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Decoding DLBCL: How Cell-of-Origin is Revolutionizing Lymphoma Treatment

Theo Raines in Health & Wellness September 2025 • 4 min read.

"A Deep Dive into Diffuse Large B-Cell Lymphoma and the Breakthrough Findings from the UK's Haematological Malignancy Research Network"

Diffuse large B-cell lymphoma (DLBCL) is a common type of aggressive non-Hodgkin lymphoma. It accounts for a significant portion of all lymphoma cases. While DLBCL is potentially curable with treatments like R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone), it's a complex disease. Its varying clinical characteristics and prognostic factors make understanding its biology crucial.

A major advancement in understanding DLBCL came with the classification of DLBCL-NOS (DLBCL not otherwise specified) into germinal center B-cell (GCB) and activated B-cell (ABC) types using gene expression profiling (GEP). This classification, based on the cell-of-origin (COO), is now a standard part of the World Health Organization's classification and is essential for enrolling patients in clinical trials. Recent research has further refined these classifications, identifying 'Burkitt-like' or 'high-grade' gene expression profiles to better distinguish between different types of aggressive lymphomas.

A groundbreaking study from the UK's Haematological Malignancy Research Network (HMRN) has provided significant insights into DLBCL. The study, which utilized a large real-world DLBCL GEP series, has expanded our understanding of the disease and its various classifications. By tracking newly diagnosed patients until death, the HMRN study offers a comprehensive look at the behavior and treatment outcomes of DLBCL.

Key Findings from the HMRN Study

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The HMRN study included data from 2,197 patients newly diagnosed with de novo DLBCL-NOS between September 2004 and August 2016. All patients were treated with curative intent and followed for mortality through March 2018. Of these patients, 706 had suitable material available for GEP, which was performed using RNA extracted from formalin-fixed paraffin-embedded (FFPE) pre-treatment biopsies. The 'DLBCL automatic classifier' (DAC) was used to classify COO, and a transcriptomic classifier was employed to identify a molecular high-grade (MHG) class.

The study found that the characteristics of patients in the COO study group were broadly similar to those of the entire cohort. Approximately 89% of patients were treated with R-CHOP, and a small percentage received CODOX-M-based chemotherapies. Interestingly, patients in the COO study group had significantly better survival rates compared to the cohort as a whole. The 5-year overall survival (OS) was 66.8% in the COO group versus 61.2% in the cohort, and relative survival (RS) was 76.0% versus 71.1%.

The standard 3-group classifier assigned patients as follows:

GCB: 384 (54.4%)
ABC: 194 (27.5%)
Unclassified: 128 (17.1%)

Consistent with other studies, patients in the GCB group were younger and had better survival rates than those in the ABC group. Additionally, the study identified a molecular high-grade (MHG) subgroup, which was almost exclusively classified as GCB by the 3-group classifier. Separation of these cases further widened the survival disparity between the ABC and GCB groups. Patients in the MHG group had substantially worse survival rates than those remaining in the GCB group, and significantly worse than the ABC group. This underscores the importance of identifying and treating this high-risk subgroup effectively.

Implications for Future Treatment Strategies

In conclusion, the HMRN study confirms the heterogeneity of DLBCL-NOS and demonstrates the prognostic strength of GEP in a real-world setting. By differentiating a poor-risk MHG group from the conventional COO classes, this research lays the groundwork for future clinical trials aimed at improving outcomes for these high-risk patients. Understanding the cell-of-origin in DLBCL is not just an academic exercise; it's a critical step toward more personalized and effective treatment strategies.

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This article is based on research published under:

DOI-LINK: 10.1111/bjh.15619, Alternate LINK

Title: Cell‐Of‐Origin In Diffuse Large B‐Cell Lymphoma: Findings From TheUk'S Population‐Based Haematological Malignancy Research Network

Subject: Hematology

Journal: British Journal of Haematology

Publisher: Wiley

Authors: Daniel Painter, Sharon Barrans, Stuart Lacy, Alexandra Smith, Simon Crouch, David Westhead, Chulin Sha, Russell Patmore, Reuben Tooze, Cathy Burton, Eve Roman

Published: 2018-11-08

Everything You Need To Know

What is cell-of-origin (COO) classification in Diffuse Large B-Cell Lymphoma (DLBCL), and why is it important?

Diffuse large B-cell lymphoma (DLBCL) is categorized into subtypes like germinal center B-cell (GCB) and activated B-cell (ABC) types, based on the cell-of-origin (COO). This classification uses gene expression profiling (GEP) to understand the genetic characteristics of the lymphoma cells. Identifying these subtypes is crucial because GCB and ABC types respond differently to treatments, impacting patient outcomes. Further research has identified 'Burkitt-like' or 'high-grade' gene expression profiles to distinguish aggressive lymphomas.

How does the Haematological Malignancy Research Network (HMRN) study enhance our understanding of Diffuse Large B-Cell Lymphoma (DLBCL)?

The Haematological Malignancy Research Network (HMRN) study significantly contributes to understanding Diffuse Large B-Cell Lymphoma (DLBCL) by providing real-world evidence on a large scale. It tracked 2,197 newly diagnosed patients with de novo DLBCL-NOS, analyzing their treatment outcomes and survival rates until death. This comprehensive approach validates the prognostic importance of gene expression profiling (GEP) in DLBCL and helps identify high-risk subgroups. The HMRN study enriches the research landscape by including detailed data on patient characteristics, treatment regimens (primarily R-CHOP), and survival outcomes.

What is the 'DLBCL automatic classifier' (DAC) and how does it aid in the classification of Diffuse Large B-Cell Lymphoma (DLBCL)?

The 'DLBCL automatic classifier' (DAC) is a tool used to classify Diffuse Large B-Cell Lymphoma (DLBCL) based on cell-of-origin (COO) using gene expression profiling (GEP). This helps in distinguishing between subtypes like germinal center B-cell (GCB) and activated B-cell (ABC) types. Additionally, transcriptomic classifiers identify molecular high-grade (MHG) cases. By automating the classification process, DAC ensures consistency and accuracy in assigning DLBCL subtypes, which is essential for clinical trials and personalized treatment strategies. The use of DAC enhances the reliability of DLBCL subtyping, enabling researchers and clinicians to better understand and manage this complex disease.

Why is identifying the molecular high-grade (MHG) subgroup significant in treating Diffuse Large B-Cell Lymphoma (DLBCL)?

The molecular high-grade (MHG) subgroup within Diffuse Large B-Cell Lymphoma (DLBCL) represents a high-risk category that needs identification for treatment strategies. The HMRN study found that MHG cases, almost exclusively classified as GCB, had significantly worse survival rates than other GCB and ABC groups. This highlights the need for tailored approaches to improve outcomes for these high-risk patients. Further research is warranted to develop effective treatments specifically targeting the MHG subgroup to overcome their poor prognosis and improve overall survival rates in DLBCL.

How does cell-of-origin (COO) classification in Diffuse Large B-Cell Lymphoma (DLBCL) influence treatment decisions and outcomes?

The cell-of-origin (COO) classification of Diffuse Large B-Cell Lymphoma (DLBCL) directly impacts treatment decisions by helping to personalize therapeutic strategies. Identifying subtypes such as germinal center B-cell (GCB) and activated B-cell (ABC) allows clinicians to tailor treatment regimens based on the expected response of each subtype. The discovery of the molecular high-grade (MHG) subgroup further refines this approach, enabling targeted interventions for high-risk patients. By integrating COO classification with gene expression profiling (GEP), clinicians can move closer to precision medicine, enhancing treatment efficacy and improving patient outcomes in DLBCL.