A Transcriptomic Continuum of Differentiation Arrest in Acute Leukemia

Abstract

Introduction: Traditional classification of acute lymphoblastic and myeloid leukemias (ALLs and AMLs) remains heavily based on phenotypic resemblance to normal hematopoietic precursors of the respective lineages. This framework can provide diagnostic challenges for immunophenotypically heterogeneous immature leukemias, which often have poor responses to treatment. This system also takes little account of modern concepts of hematopoietic identity that are mainly based on transcriptional signature identification and functional assays. Recent advances in genome-wide analytical methods developed to reconstruct landscapes of normal differentiation now provide an opportunity to re-evaluate traditional binary approaches to myeloid and lymphoid lineage assignment in leukemia. Methods: We used novel computational tools, including the recently described Iterative Clustering and Guide Gene Selection (ICGS) method to perform transcriptional analyses of a series of 125 T-ALLs and AMLs, which comprised a high proportion of phenotypically immature cases (53.1% and 40.8% respectively). The leukemias were additionally characterized by targeted next generation sequencing (NGS). ICGS was also used to analyze independent adult and pediatric T-ALL cohorts. Results: There was significant overlap in gene expression between leukemias of different diagnostic categories. In contrast to traditional clustering methods, ICGS analysis permitted unbiased classification of acute leukemias along a continuum of hematopoietic differentiation, according to the expression of a limited number of lineage-discriminating guide genes that defined hematopoietic cell expression modules. While AMLs and T-ALLs at either end of the differentiation spectrum showed specific enrichment for transcriptional signatures of the corresponding lineage precursors, leukemias that were arrested at the myeloid/ T-lymphoid interface either showed no clear evidence of mature T-lymphoid or mature myeloid identity, or had incomplete Hematopoietic Stem and Progenitor Cell (HSPC) and mature myeloid cell profiles. NGS analysis revealed that the spectrum of differentiation arrest defined by ICGS is only partially paralleled by underlying mutational genotype. Notably, interface leukemias originally diagnosed as T-ALL were significantly more likely to have PTEN mutations than the rest of the T-ALL cohort (60% v 6.7%, p=0.0151), while RUNX1-mutated AMLs were restricted to interface clusters. We found that interface leukemias 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 (ETPs). Within interface leukemias, enrichment for lymphoid progenitor population signatures including multi-lymphoid progenitors (MLPs), lymphoid-mono-dendritic progenitors (LMDPs), T-oriented CD127- and B-oriented CD127+ early lymphoid progenitors (ELPs) from an umbilical cord blood humanized mouse model and early B-cell progenitors, was more likely in cases that were originally diagnosed as AML, rather than T-ALL. In addition, transcriptional resemblance to both B/myeloid and T/myeloid mixed phenotype acute leukemias (MPALs) was primarily driven by AMLs within these interface clusters, suggesting that these cases demonstrate significant lymphoid transcriptional orientation. Conclusion: Our results suggest that traditional binary approaches to leukemia categorization are reductive, and that leukemias arrested at the T-lymphoid/ myeloid interface exhibit significant transcriptional heterogeneity. These data also provide evidence that a subset of leukemias originally diagnosed as AML may be more likely to arise from lymphoid-oriented progenitors and/or be arrested at an early stage of lymphoid orientation than is currently recognized. We believe that better identification of interface acute leukemias will allow improved evaluation of appropriate therapeutic options for these cases. Disclosures Boissel: NOVARTIS: Consultancy. Laurenti:GSK: Research Funding.