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Prediction of chemo-response in serous ovarian cancer

Overview of attention for article published in Molecular Cancer, October 2016
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Title
Prediction of chemo-response in serous ovarian cancer
Published in
Molecular Cancer, October 2016
DOI 10.1186/s12943-016-0548-9
Pubmed ID
Authors

Jesus Gonzalez Bosquet, Andreea M. Newtson, Rebecca K. Chung, Kristina W. Thiel, Timothy Ginader, Michael J. Goodheart, Kimberly K. Leslie, Brian J. Smith

Abstract

Nearly one-third of serous ovarian cancer (OVCA) patients will not respond to initial treatment with surgery and chemotherapy and die within one year of diagnosis. If patients who are unlikely to respond to current standard therapy can be identified up front, enhanced tumor analyses and treatment regimens could potentially be offered. Using the Cancer Genome Atlas (TCGA) serous OVCA database, we previously identified a robust molecular signature of 422-genes associated with chemo-response. Our objective was to test whether this signature is an accurate and sensitive predictor of chemo-response in serous OVCA. We first constructed prediction models to predict chemo-response using our previously described 422-gene signature that was associated with response to treatment in serous OVCA. Performance of all prediction models were measured with area under the curves (AUCs, a measure of the model's accuracy) and their respective confidence intervals (CIs). To optimize the prediction process, we determined which elements of the signature most contributed to chemo-response prediction. All prediction models were replicated and validated using six publicly available independent gene expression datasets. The 422-gene signature prediction models predicted chemo-response with AUCs of ~70 %. Optimization of prediction models identified the 34 most important genes in chemo-response prediction. These 34-gene models had improved performance, with AUCs approaching 80 %. Both 422-gene and 34-gene prediction models were replicated and validated in six independent datasets. These prediction models serve as the foundation for the future development and implementation of a diagnostic tool to predict response to chemotherapy for serous OVCA patients.

Twitter Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 56 98%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 11 19%
Researcher 7 12%
Student > Ph. D. Student 6 11%
Student > Master 5 9%
Professor 4 7%
Other 13 23%
Unknown 11 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 19%
Agricultural and Biological Sciences 8 14%
Medicine and Dentistry 7 12%
Mathematics 5 9%
Unspecified 2 4%
Other 6 11%
Unknown 18 32%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 29 July 2017.
All research outputs
#12,135,455
of 15,918,484 outputs
Outputs from Molecular Cancer
#848
of 1,345 outputs
Outputs of similar age
#198,380
of 295,890 outputs
Outputs of similar age from Molecular Cancer
#40
of 69 outputs
Altmetric has tracked 15,918,484 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,345 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 29th percentile – i.e., 29% 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 295,890 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.