BCCMA: Overcoming chemoresistance in ovarian cancer: Identification and validation of biomarkers and targetable drivers of platinum resistance

BCCMA：克服卵巢癌的化疗耐药性：铂类耐药的生物标志物和靶向驱动因素的识别和验证

• 批准号: 10585641
• 负责人: SANDRA ORSULIC
• 金额: --
• 依托单位: VA GREATER LOS ANGELES HEALTHCARE SYSTEM
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10585641
• 关键词: ASF1A gene; Address; Apoptosis; Architecture; Area; Autophagocytosis; Award; Biological Assay; Biological Markers; Biological Models; Cancer Patient; Cancer cell line; Catalytic Domain; Cause of Death; Cell Line; Cells; Cellular biology; Cessation of life; Characteristics; Chemoresistance; Chromatin; Chromosome Mapping; Clinical; Clinical Data; Clinical Management; Coculture Techniques; Collaborations; DNA Repair Pathway; Data; Data Set; Databases; Dependence; Development; Diagnosis; Disease Resistance; Drug Addiction; Drug Compounding; Drug Screening; Drug Targeting; Evaluation; Event; Experimental Models; Fatal Outcome; Fibroblasts; Gene Expression; Genes; Glycolysis; Goals; Histologic; Histopathology; Hypoxia; Image; Image Analysis; Imaging Device; Immunocompetent; Knowledge; Link; Malignant Epithelial Cell; Malignant Neoplasms; Malignant neoplasm of ovary; Maps; Membrane Lipids; Membrane Transport Proteins; Metabolic; Metabolism; Methods; Modeling; Molecular; Molecular Analysis; Molecular Profiling; Morphology; Multiomic Data; Mus; Mutate; NUAK1 gene; Nature; Necrosis; Neuroendocrine Cell; Neurosecretory Systems; Nuclear; Organoids; Ovarian Serous Adenocarcinoma; Pathologist; Pathology; Pathway interactions; Patient Care; Patients; Peptides; Pharmaceutical Preparations; Phenotype; Platinum; Population; Predisposition; Primary Neoplasm; Proteome; Quality of life; Recurrence; Recurrent disease; Research; Research Personnel; Resistance; Resource Sharing; Resources; Role; Sampling; Serous; Slide; Systems Biology; Technology; Testing; Therapeutic; Tissues; Treatment Efficacy; Tumor Debulking; Validation; Veterans; Woman; Xenograft Model; bioinformatics tool; biomarker development; biomarker driven; biomarker identification; biomarker validation; cancer cell; cancer therapy; chemotherapy; chromatin remodeling; clinically relevant; data integration; data modeling; digital; drug sensitivity; druggable target; efficacy testing; fatty acid oxidation; genetic signature; improved; inhibitor; metabolic abnormality assessment; metabolic imaging; mouse model; multidisciplinary; multiple omics; neoplastic cell; neuroendocrine differentiation; neuroendocrine phenotype; new therapeutic target; novel; novel strategies; novel therapeutic intervention; ovarian neoplasm; oxidized lipid; patient derived xenograft model; personalized medicine; pre-clinical; pressure; prevent; protein expression; refractory cancer; resistance mechanism; spectroscopic imaging; standard care; stem cell biomarkers; stemness; targeted agent; targeted treatment; therapeutic biomarker; therapeutic target; therapy resistant; transcriptome; treatment strategy; tumor; tumor microenvironment

This Collaborative Merit Award application (CMA), consisting of three projects (CMA1-3), addresses a critical challenge in the clinical management of ovarian cancer (OC). The most common and lethal subtype of OC is high-grade serous ovarian carcinoma (HGSOC). Standard treatment for HGSOC combines surgical cytoreduction with platinum-based chemotherapy. Patients diagnosed with HGSOC often suffer from disease relapse associated with the emergence of chemotherapy resistance. The clinically necessary key to increasing survival in HGSOC is to prevent the development of platinum resistance (PtR) or identify alternative means of targeting PtR tumors. The main goal of this interdisciplinary and collaborative project is to identify novel targets and biomarkers of therapeutic efficacy for HGSOC. This requires a better understanding of the mechanisms that result in transformation of HGSOC cells to an aggressive, therapy-resistant phenotype. Increasing evidence supports the hypothesis that a key contributor to PtR is the reprogramming of cancer cells into a less differentiated and metabolically adaptable state. This collaborative proposal by three established OC researchers will leverage their interdisciplinary expertise and rich resources to define new mechanisms of resistance in OC. CMA1 will use digital spatial profiling and systems biology to provide a holistic understanding of PtR as well as prioritize cell-intrinsic and microenvironmental clinically relevant underlying molecular pathways. Unique preclinical immunocompetent mouse models and co-culture models will be used to study the role of the tumor microenvironment in PtR. CMA2 will study metabolic adaptation associated with the emergence of PtR focusing on a shift to fatty acid oxidation in PtR HGSOC tumors. CMA2 will use resources shared with CMA1&3 and cellular biology and novel single cell metabolic imaging to define unique metabolic dependencies of PtR HGSOC. As PtR tumors are highly susceptible to death induced by oxidized lipid membranes, mechanisms of ferroptosis will be examined in PtR models treated with novel metabolism targeting agents, which will be tested with CMA1. CMA3 will explore the reprogramming of recurrent HGSOC cells into more dedifferentiated tumor subpopulations with neuroendocrine (NE)-like features. Mounting evidence in other tumors suggest progression to a NE-like state results in therapy resistance - a concept yet to be explored in OC. To identify NE-like cells in OC, the transcriptome, proteome, gene vulnerability, and drug sensitivity landscape of matched patient tumors and model systems will be evaluated for the emergence of NE-like cells under chemotherapeutic pressures. Existing drug dependency databases will be mined for identification of druggable targets in NE-like cells. Drugs effective against these cells will be tested alone or in combination as targeted therapy for PtR OCs utilizing patient derived organoid and xenograft models. Hallmarks of NE-like cells including metabolic adaptations and histologic characteristics will be explored with CMA2 & CMA1 respectively. CMA1 rationale: The evaluation of histopathology slides is the main method to establish a HGSOC diagnosis and guide treatment decisions. However, the rich data embedded within histopathology slides have not been fully exploited to understand the underlying causes of PtR and develop personalized treatment strategies. Prior research on PtR mostly used cancer cell lines and focused on cell-intrinsic events. However, data from clinical samples suggest that the tissue microenvironment (TME) is a major driver of PtR. Specifically, cancer- associated fibroblasts (CAFs) were shown to induce PtR in adjacent cancer cells. We hypothesize that higher- order features extracted from pathology slide images are associated with distinct molecular profiles, such as specific gene and protein expression, metabolism, and sensitivity to specific drugs. We will combine spatial image profiling with assays in mouse models and CAF/cancer cell co-cultures to mechanistically dissect the role of the TME in PtR. The integration of image data from patient slides with other -omics data will add a key layer of information to prioritize biologically- and clinically-relevant biomarkers and drivers of PtR.

此协作优秀奖申请(CMA)由三个项目(CMA1-3)组成，解决了一个关键问题 卵巢癌(OC)临床治疗的挑战。OC最常见和最致命的亚型是 高度浆液性卵巢癌(HGSOC)。HGSOC合并外科手术的标准治疗 以铂为基础的化疗使细胞减少。被诊断为HGSOC的患者通常患有 复发与化疗耐药的出现有关。临床上必要的增加的关键 在HGSOC中生存的目的是防止铂耐药(PTR)的发展或寻找替代方法 靶向PTR肿瘤。这一跨学科协作项目的主要目标是确定新的目标。 以及HGSOC治疗效果的生物标志物。这需要更好地理解 导致HGSOC细胞转化为侵袭性、耐药表型。越来越多的证据 支持这样一种假设，即PTR的关键因素是癌细胞重新编程为较少的 分化和新陈代谢适应状态。这份由三位成熟的OC研究人员共同提出的建议 将利用他们的跨学科专业知识和丰富的资源来定义新的阻力机制 OC。CMA1将使用数字空间剖面图和系统生物学来提供对PTR的整体理解 作为优先考虑细胞固有的和微环境临床相关的潜在分子途径。独一无二 临床前免疫活性小鼠模型和共培养模型将用于研究肿瘤的作用 PTR中的微环境。CMA2将研究与PTR聚焦出现相关的代谢适应 关于PTR HGSOC肿瘤向脂肪酸氧化的转变。CMA2将使用与CMA1和3共享的资源，并且 细胞生物学和新的单细胞代谢成像以确定PTR HGSOC的独特代谢依赖性。 由于PTR肿瘤非常容易被氧化的脂膜诱导死亡，因此铁性下垂的机制 将在使用新型新陈代谢靶向药物治疗的PTR模型中进行检查，这将进行测试 使用CMA1。CMA3将探索复发的HGSOC细胞重新编程为更多去分化的肿瘤 具有神经内分泌(NE)样特征的亚群。在其他肿瘤中越来越多的证据表明进展 去甲肾上腺素状态会导致治疗抵抗--这是OC尚未探索的一个概念。鉴定中的NE样细胞 OC、转录组、蛋白质组、基因脆弱性和匹配患者肿瘤的药物敏感性 模型系统将在化疗压力下评估NE样细胞的出现。 将挖掘现有的药物依赖数据库，以识别NE样细胞中的可药物靶点。毒品 针对这些细胞的有效性将作为PTR OCS的靶向治疗单独或联合进行测试 患者衍生的器官和异种移植模型。NE样细胞的特征包括代谢适应和 组织学特征将分别用CMA2和CMA1进行检测。 CMA1原理：组织病理学切片评估是建立HGSOC诊断的主要方法 并指导治疗决策。然而，组织病理学幻灯片中嵌入的丰富数据尚未 充分利用以了解PTR的根本原因并制定个性化治疗策略。之前 对PTR的研究主要使用癌细胞系，并集中在细胞内在事件上。然而，来自临床的数据 样本表明，组织微环境(TME)是PTR的主要驱动因素。具体来说，癌症- 相关的成纤维细胞(CAF)被证明在邻近的癌细胞中诱导PTR。我们假设更高的- 从病理切片图像中提取的顺序特征与不同的分子特征相关联，例如 特定的基因和蛋白质的表达、新陈代谢和对特定药物的敏感性。我们将结合空间 在小鼠模型和CAF/癌细胞共培养中进行图像分析以机械地解剖 TME在PTR中的作用。来自患者幻灯片的图像数据与其他组学数据的集成将增加一个关键 确定PTR的生物和临床相关生物标记物和驱动因素的优先顺序的信息层。