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Genetic-based personalized treatment of MPN
nations of somatic mutations or proteins expressed by cel- lular subtypes and mechanisms of relapse or treatment resistance. As an illustration, the use of single-cell-level sequencing in a study of MF, conducted by Psaila and col- leagues, revealed megakaryocyte-biased hematopoiesis with megakaryocyte progenitors demonstrating distinct inflammatory and metabolic signatures, and increased expression of the surface antigen G6B (MPIG6B) on MF stem cells and progenitors (Figure 4).36 These findings raise the possibility of new therapies for MF, which could target
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the MF clone and MF-associated fibrosis. In CML, insights into the intratumoral heterogeneity of CML stem cells has revealed subgroups with distinct molecular signatures that are resistant to TKI.34 Furthermore novel molecular path- ways related metabolism and the bone marrow microenvi- ronment are being deciphered. Patients with advanced SM, in particular those with an associated hematologic malig- nancy, often have multilineage involvement by KIT and multimutated clones, which are associated with a poorer prognosis.27 Additionally, through single-cell analysis,
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Figure 4. Single-cell -omics demonstrate a trajectory for megakaryocyte-biased hematopoiesis in myelofibrosis. (A–D) Force-directed graphs (FDG) for aggregates of all control + myelofibrosis (MF) cells (A), MF only (B), control only (C), and control + down-sampled MF dataset (D). In (D), the left graph shows the lineage signature gene score and in the right graph cells are colored according to the donor type (healthy donors, blue; MF patient, red). Gene expression trajectories are visualized by superimposing the expression scores of lineage signature gene sets on the FDG. Gray cells represent uncommitted hematopoietic stem and progenitor cells or cells with expression of more than one lineage signature. (Published, with permission, from Psalia B, et al.36)
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