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教学培训和实践研究，以生物学熟练程度补充Fertig博士在约翰霍普金斯大学肿瘤生物统计学方面的博士后经验，补充她的数学背景。此外，这种培训将使费尔蒂希博士能够在她未来的独立计算肿瘤学家职业生涯中寻求相关的研究问题和富有成效的多学科合作。这项建议的主要重点是开发支持肿瘤发展和维持的生物过程的量化模型。约翰霍普金斯大学肿瘤学生物统计学博士迈克尔·奥克斯和头颈研究医学博士约瑟夫·卡利法诺的导师将促进费尔蒂希博士拟议的培训和实践研究，包括提供对计算生物学中的统计方法以及头颈部癌症的生物学和临床治疗的洞察力。费尔蒂希博士将运用她在将动态模型与数值天气预报的间接测量相结合方面的经验，从患者的测量数据中推断相关的生物过程。在导师的支持下，她将开发出推断个体患者肿瘤潜在恶性肿瘤的驱动程序的算法。在拟议的技术中，Fertig博士将通过将基因表达测量与表观遗传学测量、EGFR蛋白质-蛋白质相互作用网络结构和治疗策略相结合，来推断头颈部癌症恶性过程下游的转录因子活性。通过合并这些不同的数据源，这个工具被假设具有统计能力，准确地表示头颈癌建模过程中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，当移植到临床时，将帮助临床医生确定适当的靶向治疗选择来治疗个人的癌症。 公共卫生相关性：尽管综合治疗方式，晚期头颈部肿瘤仍有50%的治愈率。该项目将把生物结构与头颈部肿瘤的测量相结合，以确定驱动单个肿瘤发展的特定路径，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.