In April 2023, a retrospective study led by Professor WeiLi Zhao from Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine was published in the prestigious international academic journal ——Signal Transduction and Targeted Therapy (IF=39.3). The title of the study is "Simplified algorithm for genetic subtyping in diffuse large B-cell lymphoma." This research introduced the LymphPlex algorithm to address relapse or disease progression in patients with diffuse large B-cell lymphoma (DLBCL). The study was also recently recognized as one of the "Top Ten Advances in Hematology in China in 2023."
Diffuse large B-cell lymphoma (DLBCL), the most prevalent subtype of non-Hodgkin’s lymphoma, presents a significant challenge in its treatment due to its molecular heterogeneity. Despite advancements in immunochemotherapy, a substantial proportion of DLBCL patients experiences recurrent or progressive disease. This study addresses this challenge by introducing the LymphPlex algorithm, a simplified yet potent tool designed to uncover the genetic intricacies of DLBCL. The primary objective is to enhance treatment outcomes through precise outcome prediction and personalized therapeutic interventions.
This retrospective study meticulously analyzed 1001 newly diagnosed DLBCL patients. Leveraging advanced techniques such as whole-exome/genome sequencing (WES/WGS), RNA-sequencing, and fluorescence in situ hybridization (FISH), the research team identified genetic alterations, gene expressions, and rearrangements within a subset of patients. The culmination of this data led to the creation of the LymphPlex algorithm, a 38-gene algorithm that underwent rigorous validation to ascertain its clinical relevance and the biological signatures associated with each genetic subtype.
The LymphPlex algorithm successfully unveiled seven distinct genetic subtypes within DLBCL, each holding unique clinical and biological significance. The TP53Mut subtype, marked by TP53 mutations, exhibited a poor prognosis with dysregulation of p53 signaling, immune deficiency, and PI3K pathway activation. The MCD-like subtype, characterized by mutations in MYD88, CD79B, and other genes, was associated with a poor prognosis, BCL2/MYC double-expression, and activation of NF-κB signaling.
Additionally, the BN2-like and EZB-like subtypes showcased favorable outcomes within specific DLBCL subgroups. BN2-like, with NF-κB activation, demonstrated a positive prognosis within ABC-DLBCL, while EZB-like, predominantly GCB-DLBCL, exhibited favorable outcomes. The N1-like subtype was dominated by ABC-DLBCL, whereas the ST2-like subtype demonstrated a favorable outcome within GCB-DLBCL.
The LymphPlex algorithm’s ability to identify distinct genetic subtypes offers a revolutionary perspective on DLBCL’s heterogeneity. Understanding the clinical relevance of each subtype is critical for tailoring treatment strategies. The TP53Mut subtype’s association with poor prognosis emphasizes the need for aggressive interventions for these patients. Conversely, the identification of favorable outcomes within specific DLBCL subgroups, such as BN2-like and EZB-like, provides an opportunity for more targeted and less aggressive therapies.
Beyond clinical relevance, the genetic subtypes identified by LymphPlex shed light on the underlying biological associations in DLBCL. For instance, the MCD-like subtype’s association with BCL2/MYC double-expression and NF-κB activation suggests potential avenues for targeted therapies. Unraveling the intricate interplay between genetic alterations and biological pathways provides a foundation for developing mechanism-based targeted therapies, a crucial step towards precision medicine in DLBCL.
The study’s findings validate previous research on DLBCL heterogeneity. The associations observed between genetic subtypes and clinical outcomes resonate with the broader scientific community’s efforts to categorize DLBCL into distinct molecular subtypes. This validation not only strengthens the credibility of the LymphPlex algorithm but also contributes to the cumulative knowledge in the field.
The identification of TP53Mut as a high-risk subtype underscores its prognostic value. Patients falling under this category may benefit from more intensive treatment regimens or novel therapeutic approaches. The LymphPlex algorithm thus serves not only as a diagnostic tool but also as a prognostic indicator, guiding clinicians in decision-making for high-risk patients.
In conclusion, the LymphPlex algorithm offers a revolutionary approach to unraveling the genetic complexities of DLBCL. The identified genetic subtypes provide a roadmap for tailored treatment strategies, potentially optimizing outcomes for patients. This study not only contributes to the current understanding of DLBCL’s heterogeneity but also sets the stage for future research and clinical trials aimed at implementing precision medicine approaches in the treatment of DLBCL. As we delve deeper into the molecular landscape of DLBCL, the insights gained from the LymphPlex algorithm hold the promise of transforming how we approach the diagnosis and treatment of this complex blood cancer.
