ArticleHematological oncology2022
High inter-follicular spatial co-localization of CD8+FOXP3+ with CD4+CD8+ cells predicts favorable outcome in follicular lymphoma.
Article in Hematological oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Molecular Biomarkers in Prediction of High-Grade Transformation and Outcome in Patients with Follicular Lymphoma: A Comprehensive Systemic Review.International journal of molecular sciences · 2024Pooled it
- Article
- Prognostic value of BMI, prognostic nutritional index, and CRP in patients with lymphoma after autologous hematopoietic stem cell transplantation.Biomedical engineering online · 2026Article
- Metabolic-immune axis in the tumor microenvironment: a new strategy for prognostic assessment and precision therapy in DLBCL and FL.Frontiers in immunology · 2025Review
- Deciphering cell to cell spatial relationship for pathology images using SpatialQPFs.Scientific reports · 2024Article
- Deep Learning Enables Spatial Mapping of the Mosaic Microenvironment of Myeloma Bone Marrow Trephine Biopsies.Cancer research · 2024Article
- Extended correlation functions for spatial analysis of multiplex imaging data.Biological imaging · 2024Article
- Microenvironmental immune cell alterations across the spectrum of nodular lymphocyte predominant Hodgkin lymphoma and T-cell/histiocyte-rich large B-cell lymphoma.Frontiers in oncology · 2023Article
- High inter-follicular spatial co-localization of CD8+FOXP3+ with CD4+CD8+ cells predicts favorable outcome in follicular lymphoma.Hematological oncology · 2022Article
- Applications of machine learning in tumor-associated macrophages.Frontiers in immunology · 2022Review
Corrections and comments
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Authors and funding
15 authors at 6 institutions in 2 countries.
Funding
Abstract
The spatial architecture of the lymphoid tissue in follicular lymphoma (FL) presents unique challenges to studying its immune microenvironment. We investigated the spatial interplay of T cells, macrophages, myeloid cells and natural killer T cells using multispectral immunofluorescence images of diagnostic biopsies of 32 patients. A deep learning-based image analysis pipeline was tailored to the needs of follicular lymphoma spatial histology research, enabling the identification of different immune cells within and outside neoplastic follicles. We analyzed the density and spatial co-localization of immune cells in the inter-follicular and intra-follicular regions of follicular lymphoma. Low inter-follicular density of CD8+FOXP3+ cells and co-localization of CD8+FOXP3+ with CD4+CD8+ cells were significantly associated with relapse (p = 0.0057 and p = 0.0019, respectively) and shorter time to progression after first-line treatment (Logrank p = 0.0097 and log-rank p = 0.0093, respectively). A low inter-follicular density of CD8+FOXP3+ cells is associated with increased risk of relapse independent of follicular lymphoma international prognostic index (FLIPI) (p = 0.038, Hazard ratio (HR) = 0.42 [0.19, 0.95], but not independent of co-localization of CD8+FOXP3+ with CD4+CD8+ cells (p = 0.43). Co-localization of CD8+FOXP3+ with CD4+CD8+ cells is predictors of time to relapse independent of the FLIPI score and density of CD8+FOXP3+ cells (p = 0.027, HR = 0.0019 [7.19 × 10
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.