Multi-omic Predictive Markers for Ovarian Cancer Therapy Response and Outcomes

卵巢癌治疗反应和结果的多组学预测标记

• 批准号: 10678828
• 负责人: FRANCESMARY MODUGNO
• 金额: $ 14.63万
• 依托单位: MAGEE-WOMEN'S RES INST AND FOUNDATION
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-08 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10678828
• 关键词: 16S ribosomal RNA sequencing; Acceleration; Affect; Aftercare; Animal Model; Bacteria; Basic Cancer Research; Basic Science; Bioinformatics; Biological Assay; Biological Markers; Biological Specimen Banks; Blood; Cancer Prognosis; Cessation of life; Classification; Clinical; Combination immunotherapy; Data; Disease; Disease Resistance; Epithelial ovarian cancer; Funding; Gene Expression; Genomics; Growth; Human; Immune; Immune response; Immunity; Immuno-Chemotherapy; Immunotherapy; In Vitro; Intervention; Laboratory Research; Localized Malignant Neoplasm; Malignant Female Reproductive System Neoplasm; Malignant Neoplasms; Malignant neoplasm of ovary; Metabolic Pathway; Metagenomics; Multiomic Data; Mus; New Agents; Newly Diagnosed; Operative Surgical Procedures; Outcome; Patient Selection; Patients; Platinum; Population; Positioning Attribute; Prediction of Response to Therapy; Prognostic Marker; Progression-Free Survivals; Resistance; Sampling; Serum; Shotgun Sequencing; Solid Neoplasm; Specimen; Testing; Translating; Treatment Efficacy; Treatment Protocols; Treatment outcome; Tumor Immunity; Tumor Tissue; United States; Woman; biomarker validation; cancer therapy; chemotherapy; cohort; conventional therapy; cytotoxicity; data modeling; experience; gastrointestinal epithelium; gut bacteria; gut microbiome; high dimensionality; immune cell infiltrate; improved; improved outcome; individual response; metabolome; metabolomics; microbial composition; microbiome; multiple omics; patient stratification; personalized medicine; predicting response; predictive marker; research study; response; standard care; success; therapy outcome; transcriptomics; treatment response; treatment stratification; tumor; tumor microenvironment; tumor progression; tumor-immune system interactions

Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy, with more than 20,000 newly- diagnosed cases and over 13,000 deaths in the United States each year. Unfortunately, there has been little change in survival since platinum-based therapies were introduced over 30 years ago. Because the search for newer, more effective agents has not been fruitful, aggressive surgery plus platinum-based chemotherapy remains the standard first-line treatment of the disease. However, individual response to platinum therapy is highly variable and unpredictable. Eventually, most women develop and succumb to platinum-resistant disease. No way exists to identify who will respond poorly to platinum-based therapy; nor are there any clinically-validated interventions to improve therapy response. Biomarkers that can predict therapy response, provide an early indication of efficacy, support patient treatment stratification, and suggest interventions to improve therapy response and survival are urgently needed. Basic cancer research discoveries in EOC and other solid tumors suggest that gut bacteria impact how a woman responds to platinum-based therapy by influencing the local tumor microenvironment (TME). Thus, gut bacteria may serve as predictive biomarkers of therapy response and outcome. However, there have been no human studies of gut bacteria and EOC therapy response, nor on the interactions among gut bacteria, TME immunity, and treatment response and outcome. Our preliminary findings in women with newly-diagnosed EOC support the animal model data. Backed by the laboratory research data and based on our preliminary findings in an EOC population, we propose to develop predictive microbiome-based biomarkers that will lead to better patient stratification. In Aim 1, we will assess the gut microbiome and systemic metabolome in 104 newly diagnosed EOC cases to identify gut bacteria predictive of response and outcome to platinum-based therapy. In Aim 2 we will use immune-profiling assays to assess TME immune infiltrates and immune gene expression in our cohort. We will then use the high- dimensional genomic, metabolomic and transcriptomic data generated from Aims 1 and 2 to identify favorable and unfavorable gut microbiomes associated with therapy response, outcomes, and local tumor immunity. We will also identify gut bacteria that can serve as intervention targets to improve therapy efficacy or block cancer progression. Our team will then be well positioned to conduct human trials to assess the effects of altering gut bacteria composition on EOC outcomes. We will also be well positioned to pursue mechanistic studies to illuminate how gut bacteria impact therapy response and outcome, thus further identifying treatment targets. This proposal uses existing biospecimens from previously-funded NCI projects together with clinical annotating data to generate high-dimensional, multi-omic data in order to develop predictive and prognostic biomarkers for patient selection or stratification.

上皮卵巢癌（EOC）是最致命的妇科恶性肿瘤，超过20,000 每年在美国，新诊断的病例和13,000多人死亡。不幸的是，那里 由于引入了30年以来，因此生存的变化很小 前。因为寻找更新，更有效的代理人并非富有成果，积极进取的手术 再加上基于铂的化学疗法仍然是该疾病的标准一线治疗。然而， 个人对铂疗法的反应是高度可变且无法预测的。最终，大多数 妇女发育并屈服于抗铂的疾病。没有办法确定谁会回应 基于铂的疗法很差；也没有任何临床验证的干预措施以改进 治疗反应。可以预测治疗反应的生物标志物，提供了早期的指示 功效，支持患者治疗分层，并提出改善治疗的干预措施 迫切需要反应和生存。 EOC和其他固体的基本癌症研究发现 肿瘤表明肠道细菌会影响女性对基于铂的治疗的反应 影响局部肿瘤微环境（TME）。因此，肠道细菌可以用作预测 治疗反应和结果的生物标志物。但是，没有人类的肠道研究 细菌和EOC治疗反应，也没有肠道细菌，TME免疫和 治疗反应和结果。 我们在具有新诊断的EOC的女性中的初步发现支持动物模型数据。由 实验室研究数据并基于我们在EOC人群中的初步发现，我们建议 开发基于预测的微生物组的生物标志物，这将导致更好的患者分层。 在AIM 1中，我们将评估104个新诊断的EOC中的肠道微生物组和全身代谢组 识别肠道细菌的病例可以预测对基于铂的治疗的反应和结果。目标 2我们将使用免疫促进测定法评估TME免疫浸润和免疫基因表达 在我们的队列中。然后，我们将使用高维基因组，代谢组和转录组数据 由目标1和2产生，以确定与 治疗反应，结局和局部肿瘤免疫。我们还将确定可以 作为提高治疗疗效或阻止癌症进展的干预靶标。我们的团队 然后将有很好的位置来进行人体试验以评估改变肠道细菌的影响 EOC结果的组成。我们还将很适合进行机械研究 阐明肠道细菌如何影响治疗反应和结果，从而进一步识别治疗 目标。该提案使用以前资助的NCI项目的现有生物测量以及 临床注释数据以生成高维的多摩变数据以开发 用于患者选择或分层的预测性和预后生物标志物。