Transient Differentiation-State Plasticity Occurs during Acute Lymphoblastic Leukemia Initiation.

Leukemia is characterized by oncogenic lesions that result in a block of differentiation, whereas phenotypic plasticity is retained. A better understanding of how these two phenomena arise during leukemogenesis in humans could help inform diagnosis and treatment strategies. Here, we leveraged the well-defined differentiation states during T-cell development to pinpoint the initiation of T-cell acute lymphoblastic leukemia (T-ALL), an aggressive form of childhood leukemia, and study the emergence of phenotypic plasticity. Single-cell whole genome sequencing of leukemic blasts was combined with multiparameter flow cytometry to couple cell identity and clonal lineages. Irrespective of genetic events, leukemia-initiating cells altered their phenotypes by differentiation and dedifferentiation. The construction of the phylogenies of individual leukemias using somatic mutations revealed that phenotypic diversity is reflected by the clonal structure of cancer. The analysis also indicated that the acquired phenotypes are heritable and stable. Together, these results demonstrate a transient period of plasticity during leukemia initiation, where phenotypic switches seem unidirectional. Significance: A method merging multicolor flow cytometry with single-cell whole genome sequencing to couple cell identity with clonal lineages uncovers differentiation-state plasticity in leukemia, reconciling blocked differentiation with phenotypic plasticity in cancer.

Phosphoproteomic profiling of T cell acute lymphoblastic leukemia reveals targetable kinases and combination treatment strategies.

Protein kinase inhibitors are amongst the most successful cancer treatments, but targetable kinases activated by genomic abnormalities are rare in T cell acute lymphoblastic leukemia. Nevertheless, kinases can be activated in the absence of genetic defects. Thus, phosphoproteomics can provide information on pathway activation and signaling networks that offer opportunities for targeted therapy. Here, we describe a mass spectrometry-based global phosphoproteomic profiling of 11 T cell acute lymphoblastic leukemia cell lines to identify targetable kinases. We report a comprehensive dataset consisting of 21,000 phosphosites on 4,896 phosphoproteins, including 217 kinases. We identify active Src-family kinases signaling as well as active cyclin-dependent kinases. We validate putative targets for therapy ex vivo and identify potential combination treatments, such as the inhibition of the INSR/IGF-1R axis to increase the sensitivity to dasatinib treatment. Ex vivo validation of selected drug combinations using patient-derived xenografts provides a proof-of-concept for phosphoproteomics-guided design of personalized treatments.

T-cell lymphoblastic lymphoma and leukemia: different diseases from a common premalignant progenitor?

T-cell lymphoblastic lymphoma (T-LBL) and lymphoblastic leukemia (T-ALL) represent malignancies that arise from the transformation of immature precursor T cells. Similarities in T-LBL and T-ALL have raised the question whether these entities represent 1 disease or reflect 2 different diseases. The genetic profiles of T-ALL have been thoroughly investigated over the last 2 decades, whereas fairly little is known about genetic driver mutations in T-LBL. Nevertheless, the comparison of clinical, immunophenotypic, and molecular observations from independent T-LBL and T-ALL studies lent strength to the theory that T-LBL and T-ALL reflect different presentations of the same disease. Alternatively, T-LBL and T-ALL may simultaneously evolve from a common malignant precursor cell, each having their own specific pathogenic requirements or cellular dependencies that differ among stroma-embedded blasts in lymphoid tissues compared with solitary leukemia cells. This review aims to cluster recent findings with regard to clinical presentation, genetic predisposition, and the acquisition of additional mutations that may give rise to differences in gene expression signatures among T-LBL and T-ALL patients. Improved insight in T-LBL in relation to T-ALL may further help to apply confirmed T-ALL therapies to T-LBL patients.