The hypomethylating agent azacitidine (AZA) is used to treat higher-risk myelodysplastic syndromes (HR-MDS) and elderly patients with low-blast count acute myeloid leukemia (LBC-AML). Platelet recovery is an early predictor of AZA response. We prospectively studied the expression profile of transcription factors, critical for late megakaryopoiesis and changes in their expression after AZA treatment in patients with HR-MDS and LBC-AML enrolled in the BMT-AZA trial (EudraCT number 2010-019673-15). Twenty-five additional patients with low-risk (LR)-MDS were also studied. At the time of diagnosis, GATA2 mRNA levels were significantly higher in MDS as compared to controls, with increasing levels from LR- to HR-MDS/AML. RUNX1 expression was also significantly higher in MDS, as compared to controls, but no differences were found between LR- and HR-MDS. Looking at biomarkers of response, we found that patients AZA responsive had higher basal GATA1 and lower FLI1 expression, compared to those with stable or progressive disease after treatment. Univariate analysis showed that increased GATA2 mRNA expression was associated with a worse overall survival. Our findings suggest that high GATA2 expression is a poor prognostic marker for survival in patients with HR-MDS and LBC-AML treated with azacitidine. Moreover, GATA1 and FLI1 mRNA expression may predict response to AZA treatment.
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http://dx.doi.org/10.1016/j.leukres.2019.106191 | DOI Listing |
Proc Natl Acad Sci U S A
January 2025
State Key Laboratory of Wheat Improvement, College of Life Science, Shandong Agricultural University, Tai'an 271018, China.
In many plants, the asymmetric division of the zygote sets up the apical-basal body axis. In the cress , the zygote coexpresses regulators of the apical and basal embryo lineages, the transcription factors WOX2 and WRKY2/WOX8, respectively. WRKY2/WOX8 activity promotes nuclear migration, cellular polarity, and mitotic asymmetry of the zygote, which are hallmarks of axis formation in many plant species.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Institute of Science and Technology Austria, AT-3400 Klosterneuburg, Austria.
Biophysical constraints limit the specificity with which transcription factors (TFs) can target regulatory DNA. While individual nontarget binding events may be low affinity, the sheer number of such interactions could present a challenge for gene regulation by degrading its precision or possibly leading to an erroneous induction state. Chromatin can prevent nontarget binding by rendering DNA physically inaccessible to TFs, at the cost of energy-consuming remodeling orchestrated by pioneer factors (PFs).
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210.
The homo-dodecameric ring-shaped RNA binding attenuation protein (TRAP) from binds up to twelve tryptophan ligands (Trp) and becomes activated to bind a specific sequence in the 5' leader region of the operon mRNA, thereby downregulating biosynthesis of Trp. Thermodynamic measurements of Trp binding have revealed a range of cooperative behavior for different TRAP variants, even if the averaged apparent affinities for Trp have been found to be similar. Proximity between the ligand binding sites, and the ligand-coupled disorder-to-order transition has implicated nearest-neighbor interactions in cooperativity.
View Article and Find Full Text PDFPLoS Comput Biol
January 2025
Department of Computer Science, Colorado State University, Fort Collins, Colorado, United States of America.
Complex deep learning models trained on very large datasets have become key enabling tools for current research in natural language processing and computer vision. By providing pre-trained models that can be fine-tuned for specific applications, they enable researchers to create accurate models with minimal effort and computational resources. Large scale genomics deep learning models come in two flavors: the first are large language models of DNA sequences trained in a self-supervised fashion, similar to the corresponding natural language models; the second are supervised learning models that leverage large scale genomics datasets from ENCODE and other sources.
View Article and Find Full Text PDFDifferentiation of antigen-activated B cells into pro-proliferative germinal center (GC) B cells depends on the activity of the transcription factors MYC and BCL6, and the epigenetic writers DOT1L and EZH2. GCB-like Diffuse Large B Cell Lymphomas (GCB-DLBCLs) arise from GCB cells and closely resemble their cell of origin. Given the dependency of GCB cells on DOT1L and EZH2, we investigated the role of these epigenetic regulators in GCB-DLBCLs and observed that GCB-DLBCLs synergistically depend on the combined activity of DOT1L and EZH2.
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