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.

项目总结/摘要 雄激素消融治疗后进展的转移性前列腺癌（PCa）（即，去势抵抗 PCa [CRPC]）仍然无法治愈。获得对PCa进展的机制性理解， 由于缺乏临床相关的PCa模型而受到阻碍。最近，患者来源的癌症模型（PDMC; 例如，在一个实施例中，患者来源的异种移植物[PDX]和类器官）已用于开发治疗相关的 接近。我们假设肿瘤标本（和相应的PDMC）的纵向研究 随着时间的推移，从同一患者获得的信息将有助于更好地了解不同的主导途径， 导致转移性进展。我们还假设类器官将补充PDX，作为 人组织和衍生的PDMC（在单个时间点获得）的综合分析，以了解 对CRPC中通常激活的靶向通路的应答和耐药机制。我们将测试这些 通过以下具体目标的假设：目标1。分析人类供体肿瘤和相应的 PDMC用于识别驱动PCa进展的显性分子改变并选择模型进行研究。我们 将从来自患有潜在致命PCa的男性的临床注释肿瘤标本中开发PDMC， 包括来源于在进展期间的不同时间获得的肿瘤样本的PDMC（纵向 研究）和来自同一肿瘤的不同区域。我们将评估人类PCa标本和PDMC的 形态学和表达与PCa进展相关的基因，并将它们置于全外显子组 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 将PDMC表征的分子和临床前结果与临床 以及供体人前列腺癌的分子细节这些研究的结果将作为确定 并对异常分子途径进行优先排序以供进一步研究。这些知识也是必不可少的， 了解每个PDMC如何提供有关人类供体肿瘤变化的信息。目标二。 在纵向研究中研究转移标本中获得的基因组改变， 赋予细胞转移能力。我们将对类器官进行遗传修饰，以产生在 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 涉及转移的步骤，即侵袭、迁移和在远处生长的能力。目标3.利用 PDMC用于研究PCa对涉及PCa的途径的靶向治疗的反应/抗性机制 进展我们将寻求一个机制的理解PCa反应和/或耐药性的治疗， 靶向AR、DNA损伤反应、Wnt-经典和PI 3 K途径的临床试验。这些研究将 为发现和阐明耐药机制、开发有效疗法提供信息， 提供PDMC作为研究信号传导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