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

项目摘要/摘要 PIS：马克西米利安·迪恩，医学博士和Ash Alizadeh，医学博士/博士 非小细胞肺癌(NSCLC)是美国最常见的癌症，也是头号癌症 癌症相关死亡的原因。放射治疗(RT)在肺癌的治疗中起着关键作用。 非小细胞肺癌，包括根治性和姑息性环境。虽然肿瘤成像和治疗的进展 在过去的几十年中，辐射输送技术显著地改进了RT， 对肿瘤的基因组和分子理解的进展在很大程度上未能影响 接受RT治疗的患者的管理。因此，发展“精密辐射” 肿瘤学“方法，被定义为使用分子生物标记物来个体化RT，仍然是一种 未得到满足的主要需求。此外，预测哪些患者会出现放射治疗引起的毒性仍然存在 这是一种挑战，并防止在症状出现之前进行早期干预。 我们的长期目标是开发新的、基于分子的精确放射肿瘤学。 非小细胞肺癌患者接受RT治疗的方法。我们的中心假设是新的生物标志物 复发风险的评估，如ctDNA分析和遗传特征分析，可用于早期预测。 在患者仍在接受治疗的情况下，评估治疗结果。我们将通过三个例子来检验我们的假设 具体目标：(1)建立中期ctdna变化预测终末期的能力。 局部晚期非小细胞肺癌患者接受RT治疗的结果，(2)开发新的， 整合了分子和临床因素的个性化风险模型，可以准确预测 复发的风险，以及(3)检验我们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会患上症状性放射性肺炎。 如果成功，我们的项目将导致对当地晚期患者进行个性化治疗的新方法 非小细胞肺癌患者接受RT治疗。我们的创新方法，其中我们将使用基于血液的 已开发的肿瘤基因分型、疾病监测和毒性预测方法 将为旨在降低治疗失败风险的研究奠定基础 接受RT治疗的非小细胞肺癌患者的毒性。我们设想，我们的方法将使未来的试验成为可能 实现分子驱动的精确放射肿瘤学的设计，并将促进 复发风险最高的患者升级治疗，复发风险最低的患者降级治疗 风险。此外，我们的工作将作为一种方法的原则证明，该方法也可能是 应用于放射肿瘤学的其他领域。

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.