Identification of Immunological Parameters as Predictive Biomarkers of Relapse in Patients with Chronic Myeloid Leukemia on Treatment-Free Remission

• Published in: Journal of clinical medicine Vol. 10; no. 1; p. 42
• Main Authors: Vigón, Lorena, Luna, Alejandro, Galán, Miguel, Rodríguez-Mora, Sara, Fuertes, Daniel, Mateos, Elena, Piris-Villaespesa, Miguel, Bautista, Guiomar, San José, Esther, Rivera-Torres, José, Steegmann, Juan Luis, de Ory, Fernando, Pérez-Olmeda, Mayte, Alcamí, José, Planelles, Vicente, López-Huertas, María Rosa, García-Gutiérrez, Valentín, Coiras, Mayte
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 25.12.2020; MDPI
• Subjects: Algorithms; Antibodies; Biomarkers; chronic myeloid leukemia; Clinical medicine; Cytotoxicity; Haplotypes; immunological response; Immunology; Kinases; Leukemia; Lymphocytes; Remission (Medicine); Software; treatment-free remission; United States > US; Indianapolis Indiana; immunological response; chronic myeloid leukemia; treatment-free remission
• ISSN: 2077-0383; 2077-0383
• DOI: 10.3390/jcm10010042

BCR-ABL is an aberrant tyrosine kinase responsible for chronic myeloid leukemia (CML). Tyrosine kinase inhibitors (TKIs) induce a potent antileukemic response mostly based on the inhibition of BCR-ABL, but they also increase the activity of Natural Killer (NK) and CD8+ T cells. After several years, patients may interrupt treatment due to sustained, deep molecular response. By unknown reasons, half of the patients relapse during treatment interruption, whereas others maintain a potent control of the residual leukemic cells for several years. In this study, several immunological parameters related to sustained antileukemic control were analyzed. According to our results, the features more related to poor antileukemic control were as follows: low levels of cytotoxic cells such as NK, (Natural Killer T) NKT and CD8±TCRγβ+ T cells; low expression of activating receptors on the surface of NK and NKT cells; impaired synthesis of proinflammatory cytokines or proteases from NK cells; and HLA-E*0103 homozygosis and KIR haplotype BX. A Random Forest algorithm predicted 90% of the accuracy for the classification of CML patients in groups of relapse or non-relapse according to these parameters. Consequently, these features may be useful as biomarkers predictive of CML relapse in patients that are candidates to initiate treatment discontinuation.