ArticleBiosensors & bioelectronics2023
Nanotechnology and machine learning enable circulating tumor cells as a reliable biomarker for radiotherapy responses of gastrointestinal cancer patients.
Article in Biosensors & bioelectronics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Window-of-Opportunity Study Utilizing Preoperative Cetuximab in Patients with Head and Neck Cancer.Cancer research communications · 2026Article
- Radiotherapy-chemodynamic cancer therapy using bismuth-based nanoparticles: a synergistic approach for enhanced cancer treatment.RSC advances · 2025Review
- Dual Biomarker Strategies for Liquid Biopsy: Integrating Circulating Tumor Cells and Circulating Tumor DNA for Enhanced Tumor Monitoring.Biosensors · 2025Review
- Liquid biopsy in cancer diagnosis and prognosis: a paradigm shift in precision oncology.Frontiers in molecular biosciences · 2025Review
- Gastrointestinal cancer resistance to treatment: the role of microbiota.Infectious agents and cancer · 2024Review
- Quantitative image analysis pipeline for detecting circulating hybrid cells in immunofluorescence images with human-level accuracy.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2024Article
- Advancing Healthcare: Synergizing Biosensors and Machine Learning for Early Cancer Diagnosis.Biosensors · 2023Review
- Circulating tumor cell abundance in head and neck squamous cell carcinoma decreases with successful chemoradiation and cetuximab treatment.Cancer letters · 2023Article
- Editorial: Biomarkers, functional mechanisms, and therapeutic potentials in gastrointestinal cancers.Frontiers in oncology · 2023Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
A highly sensitive, circulating tumor cell (CTC)-based liquid biopsy was used to monitor gastrointestinal cancer patients during treatment to determine if CTC abundance was predictive of disease recurrence. The approach used a combination of biomimetic cell rolling on recombinant E-selectin and dendrimer-mediated multivalent immunocapture at the nanoscale to purify CTCs from peripheral blood mononuclear cells. Due to the exceptionally high numbers of CTCs captured, a machine learning algorithm approach was developed to efficiently and reliably quantify abundance of immunocytochemically-labeled cells. A convolutional neural network and logistic regression model achieved 82.9% true-positive identification of CTCs with a false positive rate below 0.1% on a validation set. The approach was then used to quantify CTC abundance in peripheral blood samples from 27 subjects before, during, and following treatments. Samples drawn from the patients either prior to receiving radiotherapy or early in chemotherapy had a median 50 CTC ml
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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.