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Hedgehog pathway mutations drive oncogenic transformation in high-risk T-cell acute lymphoblastic leukemia

Overview of attention for article published in Leukemia, March 2018
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Title
Hedgehog pathway mutations drive oncogenic transformation in high-risk T-cell acute lymphoblastic leukemia
Published in
Leukemia, March 2018
DOI 10.1038/s41375-018-0097-x
Pubmed ID
Authors

Melissa A. Burns, Zi Wei Liao, Natsuko Yamagata, Gayle P. Pouliot, Kristen E. Stevenson, Donna S. Neuberg, Aaron R. Thorner, Matthew Ducar, Emily A. Silverman, Stephen P. Hunger, Mignon L. Loh, Stuart S. Winter, Kimberly P. Dunsmore, Brent Wood, Meenakshi Devidas, Marian H. Harris, Lewis B. Silverman, Stephen E. Sallan, Alejandro Gutierrez

Abstract

The role of Hedgehog signaling in normal and malignant T-cell development is controversial. Recently, Hedgehog pathway mutations have been described in T-ALL, but whether mutational activation of Hedgehog signaling drives T-cell transformation is unknown, hindering the rationale for therapeutic intervention. Here, we show that Hedgehog pathway mutations predict chemotherapy resistance in human T-ALL, and drive oncogenic transformation in a zebrafish model of the disease. We found Hedgehog pathway mutations in 16% of 109 childhood T-ALL cases, most commonly affecting its negative regulator PTCH1. Hedgehog mutations were associated with resistance to induction chemotherapy (P = 0.009). Transduction of wild-type PTCH1 into PTCH1-mutant T-ALL cells induced apoptosis (P = 0.005), a phenotype that was reversed by downstream Hedgehog pathway activation (P = 0.007). Transduction of most mutant PTCH1, SUFU, and GLI alleles into mammalian cells induced aberrant regulation of Hedgehog signaling, indicating that these mutations are pathogenic. Using a CRISPR/Cas9 system for lineage-restricted gene disruption in transgenic zebrafish, we found that ptch1 mutations accelerated the onset of notch1-induced T-ALL (P = 0.0001), and pharmacologic Hedgehog pathway inhibition had therapeutic activity. Thus, Hedgehog-activating mutations are driver oncogenic alterations in high-risk T-ALL, providing a molecular rationale for targeted therapy in this disease.

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 58 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 16%
Student > Master 8 14%
Student > Bachelor 8 14%
Student > Doctoral Student 7 12%
Student > Ph. D. Student 5 9%
Other 10 17%
Unknown 11 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 28%
Medicine and Dentistry 9 16%
Immunology and Microbiology 4 7%
Agricultural and Biological Sciences 3 5%
Neuroscience 3 5%
Other 7 12%
Unknown 16 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 April 2018.
All research outputs
#15,746,742
of 24,003,070 outputs
Outputs from Leukemia
#4,187
of 5,213 outputs
Outputs of similar age
#204,296
of 335,601 outputs
Outputs of similar age from Leukemia
#67
of 97 outputs
Altmetric has tracked 24,003,070 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,213 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.3. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 335,601 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 97 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.