ArticleFrontiers in genetics2022
Immunophenotypic Landscape and Prognosis-Related mRNA Signature in Diffuse Large B Cell Lymphoma.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- The GPR183-oxysterol axis in cancer: immune trafficking, spatial organization, and therapeutic potential.Frontiers in immunology · 2026Review
- Spatial transcriptomics reveals prognostically LYZCancer immunology, immunotherapy : CII · 2025Article
- Machine learning algorithms for predicting glioma patient prognosis based on CD163+FPR3+ macrophage signature.NPJ precision oncology · 2024Article
- A Bruton tyrosine kinase inhibitor-resistance gene signature predicts prognosis and identifies TRIP13 as a potential therapeutic target in diffuse large B-cell lymphoma.Scientific reports · 2024Article
- Prognostic Significance of Ribosome-related Genes Signature in Diffuse Large B Cell Lymphoma.Journal of Cancer · 2023Article
- Hypoxia-related tumor environment correlated with immune infiltration and therapeutic sensitivity in diffuse large B-cell lymphoma.Frontiers in genetics · 2022Article
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Authors and funding
12 authors.
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Abstract
Diffuse large B cell lymphoma (DLBCL) exhibits a tightly complexity immune landscape. In this study, we intended to identify different immune phenotype and to examine the immune related mRNA signature for clinical characteristic, therapeutic responsiveness as well as risk stratification and survival prediction in DLBCL. We identified two immune infiltration subtypes of DLBCL patients based on 28 immune cell types. GSEA analysis uncovered the concordant classification of two robust significant subtypes of DLBCL. Considering the convenient application of the immune infiltration subtypes for prognostic prediction, we developed a risk score based on the differentially expressed genes between the Immunity-H and Immunity-L groups. By a least absolute shrinkage and selection operator (LASSO)-Cox regression model, a sixteen-gene risk signature, comprising ANTXR1, CD3D, TIMP1, FPR3, NID2, CTLA4, LPAR6, GPR183, LYZ, PTGDS, ITK, FBN1, FRMD6, PLAU, MICAL2, C1S, was established. The comprehensive results showed that the high-risk group was correlated with lower immune infiltration, more aggressive phenotypes, lower overall survival and more sensitive to lenalidomide. In contrast, a low-risk group score was associated with higher immune infiltration, less aggressive phenotypes, better overall survival and more likely to benefit from PD-1/PD-L1 inhibitors. Finally, a nomogram comprised of the risk score and IPI score was verified to more accurately predict the overall survival of DLBCL than traditional clinical prediction models. Altogether, our data demonstrate the heterogeneity of immune patterns within DLBCL and deepen our molecular understanding of this tumor entity.
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