Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Diversity of Antigen Receptors

Diversity of Antigen Receptors

Antigen receptors are essential components of the immune system crucial in defending the body against foreign invaders. These receptors are present on the surface of B and T cells, enabling them to recognize antigens and mount an appropriate immune response.
Before encountering any antigen, lymphocytes express these receptors. On B cells, the antigen receptor is a membrane-bound antibody molecule called BCR; on T cells, it is a T cell receptor or TCR. B and T cell receptors are composed of two...

T Cell Activation and Clonal Selection

T Cell Activation and Clonal Selection

T cells are integral to our adaptive immune system, recognizing and effectively responding to foreign antigens. T cell activation and clonal selection are pivotal in orchestrating this immune response. This article elucidates these mechanisms, detailing the roles of cluster of differentiation (CD) markers, major histocompatibility complex (MHC) molecules, costimulatory signals, and the process of clonal selection.
Naive T cells that have not yet encountered an antigen express two primary CD...

Tumor Immunotherapy

Tumor Immunotherapy

Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Ecological and evolutionary implications of a mobile genetic element-richhaloarchaeon with unique osmotic resilience.

Microbiology spectrum·2026

Same author

Effect of different structures of β-glucan on extruded starch: physicochemical properties, multiscale structure, and in vitro digestibility.

Food chemistry·2026

Same author

Computational prediction of TCR cross-reactivity: principles, challenges and translational opportunities.

Journal of translational medicine·2026

Same author

Metatranscriptomic discovery of a novel viral class from the Yangshan deep-water port virosphere.

Archives of virology·2026

Same author

Patient-derived organotypic tumor spheroids as a functional platform for predicting immunotherapeutic responses and guiding precision treatment for hepatocellular carcinoma.

Journal for immunotherapy of cancer·2026

Same author

Uncovering novel virophages and giant viruses in high-altitude Lake Namtso: diversity and evolution of host-virus-virophage tripartite interaction systems.

Archives of microbiology·2026

Search research articles

Related Experiment Video

Updated: Jan 13, 2026

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

Published on: February 6, 2017

ProTCR: a protein language model-driven framework for decoding TCR-antigen recognition toward precision

Minrui Xu^1,2, Manman Lu^1,3, Peng Liu¹

¹Shanghai-MOST Key Laboratory of Health and Disease Genomics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai 200237, China.

Briefings in Bioinformatics

|January 11, 2026

Summary

A new computational model, ProTCR, accurately predicts T-cell receptor (TCR) interactions with peptides. This advances TCR-based immunotherapies by identifying therapeutic targets for cancer and infectious diseases like SARS-CoV-2.

Keywords:

TCR-peptides model interpretability precision immunotherapy protein language model

More Related Videos

Identification of Mediators of T-cell Receptor Signaling via the Screening of Chemical Inhibitor Libraries

Identification of Mediators of T-cell Receptor Signaling via the Screening of Chemical Inhibitor Libraries

Published on: January 22, 2019

Generating De Novo Antigen-specific Human T Cell Receptors by Retroviral Transduction of Centric Hemichain

Generating De Novo Antigen-specific Human T Cell Receptors by Retroviral Transduction of Centric Hemichain

Published on: October 25, 2016

Related Experiment Videos

Last Updated: Jan 13, 2026

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

Published on: February 6, 2017

Identification of Mediators of T-cell Receptor Signaling via the Screening of Chemical Inhibitor Libraries

Identification of Mediators of T-cell Receptor Signaling via the Screening of Chemical Inhibitor Libraries

Published on: January 22, 2019

Generating De Novo Antigen-specific Human T Cell Receptors by Retroviral Transduction of Centric Hemichain

Generating De Novo Antigen-specific Human T Cell Receptors by Retroviral Transduction of Centric Hemichain

Published on: October 25, 2016

Area of Science:

Immunology
Computational Biology
Bioinformatics

Background:

T-cell receptors (TCRs) are crucial for adaptive immunity, recognizing neoantigens to initiate immune responses.
Identifying specific TCR-peptide interactions is vital for developing effective TCR-based immunotherapies but remains a significant challenge.
Existing methods often rely on known peptide-TCR pairs, limiting their applicability.

Purpose of the Study:

To develop a novel computational model, ProTCR, for accurate prediction of TCR-peptide recognition.
To enhance the generalizability and biological interpretability of TCR recognition pattern analysis.
To provide a computational foundation for designing precision immunotherapies.

Main Methods:

Integration of the protein language model ProtT5 with deep learning techniques in a dual-pathway network.
Utilizing both global and local feature extraction for efficient amino acid sequence representation.
Validation across diverse datasets including neoantigens, novel peptides, and MHC class II-restricted epitopes.

Main Results:

ProTCR demonstrated robust performance and broad applicability across various datasets, outperforming previous methods.
The model accurately predicted TCR-peptide interactions for unseen peptides and diverse antigenic peptides.
Consistent high accuracy and stability were observed when applied to clinically relevant scenarios, including cancer immunotherapy and pathogen recognition (influenza, SARS-CoV-2).

Conclusions:

ProTCR offers a powerful and versatile tool for elucidating immune response mechanisms.
The model overcomes limitations of previous approaches by not solely relying on known TCR-peptide pairs.
ProTCR provides a strong computational foundation for advancing neoantigen and TCR-based precision immunotherapy strategies.