↓ Skip to main content

Novel biomarkers that assist in accurate discrimination of squamous cell carcinoma from adenocarcinoma of the lung

Overview of attention for article published in BMC Cancer, September 2016
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

twitter
3 X users

Citations

dimensions_citation
42 Dimensions

Readers on

mendeley
61 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Novel biomarkers that assist in accurate discrimination of squamous cell carcinoma from adenocarcinoma of the lung
Published in
BMC Cancer, September 2016
DOI 10.1186/s12885-016-2792-1
Pubmed ID
Authors

Kazuya Takamochi, Hiroko Ohmiya, Masayoshi Itoh, Kaoru Mogushi, Tsuyoshi Saito, Kieko Hara, Keiko Mitani, Yasushi Kogo, Yasunari Yamanaka, Jun Kawai, Yoshihide Hayashizaki, Shiaki Oh, Kenji Suzuki, Hideya Kawaji

Abstract

Targeted therapies based on the molecular and histological features of cancer types are becoming standard practice. The most effective regimen in lung cancers is different between squamous cell carcinoma (SCC) and adenocarcinoma (AD). Therefore a precise diagnosis is crucial, but this has been difficult, particularly for poorly differentiated SCC (PDSCC) and AD without a lepidic growth component (non-lepidic AD). Biomarkers enabling a precise diagnosis are therefore urgently needed. Cap Analysis of Gene Expression (CAGE) is a method used to quantify promoter activities across the whole genome by determining the 5' ends of capped RNA molecules with next-generation sequencing. We performed CAGE on 97 frozen tissues from surgically resected lung cancers (22 SCC and 75 AD), and confirmed the findings by immunohistochemical analysis (IHC) in an independent group (29 SCC and 45 AD). Using the genome-wide promoter activity profiles, we confirmed that the expression of known molecular markers used in IHC for SCC (CK5, CK6, p40 and desmoglein-3) and AD (TTF-1 and napsin A) were different between SCC and AD. We identified two novel marker candidates, SPATS2 for SCC and ST6GALNAC1 for AD, as showing comparable performance and complementary utility to the known markers in discriminating PDSCC and non-lepidic AD. We subsequently confirmed their utility at the protein level by IHC in an independent group. We identified two genes, SPATS2 and ST6GALNAC1, as novel complemental biomarkers discriminating SCC and AD. These findings will contribute to a more accurate diagnosis of NSCLC, which is crucial for precision medicine for lung cancer.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 61 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 9 15%
Student > Ph. D. Student 7 11%
Other 5 8%
Researcher 5 8%
Student > Postgraduate 4 7%
Other 9 15%
Unknown 22 36%
Readers by discipline Count As %
Medicine and Dentistry 12 20%
Biochemistry, Genetics and Molecular Biology 9 15%
Pharmacology, Toxicology and Pharmaceutical Science 4 7%
Agricultural and Biological Sciences 3 5%
Computer Science 3 5%
Other 8 13%
Unknown 22 36%
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 07 August 2019.
All research outputs
#14,273,624
of 22,890,496 outputs
Outputs from BMC Cancer
#3,371
of 8,327 outputs
Outputs of similar age
#184,397
of 322,600 outputs
Outputs of similar age from BMC Cancer
#57
of 162 outputs
Altmetric has tracked 22,890,496 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,327 research outputs from this source. They receive a mean Attention Score of 4.3. This one has gotten more attention than average, scoring higher than 56% 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 322,600 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 162 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 62% of its contemporaries.