The contribution of single-cell analysis of acute leukemia in the therapeutic strategy

Abstract

After decades during which the treatment of acute myeloblastic leukemia was limited to variations around a skeleton of cytarabine/anthracycline, targeted therapies appeared. These therapies, first based on monoclonal antibodies, also rely on specific inhibitors of various molecular abnormalities. A significant but modest prognosis improvement has been observed thanks to these new treatments that are limited by a high rate of relapse, due to the intrinsic chemo and immune-resistance of leukemia stem cell, together with the acquisition of these resistances by clonal evolution. Relapses are also influenced by the equilibrium between the pro or anti-tumor signals from the bone marrow stromal microenvironment and immune effectors. What should be the place of the targeted therapeutic options in light of the tumor heterogeneity inherent to leukemia and the clonal drift of which this type of tumor is capable? Novel approaches by single cell analysis and next generation sequencing precisely define clonal heterogeneity and evolution, leading to a personalized and time variable adapted treatment. Indeed, the evolution of leukemia, either spontaneous or under therapy selection pressure, is a very complex phenomenon. The model of linear evolution is to be forgotten because single cell analysis of samples at diagnosis and at relapse show that tumor escape to therapy occurs from ancestral as well as terminal clones. The determination by the single cell technique of the trajectories of the different tumor sub-populations allows the identification of clones that accumulate factors of resistance to chemo/immunotherapy (“pan-resistant clones”), making possible to choose the combinatorial agents most likely to eradicate these cells. In addition, the single cell technique identifies the nature of each cell and can analyze, on the same sample, both the tumor cells and their environment. It is thus possible to evaluate the populations of immune effectors (T-lymphocytes, natural killer cells) for the leukemia stress-induced alteration of their functions. Finally, the single cells techniques are an invaluable tool for evaluation of the measurable residual disease since not only able to quantify but also to determine the most appropriate treatment according to the sensitivity profile to immuno-chemotherapy of remaining leukemic cells.

Big data and single‐cell sequencing in acute myeloid leukemia research

“…83 The sc-seq technique provides a means at single-cell resolution to dissect intratumoral genetic and epigenetic heterogeneity, and then identify clones that accumulate resistance factors associated with chemo/immunotherapy, ultimately affecting prognosis and treatment outcomes. 106 Given that AML exhibits molecular heterogeneity, single-cell techniques offer a potent means to gain critical insights into leukemia initiation, evolution, and recurrence. 107 Also, some information is provided by sc-seq techniques on the genetic landscape, 25 subclonal structures, regulatory networks, gene expression, and proteomic profile.…”

“…83 Profiling intratumoral genetic and epigenetic heterogeneity at single-cell resolution has the potential to uncover clones that amass resistance factors against chemotherapy or immunotherapy, modulating prognosis and response to treatment. 106 Revealing the unique features of single cells, including the proliferation, self-renewal, and resistance mechanisms, may assist in improving the identification of the targeted cluster. 83 There is no doubt that in the AML context, sc-seq experiments generate a significantly larger amount of biological information compared to other commonly used single-cell methods such as karyotyping, immunophenotyping, in situ hybridization, flow cytometry, and mass cytometry.…”

“…However, it often failed to recognize rare alleles, or definitely determine the co‐occurrence of mutations within the same cells, thereby necessitating single‐cell resolution which can prove critical 83 . The sc‐seq technique provides a means at single‐cell resolution to dissect intratumoral genetic and epigenetic heterogeneity, and then identify clones that accumulate resistance factors associated with chemo/immunotherapy, ultimately affecting prognosis and treatment outcomes 106 . Given that AML exhibits molecular heterogeneity, single‐cell techniques offer a potent means to gain critical insights into leukemia initiation, evolution, and recurrence 107 .…”

“…Sc‐seq techniques are with an enormous impact, offering unique opportunities to reveal the heterogeneity in tumors, identify uncommon cells, and follow the evolution of clones 83 . Profiling intratumoral genetic and epigenetic heterogeneity at single‐cell resolution has the potential to uncover clones that amass resistance factors against chemotherapy or immunotherapy, modulating prognosis and response to treatment 106 . Revealing the unique features of single cells, including the proliferation, self‐renewal, and resistance mechanisms, may assist in improving the identification of the targeted cluster 83 .…”

The contribution of cell hashing for single-cell analysis of acute leukemia

“…As a consequence, improvement of AML prognosis via the development of individualized therapeutic schedules that take into account the initial heterogeneity of AMLs and the possibilities of clonal drift over time (i.e. the spatio-temporal heterogeneity of AML blasts and leukemia stem cells or LSCs) is required [5,6].…”