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Dove Medical Press

The utilization of next-generation sequencing to detect somatic mutations and predict clinical prognosis of Chinese non-small cell lung cancer patients

Overview of attention for article published in OncoTargets and therapy, May 2018
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  • Good Attention Score compared to outputs of the same age (65th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

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1 X user
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7 patents
reddit
1 Redditor

Citations

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11 Dimensions

Readers on

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31 Mendeley
Title
The utilization of next-generation sequencing to detect somatic mutations and predict clinical prognosis of Chinese non-small cell lung cancer patients
Published in
OncoTargets and therapy, May 2018
DOI 10.2147/ott.s155995
Pubmed ID
Authors

Liming Cao, Long Long, Min Li, Huaping Yang, Pengbo Deng, Xinru Mao, Jianxing Xiang, Bing Li, Tengfei Zhang, Chengping Hu

Abstract

The development of next-generation sequencing (NGS) has revolutionized the understanding of oncogenesis of multiple types of cancer, including non-small cell lung cancer (NSCLC). However, there has been some debate over the utility of NGS for predicting patient prognosis and determining molecular targeted therapy. Therefore, we sought to demonstrate the numerous applications of NGS in the prognostic predictions and treatment of NSCLC patients. We performed NGS on either liquid or tissue tumor biopsies obtained from 53 NSCLC patients. The sequences were analyzed for oncogenic mutations, which were then correlated to clinical prognosis and smoking history. NGS of tumor biopsies detected both well-known driver mutations as well as rare or novel mutations. EGFR was the most frequently mutated gene, accounting for 32.4% (33/102) of the somatic mutations in this study. The EGFR mutations detected included rare variants such as EGFR exon 19 insertion (K745_E746insIPVAIK) and in cis H835L+L833V. Additionally, novel RET fusion mutations PCM1-RET and ADD3-RET were detected in two adenocarcinoma patients. To demonstrate the functional applications of NGS, we correlated mutations with patient characteristics, outcomes of matched targeted therapy, and outcomes based on allelic frequency of the EGFR-T790M mutation. Finally, we demonstrated that circulating tumor DNA can be used both to measure response to targeted therapy and as a predictor of clinical outcome, by presenting a case study of a single patient. We demonstrated that NGS can be used in multiple applications to effectively identify potential oncogenic driver mutations, guide mutation-targeted therapy decisions, and predict clinical outcomes in Chinese NSCLC patients.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 16%
Student > Doctoral Student 4 13%
Student > Master 3 10%
Student > Ph. D. Student 3 10%
Other 2 6%
Other 4 13%
Unknown 10 32%
Readers by discipline Count As %
Medicine and Dentistry 8 26%
Biochemistry, Genetics and Molecular Biology 4 13%
Pharmacology, Toxicology and Pharmaceutical Science 4 13%
Computer Science 1 3%
Agricultural and Biological Sciences 1 3%
Other 0 0%
Unknown 13 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 26 December 2023.
All research outputs
#7,208,166
of 25,382,440 outputs
Outputs from OncoTargets and therapy
#365
of 3,016 outputs
Outputs of similar age
#116,831
of 339,234 outputs
Outputs of similar age from OncoTargets and therapy
#9
of 95 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 3,016 research outputs from this source. They receive a mean Attention Score of 2.9. This one has done well, scoring higher than 87% 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 339,234 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 95 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.