Acute myeloid leukemia (AML) is the most common form of acute leukemia in adults. Long-term survival of patients with AML has changed little over the past decade, necessitating the identification and validation of new AML targets. Integration of genomic approaches with small-molecule and genetically based high-throughput screening holds the promise of improved discovery of candidate targets for cancer therapy. Here, we identified a role for glycogen synthase kinase 3α (GSK-3α) in AML by performing 2 independent small-molecule library screens and an shRNA screen for perturbations that induced a differentiation expression signature in AML cells. GSK-3 is a serine-threonine kinase involved in diverse cellular processes, including differentiation, signal transduction, cell cycle regulation, and proliferation. We demonstrated that specific loss of GSK-3α induced differentiation in AML by multiple measurements, including induction of gene expression signatures, morphological changes, and cell surface markers consistent with myeloid maturation. GSK-3α–specific suppression also led to impaired growth and proliferation in vitro, induction of apoptosis, loss of colony formation in methylcellulose, and anti-AML activity in vivo. Although the role of GSK-3β has been well studied in cancer development, these studies support a role for GSK-3α in AML.
Versha Banerji, Stacey M. Frumm, Kenneth N. Ross, Loretta S. Li, Anna C. Schinzel, Cynthia K. Hahn, Rose M. Kakoza, Kwan T. Chow, Linda Ross, Gabriela Alexe, Nicola Tolliday, Haig Inguilizian, Ilene Galinsky, Richard M. Stone, Daniel J. DeAngelo, Giovanni Roti, Jon C. Aster, William C. Hahn, Andrew L. Kung, Kimberly Stegmaier
Usage data is cumulative from January 2024 through January 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 462 | 105 |
86 | 51 | |
Figure | 204 | 31 |
Table | 29 | 0 |
Supplemental data | 55 | 5 |
Citation downloads | 37 | 0 |
Totals | 873 | 192 |
Total Views | 1,065 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.