Omics Technologies to Decipher Regulatory Networks in Granulocytic Cell Differentiation.
Svetlana E NovikovaOlga TikhonovaLeonid KurbatovTatiana FarafonovaIgor VakhrushevAlexey LupatovKonstantin YaryginVictor G ZgodaPublished in: Biomolecules (2021)
Induced granulocytic differentiation of human leukemic cells under all-trans-retinoid acid (ATRA) treatment underlies differentiation therapy of acute myeloid leukemia. Knowing the regulation of this process it is possible to identify potential targets for antileukemic drugs and develop novel approaches to differentiation therapy. In this study, we have performed transcriptomic and proteomic profiling to reveal up- and down-regulated transcripts and proteins during time-course experiments. Using data on differentially expressed transcripts and proteins we have applied upstream regulator search and obtained transcriptome- and proteome-based regulatory networks of induced granulocytic differentiation that cover both up-regulated (HIC1, NFKBIA, and CASP9) and down-regulated (PARP1, VDR, and RXRA) elements. To verify the designed network we measured HIC1 and PARP1 protein abundance during granulocytic differentiation by selected reaction monitoring (SRM) using stable isotopically labeled peptide standards. We also revealed that transcription factor CEBPB and LYN kinase were involved in differentiation onset, and evaluated their protein levels by SRM technique. Obtained results indicate that the omics data reflect involvement of the DNA repair system and the MAPK kinase cascade as well as show the balance between the processes of the cell survival and apoptosis in a p53-independent manner. The differentially expressed transcripts and proteins, predicted transcriptional factors, and key molecules such as HIC1, CEBPB, LYN, and PARP1 may be considered as potential targets for differentiation therapy of acute myeloid leukemia.
Keyphrases
- transcription factor
- dna repair
- acute myeloid leukemia
- single cell
- dna damage
- oxidative stress
- gene expression
- induced apoptosis
- cell cycle arrest
- endothelial cells
- signaling pathway
- machine learning
- electronic health record
- diabetic rats
- bone marrow
- big data
- dna binding
- allogeneic hematopoietic stem cell transplantation
- binding protein
- climate change
- acute lymphoblastic leukemia
- cell therapy
- label free