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Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set

Overview of attention for article published in BMC Medicine, October 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

blogs
1 blog
twitter
9 X users
patent
4 patents
facebook
1 Facebook page

Citations

dimensions_citation
108 Dimensions

Readers on

mendeley
143 Mendeley
citeulike
4 CiteULike
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Title
Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set
Published in
BMC Medicine, October 2016
DOI 10.1186/s12916-016-0705-4
Pubmed ID
Authors

Jason Roszik, Lauren E. Haydu, Kenneth R. Hess, Junna Oba, Aron Y. Joon, Alan E. Siroy, Tatiana V. Karpinets, Francesco C. Stingo, Veera Baladandayuthapani, Michael T. Tetzlaff, Jennifer A. Wargo, Ken Chen, Marie-Andrée Forget, Cara L. Haymaker, Jie Qing Chen, Funda Meric-Bernstam, Agda K. Eterovic, Kenna R. Shaw, Gordon B. Mills, Jeffrey E. Gershenwald, Laszlo G. Radvanyi, Patrick Hwu, P. Andrew Futreal, Don L. Gibbons, Alexander J. Lazar, Chantale Bernatchez, Michael A. Davies, Scott E. Woodman

Abstract

While clinical outcomes following immunotherapy have shown an association with tumor mutation load using whole exome sequencing (WES), its clinical applicability is currently limited by cost and bioinformatics requirements. We developed a method to accurately derive the predicted total mutation load (PTML) within individual tumors from a small set of genes that can be used in clinical next generation sequencing (NGS) panels. PTML was derived from the actual total mutation load (ATML) of 575 distinct melanoma and lung cancer samples and validated using independent melanoma (n = 312) and lung cancer (n = 217) cohorts. The correlation of PTML status with clinical outcome, following distinct immunotherapies, was assessed using the Kaplan-Meier method. PTML (derived from 170 genes) was highly correlated with ATML in cutaneous melanoma and lung adenocarcinoma validation cohorts (R(2) = 0.73 and R(2) = 0.82, respectively). PTML was strongly associated with clinical outcome to ipilimumab (anti-CTLA-4, three cohorts) and adoptive T-cell therapy (1 cohort) clinical outcome in melanoma. Clinical benefit from pembrolizumab (anti-PD-1) in lung cancer was also shown to significantly correlate with PTML status (log rank P value < 0.05 in all cohorts). The approach of using small NGS gene panels, already applied to guide employment of targeted therapies, may have utility in the personalized use of immunotherapy in cancer.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 143 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
Unknown 142 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 35 24%
Student > Ph. D. Student 15 10%
Other 14 10%
Student > Bachelor 12 8%
Student > Master 10 7%
Other 30 21%
Unknown 27 19%
Readers by discipline Count As %
Medicine and Dentistry 35 24%
Biochemistry, Genetics and Molecular Biology 32 22%
Agricultural and Biological Sciences 18 13%
Unspecified 8 6%
Immunology and Microbiology 8 6%
Other 11 8%
Unknown 31 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 05 March 2024.
All research outputs
#1,940,219
of 25,508,813 outputs
Outputs from BMC Medicine
#1,368
of 4,036 outputs
Outputs of similar age
#33,661
of 321,082 outputs
Outputs of similar age from BMC Medicine
#28
of 70 outputs
Altmetric has tracked 25,508,813 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,036 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 45.8. This one has gotten more attention than average, scoring higher than 66% 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 321,082 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 70 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 61% of its contemporaries.