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: 10157567
• 负责人: Ash Arash Alizadeh
• 金额: $ 65.47万
• 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/10157567
• 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; Structure; 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; prognostic; 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.

项目总结/摘要 PI：Ash Alizadeh，医学博士/博士&马克西米利安迪恩，医学博士/博士 经典型霍奇金淋巴瘤（HL）是人类最容易治愈的恶性肿瘤之一。然而，在这方面， 个性化HL治疗和最大限度减少长期伴随毒性的策略 化疗目前仅限于基线风险因素和成像。这是由于我们 对靶向途径的不完全理解和缺乏良好的生物标志物。因为 肿瘤组织中恶性细胞的低比例和连续的技术挑战， HL的景观并不明确。 我们的长期目标是研究基线和动态危险因素的能力，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 HL患者的治疗结果，并为个体化精准医疗提供依据。 我们的中心假设是HL的临床和生物学异质性反映了不同的 使用超灵敏ctDNA技术可非侵入性测量的基因组特征，以及 将临时PET和基于血液的方法相结合， 提高了精确度。我们将通过三个具体目标来检验我们的假设：（1） 非侵入性地定义HL体细胞变异的基因组景观，并确定 基因组变异与初始疾病表现时生物异质性的关系，（2） 将基线时的分子特征和分子缓解与最终治疗相关 结果，并在个性化的动态风险中整合临床和分子生物标志物 预测HL结局的模型，以及（3）在功能上表征HL中的新突变。 白细胞介素-4受体（IL4R）导致功能获得性IL4/STAT6信号传导，并测试 这些突变的精确治疗靶向的效用。 如果成功，我们的项目将导致新的方法来选择更好的治疗方法， 失败的风险，并尽量减少大多数患者的毒性反应良好， 疗法我们的创新方法，我们将联合收割机结合血液为基础的方法， 基因分型和疾病监测与成像研究，将提供基础， HL的个性化治疗方法。