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B Cell Activation and Differentiation01:24

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The adaptive immune response, a sophisticated defense mechanism, relies on the activation and differentiation of B lymphocytes, or B cells. These processes enable our bodies to mount a tailored response against specific pathogens such as bacteria, free virus particles, toxins, and parasites.
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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.
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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.
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The physiological function of a cell and cellular communication are outcomes of a range of extrinsic signals, intracellular signaling pathways, and cellular responses. No two cell types express the same repertoire of signaling components. Receptors are highly selective for their cognate ligands, but once activated, they can alter multiple cellular processes such as DNA transcription, protein synthesis, and metabolic activity. 
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CoMBCR: Co-Learning Multi-Modalities of BCRs and gene expressions.

Yiping Zou1,2, Jiaqi Luo1,2, Shuaicheng Li1,2

  • 1Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong, China.

Bioinformatics (Oxford, England)
|March 10, 2026
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Summary

CoMBCR integrates B-cell receptors (BCRs) and gene expression for unified analysis. This tool enhances understanding of B-cell biology, immune responses, and malignant cell development.

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Area of Science:

  • Immunology
  • Bioinformatics
  • Computational Biology

Background:

  • B-cell receptors (BCRs) and gene expression are key B-cell modalities, often analyzed independently.
  • Existing methods do not fully leverage the complementary information from BCRs and gene expression.
  • A unified approach is needed to co-learn these distinct yet related B-cell features.

Purpose of the Study:

  • To develop CoMBCR, a novel B-cell embedding tool for co-learning BCRs and gene expression.
  • To represent B-cell data within a unified latent space for enhanced downstream analysis.
  • To improve the biological insights derived from multi-modal B-cell data.

Main Methods:

  • CoMBCR employs a co-learning strategy to integrate BCR and gene expression data.
  • The tool generates a unified latent space for B-cell representation.
  • Application to diverse datasets including SARS-CoV-2 specific B cells and lymphoma patient data.

Main Results:

  • CoMBCR outperforms BCR-only methods in capturing B-cell biological features, improving SARS-CoV-2 binding prediction by 0.1 MCC.
  • Modality gap analysis in CoMBCR identified immune responses and CDR3 motif preferences in SARS-CoV-2 memory B cells.
  • Integration with spatial transcriptomics enabled CoMBCR to trace malignant B-cell development and survival patterns in lymphoma.

Conclusions:

  • CoMBCR provides a powerful framework for integrated analysis of BCR and gene expression data.
  • The tool offers significant advancements in understanding B-cell immunity and malignant B-cell biology.
  • CoMBCR facilitates deeper biological discoveries through multi-modal B-cell data integration.