ArticleFrontiers in immunology2018
Network Representation of T-Cell Repertoire- A Novel Tool to Analyze Immune Response to Cancer Formation.
Article in Frontiers in immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Machine Learning of Personal Repertoires From Public T Cell Receptors.Immunological reviews · 2026Review
- Human TCR repertoire in cancer.Cancer medicine · 2024Review
- A novel approach to T-cell receptor beta chain (TCRB) repertoire encoding using lossless string compression.Bioinformatics (Oxford, England) · 2023Article
- GENTLE: a novel bioinformatics tool for generating features and building classifiers from T cell repertoire cancer data.BMC bioinformatics · 2023Article
- A vectorial tree distance measure.Scientific reports · 2022Article
- Breast cancer is marked by specific, Public T-cell receptor CDR3 regions shared by mice and humans.PLoS computational biology · 2021Article
- Predicting Cross-Reactivity and Antigen Specificity of T Cell Receptors.Frontiers in immunology · 2020Review
- Characteristics of TCR Repertoire Associated With Successful Immune Checkpoint Therapy Responses.Frontiers in immunology · 2020Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The T cell repertoire potentially presents complexity compatible, or greater than, that of the human brain. T cell based immune response is involved with practically every part of human physiology, and high-throughput biology needed to follow the T-cell repertoire has made great leaps with the advent of massive parallel sequencing [1]. Nevertheless, tools to handle and observe the dynamics of this complexity have only recently started to emerge [e.g., 2, 3, 4] in parallel with sequencing technologies. Here, we present a network-based view of the dynamics of the T cell repertoire, during the course of mammary tumors development in a mouse model. The transition from the T cell receptor as a feature, to network-based clustering, followed by network-based temporal analyses, provides novel insights to the workings of the system and provides novel tools to observe cancer progression via the perspective of the immune system. The crux of the approach here is at the network-motivated clustering. The purpose of the clustering step is not merely data reduction and exposing structures, but rather to detect hubs, or attractors, within the T cell receptor repertoire that might shed light on the behavior of the immune system as a dynamic network. The
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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.