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Boissel, N.

Publications and source records attributed to Boissel, N..

2 recordsLinked to original sources

In vivo isogenic modelling unveils a TP53-mediated relapse phenotype in T-cell acute lymphoblastic leukemia

Many patients with T-cell acute lymphoblastic leukemia (T-ALL) relapse into a treatment-resistant disease. The mechanisms driving relapse remain largely elusive, in part due to the lack of faithful experimental models. Here, we leveraged patient-derived xenograft (PDX) pairs generated from diagnosis and relapse T-ALLs to functionally address the cellular mechanisms driving TP53-altered relapse. Beyond inter-T-ALL variability, comparative analyses revealed a unique, cell-intrinsic relapse phenotype that includes greater leukemia-initiating capacity and that can be conferred to diagnosis cells by TP53 silencing. Transcriptomic profiling linked the relapse phenotype to deregulated OXPHOS metabolism and MYC signaling. Integration of single-cell profilings uncovered TP53-wildtype cell populations at diagnosis expressing a relapse profile, possibly reflecting a pre-existing modulation of TP53 signaling. These cells sequentially evolved towards biallelic TP53 inactivation at relapse. Collectively, our findings support a model in which T-ALL relapses emerge from a selected pre-existing transcriptional state characterized by deregulated metabolism that favors subsequent TP53 inactivation.

cancer biology↗

A transcriptomic continuum of differentiation arrest identifies myeloid interface acute leukemias with poor prognosis

Classification of acute lymphoblastic and myeloid leukemias (ALL and AML) remains heavily based on phenotypic resemblance to normal hematopoietic precursors. This framework can provide diagnostic challenges for immunophenotypically heterogeneous immature leukemias, and ignores recent advances in understanding of developmental multipotency of diverse normal hematopoietic progenitor populations that are identified by transcriptional signatures. We performed transcriptional analyses of a large series of acute myeloid and lymphoid leukemias and detected significant overlap in gene expression between cases in different diagnostic categories. Bioinformatic classification of leukemias along a continuum of hematopoietic differentiation identified leukemias at the myeloid/T-lymphoid interface, which shared gene expression programs with a series of multi or oligopotent hematopoietic progenitor populations, including the most immature CD34+CD1a-CD7- subset of early thymic precursors. Within these interface acute leukemias (IALs), transcriptional resemblance to early lymphoid progenitor populations and biphenotypic leukemias was more evident in cases originally diagnosed as AML, rather than T-ALL. Further prognostic analyses revealed that expression of IAL transcriptional programs significantly correlated with poor outcome in independent AML patient cohorts. Our results suggest that traditional binary approaches to acute leukemia categorization are reductive, and that identification of IALs could allow better treatment allocation and evaluation of therapeutic options.

cancer biology↗