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

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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.