Everett Moding: Integrating ctDNA Analysis and Radiomics for Dynamic Risk Assessment in Localized Lung Cancer
Everett Moding, Physician Scientist at Stanford Radiation Oncology at X:
“Our study integrating ctDNA and radiomics to predict outcomes in NSCLC treated with CRT is online at Cancer Discovery!
We optimized tissue-free variant calling from plasma samples and combined mid-chemoradiation (CRT) ctDNA levels with radiomics and biological/molecular features to improve prediction of outcomes in patients with non-small cell lung cancer (NSCLC) treated with CRT.
We show the importance of accounting for clonal hematopoiesis that persists during CRT and demonstrate that machine learning can integrate genomic features of putative tumor variants to improve tissue-free variant calling (SNV score).
We utilized the SNV score to demonstrate that ctDNA levels decrease mid-way through CRT, and both ctDNA log fold change and mid-CRT ctDNA concentration are associated with progression-free survival (PFS).
Mid-CRT ctDNA concentration was strongly associated with PFS in independent cohorts of patients treated at MD Anderson and Stanford.
To improve outcome prediction, we explored other complementary biomarkers. In collaboration with Ruijiang Li, we built a radiomic model that analyzes pre-treatment CT images to predict PFS after CRT.
We explored other biological/molecular features and developed a final model (CIRI-LCRT) that integrates pre-CRT tumor histology and radiomics with mid-CRT ctDNA to predict PFS. CIRI-LCRT can be updated real-time to provide personalized risk estimates.
CIRI-LCRT outperformed individual risk factors, demonstrating the complementarity of ctDNA analysis, radiomics, and biological risk factors for predicting patient outcomes.
Remarkably, CIRI-LCRT performed similarly to ctDNA MRD analysis after CRT despite being 2 months earlier! We are excited about the potential for CIRI-LCRT to enable personalized and response-adapted therapies like adapting RT or changing concurrent systemic therapy.”
Title: Integrating ctDNA Analysis and Radiomics for Dynamic Risk Assessment in Localized Lung Cancer
Authors: Everett J. Moding, Mohammad Shahrokh Esfahani, Cheng Jin, Angela B. Hui, Barzin Y. Nabet, Yufei Liu, Jacob J. Chabon, Michael S. Binkley, David M. Kurtz, Emily G. Hamilton, Aadel A. Chaudhuri, Chih Long Liu, Zhe Li, Rene F. Bonilla, Alice L. Jiang, Brianna C. Lau, Pablo Lopez, Jianzhong He, Yawei Qiao, Ting Xu, Luyang Yao, Saumil Gandhi, Zhongxing Liao, Millie Das, Kavitha J. Ramchandran, Sukhmani K. Padda, Joel W. Neal, Heather A. Wakelee, Michael F. Gensheimer, Billy W. Loo, Jr, Ruijiang Li, Steven H. Lin, Ash A. Alizadeh, Maximilian Diehn.
Read The Full Article at Cancer Discovery.
Read more posts featuring NSCLC.
-
Challenging the Status Quo in Colorectal Cancer 2024
December 6-8, 2024
-
ESMO 2024 Congress
September 13-17, 2024
-
ASCO Annual Meeting
May 30 - June 4, 2024
-
Yvonne Award 2024
May 31, 2024
-
OncoThon 2024, Online
Feb. 15, 2024
-
Global Summit on War & Cancer 2023, Online
Dec. 14-16, 2023