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Proteogenomics

Overview of attention for book
Attention for Chapter 8: Developments for Personalized Medicine of Lung Cancer Subtypes: Mass Spectrometry-Based Clinical Proteogenomic Analysis of Oncogenic Mutations.
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
15 Mendeley
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Chapter title
Developments for Personalized Medicine of Lung Cancer Subtypes: Mass Spectrometry-Based Clinical Proteogenomic Analysis of Oncogenic Mutations.
Chapter number 8
Book title
Proteogenomics
Published in
Advances in experimental medicine and biology, September 2016
DOI 10.1007/978-3-319-42316-6_8
Pubmed ID
Book ISBNs
978-3-31-942314-2, 978-3-31-942316-6
Authors

Toshihide Nishimura, Haruhiko Nakamura, Nishimura, Toshihide, Nakamura, Haruhiko

Editors

Ákos Végvári

Abstract

Molecular therapies targeting lung cancers with mutated epidermal growth factor receptor (EGFR) by EGFR-tyrosin kinase inhibitors (EGFR-TKIs), gefitinib and erlotinib, changed the treatment system of lung cancer. It was revealed that drug efficacy differs by race (e.g., Caucasians vs. Asians) due to oncogenic driver mutations specific to each race, exemplified by gefitinib / erlotinib. The molecular target drugs for lung cancer with anaplastic lymphoma kinase (ALK) gene translocation (the fusion gene, EML4-ALK) was approved, and those targeting lung cancers addicted ROS1, RET, and HER2 have been under development. Both identification and quantification of gatekeeper mutations need to be performed using lung cancer tissue specimens obtained from patients to improve the treatment for lung cancer patients: (1) identification and quantitation data of targeted mutated proteins, including investigation of mutation heterogeneity within a tissue; (2) exploratory mass spectrometry (MS)-based clinical proteogenomic analysis of mutated proteins; and also importantly (3) analysis of dynamic protein-protein interaction (PPI) networks of proteins significantly related to a subgroup of patients with lung cancer not only with good efficacy but also with acquired resistance. MS-based proteogenomics is a promising approach to directly capture mutated and fusion proteins expressed in a clinical sample. Technological developments are further expected, which will provide a powerful solution for the stratification of patients and drug discovery (Precision Medicine).

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 20%
Student > Ph. D. Student 2 13%
Other 1 7%
Professor 1 7%
Student > Doctoral Student 1 7%
Other 2 13%
Unknown 5 33%
Readers by discipline Count As %
Computer Science 3 20%
Biochemistry, Genetics and Molecular Biology 3 20%
Medicine and Dentistry 2 13%
Economics, Econometrics and Finance 1 7%
Pharmacology, Toxicology and Pharmaceutical Science 1 7%
Other 0 0%
Unknown 5 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 28 March 2019.
All research outputs
#4,192,991
of 22,890,496 outputs
Outputs from Advances in experimental medicine and biology
#694
of 4,952 outputs
Outputs of similar age
#70,394
of 322,482 outputs
Outputs of similar age from Advances in experimental medicine and biology
#17
of 119 outputs
Altmetric has tracked 22,890,496 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,952 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has done well, scoring higher than 84% 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 322,482 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 76% of its contemporaries.
We're also able to compare this research output to 119 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.