Circulating Genomic Determinants of Treatment Failure in Hodgkin Lymphoma

霍奇金淋巴瘤治疗失败的循环基因组决定因素

• 批准号: 10364663
• 负责人: Ash Arash Alizadeh
• 金额: $ 64.09万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-03-04 至 2026-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10364663
• 关键词: Antibody-drug conjugates; Biological Assay; Biological Markers; Biotechnology; Blood; Cancer Patient; Cells; Clinical; Cytotoxic Chemotherapy; DNA Sequence Alteration; Dependence; Development; Diagnosis; Disease; Disease remission; Doctor of Medicine; Doctor of Philosophy; Event; Failure; Fibrinogen; Frequencies; Genetic; Genomics; Genotype; Goals; Heterogeneity; Hodgkin Disease; Human; Human Herpesvirus 4; IL4 gene; Image; Individual; Interleukin 4 Receptor; Malignant Neoplasms; Measurable; Measurement; Measures; Metabolic; Methods; Modeling; Molecular; Monitor; Mutation; Nature; Outcome; Pathologic; Pathway interactions; Patients; Phenotype; Plasma; Positron-Emission Tomography; Precision therapeutics; Property; Public Health; Recurrence; Regimen; Risk; Risk Factors; STAT6 gene; Signal Transduction; Somatic Mutation; Stereotyping; Techniques; Testing; Therapeutic; Toxic effect; Toxicity due to chemotherapy; Treatment Efficacy; Treatment Failure; Treatment outcome; Tumor Tissue; Tumor Volume; Variant; Viral Genome; Work; base; biological heterogeneity; cancer cell; cancer imaging; clinical biomarkers; clinical heterogeneity; cohort; cytokine; disorder risk; exome; experimental study; gain of function; gain of function mutation; genetic variant; high risk; imaging modality; imaging study; immune checkpoint blockade; improved; indexing; innovation; insight; integration site; liquid biopsy; molecular marker; neoplastic cell; novel; novel therapeutic intervention; outcome prediction; personalized medicine; personalized risk prediction; pre-clinical; precision medicine; predictive modeling; prognostication; response; response biomarker; risk prediction; targeted treatment; therapeutic target; therapy outcome; tumor; tumor DNA

PROJECT SUMMARY/ABSTRACT PIs: Ash Alizadeh, M.D./Ph.D. & Maximilian Diehn, M.D./Ph.D. Classical Hodgkin lymphoma (HL) is among the most curable human malignancies. However, strategies to personalize HL therapies and to minimize long-term attendant toxicities of chemotherapy are currently limited to baseline risk factors and imaging. This is due to our incomplete understanding of targetable pathways and lack of good biomarkers. Because of the low fraction of malignant cells in tumor tissue and consecutive technical challenges, the landscape of HL is not well-defined. Our long-term goal is to study the ability of baseline and dynamic risk factors, including genetic mutations, circulating tumor DNA (ctDNA) and imaging studies (PET), to accurately predict treatment outcomes in HL patients, and to provide a basis for individualized precision medicine. Our central hypothesis is that clinical and biological heterogeneity in HL reflects distinct genomic features that are noninvasively measurable using ultrasensitive ctDNA techniques, and that refining early response assessment integrating interim PET and blood based methods improves prognostication. We will test our hypotheses via three specific aims: (1) To noninvasively define the genomic landscape of somatic variations in HL, and to determine the relationship of genomic variants with biological heterogeneity at initial disease presentation, (2) To associate molecular features at baseline and molecular response with ultimate therapeutic outcome, and to integrate clinical and molecular biomarkers in a personalized dynamic risk model for predicting HL outcomes, and (3) To functionally characterize novel mutations in Interleukin-4 receptor (IL4R) resulting in gain-of-function IL4/STAT6 signaling, and to test the utility of precision therapeutic targeting of these mutations. If successful, our project will lead to novel ways to select better therapies for patients at highest risk of failure, and to minimize toxicity for the majority of patients responding well to standard therapy. Our innovative approach, in which we will combine blood-based methods for genotyping and disease monitoring with imaging studies, will provide the basis for a personalized treatment approach in HL.

项目摘要/摘要 PIS：Ash Alizadeh医学博士和马克西米利安·迪恩医学博士/博士 经典型霍奇金淋巴瘤(HL)是人类最易治愈的恶性肿瘤之一。然而， 使HL治疗个性化并将长期伴随的毒性降至最低的策略 化疗目前仅限于基线风险因素和成像。这要归功于我们 对靶向途径的了解不完全，缺乏良好的生物标记物。因为 肿瘤组织中恶性细胞比例较低，以及连续的技术挑战， HL的景观并不是很清晰。 我们的长期目标是研究基线和动态风险因素的能力，包括遗传因素 突变、循环肿瘤DNA(CtDNA)和成像研究(PET)，以准确预测 对HL患者的治疗结果进行分析，为个体化精准用药提供依据。 我们的中心假设是，HL的临床和生物异质性反映了不同的 使用超灵敏的ctDNA技术可以非侵入性测量的基因组特征，以及 完善早期反应评估结合中期PET和血液为基础的方法 提高了预测能力。我们将通过三个具体目标来检验我们的假设：(1) 无创性地定义HL的体细胞变异的基因组图谱，并确定 基因组变异与发病初期生物异质性的关系，(2) 将基线的分子特征和分子反应与最终治疗联系起来 结果，并将临床和分子生物标记物整合到个性化动态风险中 用于预测HL结局的模型，以及(3)从功能上表征HL的新突变 白介素4受体(IL4R)产生功能增强的IL4/STAT6信号，并检测 这些突变的精确治疗靶向的效用。 如果成功，我们的项目将带来新的方法，为患者选择更好的治疗方案 失败的风险，并将对大多数对标准反应良好的患者的毒性降至最低 心理治疗。我们的创新方法，其中我们将结合基于血液的方法来 基因分型和疾病监测与成像研究将为 HL的个体化治疗方法。