Thinking Outside the Box: Indirect Myc Modulation in Canine B-Cell Lymphoma.
Luca LicenziatoEugenio MazzoneChiara TarantelliPaolo AccorneroAndrea RinaldiSara DivariWilfred LeungSuzin WebbRaffaella De MariaLuca AresuPublished in: Animals : an open access journal from MDPI (2024)
B-cell lymphomas (BCL) is the most frequent hematological cancer in dogs. Treatment typically consists of chemotherapy, with CHOP-based protocols. However, outcome remains generally poor, urging the exploration of new therapeutic strategies with a targeted approach. Myc transcription factor plays a crucial role in regulating cellular processes, and its dysregulation is implicated in numerous human and canine malignancies, including canine BCL (cBCL). This study aims to evaluate the efficacy of indirectly inhibiting Myc in cBCL using BI2536 and MZ1 compounds in two in vitro models (CLBL-1 and KLR-1201). Both BI2536 and MZ1, alone and combined, affected cell viability in a significant concentration- and time-dependent manner. Western Blot revealed an upregulation of PLK1 expression in both cell lines upon treatment with BI2536, in association with a reduction in c-Myc protein levels. Conversely, MZ1 led to a decrease in its primary target, BRD4, along with a reduction in c-Myc. Furthermore, BI2536, both alone and in combination with MZ1, induced larger transcriptomic changes in cells compared to MZ1 alone, primarily affecting MYC target genes and genes involved in cell cycle regulation. These data underscore the potential role of Myc as therapeutic target in cBCL, providing a novel approach to indirectly modulate this molecule.
Keyphrases
- transcription factor
- cell cycle
- cell proliferation
- poor prognosis
- dna binding
- diffuse large b cell lymphoma
- signaling pathway
- induced apoptosis
- genome wide identification
- endothelial cells
- south africa
- single cell
- combination therapy
- electronic health record
- big data
- genome wide
- young adults
- drug induced
- risk assessment
- radiation therapy
- cell cycle arrest
- endoplasmic reticulum stress
- deep learning
- rna seq
- data analysis
- lymph node metastasis
- cancer therapy