Molecular origins and evolution to treatment resistance in genitourinary cancers

项目总结 在单位主任埃利泽·范·艾伦博士的领导下，范·艾伦实验室的NCI资助了研究项目 研究泌尿生殖(GU)癌(前列腺癌、膀胱癌、肾癌、睾丸癌)，重点了解治疗方法 通过综合计算和分子方法在这些疾病中的抗药性 耐心体验。凭借她的多学科培训和协作领导，研究专家Jihye博士 帕克一直是这些研究项目不可或缺的一部分，为各种发现和小说做出了贡献 计算方法。我们的研究计划导致了选择性的分子基础的发现 膀胱癌和睾丸癌的化疗敏感性和雄激素抑制药耐药性的生物学理解 前列腺癌，创造了新的药物发现范例和患者分层方法。我们还开发了 发现与治疗相关的相互作用的综合计算和实验方法 肿瘤、生殖系和免疫轴的耐药性与我们以患者为中心的研究范式在胃腺癌中的应用。 此外，我们在实体瘤中直接发现了决定癌症免疫治疗的肿瘤内在因素。 染色质失调是选择性免疫治疗反应的一个原因，并形成了 药物开发和治疗组合的新文件。尽管取得了这些进展，但大多数患者 晚期GU癌症仍然对治疗产生抵抗，并存在生物学相关性和相互作用 这些癌症中特定的生殖系、体细胞或免疫系统在很大程度上仍不清楚。此外，我们面临着 处理海量新类型数据以高效分析的计算挑战。朴医生现在是 领导利用以患者为中心的综合方法，特别是纵向单一细胞的努力 肿瘤的转录和全基因组及表观遗传学特征，以了解其生物学基础 分子敏化与肿瘤进化的观点，并确定驱动致死的范例 Gu癌的免疫耐药疾病。朴博士还将为发展 全面、可扩展的分析工具，可以集成多个组学数据并研究系统级别 生殖系、体细胞和免疫系统之间的相互作用。这些方法将在 开放基于云的平台(Terra)并扩大癌症社区内的合作。总体而言，朴医生的 最近和正在进行的贡献旨在揭示导致谷氨酸致死性疾病的综合分子因素。 并阐明这些过程的生物学过程，从而转化为有效的治疗和患者 分层模式和利用尖端技术的综合计算方法的更广泛可获得性 分子图谱的方法。在单位主任埃利泽·范·艾伦博士的领导下，朴博士的科学和 计算工作将继续建立一个跨学科的、与科学家高度合作的小组 来自不同的科学领域，推动了这些全面的临床计算研究计划。 1

PROJECT SUMMARY Under Unit Director Dr. Eliezer Van Allen's leadership, the Van Allen laboratory's NCI funded research programs study genitourinary (GU) cancers (prostate, bladder, kidney, testes), with a focus on understanding treatment resistance in these diseases through integrative computational and molecular approaches grounded in the patient experience. With her multidisciplinary training and collaborative leadership, Research Specialist Dr. Jihye Park has been an integral part of these research programs contributing to various discovery and novel computational methods. Our research programs led to the discovery of the molecular basis of selective chemosensitivity in bladder and testes cancers, and biological understanding of androgen inhibitor resistance in prostate cancer, creating new drug discovery paradigms and means of patient stratification. We also developed integrative computational and experimental approaches to discover the interaction relevant to treatment resistance across the tumor, germline, and immune axes with our patient-centered paradigm in GU cancers. Furthermore, we discovered tumor-intrinsic factors determining cancer immunotherapy in solid tumors, directly invoking chromatin dysregulation as a cause of selective immunotherapy response and forming the basis for new files of drug development and therapeutic combinations. Despite these advances, the majority of patients with advanced GU cancers still experience resistance to therapies and the biological relevance and interplay of specific germline, somatic, or immune systems in these cancers are still largely unknown. Furthermore, we face computational challenges to handle vast amounts of new types of data to analyze efficiently. Dr. Park is now leading the effort to utilize integrated patient-centered approaches, specifically longitudinal single cell transcriptional and whole genome and epigenetic characterization of tumors, to understand the biological basis of molecular sensitization with tumor evolution perspectives and determine the paradigms that drive lethal immunotherapy resistant disease in GU cancers. Dr. Park will also contribute to the development of comprehensive and scalable analytic tools that can integrate multi-omics data and study systems level interactions between germline, somatic, and immune systems. These methods will be implemented within an open cloud-based platform (Terra) and amplify collaborations within the cancer community. Overall, Dr. Park's recent and ongoing contributions aim to reveal the integrated molecular factors that drive lethal disease in GU cancers and elucidate the biology of these processes, toward translation of effective therapeutic and patient stratification modalities, and broader accessibility of comprehensive computational methods utilizing cutting edge molecular profiling approaches. With Unit Director Dr. Eliezer Van Allen, Dr. Park's leadership and scientific and computational efforts will continue to establish an interdisciplinary and highly collaborative group with scientists from diverse scientific domains driving these comprehensive clinical computational research programs. 1