TGF-β/SMAD Pathway Is Modulated by miR-26b-5p: Another Piece in the Puzzle of Chronic Lymphocytic Leukemia Progression.
Maria Elena MarquezSandra SernboEugenia PayqueRita UriaJuan Pablo TosarJuliana QuerolCatalina BercaAngimar UrieperoDaniel PrietoDiego Alvarez-SaraviaAna Carolina OliverVictoria IrigoinGimena Dos SantosMaría Cecilia Guillermo EspositoAna Inés LandoniMarcelo A NavarreteFlorencia PalaciosPablo OppezzoPublished in: Cancers (2022)
Clinical and molecular heterogeneity are hallmarks of chronic lymphocytic leukemia (CLL), a neoplasm characterized by accumulation of mature and clonal long-lived CD5 + B-lymphocytes. Mutational status of the IgHV gene of leukemic clones is a powerful prognostic tool in CLL, and it is well established that unmutated CLLs (U-CLLs) have worse evolution than mutated cases. Nevertheless, progression and treatment requirement of patients can evolve independently from the mutational status. Microenvironment signaling or epigenetic changes partially explain this different behavior. Thus, we think that detailed characterization of the miRNAs landscape from patients with different clinical evolution could facilitate the understanding of this heterogeneity. Since miRNAs are key players in leukemia pathogenesis and evolution, we aim to better characterize different CLL behaviors by comparing the miRNome of clinically progressive U-CLLs vs. stable U-CLLs. Our data show up-regulation of miR-26b-5p, miR-106b-5p, and miR-142-5p in progressive cases and indicate a key role for miR-26b-5p during CLL progression. Specifically, up-regulation of miR-26b-5p in CLL cells blocks TGF-β/SMAD pathway by down-modulation of SMAD-4, resulting in lower expression of p21 -Cip1 kinase inhibitor and higher expression of c-Myc oncogene. This work describes a new molecular mechanism linking CLL progression with TGF-β modulation and proposes an alternative strategy to explore in CLL therapy.
Keyphrases
- chronic lymphocytic leukemia
- transforming growth factor
- epithelial mesenchymal transition
- poor prognosis
- multiple sclerosis
- single cell
- end stage renal disease
- acute myeloid leukemia
- stem cells
- chronic kidney disease
- ejection fraction
- dna methylation
- gene expression
- bone marrow
- low grade
- machine learning
- binding protein
- deep learning
- oxidative stress
- patient reported outcomes
- artificial intelligence
- single molecule
- patient reported
- genome wide identification