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A cross-platform transcriptomic risk score integrating LymphoMAP microenvironment archetypes and immune
Xiaochang Chen1, Jin Zhang1, Shenhe Jin1
1Department of Hematology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310016, P.R. China.
Oncology Letters
|June 15, 2026
Summary
This study links Diffuse Large B-cell Lymphoma (DLBCL) microenvironment archetypes and immune evasion to genetic subtypes. Integrating these into a transcriptomic risk score improves prognostic accuracy beyond the standard International Prognostic Index (IPI) for DLBCL patients.
Area of Science:
- Oncology
- Immunology
- Genetics
- Bioinformatics
Background:
- Diffuse Large B-cell Lymphoma (DLBCL) exhibits significant clinical heterogeneity.
- Existing prognostic indices, like the International Prognostic Index (IPI), do not fully capture DLBCL's biological diversity.
- Understanding the interplay between tumor microenvironment, immune evasion, and genetic subtypes is crucial for improved risk stratification.
Purpose of the Study:
- To investigate the relationship between transcriptome-inferred LymphoMAP archetypes (lymph node-like, fibroblast-macrophage-rich, T cell-exhausted) and DLBCL genetic subtypes.
- To assess the association of these archetypes with immune evasion-associated programs.
- To determine if integrating these dimensions into a transcriptomic risk score enhances risk stratification beyond the IPI.
Main Methods:
- Inference of LymphoMAP archetypes and quantification of immune evasion programs using single-sample gene set enrichment analysis in the DLBCL-2018 cohort (n=562).
- Development of a transcriptomic risk score (RScore-Expr) using an elastic-net Cox model in an immunochemotherapy-treated subset (n=234).
- External validation of RScore-Expr in four independent Gene Expression Omnibus cohorts (n=1,173) using random-effects meta-analysis.
Main Results:
- LymphoMAP archetypes showed significant associations with genetic subtypes and distinct immune program patterns.
- An integrated model combining archetypes and immune evasion identified high-risk patients (log-rank P=0.0026) with modest discrimination (C-index: 0.624).
- The RScore-Expr significantly improved corrected discrimination (0.639 to 0.687) and model fit when added to the IPI, showing consistent survival association in external cohorts (HR=1.13, P=0.033).
Conclusions:
- A framework linking microenvironment archetypes, immune evasion, and tumor genetics provides a more comprehensive understanding of DLBCL.
- The externally validated RScore-Expr offers added prognostic value beyond the IPI in DLBCL.
- This integrated transcriptomic approach enhances risk stratification for DLBCL patients.
