Molecularly-based outcome and toxicity prediction after radiotherapy for lung cancer

肺癌放疗后基于分子的结果和毒性预测

基本信息

批准号：
10397617
负责人：
Ash Arash Alizadeh
金额：
$ 61.68万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-01 至 2025-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10397617
关键词：
Area Biological Markers Blood Blood specimen Cancer Etiology Cancer Patient Cancer Personalized Profiling by Deep Sequencing Cells Cessation of life Clinical Clinical Trials DNA analysis Data Development Disease Doctor of Medicine Doctor of Philosophy Early Intervention Foundations Future Gene Expression Genetic Fingerprintings Genomics Genotype Goals Immunotherapy Malignant Neoplasms Malignant neoplasm of lung Measures Methods Modeling Molecular Monitor Mutation Non-Small-Cell Lung Carcinoma Nucleic Acids Outcome Patient-Focused Outcomes Patients Play Prediction of Response to Therapy Prognostic Factor Pulmonary Inflammation RNA RNA analysis Radiation Oncology Radiation Pneumonitis Radiation therapy Recurrence Residual Tumors Risk Risk Factors Role Symptoms Techniques Testing Tissues Toxic effect Training Treatment Failure Treatment outcome Treatment-related toxicity United States Work base cancer imaging chemoradiation clinical risk cohort detection method experimental study genetic profiling high risk improved in vivo indexing innovation liquid biopsy molecular marker mouse model new technology novel novel marker outcome prediction palliative personalized medicine personalized predictions predictive modeling predictive tools prevent prospective radiation delivery radiation resistance radiation risk side effect tool treatment risk trial design tumor tumor DNA

项目摘要

PROJECT SUMMARY/ABSTRACT PIs: Maximilian Diehn, M.D./Ph.D. & Ash Alizadeh, M.D./Ph.D. Non-small cell lung cancer (NSCLC) is the most common cancer in the U.S. and the number one cause of cancer-related deaths. Radiation therapy (RT) plays a critical role in the treatment of NSCLC, both in the curative and palliative settings. While advances in tumor imaging and radiation delivery techniques over the past several decades have significantly improved RT, advances in genomic and molecular understanding of tumors have largely failed to impact management of patients treated with RT. Therefore, development of “precision radiation oncology” approaches, defined as the use of molecular biomarkers to personalize RT, remains a major unmet need. Additionally, predicting which patients will develop RT-induced toxicity remains a challenge and prevents early intervention prior to onset of symptoms. Our long-term goal is to develop novel, molecularly-based precision radiation oncology approaches for NSCLC patients treated with RT. Our central hypothesis is that novel biomarkers of recurrence risk, such as analysis of ctDNA and genetic profiling, can be used for early prediction of treatment outcomes while a patient is still on therapy. We will test our hypothesis via three specific aims: (1) To establish the ability of mid-treatment ctDNA changes to predict ultimate outcomes in locally advanced NSCLC patients treated with RT, (2) To develop novel, personalized risk models that integrate molecular and clinical factors and can accurately predict the risk of recurrence, and (3) To test the hypothesis that a novel liquid biopsy approach we have recently developed can predict which patients will develop symptomatic radiation pneumonitis. If successful, our project will lead to novel ways to personalize therapy for locally advanced NSCLC patients treated with RT. Our innovative approach, in which we will employ blood-based methods for tumor genotyping, disease monitoring, and toxicity prediction that were developed by our group, will lay the foundation for studies aimed at reducing risk of treatment failure and toxicity in NSCLC patients treated with RT. We envision that our approach will enable future trial designs that implement molecularly-driven precision radiation oncology and will facilitate treatment escalation for patients at highest risk of recurrence and de-escalation for those at lowest risk. Additionally, our work will serve as proof-of-principle for an approach that could also be applied to other areas of radiation oncology.

项目概要/摘要 PI：Maximilian Diehn，医学博士/博士和 Ash Alizadeh，医学博士/博士非小细胞肺癌 (NSCLC) 是美国最常见的癌症，也是排名第一的癌症放射治疗（RT）在癌症相关死亡的治疗中起着至关重要的作用。 NSCLC，无论是在治疗还是姑息治疗方面，肿瘤成像和治疗方面都取得了进展。过去几十年的放射治疗技术显着改善了 RT，对肿瘤的基因组和分子理解的进步在很大程度上未能影响因此，“精准放疗”的发展。肿瘤学”方法，定义为使用分子生物标志物来个性化 RT，仍然是一种此外，预测哪些患者将出现放疗引起的毒性仍然是一个未满足的主要需求。一个挑战并妨碍在症状出现之前进行早期干预。我们的长期目标是开发新颖的、基于分子的精准放射肿瘤学 NSCLC 患者接受放疗的方法我们的中心假设是新的生物标志物。复发风险的分析，例如 ctDNA 和基因谱分析，可用于早期预测我们将通过三个方面来检验我们的假设。具体目标：(1) 建立治疗中期 ctDNA 变化预测最终结果的能力接受 RT 治疗的局部晚期 NSCLC 患者的结果，(2) 开发新的、整合分子和临床因素并能准确预测的个性化风险模型复发的风险，以及（3）检验我们拥有一种新的液体活检方法的假设最近开发的可以预测哪些患者将出现有症状的放射性肺炎。如果成功，我们的项目将为局部晚期患者提供个性化治疗的新方法 NSCLC 患者接受放疗治疗，我们将采用基于血液的创新方法。开发的肿瘤基因分型、疾病监测和毒性预测方法我们小组的研究将为旨在降低治疗失败风险的研究奠定基础接受放疗的非小细胞肺癌患者的毒性我们预计我们的方法将使未来的试验成为可能。实施分子驱动的精准放射肿瘤学的设计并将促进对复发风险最高的患者进行治疗升级，对复发风险最低的患者进行降级治疗此外，我们的工作将作为一种方法的原理证明，该方法也可能是一种方法。应用于放射肿瘤学的其他领域。