Patient-Derived Models of Prostate Cancer for Personalized Medicine

用于个体化医疗的前列腺癌患者衍生模型

• 批准号: 10683753
• 负责人: Yu Chen
• 金额: $ 100.55万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10683753
• 关键词: Address; Androgen Receptor; Area; Biological; Biological Models; Cancer Model; Cells; Clinical; Clinical Research; Clinical Trials; Complement; Critical Pathways; DNA Damage; DNA Sequence Alteration; Databases; Development; Distant; Evolution; Gene Expression; Gene Modified; Genes; Genetic; Genetic study; Genomics; Goals; Growth; Human; Invaded; Investigation; Knowledge; Link; Longitudinal Studies; Malignant Bone Neoplasm; Malignant Neoplasms; Malignant neoplasm of prostate; Metastatic Prostate Cancer; Modeling; Molecular; Morphology; Mutation; Neoplasm Metastasis; Organoids; PIK3CG gene; Pathologic; Pathologist; Pathway interactions; Patients; Pharmaceutical Preparations; Physicians; Poly(ADP-ribose) Polymerase Inhibitor; Research Personnel; Resistance; Role; Sampling; Scientist; Seminal; Signal Transduction; Site; Specimen; Testing; Therapeutic; Time; Tissues; Variant; androgen deprivation therapy; cancer genomics; castration resistant prostate cancer; clinically relevant; design; drug testing; effective therapy; enzalutamide; epigenomics; exome sequencing; genome sequencing; human tissue; improved; inhibitor; insight; men; migration; patient derived xenograft model; personalized medicine; pre-clinical; prostate cancer model; prostate cancer progression; resistance mechanism; response; success; targeted treatment; therapy development; therapy resistant; transcriptome sequencing; treatment response; treatment strategy; tumor; whole genome

PROJECT SUMMARY/ABSTRACT Metastatic prostate cancer (PCa) that progresses after androgen ablation therapy (i.e., castration-resistant PCa [CRPC]) remains incurable. Gaining a mechanistic understanding of PCa progression has been hampered by a lack of clinically relevant PCa models. Recently, patient-derived models of cancer (PDMCs; e.g., patient-derived xenografts [PDXs] and organoids) have been used to develop therapeutically relevant approaches. We hypothesize that longitudinal studies of tumor specimens (and corresponding PDMCs) obtained over time from the same patient will lead to a better understanding of the diverse dominant pathways that drive metastatic progression. We also hypothesize that organoids will complement PDXs as part of an integrated analysis of human tissue and derived PDMCs (obtained at single time points) to understand the mechanisms of response and resistance to target pathways commonly activated in CRPC. We will test these hypotheses through the following specific aims: Aim 1. Analyze human donor tumors and corresponding PDMCs to identify dominant molecular alterations that drive PCa progression and select models to study. We will develop PDMCs from clinically annotated tumor specimens derived from men with potentially lethal PCa, including PDMCs derived from tumor specimens obtained at different times during progression (longitudinal studies) and from different areas of the same tumor. We will assess human PCa specimens and PDMCs’ morphology and expression of genes associated with PCa progression and subject them to whole-exome sequencing and RNA sequencing. PCa specimens and PDMCs derived from the longitudinal studies will also be subjected to whole-genome sequencing and epigenomic analysis. Finally, we will develop a publicly available interactive database linking molecular and preclinical results of PDMC characterization with clinical and molecular details of donor human PCa. These studies' findings will serve as the basis for the identification and prioritization of aberrant molecular pathways for further study. This knowledge is also essential to understanding how each PDMC provides information about the alterations in human donor tumor. Aim 2. Study genomic alterations acquired in metastasis specimens in the longitudinal studies for their potential to confer metastatic ability to cells. We will genetically modify organoids to create the genomic alterations found in the metastases. We will subsequently study how the genetic modification of these genes influences specific steps involved in metastasis, namely invasion, migration, and ability to grow at distant sites. Aim 3. Utilize PDMCs to study mechanisms of PCa response/resistance to targeted therapies on pathways implicated in PCa progression. We will seek a mechanistic understanding of PCa response and/or resistance to therapies in clinical trials targeting the AR, DNA damage response, Wnt-canonical, and PI3K pathways. These studies will inform the discovery and elucidation of resistance mechanisms, the development of effective therapies and will provide insights into the roles of PDMCs as model systems for studying signaling and therapeutic response.

项目摘要/摘要 雄激素消融治疗后进展的转移性前列腺癌(即耐去势前列腺癌) PCA[CRPC])仍然无法治愈。获得对主成分分析进展的机械理解一直是 由于缺乏临床相关的PCA模型而受到阻碍。最近，患者衍生的癌症模型(PDMCs； 例如，患者来源的异种移植物[PDX]和有机化合物)已被用于开发与治疗相关的 接近了。我们假设对肿瘤标本(和相应的PDMC)的纵向研究 随着时间的推移，从同一患者那里获得的信息将有助于更好地理解不同的优势通路 这推动了转移的进展。我们还假设有机化合物将补充PDX作为 对人体组织和衍生的PDMCs(在单个时间点获得)进行综合分析，以了解 CRPC中常见的对靶通路的反应和抵抗机制。我们将测试这些 假设通过以下具体目标：目的1.分析人类供体肿瘤和相应的 PDMC，以确定驱动前列腺癌进展的主导分子变化，并选择模型进行研究。我们 将从患有潜在致命性前列腺癌的男性患者的临床注释肿瘤标本中培养出PDMC， 包括从进展过程中不同时间(纵向)获得的肿瘤标本中提取的PDMC 研究)以及来自同一肿瘤的不同区域。我们将评估人类前列腺癌标本和PDMC的 前列腺癌进展相关基因的形态和表达及其与完整外显子组的关系 测序和RNA测序。来自纵向研究的PCA标本和PDMC也将 进行全基因组测序和表观基因组分析。最后，我们将制定一个公开的 可用的交互式数据库将PDMC表征的分子和临床前结果与临床联系起来 以及捐献者人类前列腺癌的分子细节。这些研究的发现将作为鉴定的基础 以及为进一步研究确定异常分子途径的优先顺序。这方面的知识对 了解每个PDMC如何提供有关人类供体肿瘤变化的信息。目标2. 在纵向研究中研究在转移标本中获得的基因组改变的可能性 赋予细胞转移能力。我们将对有机化合物进行基因改造，以创造出在 转移瘤。我们随后将研究这些基因的遗传修饰如何影响特定的 参与转移的步骤，即侵袭、迁移和在远处部位生长的能力。目标3.利用 PDMCs研究PCa反应/耐受靶向治疗途径与PCa的关系 进步。我们将寻求对PCa反应和/或治疗抵抗的机制理解 针对AR、DNA损伤反应、Wnt-Canonical和PI3K通路的临床试验。这些研究将 告知耐药机制的发现和阐明，有效治疗方法的发展和意志 提供对PDMCs作为研究信号和治疗反应的模型系统的作用的见解。

项目成果

Distinct mechanisms for TMPRSS2 expression explain organ-specific inhibition of SARS-CoV-2 infection by enzalutamide.

• DOI: 10.1038/s41467-021-21171-x
• 发表时间: 2021-02-08
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Li F;Han M;Dai P;Xu W;He J;Tao X;Wu Y;Tong X;Xia X;Guo W;Zhou Y;Li Y;Zhu Y;Zhang X;Liu Z;Aji R;Cai X;Li Y;Qu D;Chen Y;Jiang S;Wang Q;Ji H;Xie Y;Sun Y;Lu L;Gao D
• 通讯作者: Gao D