKT/MAPK network function in human breast cancer cells. Aim 3. Determine the response to rational combinatorial targeted therapy of the EGFR/MAPK/AKT network on cell proliferation and tumor growth. These aims will be addressed using a systems biology approach using experimental data from cell lines, functional proteomics and xenograft tumors in mice, integrated with computational modeling of the signaling network. PUBLIC HEALTH RELEVANCE: The treatment and management of patients with cancer is entering a new and very exciting era. New drugs that target specific proteins are showing tremendous promise if they are given to the right patients. In this proposal we will determine what combinations of these new drugs work best for different tumors based on the aberrations within the cancer cells. With the idea being that different tumors will need a different combination of drugs and in the future we can give specific combinations of drugs to different individuals.

描述（由申请人提供）：针对信号分子的分子疗法的临床应用为癌症患者的治疗带来了巨大的希望。在细胞内，信号通过特定的信号转导途径传递，其中许多信号转导途径可以相互作用形成网络。瞄准该网络内的节点或分子可能具有挑战性，因为信号可以绕过抑制并继续传播。使用靶向疗法抑制癌细胞增殖的挑战之一是了解信号如何流过网络以及必须阻断哪些分子组合才能有效抑制增殖。我的长期目标是了解癌症信号网络的系统功能，并利用这些知识开发和实施新的患者管理方法。本申请的目的是确定乳腺癌中 EGFR 信号网络的调节因子，以确定治疗靶点的最佳组合，并确定调节分子和稳态环的活性差异如何改变对靶向治疗的反应。我们将整合现有的蛋白质组学和计算建模技术来解决癌症联合靶向治疗中的这些重要问题。目标 1. 确定靶向拉帕替尼耐药乳腺癌细胞中 EGFR 信号网络的合理方法。目标 2. 确定靶向调节分子的方法，这些调节分子定义了人类乳腺癌细胞中的 EGFR/AKT/MAPK 网络功能。目标 3. 确定 EGFR/MAPK/AKT 网络合理组合靶向治疗对细胞增殖和肿瘤生长的反应。这些目标将通过系统生物学方法来解决，该方法使用来自小鼠细胞系、功能蛋白质组学和异种移植肿瘤的实验数据，并与信号网络的计算模型相结合。公共卫生相关性：癌症患者的治疗和管理正在进入一个令人兴奋的新时代。如果给予正确的患者，针对特定蛋白质的新药将显示出巨大的前景。在这项提案中，我们将根据癌细胞内的畸变确定这些新药的哪些组合对不同的肿瘤最有效。我们的想法是，不同的肿瘤需要不同的药物组合，将来我们可以为不同的个体提供特定的药物组合。

项目成果

The glucose-deprivation network counteracts lapatinib-induced toxicity in resistant ErbB2-positive breast cancer cells.

葡萄糖剥夺网络可以抵消拉帕替尼诱导的耐药性 ErbB2 阳性乳腺癌细胞的毒性。

• 发表时间: 2012
• 影响因子: 9.9
• 作者: Komurov, Kakajan;Tseng, Jen;Muller, Melissa;Seviour, Elena G;Moss, Tyler J;Yang, Lifeng;Nagrath, Deepak;Ram, Prahlad T
• 通讯作者: Ram, Prahlad T