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Bioinformatic Description of Immunotherapy Targets for Pediatric T-Cell Leukemia and the Impact of Normal Gene Sets Used for Comparison

Overview of attention for article published in Frontiers in oncology, June 2014
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  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

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Title
Bioinformatic Description of Immunotherapy Targets for Pediatric T-Cell Leukemia and the Impact of Normal Gene Sets Used for Comparison
Published in
Frontiers in oncology, June 2014
DOI 10.3389/fonc.2014.00134
Pubmed ID
Authors

Rimas J. Orentas, Jessica Nordlund, Jianbin He, Sivasish Sindiri, Crystal Mackall, Terry J. Fry, Javed Khan

Abstract

Pediatric lymphoid leukemia has the highest cure rate of all pediatric malignancies, yet due to its prevalence, still accounts for the majority of childhood cancer deaths and requires long-term highly toxic therapy. The ability to target B-cell ALL with immunoglobulin-like binders, whether anti-CD22 antibody or anti-CD19 CAR-Ts, has impacted treatment options for some patients. The development of new ways to target B-cell antigens continues at rapid pace. T-cell ALL accounts for up to 20% of childhood leukemia but has yet to see a set of high-value immunotherapeutic targets identified. To find new targets for T-ALL immunotherapy, we employed a bioinformatic comparison to broad normal tissue arrays, hematopoietic stem cells (HSC), and mature lymphocytes, then filtered the results for transcripts encoding plasma membrane proteins. T-ALL bears a core T-cell signature and transcripts encoding TCR/CD3 components and canonical markers of T-cell development predominate, especially when comparison was made to normal tissue or HSC. However, when comparison to mature lymphocytes was also undertaken, we identified two antigens that may drive, or be associated with leukemogenesis; TALLA-1 and hedgehog interacting protein. In addition, TCR subfamilies, CD1, activation and adhesion markers, membrane-organizing molecules, and receptors linked to metabolism and inflammation were also identified. Of these, only CD52, CD37, and CD98 are currently being targeted clinically. This work provides a set of targets to be considered for future development of immunotherapies for T-ALL.

X Demographics

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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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Korea, Republic of 1 3%
United States 1 3%
Portugal 1 3%
Germany 1 3%
Unknown 36 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 33%
Student > Ph. D. Student 11 28%
Student > Bachelor 4 10%
Student > Master 3 8%
Professor 1 3%
Other 3 8%
Unknown 5 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 28%
Biochemistry, Genetics and Molecular Biology 7 18%
Medicine and Dentistry 5 13%
Immunology and Microbiology 4 10%
Engineering 2 5%
Other 7 18%
Unknown 4 10%
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 25 June 2014.
All research outputs
#16,720,137
of 25,371,288 outputs
Outputs from Frontiers in oncology
#6,608
of 22,414 outputs
Outputs of similar age
#140,076
of 244,218 outputs
Outputs of similar age from Frontiers in oncology
#37
of 96 outputs
Altmetric has tracked 25,371,288 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 22,414 research outputs from this source. They receive a mean Attention Score of 3.0. This one has gotten more attention than average, scoring higher than 64% of its peers.
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 244,218 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 96 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.