Back

Gene Expression Profiling Unveils the Temporal Dynamics of CIGB-300-Regulated Transcriptome in AML Cells

Vazquez-Blomquist, D.; Ramon, A. C.; Rosales, M.; Perez, G. V.; Rosales, A.; Palenzuela, D.; Perera, Y.; Perea, S. E.

2023-03-08 cancer biology
10.1101/2023.03.06.530131 bioRxiv
Show abstract

Protein kinase CK2 activity is implicated in the pathogenesis of various hematological malignancies like Acute Myeloid Leukemia (AML) that remains challenging concerning treatment. Consequently, here we used Illumina HT-12 microarray gene RNA expression profiling to study the molecular events that might support the anti-leukemic effect of CIGB-300 peptide which targets both CK2 substrates and the CK2 catalytic subunits on HL-60 and OCI-AML3 cell lines. As a result, 185 and 812 genes appeared significantly modulated in HL-60 cells at 30 min and 3 h of incubation with CIGB-300 for p< 0.01 and FC>[boxv]1.5[boxv], respectively; while 222 and 332 genes appeared modulated in OCI-AML3 cells. Importantly, functional enrichment analysis evidenced that genes and transcription factors related to apoptosis, cell cycle, leukocyte differentiation, signaling by cytokines/interleukins, and NF-kB, TNF signaling pathways were significantly represented in AML cells transcriptomic profiles. The influence of CIGB-300 on these biological processes and pathways is dependent on the cellular background, in first place, and treatment duration. Of note, the impact of the peptide on NF-kB signaling was corroborated by the quantification of selected NF-kB target genes, as well as the measurement of p50 binding activity and soluble TNF- induction. Quantification of CSF1/M-CSF and CDKN1A/P21 by PCR supports peptide effects on differentiation and cell cycle. Overall, here we explore for the first time the temporal dynamics of the gene expression profile regulated by CIGB-300 and provide fresh molecular clues concerning the antineoplastic effect of CIGB-300 in two relevant AML backgrounds.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.