Mutations in protein tyrosine phosphatase non-receptor type 11 (PTPN11) have been considered late acquired mutations in acute myeloid leukemia (AML) development. Using single-cell DNA sequencing, we found that PTPN11 mutations can occur as initiating events in some patients with AML when accompanied by strong oncogenic drivers, commonly NPM1 mutations. The resulting AML has a diverse set of variably differentiated myeloid cells with few myeloid cells that lack leukemic mutations. The role of Ptpn11 as a codriver was confirmed in a murine model that exhibits an AML phenotype with a comparable immune diversity that is serially engraftable and reconstituted from early precursor cells. Furthermore, lineage-negative bone marrow cells from these mice reconstitute the full diversity of mature myeloid cells, and these cells exhibit an altered cytokine response after physiologic stimulation. Our work highlights how PTPN11-mutated AML is derived from a multitude of codominant and late acquired aberrations that have a previously unrecognized differentiated myeloid clonal expansion potentially contributing to pathogenesis of the disease.
Sydney Fobare, Chia Sharpe, Kate Quinn, Kinsey Bryant, Linde A. Miles, Robert L. Bowman, Carolyn Cheney, Casie Furby, Marissa Long, Kaytlynn Fyock, Ben Wronowski, James R. Lerma, Krzysztof Mrózek, Deedra Nicolet, Thomas M. Sesterhenn, Megan E. Johnstone, Jianmin Pan, Shesh N. Rai, Chandrashekhar Pasare, Nives Zimmermann, Wen-Mei Yu, Cheng-Kui Qu, Andrew Carroll, Richard Stone, Eunice S. Wang, Jonathan Kolitz, Bayard Powell, John P. Perentesis, Ann-Kathrin Eisfeld, Erin Hertlein, John C. Byrd
Usage data is cumulative from February 2026 through June 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 1,460 | 0 |
| 356 | 0 | |
| Figure | 574 | 0 |
| Table | 87 | 0 |
| Supplemental data | 190 | 0 |
| Citation downloads | 164 | 0 |
| Totals | 2,831 | 0 |
| Total Views | 2,831 | |
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.