ETP-ALL cells have distinct transcriptional profile. (A) Schematic depicting the cohort, sample collection, processing and sorting of cells for single-cell transcriptional profiling using SMART-seq2 protocol. (B) t-SNE of the processed single-cell RNA-seq gene expression data reveals distinct patient-specific clusters along with heterogeneous clusters. (C) Clusters were further analyzed using PAGODA2 to identify the cell type of individual cells. (D) Correlation distance matrix (1-Pearson correlation coefficient) derived from normalized gene expression values of individual malignant cells. The silhouette plot on top of the matrix depicts the uniqueness of each of the patient-specific malignant clusters. (E) Marker gene analyses identify heterogeneous clusters as CD4⁺ T cells, CD8⁺ T cells, natural killer (NK) cells, B cells, and myeloid cells. Expression of the top marker genes for each of the clusters containing normal cells is depicted as heatmap. (F) Cells from normal donors are highlighted in the heatmap (top) and fall into normal cell clusters. Malignant clusters identified by calling of those pathogenic variants (SNVs and CNVs) in single cells that were identified in individual patients by clinical targeted sequencing (middle; Table 1). Expression of transcription factors (TFs) distinguishing malignant cells from nonmalignant cells sequenced in this study (as inferred from random forest model). *NFE2 was ranked lower when only untreated leukemic cells were used to build the model, whereas *BCL11A was ranked higher.