↓ Skip to main content

Identification and validation of a 44-gene expression signature for the classification of renal cell carcinomas

Overview of attention for article published in Journal of Experimental & Clinical Cancer Research, December 2017
Altmetric Badge

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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
1 X user

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
18 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
Identification and validation of a 44-gene expression signature for the classification of renal cell carcinomas
Published in
Journal of Experimental & Clinical Cancer Research, December 2017
DOI 10.1186/s13046-017-0651-9
Pubmed ID
Authors

Qifeng Wang, Hualei Gan, Chengshu Chen, Yifeng Sun, Jinying Chen, Midie Xu, Weiwei Weng, Liyu Cao, Qinghua Xu, Jian Wang

Abstract

Renal cancers account for more than 3% of all adult malignancies and cause more than 23,400 deaths per year in China alone. The four most common types of kidney tumours include clear cell, papillary, chromophobe and benign oncocytoma. These histological subtypes vary in their clinical course and prognosis, and different clinical strategies have been developed for their management. Some kidney tumours can be very difficult to distinguish based on the pathological assessment of morphology and immunohistochemistry. Six renal cell carcinoma microarray data sets, including 106 clear cell, 66 papillary, 42 chromophobe, 46 oncocytoma and 35 adjacent normal tissue samples, were subjected to integrative analysis. These data were combined and used as a training set for candidate gene expression signature identification. In addition, two independent cohorts of 1020 RNA-Seq samples from The Cancer Genome Atlas database and 129 qRT-PCR samples from Fudan University Shanghai Cancer Center (FUSCC) were analysed to validate the selected gene expression signature. A 44-gene expression signature derived from microarray analysis was strongly associated with the histological differentiation of renal tumours and could be used for tumour subtype classification. The signature performance was further validated in 1020 RNA-Seq samples and 129 qRT-PCR samples with overall accuracies of 93.4 and 93.0%, respectively. A 44-gene expression signature that could accurately discriminate renal tumour subtypes was identified in this study. Our results may prompt further development of this gene expression signature into a molecular assay amenable to routine clinical practice.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 17%
Researcher 3 17%
Student > Ph. D. Student 3 17%
Other 2 11%
Lecturer 1 6%
Other 2 11%
Unknown 4 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 28%
Medicine and Dentistry 5 28%
Engineering 2 11%
Nursing and Health Professions 1 6%
Unknown 5 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 14 March 2019.
All research outputs
#2,444,430
of 25,382,440 outputs
Outputs from Journal of Experimental & Clinical Cancer Research
#101
of 2,380 outputs
Outputs of similar age
#52,657
of 446,025 outputs
Outputs of similar age from Journal of Experimental & Clinical Cancer Research
#2
of 40 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,380 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 95% 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 446,025 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 88% of its contemporaries.
We're also able to compare this research output to 40 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 95% of its contemporaries.