ArticleJCO clinical cancer informatics2025
Early Circulating Tumor DNA Kinetics as a Dynamic Biomarker of Cancer Treatment Response.
Article in JCO clinical cancer informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Circulating Cell-free DNA as a biomarker for radiation-induced injury: From mechanistic insights to clinical translation.Cancer metastasis reviews · 2026Review
- Cell-Free DNA Release Kinetics and Fragmentation Reflect Treatment Response and Resistance In Vitro.Cells · 2026Article
- Timing matters: how mechanism-guided sequencing shapes the efficacy of radiotherapy-immunotherapy combinations : A systematic review.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Review
- Coupled SDE-ODE Modeling of Tumor-Immune Dynamics to Infer Biomarker Release.Bulletin of mathematical biology · 2026Article
- Methylated circulating tumor DNA: technical challenges and clinical applications in non-small cell lung cancer patients-a narrative review.Translational lung cancer research · 2026Review
- Liquid Biopsy in Colorectal Cancer: Future Perspectives Through the Lens of Artificial Intelligence-A Comprehensive Review of Novel Literature.International journal of molecular sciences · 2026Review
- Investigational CRISPR-Cas9-edited T cells for metastatic colorectal cancer treatment: Clinical insights for future development.Molecular therapy. Oncology · 2026Article
- Integration of Nanotechnology with ctDNA: New Advances for Monitoring Neoadjuvant Chemotherapy.International journal of nanomedicine · 2026Review
- Artificial intelligence for triple-negative breast cancer from imaging to multi-omics.Frontiers in oncology · 2026Review
- Extrachromosomal DNA: shaping the evolutionary dynamics of cancer.Trends in cancer · 2025Review
- Lung cancer immunotherapy in 2025: where we stand and what comes next?Frontiers in immunology · 2025Review
- A Critical Review of Deep Learning Technique and Its Applications in Clinical Cytology.Journal of cytologyReview
Corrections and comments
- Update of
Authors and funding
4 authors.
Funding
Abstract
purposeCirculating tumor DNA (ctDNA) assays are promising tools for the prediction of cancer treatment response. Here, we build a framework for the design of ctDNA biomarkers of therapy response that incorporate variations in ctDNA dynamics driven by specific treatment mechanisms. These biomarkers are based on novel proposals for ctDNA sampling protocols, consisting of frequent sampling within a compact time window surrounding therapy initiation-which we hypothesize to hold valuable prognostic information on longer-term treatment response.
methodsWe develop mathematical models of ctDNA kinetics driven by tumor response to several therapy classes and use them to simulate randomized virtual patient cohorts to test candidate biomarkers.
resultsUsing this approach, we propose specific biomarkers, on the basis of ctDNA longitudinal features, for targeted therapy and radiation therapy. We evaluate and demonstrate the efficacy of these biomarkers in predicting treatment response within a randomized virtual patient cohort data set.
conclusionThis study highlights a need for tailoring ctDNA sampling protocols and interpretation methodology to specific biologic mechanisms of therapy response, and it provides a novel modeling and simulation framework for doing so. In addition, it highlights the potential of ctDNA assays for making early, rapid predictions of treatment response within the first days or weeks of treatment and generates hypotheses for further clinical testing.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.