Individualized tumor-informed circulating tumor DNA analysis for postoperative monitoring of non-small cell lung cancer
- PMID: 37683638
- DOI: 10.1016/j.ccell.2023.08.010
Individualized tumor-informed circulating tumor DNA analysis for postoperative monitoring of non-small cell lung cancer
Abstract
We report a personalized tumor-informed technology, Patient-specific pROgnostic and Potential tHErapeutic marker Tracking (PROPHET) using deep sequencing of 50 patient-specific variants to detect molecular residual disease (MRD) with a limit of detection of 0.004%. PROPHET and state-of-the-art fixed-panel assays were applied to 760 plasma samples from 181 prospectively enrolled early stage non-small cell lung cancer patients. PROPHET shows higher sensitivity of 45% at baseline with circulating tumor DNA (ctDNA). It outperforms fixed-panel assays in prognostic analysis and demonstrates a median lead-time of 299 days to radiologically confirmed recurrence. Personalized non-canonical variants account for 98.2% with prognostic effects similar to canonical variants. The proposed tumor-node-metastasis-blood (TNMB) classification surpasses TNM staging for prognostic prediction at the decision point of adjuvant treatment. PROPHET shows potential to evaluate the effect of adjuvant therapy and serve as an arbiter of the equivocal radiological diagnosis. These findings highlight the potential advantages of personalized cancer techniques in MRD detection.
Keywords: Circulating tumor DNA; Liquid biopsy; Minimal residual disease; Non-canonical variant; Non-small cell lung cancer; Surveillance; Tumor-informed.
Copyright © 2023 Elsevier Inc. All rights reserved.
Conflict of interest statement
Declaration of interests Z.Z., C.W., X.L., D.P., F.Q., S.W., X.Z., and S.C. are employment and stock/stock option ownership in Burning Rock Biotech. The remaining authors declare no potential conflict of interest.
Comment in
-
Integrating minimal residual disease monitoring into clinical practice for NSCLC: Is the era upon us?Cancer Cell. 2023 Oct 9;41(10):1699-1701. doi: 10.1016/j.ccell.2023.09.009. Cancer Cell. 2023. PMID: 37816330
Publication types
MeSH terms
Substances
LinkOut - more resources
Other Literature Sources