ReviewFrontiers in immunology2021
Single-Cell TCR and Transcriptome Analysis: An Indispensable Tool for Studying T-Cell Biology and Cancer Immunotherapy.
Review in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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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.
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Who cites it
14 citing papers in PubMed, 23 citations in OpenAlex.
- Advances in neoantigen-based immunotherapy for head and neck squamous cell carcinoma: a comprehensive review.Frontiers in oncology · 2025Review
- TCR-T cell therapy: current development approaches, preclinical evaluation, and perspectives on regulatory challenges.Journal of translational medicine · 2024Review
- Exploring the potential of the TCR repertoire as a tumor biomarker (Review).Oncology letters · 2024Review
- Unified cross-modality integration and analysis of T cell receptors and T cell transcriptomes by low-resource-aware representation learning.Cell genomics · 2024Article
- scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles.Genome biology · 2023Article
- T-Cell Receptor Repertoire Sequencing in the Era of Cancer Immunotherapy.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023Article
- Review
- Antigen-specificity measurements are the key to understanding T cell responses.Frontiers in immunology · 2023Review
- T-Cell Receptor Repertoire Sequencing and Its Applications: Focus on Infectious Diseases and Cancer.International journal of molecular sciences · 2022Review
- Revealing the Immune Heterogeneity between Systemic Lupus Erythematosus and Rheumatoid Arthritis Based on Multi-Omics Data Analysis.International journal of molecular sciences · 2022Article
- Evaluation of the TCR Repertoire as a Predictive and Prognostic Biomarker in Cancer: Diversity or Clonality?Cancers · 2022Review
- A CD8Frontiers in immunology · 2022Article
- T-Cell Receptor Repertoire Analysis with Computational Tools-An Immunologist's Perspective.Cells · 2021Review
- Analysis of T-Cell Receptor Repertoire in Transplantation: Fingerprint of T Cell-mediated Alloresponse.Frontiers in immunology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
T cells have been known to be the driving force for immune response and cancer immunotherapy. Recent advances on single-cell sequencing techniques have empowered scientists to discover new biology at the single-cell level. Here, we review the single-cell techniques used for T-cell studies, including T-cell receptor (TCR) and transcriptome analysis. In addition, we summarize the approaches used for the identification of T-cell neoantigens, an important aspect for T-cell mediated cancer immunotherapy. More importantly, we discuss the applications of single-cell techniques for T-cell studies, including T-cell development and differentiation, as well as the role of T cells in autoimmunity, infectious disease and cancer immunotherapy. Taken together, this powerful tool not only can validate previous observation by conventional approaches, but also can pave the way for new discovery, such as previous unidentified T-cell subpopulations that potentially responsible for clinical outcomes in patients with autoimmunity or cancer.
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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.