ArticleScience translational medicine2020
De novo prediction of cancer-associated T cell receptors for noninvasive cancer detection.
Article in Science translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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Who cites it
51 citing papers in PubMed, 98 citations in OpenAlex.
- The landscape of peripheral blood RNA modifications and its clinical implications for diagnosis of hepatocellular carcinoma.Cell communication and signaling : CCS · 2026Article
- Machine Learning of Personal Repertoires From Public T Cell Receptors.Immunological reviews · 2026Review
- Deciphering small sequence differences in T cell receptor-antigen pairing.Nature communications · 2026Article
- Advances in predicting T cell epitope recognition for cancer immunotherapy.Nature cancer · 2026Review
- TCRdb 2.0: an updated T-cell receptor sequence database.Nucleic acids research · 2026Article
- Peripheral Blood TCR Clonotype Diversity as a Biomarker for Colorectal Cancer.Bioengineering (Basel, Switzerland) · 2025Article
- Deep learning-driven TCRβ repertoire analysis enhances diagnosis and enables mining of immunological biomarkers in systemic lupus erythematosus.BioData mining · 2025Article
- T-cell Receptor Profiling of Blood to Detect Lung Cancer.Cancer immunology research · 2025Article
- Challenges and future directions of AIRR-seq-based diagnostics.Immunoinformatics (Amsterdam, Netherlands) · 2025Article
- Circulating T-cell receptor repertoire for cancer early detection.NPJ precision oncology · 2025Article
- Computation strategies and clinical applications in neoantigen discovery towards precision cancer immunotherapy.Biomarker research · 2025Review
- Age-dependent cytokine surge in blood precedes cancer diagnosis.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- EpicPred: predicting phenotypes driven by epitope-binding TCRs using attention-based multiple instance learning.Bioinformatics (Oxford, England) · 2025Article
- Deep learning-based prediction of autoimmune diseases.Scientific reports · 2025Article
- Multimodal learning for scalable representation of high-dimensional medical data.Frontiers in digital health · 2025Article
- Peripheral blood TCR repertoire improves early detection across multiple cancer types utilizing a cancer predictor.Frontiers in oncology · 2025Article
- T-cell receptor dynamics in digestive system cancers: a multi-layer machine learning approach for tumor diagnosis and staging.Frontiers in immunology · 2025Article
- AutoTFCNNY: A multi-instance neural network for enhanced early cancer detection using TCR data.PloS one · 2025Article
- Microfluidic biosensors for biomarker detection in body fluids: a key approach for early cancer diagnosis.Biomarker research · 2024Review
- A comprehensive benchmarking for evaluating TCR embeddings in modeling TCR-epitope interactions.Briefings in bioinformatics · 2024Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
The adaptive immune system recognizes tumor antigens at an early stage to eradicate cancer cells. This process is accompanied by systemic proliferation of the tumor antigen-specific T lymphocytes. While detection of asymptomatic early-stage cancers is challenging due to small tumor size and limited somatic alterations, tracking peripheral T cell repertoire changes may provide an attractive solution to cancer diagnosis. Here, we developed a deep learning method called DeepCAT to enable de novo prediction of cancer-associated T cell receptors (TCRs). We validated DeepCAT using cancer-specific or non-cancer TCRs obtained from multiple major histocompatibility complex I (MHC-I) multimer-sorting experiments and demonstrated its prediction power for TCRs specific to cancer antigens. We blindly applied DeepCAT to distinguish over 250 patients with cancer from over 600 healthy individuals using blood TCR sequences and observed high prediction accuracy, with area under the curve (AUC) ≥ 0.95 for multiple early-stage cancers. This work sets the stage for using the peripheral blood TCR repertoire for noninvasive cancer detection.
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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.