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.

上皮性卵巢癌（EOC）是最致命的妇科恶性肿瘤， 美国每年有超过13,000例新诊断的病例和超过13,000例死亡。可惜 自铂类药物治疗引入30年以来， 前因为寻找更新的，更有效的代理商一直没有成果，积极的手术 加上铂基化疗仍然是该疾病的标准一线治疗。然而，在这方面， 个体对铂治疗的反应是高度可变和不可预测的。最终，大多数 妇女发展并死于铂耐药性疾病。没有办法确定谁会回应 对铂类药物治疗效果不佳;也没有任何临床验证的干预措施可以改善 治疗反应可以预测治疗反应的生物标志物提供了治疗反应的早期指示。 有效性，支持患者治疗分层，并建议干预措施以改善治疗 我们迫切需要应对和生存。EOC和其他固体癌症的基础癌症研究发现 肿瘤表明，肠道细菌通过以下方式影响女性对铂类药物治疗的反应： 影响局部肿瘤微环境（TME）。因此，肠道细菌可以作为预测 治疗反应和结果的生物标志物。然而，还没有关于肠道的人类研究。 细菌和EOC治疗反应，也不是肠道细菌，TME免疫， 治疗反应和结果。 我们在新诊断EOC的女性中的初步发现支持动物模型数据。背靠 实验室研究数据和基于我们在平机会人群中的初步研究结果，我们建议 开发基于微生物组的预测性生物标志物，从而更好地对患者进行分层。 在目标1中，我们将评估104例新诊断EOC的肠道微生物组和全身代谢组 病例，以确定预测铂类治疗反应和结果的肠道细菌。在Aim中 我们将使用免疫分析法来评估TME免疫浸润和免疫基因表达 in our cohort队列.我们将使用高维度的基因组、代谢组和转录组数据 根据目标1和2生成，以确定与以下相关的有利和不利肠道微生物组： 治疗反应、结果和局部肿瘤免疫。我们还将鉴定出肠道细菌， 作为干预靶点以提高治疗效果或阻断癌症进展。我们的团队 然后将很好地进行人体试验，以评估改变肠道细菌的影响， 关于EOC的结果。我们也将有能力进行机械研究， 阐明肠道细菌如何影响治疗反应和结果，从而进一步确定治疗 目标的该提案使用来自先前资助的NCI项目的现有生物标本， 临床注释数据，以生成高维、多组学数据， 用于患者选择或分层的预测和预后生物标志物。