Immune checkpoints PD1/PDL1, TIM3/GAL9 and key immune mediators landscape reveal differential expression dynamics on

María Jazmín Toloza1, Marco Lincango1, María Fernanda Camacho1

  • 1Laboratorio de Genética Hematológica, Instituto de Medicina Experimental, IMEX-CONICET/ Academia Nacional de Medicina, Pacheco de Melo 3081, Ciudad Autónoma de Buenos Aires, C1425AUM, Argentina.

Annals of Hematology
|November 6, 2024
PubMed

Insights

Chronic myeloid leukemia (CML) patients show impaired immune systems, which improve with tyrosine kinase inhibitor treatment. This study tracked immune gene expression in CML patients on imatinib, revealing key changes related to treatment response.

Area of Science:

  • Immunology
  • Hematology
  • Oncology

Background:

  • Chronic myeloid leukemia (CML) is characterized by immune system impairment, affecting anti-tumor responses.
  • Maximal immune recovery in CML patients is linked to deep molecular responses achieved with tyrosine kinase inhibitors (TKIs).

Purpose of the Study:

  • To investigate the dynamic expression patterns of 19 key immune mediators in CML patients during their first year of imatinib treatment.
  • To correlate immune gene expression profiles with treatment response and molecular outcomes in CML.

Main Methods:

  • Gene expression analysis of 19 immune mediators in 171 peripheral blood samples from 89 CML patients and 52 healthy donors.
  • Longitudinal monitoring of 43 CML patients over a one-year period on imatinib therapy.
  • Univariate, unsupervised, and multivariate analyses to assess gene expression dynamics and treatment response.

Main Results:

  • Most immune mediators were initially diminished in CML patients, with exceptions like TNF, ARG1, and IL4.
  • Immune mediator levels generally normalized during treatment, with transient increases in TNF and IL6 at 3 months, particularly in optimal responders.
  • Non-optimal responders showed elevated ARG1 and a shift from PD1/PDL1 to TIM3/GAL9 immune checkpoint dominance over 12 months.

Conclusions:

  • Longitudinal immune gene expression profiling in CML patients on imatinib provides insights into immune recovery dynamics.
  • Immune mediator expression patterns, particularly ARG1 and immune checkpoints, may distinguish between optimal and non-optimal treatment responses in CML.
  • Understanding these immune dynamics could inform therapeutic strategies and improve outcomes for CML patients.

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