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Practical microenvironment classification in diffuse large B cell lymphoma using digital pathology.

Yu-Qing Wang1, Shuo Wang2, Hong-Mei Yi3

  • 1Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China; Department of Hematology, The First Affiliated Hospital of Harbin Medical University, Harbin, China.

Cell Reports. Medicine
|March 20, 2025
PubMed
Summary
This summary is machine-generated.

A new method classifies diffuse large B cell lymphoma (DLBCL) subtypes using immunohistochemistry, improving upon transcriptomic classification. This approach reveals survival differences and potential therapeutic targets for DLBCL patients.

Keywords:
algorithmcell of origindiffuse large B cell lymphomadigital pathologyimmune evasionimmunotherapylymphoma microenvironment

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Area of Science:

  • Hematology
  • Oncology
  • Immunology
  • Pathology

Background:

  • Diffuse large B cell lymphoma (DLBCL) is a heterogeneous cancer with outcomes influenced by the tumor and its microenvironment.
  • Existing transcriptomic classifications of DLBCL subtypes based on the lymphoma microenvironment (LME) are difficult to implement clinically.

Purpose of the Study:

  • To develop and validate a practical LME classification for DLBCL using immunohistochemistry and digital pathology.
  • To correlate this novel classification with patient survival and immune escape mechanisms.

Main Methods:

  • Utilized deconvolution methods to quantify microenvironment components from immunohistochemistry staining (CD3, CD8, CD68, PD-L1, collagen).
  • Developed a staining-based algorithm for LME classification, validated against transcriptome-based subtypes and single-cell sequencing data.
  • Analyzed survival outcomes (overall and progression-free) in DLBCL patients treated with R-CHOP or R-CHOP-X immunochemotherapy across LME subtypes.

Main Results:

  • The immunohistochemistry-based LME classification showed over 80% concordance with transcriptomic subtypes.
  • Distinct immune microenvironments identified by the algorithm aligned with transcriptomic profiles.
  • Significant differences in survival were observed among LME subtypes following standard and advanced immunochemotherapy.

Conclusions:

  • The developed immunohistochemistry-based algorithm provides a feasible method for classifying DLBCL subtypes based on LME.
  • LME subtypes are associated with differential immune escape mechanisms, suggesting specific immunotherapeutic targets.
  • This classification has potential applications in precision medicine trials for DLBCL.