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Vol. 47. Núm. S3.
HEMO 2025 / III Simpósio Brasileiro de Citometria de Fluxo
(Outubro 2025)
Vol. 47. Núm. S3.
HEMO 2025 / III Simpósio Brasileiro de Citometria de Fluxo
(Outubro 2025)
ID - 750
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THE GAB2 NETWORK IN ACTION: UNVEILING GAB2, GRB2, PIK3R1, AND LYN IN CHRONIC MYELOID LEUKEMIA
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D Kusma Wosniakia, B Nichele Kusmaa, AM Marina, M de Marchia, E Cilião Munhozb, JS de Holanda Fariasb, E Batista Mendesa, S Halbachc, M Nóbrega Aokia, DL Zanettea
a Laboratory for Applied Science and Technology in Health, Instituto Carlos Chagas (ICC), Fundação Oswaldo Cruz (Fiocruz), Curitiba, Brazil
b Hospital Erasto Gaertner (HEG), Curitiba, Brazil
c Institute of Molecular Medicine, ZBMZ, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
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Vol. 47. Núm S3

HEMO 2025 / III Simpósio Brasileiro de Citometria de Fluxo

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Introduction

Chronic Myeloid Leukemia (CML) is a myeloproliferative disorder driven by the BCR::ABL1 fusion kinase, resulting from a t(9;22) translocation. Tyrosine kinase inhibitors (TKIs) revolutionized CML therapy, yet some patients develop resistance or show a suboptimal response. While ABL1 mutations underlie BCR::ABL1-dependent resistance, independent mechanisms remain unclear. GAB2, a key adaptor protein downstream of growth factor receptors and BCR::ABL1, activates MAPK and PI3K pathways, contributing to CML pathogenesis and TKI resistance.

Objectives

To evaluate the role of GAB2 as potential biomerkers in CML and its interacting network.

Material and methods

Potential functional partners of GAB2 were evaluated using the STRING database and transcriptomic datasets from GEO database (GEO ID: GSE33075). GAB2 itself and its interacting partners (GRB2, PIK3R1 and LYN) were analysed using qPCR in peripheral blood samples from CML patients in distinct stages of the disease: Diagnosis, Treatment-free remission (TFR), Imatinib - Good therapy response (Imatinib-GTR), Imatinib - Bad therapy response (Imatinib-BTR), patients with T315I mutation (T315I), and health controls (HC). Statistical models (Kruskall-Wallis, Dunn’s post-test, Pearson Correlation and Simple Linear regression) were performed to evaluate the potential of the network.

Results

String interaction database revealed eleven proteins were associated to GAB2, which were evaluated in the GEO dataset, from which GAB2, GRB2, PIK3R1 and LYN were selected for qPCR analysis in peripheral blood of CML patients. Interestingly, this analysis revealed that all those genes were highly expressed in samples of healthy controls (GAB2: P < 0.0001, GRB2: P < 0.0001 and LYN: P = 0.02) and in good responder groups, which included TFR and IM-GTR (for TFR: GAB2: P < 0.0001, GRB2: P < 0.0001, PIK3R1: P < 0.0001 and LYN: P < 0.0001 and for IM-GTR: GAB2: P < 0.0001, GRB2: P = 0.004, PIK3R1: P = 0.005 and LYN: p = 0.03), while showing lower expression in IM-BTR) (Figure A, clinical samples evaluation). Our results showed a linear regression in the decreasing expression pattern of GAB2 and partners for good therapy responders, diagnosis and bad therapy responders (R2 for GAB2: 0.9, GRB2: 0.9, PIK3R1: 0.8 and LYN: 0.7), demonstrating strongly the relation between the four genes and CML and the possible network of GAB2, GRB2, LYN and PIK3R1 (Figure B, linear regression). Additionally, samples from patients harbouring a BCR::ABL1 T315I mutation showed an up- regulation of the 4-gene panel when compared to IM-BTR, which did not harbour the T315I mutation (GAB2: p < 0.0001, GRB2: p < 0.0001, PIK3R1: p = 0.0003 and LYN: p = 0.02), showing a possible activity of GAB2 and partners as a BCR::ABL1-independent mechanism of resistance.

Discussion and conclusion

Our study reveals a strikingly coordinated expression pattern among GAB2 and its key interaction partners—GRB2, PIK3R1, and LYN—in clinical samples from CML patients. Notably, these patterns were not only consistent but also significantly distinct between good and poor responders to Imatinib. This strong correlation suggests that GAB2 and its network play a pivotal role in response modulation, shedding light on potential biomarkers or therapeutic targets for optimizing CML treatment.

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Hematology, Transfusion and Cell Therapy
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