Skip to content
DraconiticResearch
Search Sources API
197,768 studies31 sourcesUpdated 49 min ago
Peer-reviewedCC BYHematology, Transfusion and Cell Therapy

AN IMPAIRED DNAM-1/NKP80 NK-CELL ACTIVATION AND T-CELL EXHAUSTION PROFILE AT DIAGNOSIS PRECEDE SUBOPTIMAL EARLY MOLECULAR RESPONSE IN CML

2 more authors
  1. 1Hematology, Hemotherapy and Cell Therapy Division, Department of Medical Imaging, Hematology, and Oncology, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil
  2. 2Division of Hematology and Oncology, Department of Medicine, University of Alabama at Birmingham, United States
  3. 3Hematology and Hemotherapy Center, University of Campinas, Campinas, SP, Brazil

Abstract

In Chronic Myeloid Leukemia (CML), early risk assessment traditionally relies on clinical scoring systems such as Sokal and ELTS, which do not capture host immune surveillance, a potential determinant of tyrosine kinase inhibitor (TKI) efficacy. Early identification of patients unlikely to achieve optimal molecular response may be particularly relevant when rapid disease control is clinically desirable. While TKIs modulate cytotoxic responses, the utility of baseline NK and T-cell profiles for early risk stratification remains unexplored. We hypothesized that baseline NK- and T-cell profiles could identify patients at risk of early suboptimal response to TKI therapy. We prospectively evaluated peripheral blood samples from 15 CML patients treated with Imatinib in a Brazilian public healthcare setting across four longitudinal timepoints: diagnosis (DX), 6, 9, and 12 months, alongside healthy donors (HD, n = 19). According to ELN response criteria at 12 months (BCR::ABL1 IS ≤ 0.1%), patients were stratified into Optimal (n = 7) and Warning/Non-Optimal (n = 8) response groups. Baseline clinical risk scores (Sokal and ELTS), age, and sex did not differ between groups. Long-term follow-up data have continuously been collected. NK and T-cell subpopulations, functional maturation, activating receptors, and immune checkpoints were assessed by multiparametric flow cytometry. Patients who subsequently developed a warning response displayed a distinct immune signature already detected at diagnosis. As compared to optimal responders and HDs, those with non-optimal response combined a shift toward innate cell immaturity, with reduced cytotoxic (CD56dim) and mature (CD57+) NK cells, with adaptive alterations including reduced CD8+ effector memory and increased CD8+ naïve T cells. Baseline expression of activating and maturation-associated NK markers, including DNAM1+ NK and NKp80+ cells, was significantly reduced in Warning/Non-Optimal responders, with trends toward lower NKG2D and NKp46. During therapy, only optimal responders progressively reconstituted NKp80 expression back to healthy levels by 12 months. Classical NK inhibitory receptors KIR2DL1, NKG2A, and TIGIT did not discriminate response groups across time. Warning/Non-Optimal responders also displayed elevated baseline PD-1+ and CTLA-4+ T cells. While PD-1 progressively normalized during TKI therapy in Optimal responders, it remained persistently elevated in non-optimal responders. Integration of baseline NK-cell maturation/activation (DNAM-1low and NKp80low NK) and T-cell exhaustion (PD1high) generated an immunological profile capable of discriminating patients acquiring early optimal molecular responses from those developing the warning status. Therefore, a DNAM-1high/NKP80high/PD-1low immune signature identified CML patients who achieved early optimal molecular response, whereas NK-cell immaturity and T-cell exhaustion characterized patients at risk of suboptimal response to Imatinib. In summary, preserved NK cell maturation and low T-cell exhaustion favors early BCR::ABL1 clearance. The novelty of this data is that the abnormal cytotoxic immunophenotype before TKI initiation predicts early response. Our findings highlight that the baseline immune profiling may therefore complement the conventional clinical scores and support personalized TKI management, particularly in resource-constrained healthcare settings, where TKIs are not fully available. Supported by CNPq and FAPESP.

Related

  1. p53 activation via pharmacologic MDM2 inhibition constrains exhaustion and enhances antitumor function of human CD8+ T cells
    Alexandra Boix de Jesus, Hy B. Dao, Anthony Imani +13
    Frontiers in ImmunologyPeer-reviewedCC BY 4.0Full textImmunologyCrossrefEurope PMCPMC
  2. Altered MAIT cell activation characteristics with impaired IL-10 and IL-17A response programs in active Crohn’s disease
    Journal of immunology (Baltimore, Md. : 1950)Peer-reviewedCC BYFull textImmunologyEurope PMC
  3. Thymosin α1 Augments CD8⁺ T-Cell Activation and Reverses Exhaustion In Vitro
    Smriti Mishra, Gaurang Telang, Anurag Sureshbabu +4
    Asian Pacific Journal of Cancer Prevention : APJCPPeer-reviewedCC BY-NC 4.0Full textImmunologyPMC
  4. SVEP1 couples adipose niche remodeling to macrophage activation and impaired metabolism in obesity
    N. Kislev, N. Kavin, R. Izgilov +1
    bioRxivPreprintCC BYFull textCell biologybioRxiv
  5. Multiple Sclerosis Patient Macrophages Impaired Metabolism Leads to an Altered Response to Activation Stimuli
    Jennifer Fransson, Corinne Bachelin, Farid Ichou +10
    Neurology Neuroimmunology & NeuroinflammationPeer-reviewedCC BY-NC-ND14 citedGeneral biologyHAL
BibTeX
@article{binelli2026impaired,
  title = {{AN IMPAIRED DNAM-1/NKP80 NK-CELL ACTIVATION AND T-CELL EXHAUSTION PROFILE AT DIAGNOSIS PRECEDE SUBOPTIMAL EARLY MOLECULAR RESPONSE IN CML}},
  author = {Larissa Sarri BINELLI and Leonardo Carvalho PALMA and Allana Guimarães de CARVALHO and Camila Araújo Bernardino GARCIA and Mariana MEDEIROS and Beatriz Lima ADJAFRE and Leticia Olops MARANI and Rafael Lopes PACCA and Isabela Catarin ARRUDA and Priscila Santos SCHEUCHER and Josiane Lilian Santos SCHIAVINATO and Robert Samuel WELNER and Kátia Borgia Barbosa PAGNANO and Lorena Lôbo de Figueiredo PONTES},
  journal = {Hematology, Transfusion and Cell Therapy},
  year = {2026},
  month = oct,
  doi = {10.1016/j.htct.2026.107478},
  url = {https://doi.org/10.1016/j.htct.2026.107478},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - AN IMPAIRED DNAM-1/NKP80 NK-CELL ACTIVATION AND T-CELL EXHAUSTION PROFILE AT DIAGNOSIS PRECEDE SUBOPTIMAL EARLY MOLECULAR RESPONSE IN CML
AU  - Larissa Sarri BINELLI
AU  - Leonardo Carvalho PALMA
AU  - Allana Guimarães de CARVALHO
AU  - Camila Araújo Bernardino GARCIA
AU  - Mariana MEDEIROS
AU  - Beatriz Lima ADJAFRE
AU  - Leticia Olops MARANI
AU  - Rafael Lopes PACCA
AU  - Isabela Catarin ARRUDA
AU  - Priscila Santos SCHEUCHER
AU  - Josiane Lilian Santos SCHIAVINATO
AU  - Robert Samuel WELNER
AU  - Kátia Borgia Barbosa PAGNANO
AU  - Lorena Lôbo de Figueiredo PONTES
PY  - 2026
DA  - 2026/10/23
JO  - Hematology, Transfusion and Cell Therapy
DO  - 10.1016/j.htct.2026.107478
UR  - https://doi.org/10.1016/j.htct.2026.107478
AB  - In Chronic Myeloid Leukemia (CML), early risk assessment traditionally relies on clinical scoring systems such as Sokal and ELTS, which do not capture host immune surveillance, a potential determinant of tyrosine kinase inhibitor (TKI) efficacy. Early identification of patients unlikely to achieve optimal molecular response may be particularly relevant when rapid disease control is clinically desirable. While TKIs modulate cytotoxic responses, the utility of baseline NK and T-cell profiles for early risk stratification remains unexplored. We hypothesized that baseline NK- and T-cell profiles could identify patients at risk of early suboptimal response to TKI therapy. We prospectively evaluated peripheral blood samples from 15 CML patients treated with Imatinib in a Brazilian public healthcare setting across four longitudinal timepoints: diagnosis (DX), 6, 9, and 12 months, alongside healthy donors (HD, n = 19). According to ELN response criteria at 12 months (BCR::ABL1 IS ≤ 0.1%), patients were stratified into Optimal (n = 7) and Warning/Non-Optimal (n = 8) response groups. Baseline clinical risk scores (Sokal and ELTS), age, and sex did not differ between groups. Long-term follow-up data have continuously been collected. NK and T-cell subpopulations, functional maturation, activating receptors, and immune checkpoints were assessed by multiparametric flow cytometry. Patients who subsequently developed a warning response displayed a distinct immune signature already detected at diagnosis. As compared to optimal responders and HDs, those with non-optimal response combined a shift toward innate cell immaturity, with reduced cytotoxic (CD56dim) and mature (CD57+) NK cells, with adaptive alterations including reduced CD8+ effector memory and increased CD8+ naïve T cells. Baseline expression of activating and maturation-associated NK markers, including DNAM1+ NK and NKp80+ cells, was significantly reduced in Warning/Non-Optimal responders, with trends toward lower NKG2D and NKp46. During therapy, only optimal responders progressively reconstituted NKp80 expression back to healthy levels by 12 months. Classical NK inhibitory receptors KIR2DL1, NKG2A, and TIGIT did not discriminate response groups across time. Warning/Non-Optimal responders also displayed elevated baseline PD-1+ and CTLA-4+ T cells. While PD-1 progressively normalized during TKI therapy in Optimal responders, it remained persistently elevated in non-optimal responders. Integration of baseline NK-cell maturation/activation (DNAM-1low and NKp80low NK) and T-cell exhaustion (PD1high) generated an immunological profile capable of discriminating patients acquiring early optimal molecular responses from those developing the warning status. Therefore, a DNAM-1high/NKP80high/PD-1low immune signature identified CML patients who achieved early optimal molecular response, whereas NK-cell immaturity and T-cell exhaustion characterized patients at risk of suboptimal response to Imatinib. In summary, preserved NK cell maturation and low T-cell exhaustion favors early BCR::ABL1 clearance. The novelty of this data is that the abnormal cytotoxic immunophenotype before TKI initiation predicts early response. Our findings highlight that the baseline immune profiling may therefore complement the conventional clinical scores and support personalized TKI management, particularly in resource-constrained healthcare settings, where TKIs are not fully available. Supported by CNPq and FAPESP.
SN  - 2531-1379
SN  - 2531-1387
ER  -