Phospho-Specific Flow Cytometry Reveals Signaling Heterogeneity in T-Cell Acute Lymphoblastic Leukemia Cell Lines.
Omar PerbelliniChiara CavalliniRoberto ChignolaMarilisa GalassoMaria T ScupoliPublished in: Cells (2022)
Several signaling pathways are aberrantly activated in T-ALL due to genetic alterations of their components and in response to external microenvironmental cues. To functionally characterize elements of the signaling network in T-ALL, here we analyzed ten signaling proteins that are frequently altered in T-ALL -namely Akt, Erk1/2, JNK, Lck, NF-κB p65, p38, STAT3, STAT5, ZAP70, Rb- in Jurkat, CEM and MOLT4 cell lines, using phospho-specific flow cytometry. Phosphorylation statuses of signaling proteins were measured in the basal condition or under modulation with H 2 O 2 , PMA, CXCL12 or IL7. Signaling profiles are characterized by a high variability across the analyzed T-ALL cell lines. Hierarchical clustering analysis documents that higher intrinsic phosphorylation of Erk1/2, Lck, ZAP70, and Akt, together with ZAP70 phosphorylation induced by H 2 O 2 , identifies Jurkat cells. In contrast, CEM are characterized by higher intrinsic phosphorylation of JNK and Rb and higher responsiveness of Akt to external stimuli. MOLT4 cells are characterized by higher basal STAT3 phosphorylation. These data document that phospho-specific flow cytometry reveals a high variability in intrinsic as well as modulated signaling networks across different T-ALL cell lines. Characterizing signaling network profiles across individual leukemia could provide the basis to identify molecular targets for personalized T-ALL therapy.
Keyphrases
- signaling pathway
- flow cytometry
- induced apoptosis
- cell proliferation
- acute lymphoblastic leukemia
- pi k akt
- cell cycle arrest
- magnetic resonance imaging
- cell death
- machine learning
- computed tomography
- acute myeloid leukemia
- single cell
- gene expression
- immune response
- big data
- artificial intelligence
- rna seq
- data analysis