Hematopoietic architecture drives biological and metabolic heterogeneity and predicts treatment-free remission outcomes in chronic myeloid leukemia

I Isabelle De Araujo (1CHU de Toulouse Institut Universitaire du Cancer - Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France) M Mathilde Marlas (1CHU de Toulouse Institut Universitaire du Cancer - Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France) M Marie-Laure Nicolau (1CHU de Toulouse Institut Universitaire du Cancer - Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France) I Inès Vergnolle (1CHU de Toulouse Institut Universitaire du Cancer - Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France) L Lucie Donaty (1CHU de Toulouse Institut Universitaire du Cancer - Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France) I Isabelle Luquet (26Laboratory of Hematology, Centre Hospitalier Universitaire de Toulouse, Toulouse, France) A Alban Canali (1CHU de Toulouse Institut Universitaire du Cancer - Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France) L Lucie Rigolot (26Laboratory of Hematology, Centre Hospitalier Universitaire de Toulouse, Toulouse, France) L Laetitia Largeaud (1CHU de Toulouse Institut Universitaire du Cancer - Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France) Éric Delabesse (26Laboratory of Hematology, Centre Hospitalier Universitaire de Toulouse, Toulouse, France) V Véronique De Mas (3Centre de Recherches en Cancérologie de Toulouse, Université de Toulouse, INSERM U1037, Centre National de la Recherche Scientifique U5077, Toulouse, France) L Léopoldine Lapierre S Sarah Bertoli C Christian Récher J Jean-Emmanuel Sarry F Françoise Huguet (3Service d’Hématologie, Institut Universitaire du Cancer de Toulouse-Oncopole, Centre Hospitalier Universitaire de Toulouse, Toulouse, France) S Suzanne Tavitian F Francois Vergez (3Centre de Recherches en Cancérologie de Toulouse, Université de Toulouse, INSERM U1037, Centre National de la Recherche Scientifique U5077, Toulouse, France)

Abstract

Abstract Introduction Hematopoiesis is a series of physiological processes that ensure the continuous production of blood cells and that is based on a hierarchical organization of heterogeneous cell populations.Chronic myeloid leukemia (CML) is a malignant hematologic disorder driven exclusively by the BCR::ABL1 fusion gene that impacts key stages of the hematopoietic processes. We dissected the organization of stem and progenitor cells in a cohort of 180 patients to better assess differences in biological pathways and therapeutic responses in this myeloid malignancy driven by a single oncogenic event.MethodsBetween 2008 and 2019, 180 CML patients (>18 years) were included in the StemFlow database of Toulouse University Hospital. Multi-parameter flow cytometry (MFC) was performed at diagnosis on whole bone marrow (BM). Data on standardized 10-color staining combinations were acquired on Navios instruments analyzed using Kaluza (Beckman-Coulter). The combination comprised CD45, CD38, CD135 and CD45RA for CD34+ sub-population analysis.ResultsWe quantified 6 different stem (MPP, LMPP, EMP) and progenitor cell populations (CMP, GMP, MEP) of normal BM (n=36) and CML (n=180). MPP and CMP were the main CD34+CD38- stem and CD34+CD38+ progenitor cells in NBM and were under-represented in CML (2% vs 0.8% and 46% vs 24%, p<0.0001). The major CD34+ population in CML was the CD34+CD38+CD135-CD45RA- MEP (66.3% vs 22.5% in NBM, p<0.0001). This result was independently validated through gene signatures and transcriptomic data analyses.To explore the biological differences between NBM-MEP and CML-MEP, we exploited freely available transcriptomic databases of sorted cells. Transcriptomes of CML-MEP showed enrichment in OxPHOS gene signatures compared with NBM-MEP. Consistently, while the mitochondrial mass of CML-MEP was greater than that of NBM-MEP (p=0.016), the mitochondrial fitness was markedly impaired in CML-MEP, with higher mitochondrial ROS levels compared with NBM-MEP (p=0.0033 and p=0.034, respectively). Altogether, whereas CML-MEP retained their overall lineage identities, they underwent metabolic reprogramming in their OxPHOS state.Unsupervised hierarchical clustering followed by principal component analysis (PCA) identified the frequencies of the MPP and MEP populations as the main sources of variation across the CML samples. The BM of the 1st group (47% of the CML samples) had an abnormal differentiation pattern characterized by a major increased frequency of EMP and MEP (MEP-like pattern). In contrast, the BM of the 2nd group (53% of the CML) had a higher frequency of MPP, CMP and GMP (MPP-like pattern). MEP-like CML were better responders to TKI (median time to achieve MR was 3.9 vs 6.0 months p=0.0041; MMR was 9.0 vs 13.5m, p=0.0013; MR4 was 24.4 vs 48.0m, p<0.0001). In multivariate analyses, the MEP-like profile remained consistently and significantly associated with a shorter time to molecular response (time to MR4, HR=2.35, p<0.0001). ELTS score (HR=0.66, p=0.035), 1st gen TKI treatment (HR=0.63, p=0.034), and transcript type (HR=1.37, p=0.021) also showed significant associations, whereas age, Sokal score, ACA, and gender did not retain statistical significance.We next analyzed data from 66 patients (40 MEP-like and 26 MPP-like CML) who met the bio-clinical criteria for TKI discontinuation according to Fi-LMC recommendations. The majority of MEP-like CML patients maintained MMR (median time to MMR loss not reached, plateau at 58.9%, HR=0.28, p=0.0005). In contrast, MPP-like CML patients rapidly lost MMR (median of 4.3 months, plateau at 23.1%). Under these treatment discontinuation conditions, the MEP-like profile emerged as the only significant prognostic factor in the multivariate analysis, which included variables such as 5-y TKI treatment duration, sustained MR4>2 y, risk classification, TKI gen, transcript type, gender, and ACA. ConclusionThis study shows that leukemic hematopoiesis is biased toward a progenitor with a MEP-like phenotype and gene expression profile in CML. We provided biological and clinical evidence that CML is maintained by two distinct cellular organizations (MEP-like and MPP-like) linked to response to TKI therapy. These data suggest that the cellular architecture of CML should be considered as a biomarker for predicting intrinsic CML cell vulnerabilities and that OxPHOS metabolism could be targetable to increase the number of patients eligible to treatment discontinuation.

Article Details

Journal Blood
Volume / Issue Vol. 146, Issue Supplement 1
Published November 03, 2025
Pages 3787-3787
ISSN 0006-4971
Publisher Elsevier BV

Journal Info

Blood

Elsevier BV

ISSN: 0006-4971 Health Sciences

Authors (18)

I

Isabelle De Araujo

1CHU de Toulouse Institut Universitaire du Cancer - Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France

M

Mathilde Marlas

1CHU de Toulouse Institut Universitaire du Cancer - Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France

M

Marie-Laure Nicolau

1CHU de Toulouse Institut Universitaire du Cancer - Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France

I

Inès Vergnolle

1CHU de Toulouse Institut Universitaire du Cancer - Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France

L

Lucie Donaty

1CHU de Toulouse Institut Universitaire du Cancer - Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France

I

Isabelle Luquet

26Laboratory of Hematology, Centre Hospitalier Universitaire de Toulouse, Toulouse, France

A

Alban Canali

1CHU de Toulouse Institut Universitaire du Cancer - Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France

L

Lucie Rigolot

26Laboratory of Hematology, Centre Hospitalier Universitaire de Toulouse, Toulouse, France

L

Laetitia Largeaud

1CHU de Toulouse Institut Universitaire du Cancer - Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France

Éric Delabesse

26Laboratory of Hematology, Centre Hospitalier Universitaire de Toulouse, Toulouse, France

V

Véronique De Mas

3Centre de Recherches en Cancérologie de Toulouse, Université de Toulouse, INSERM U1037, Centre National de la Recherche Scientifique U5077, Toulouse, France

L

Léopoldine Lapierre

S

Sarah Bertoli

C

Christian Récher

J

Jean-Emmanuel Sarry

F

Françoise Huguet

3Service d’Hématologie, Institut Universitaire du Cancer de Toulouse-Oncopole, Centre Hospitalier Universitaire de Toulouse, Toulouse, France

S

Suzanne Tavitian

F

Francois Vergez

3Centre de Recherches en Cancérologie de Toulouse, Université de Toulouse, INSERM U1037, Centre National de la Recherche Scientifique U5077, Toulouse, France