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Usage Information

ATM-dependent DNA damage response constrains cell growth and drives clonal hematopoiesis in telomere biology disorders
Christopher M. Sande, … , Timothy S. Olson, Daria V. Babushok
Christopher M. Sande, … , Timothy S. Olson, Daria V. Babushok
Published April 3, 2025
Citation Information: J Clin Invest. 2025;135(8):e181659. https://doi.org/10.1172/JCI181659.
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Research Article Hematology Oncology Article has an altmetric score of 15

ATM-dependent DNA damage response constrains cell growth and drives clonal hematopoiesis in telomere biology disorders

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Abstract

Telomere biology disorders (TBDs) are genetic diseases caused by defective telomere maintenance. TBD patients often develop bone marrow failure and have an increased risk of myeloid neoplasms. To better understand the factors underlying hematopoietic outcomes in TBD, we comprehensively evaluated acquired genetic alterations in hematopoietic cells from 166 pediatric and adult TBD patients. Of these patients, 47.6% (28.8% of children, 56.1% of adults) had clonal hematopoiesis. Recurrent somatic alterations involved telomere maintenance genes (7.6%), spliceosome genes (10.4%, mainly U2AF1 p.S34), and chromosomal alterations (20.2%), including 1q gain (5.9%). Somatic variants affecting the DNA damage response (DDR) were identified in 21.5% of patients, including 20 presumed loss-of-function variants in ataxia-telangiectasia mutated (ATM). Using multimodal approaches, including single-cell sequencing, assays of ATM activation, telomere dysfunction-induced foci analysis, and cell-growth assays, we demonstrate telomere dysfunction–induced activation of the ATM-dependent DDR pathway with increased senescence and apoptosis in TBD patient cells. Pharmacologic ATM inhibition, modeling the effects of somatic ATM variants, selectively improved TBD cell fitness by allowing cells to bypass DDR-mediated senescence without detectably inducing chromosomal instability. Our results indicate that ATM-dependent DDR induced by telomere dysfunction is a key contributor to TBD pathogenesis and suggest dampening hyperactive ATM-dependent DDR as a potential therapeutic intervention.

Authors

Christopher M. Sande, Stone Chen, Dana V. Mitchell, Ping Lin, Diana M. Abraham, Jessie Minxuan Cheng, Talia Gebhard, Rujul J. Deolikar, Colby Freeman, Mary Zhou, Sushant Kumar, Michael Bowman, Robert L. Bowman, Shannon Zheng, Bolormaa Munkhbileg, Qijun Chen, Natasha L. Stanley, Kathy Guo, Ajibike Lapite, Ryan Hausler, Deanne M. Taylor, James Corines, Jennifer J.D. Morrissette, David B. Lieberman, Guang Yang, Olga Shestova, Saar Gill, Jiayin Zheng, Kelcy Smith-Simmer, Lauren G. Banaszak, Kyle N. Shoger, Erica F. Reinig, Madilynn Peterson, Peter Nicholas, Amanda J. Walne, Inderjeet Dokal, Justin P. Rosenheck, Karolyn A. Oetjen, Daniel C. Link, Andrew E. Gelman, Christopher R. Reilly, Ritika Dutta, R. Coleman Lindsley, Karyn J. Brundige, Suneet Agarwal, Alison A. Bertuch, Jane E. Churpek, Laneshia K. Tague, F. Brad Johnson, Timothy S. Olson, Daria V. Babushok

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Usage data is cumulative from April 2025 through June 2025.

Usage JCI PMC
Text version 1,688 90
PDF 338 35
Figure 230 0
Table 11 0
Supplemental data 135 13
Citation downloads 24 0
Totals 2,426 138
Total Views 2,564

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.

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