ESH CLL 2026 | Genomic drivers and evolution of Richter’s transformation in CLL

Thanks to the studies that we and others have been performing in the last couple or three years, we now understand which are the main genomic alterations that play a role in driving this transformation. We know that there are, in resistance formation, many patients carry alterations affecting the cell cycle pathway. There are lots of TP53 mutations, CDKN2A and B deletions, and other players in cell cycle. There are other alterations in the MAPK pathway, there are lots of TP53 mutations, CDKN2A and B deletions, and other players in cell cycle. There are other alterations in the MAPK pathway alterations, also NOTCH1 pathway alterations, and NF-kappa-B. So I will summarize that probably alterations in these four main biological pathways are the main drivers of Richter transformation, and we also know from longitudinal studies in which we analyze longitudinal samples over the disease course that over this period at the end of this trajectory towards Richter transformation there is a massive accumulation of genomic alterations. Probably these alterations in this biological pathway coupled with genomic alterations at the latest stage is what drives this Richter transformation. I think that the information that we currently have is still limited to really draw solid conclusions about this, because most of the patients that we and others have analyzed, it’s true that they receive a targeted therapy before the Richter transformation, but most of them also receive chemo-immunotherapy before. So they are not chemo-free patients, so our understanding of how these therapies might select these Richter transformation clones might require additional studies in the future. But from these patients that we have analyzed so far we know that the Richter cells may be less dependent on the B-cell receptor pathway in some patients, not in all, but in some, and this might be a mechanism that allows the cells to escape under treatment pressure, for instance, of an BTK inhibition, so this therapy may, in some patients, help or select how these clones to grow, but as I said, this information is still limited, and we need more studies and more patients to properly confirm and understand which is the treatment pressure in this evolution. I’m quite fascinated with all these single-cell technologies that allow us to decipher which is the sub-clonal heterogeneity within CLL and Richter transformation, and help us to understand how these tumors evolve over the lifespan of the patient. So we have presented some data here which we can reconstruct like phylogenetic trees of how these tumors evolve and detail the timeline of events that drive this transformation. So I think that this kind of single-cell technology will allow us to better understand this evolutionary process and then this will allow us to probably use also single-cell technologies or cell-free DNA to try to detect these clones at an early stage and probably in the future we may think of clinical trials designed to target these early clones at an early stage, but this is something that we will see probably in the next conferences in the short future.

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