From Indolent to Aggressive: Understanding Lymphoma Transformation

The transformation of indolent lymphomas to diffuse large B-cell lymphoma (DLBCL) is a recognized but unpredictable clinical event known for its wide variability in incidence and adverse outcomes, with advancements in technology allowing for a deeper exploration of their genetic basis and relationship to de novo DLBCL, highlighting the need for further research in this area.

Indolent B-cell lymphomas make up 40% to 50% of non-Hodgkin's lymphomas (NHL) in the Western world and usually progress slowly. Some indolent B-cell lymphomas can transform into aggressive lymphomas, with follicular lymphoma (FL) and chronic lymphocytic leukemia (CLL) being the most studied. Warning signs of transformation include sudden deterioration and new symptoms. Histological confirmation is crucial for diagnosing transformation in these indolent lymphomas.

There is a lack of comprehensive epidemiological data on the transformation of indolent lymphomas, making it difficult to accurately assess true risk. Studies have shown a continuous risk of transformation in patients with FL, but modern treatments may be reducing this risk. Rituximab has been linked to a lower risk of transformation in patients with FL, with certain chemotherapy regimens also impacting risk. In CLL, the risk of transformation varies depending on treatment history, with recent studies showing consistent transformation rates with historical data. Risk factors for transformation in CLL include treatment history and initial response to therapy.

Transformation in indolent B-cell lymphomas is the result of additional genetic and epigenetic alterations and interactions with the microenvironment that aid in immune evasion. Next-generation sequencing and immuno-profiling have greatly advanced our understanding of DLBCL and indolent lymphomas, but studying transformed lymphomas is more challenging due to the need to compare samples from before and after transformation, technical difficulties, and limitations in replicating the biology of transformed lymphomas in animal models. Despite these challenges, research on transformation has revealed key insights into the biology of lymphomas in recent years. Studies on transformed FL have shown that transformed genomes have a higher mutation burden and specific genetic alterations, such as deletions in chromosome 1p and 6q, gains in chromosome 2, and dysregulation of genes like MYC, BCL2, and BCL6, all of which contribute to the transformation process.

Seminal studies have reconstructed temporal evolutionary pathways underlying FL tumor evolution through sequential tumor biopsies, showing that most transformed follicular lymphoma (tFL) cases are clonally related to FL at diagnosis. Unlike other lymphomas, tFLs do not evolve directly from the dominant FL clone, but rather from a common precursor clone that later diverges with additional alterations. Early initiation events in FL include mutations in histone modifying enzymes and acquisition of BCR N-glycosylation sites, likely present in less evolved CPC clones. Strategies targeting these early lesions in FL may help prevent disease recurrence and histological transformation.

Identifying patients at risk of FL transformation remains challenging due to the emergence of mutated clones not easily detectable in diagnostic samples. Genetic subtyping in FL is still in its early stages, with recent studies revealing different subtypes associated with varying risks of transformation. Using machine learning-based genetic classifiers shows promise in predicting future risk of transformation from the initial diagnosis. Monitoring circulating tumor DNA may offer a minimally invasive approach to detecting rare mutations predictive of transformation at an earlier clinical time point.

Single-cell transcriptomic analyses of FL LN biopsies have shown a high level of tumor heterogeneity with B cells exhibiting functional plasticity and distinct T cell compositions. FL cells deviate from regulated GC programs, displaying a range of states from GC-like to memory-like, which are consistent across patients. A larger study on almost 150 patients with FL revealed diverse B cell phenotypes, with the memory B cell-like subtype associated with an increased risk of transformation. Ongoing investigations are exploring the phenotypic and genotypic co-evolution of malignant B cells and the TME landscape during transformation, including an 'exhausted' CD8 T cell signature emerging. In Richter's syndrome (RS), various genetic and biological risk factors for transformation have been identified, with genetic studies confirming clonal-related and clonal-unrelated RS cases, highlighting increased mutation rates and alterations in core pathways leading to RS. Subtypes within RS have emerged, including TP53-altered subtypes and those with intact TP53, such as NOTCH1-Tri12 RS and SF3B1-EGR2 mutated RS, with WGD-RS containing most transformed M-CLL cases.

Pairing RS and CLL transcriptomes has revealed common altered transcriptional pathways in transformation, including MYC signaling and cell cycle regulation. Differentiation in cell states during transformation is linked to changes in chromatin and pathways involved in oxidative phosphorylation and immune evasion. Analysis of methylation patterns has shown global hypomethylation in RS, highlighting pathways like NOTCH and Wnt signaling. Advances in sequencing have allowed for the detection of early RS clonal genetic changes years before clinical diagnosis, shedding light on the evolution and timing of RS development.

In recent years, murine models of disease have advanced alongside new human biologic investigations, including the development of new RS xenograft and genetically engineered mouse models. Using a CRISPR-Cas9 editing strategy, CLL development and evolution to DLBCL RS has been successfully modeled in mice, revealing shared genetic and functional similarities to human RS. The murine RS models implicate the MYC/PI3K axis in transformation, provide insights into clonal evolution, and highlight potential therapeutic vulnerabilities. Studies on transformed MZL and WM show increased genomic complexity and alterations in genes like TNFAIP3, TP53, and CDKN2A/B, shedding light on the biology of these transformed lymphomas.

Research on the transformation of WM and MZL has shown distinct genetic profiles and risk factors associated with transformation, such as MYD88 mutation status and alterations in genes related to NF-kB signaling and DNA damage repair. Despite advancements in understanding the drivers of transformation, the impact of chronic antigenic stimulation on the evolution toward transformation remains unclear. Further studies are needed to define transformation-triggering events, elucidate immune evasion mechanisms, and identify therapeutic vulnerabilities in transformed lymphomas using innovative technologies and model systems.

Large well-annotated DLBCL datasets have allowed for comparative analysis with transformed datasets, revealing distinct genetic alterations in RS and DLBCL cases. RS cases were found to cluster separately from DLBCL, with some similarities to specific DLBCL clusters. Methylation and transcriptional signatures can distinguish RS from DLBCL, with RS showing a distinct pattern of hypomethylation and upregulation in certain pathways. Clonally related RS has unique molecular features associated with poor prognosis, while clonally unrelated RS shares biologic features with de novo DLBCL.

Transformed lymphomas have poorer outcomes compared to their indolent counterparts due to challenges in consensus therapeutic approaches, exclusion from clinical trials, and limited treatment options. Patients with CLL transformed to RS have a median overall survival of less than one year, while studies have shown that some transformed lymphomas share biological similarities with DLBCL. Despite improvements in survival rates post-transformation for FL patients, transformation remains a significant cause of morbidity and mortality.

The timing of transformation events can impact outcomes, with early transformations associated with inferior survival rates. The biology of transformation, including the cell of origin and genetic factors, raises questions about the emergence and prevention of transformation. Further research is needed to understand the impact of newer therapies on clonal evolution and the shared biology of transformation across different indolent histologies.

Reference
Parry EM, Roulland S, Okosun J. DLBCL arising from indolent lymphomas: How are they different? Seminars in Hematology. 2023;60(5): 277-284. doi:10.1053/j.seminhematol.2023.11.002.