Identifying Malignant Cell Signaling from Protein Interactions an Polyomic Data

描述（由申请人提供）：拟议的奖励计划结合了教学培训和实践研究，以补充Fertig博士在约翰霍普金斯肿瘤生物统计学的博士后经验，并具有生物学熟练程度，补充了她的数学背景。此外，这项培训将使Fertig博士能够在她未来作为一名独立的计算肿瘤学家的职业生涯中追求相关的研究问题和富有成效的多学科合作。该提案的主要重点是开发肿瘤发展和维持的生物过程的定量模型。约翰霍普金斯大学肿瘤生物统计学博士Michael Ochs和头颈部研究医学博士Joseph Califano将促进Fertig博士提出的培训和实践研究，包括分别为计算生物学中的统计方法和头颈癌的生物学和临床治疗提供见解。Fertig博士将运用她在将动态模型与数值天气预报的间接测量结果相结合方面的经验，从患者测量结果中推断相关的生物过程。在导师的支持下，她将开发算法来推断个体患者肿瘤中潜在的恶性肿瘤的驱动过程。在提出的技术中，Fertig博士将通过整合基因表达测量与表观遗传测量，EGFR蛋白质-蛋白质相互作用网络结构和治疗策略来推断恶性过程下游头颈癌中的转录因子活性。通过合并这些不同的数据源，假设该工具具有统计能力，可以准确表示头颈癌中建模过程产生的特定转录因子激活的概率，这将通过靶向细胞系实验进一步验证。因此，这项研究将开发工具，当迁移到诊所时，将帮助临床医生确定治疗个体癌症的靶向治疗的适当选择。 公共卫生相关性：项目叙述尽管采用联合治疗方式，晚期头颈部肿瘤的治愈率仍为50%。该项目将生物结构与头颈部肿瘤测量相结合，以确定驱动个体肿瘤发展的特定途径，从而评估该患者的个性化治疗计划。尽管应用于头颈部癌症，但开发的工具将具有广泛的临床意义。

DESCRIPTION (provided by applicant): The proposed award plan combines didactic training and hands-on research to supplement Dr. Fertig's postdoctoral experience in Johns Hopkins Oncology Biostatistics with biological proficiency, complementing her mathematical background. Moreover, this training will enable Dr. Fertig to pursue pertinent research questions and fruitful, multi- disciplinary collaborations in her future career as an independent computational oncologist. The primary focus of this proposal is the development of quantitative models of the biological processes underlying the development and maintenance of tumors Mentors Michael Ochs, PhD of Oncology Biostatistics, and Joseph Califano, MD of Head and Neck Research, at Johns Hopkins will foster Dr. Fertig's proposed training and hands-on research, including providing insight to statistical methods in computational biology and to the biology and clinical treatment of head and neck cancer respectively. Dr. Fertig will apply her experience in merging dynamic models with indirect measurements from Numerical Weather Prediction to inferring relevant biological processes from patient measurements. With the support of her mentors, she will develop algorithms that infer driver processes underlying malignancies in an individual patient's tumor. In the proposed techniques, Dr. Fertig will infer transcription factor activity in head and neck cancer downstream of the malignant processes by integrating gene expression measurements with epigenetic measurements, EGFR protein-protein interaction network structure, and therapeutic strategy. By merging these diverse data sources, this tool is hypothesized to have the statistical power to accurately represent the probability of activation of specific transcription factors resulting from the modeled processes in head and neck cancer, which will be further validated through targeted cell line experiments. Thus, this research will develop tools that, when migrated to the clinic, will assist clinicians in identifying the appropriate choice of targeted therapeutics to treat an individual's cancer. PUBLIC HEALTH RELEVANCE: Project Narrative Advanced head and neck tumors have a 50% cure rate in spite of combined treatment modalities. This project will merge biological structure with head and neck tumor measurements to pinpoint specific pathways that drive individual tumor development, and thus assess personalized treatment plans for that patient. Although applied to head and neck cancers, the developed tools will have broad clinical implications.