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Modifier locus mapping of a transgenic F2 mouse population identifies CCDC115 as a novel aggressive prostate cancer modifier gene in humans

Overview of attention for article published in BMC Genomics, June 2018
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  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

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Citations

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Title
Modifier locus mapping of a transgenic F2 mouse population identifies CCDC115 as a novel aggressive prostate cancer modifier gene in humans
Published in
BMC Genomics, June 2018
DOI 10.1186/s12864-018-4827-2
Pubmed ID
Authors

Jean M. Winter, Natasha L. Curry, Derek M. Gildea, Kendra A. Williams, Minnkyong Lee, Ying Hu, Nigel P. S. Crawford

Abstract

It is well known that development of prostate cancer (PC) can be attributed to somatic mutations of the genome, acquired within proto-oncogenes or tumor-suppressor genes. What is less well understood is how germline variation contributes to disease aggressiveness in PC patients. To map germline modifiers of aggressive neuroendocrine PC, we generated a genetically diverse F2 intercross population using the transgenic TRAMP mouse model and the wild-derived WSB/EiJ (WSB) strain. The relevance of germline modifiers of aggressive PC identified in these mice was extensively correlated in human PC datasets and functionally validated in cell lines. Aggressive PC traits were quantified in a population of 30 week old (TRAMP x WSB) F2 mice (n = 307). Correlation of germline genotype with aggressive disease phenotype revealed seven modifier loci that were significantly associated with aggressive disease. RNA-seq were analyzed using cis-eQTL and trait correlation analyses to identify candidate genes within each of these loci. Analysis of 92 (TRAMP x WSB) F2 prostates revealed 25 candidate genes that harbored both a significant cis-eQTL and mRNA expression correlations with an aggressive PC trait. We further delineated these candidate genes based on their clinical relevance, by interrogating human PC GWAS and PC tumor gene expression datasets. We identified four genes (CCDC115, DNAJC10, RNF149, and STYXL1), which encompassed all of the following characteristics: 1) one or more germline variants associated with aggressive PC traits; 2) differential mRNA levels associated with aggressive PC traits; and 3) differential mRNA expression between normal and tumor tissue. Functional validation studies of these four genes using the human LNCaP prostate adenocarcinoma cell line revealed ectopic overexpression of CCDC115 can significantly impede cell growth in vitro and tumor growth in vivo. Furthermore, CCDC115 human prostate tumor expression was associated with better survival outcomes. We have demonstrated how modifier locus mapping in mouse models of PC, coupled with in silico analyses of human PC datasets, can reveal novel germline modifier genes of aggressive PC. We have also characterized CCDC115 as being associated with less aggressive PC in humans, placing it as a potential prognostic marker of aggressive PC.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 43%
Student > Master 2 14%
Other 1 7%
Student > Ph. D. Student 1 7%
Researcher 1 7%
Other 2 14%
Unknown 1 7%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 36%
Unspecified 1 7%
Pharmacology, Toxicology and Pharmaceutical Science 1 7%
Nursing and Health Professions 1 7%
Agricultural and Biological Sciences 1 7%
Other 2 14%
Unknown 3 21%

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 19 June 2018.
All research outputs
#7,085,851
of 13,104,802 outputs
Outputs from BMC Genomics
#3,532
of 7,728 outputs
Outputs of similar age
#123,578
of 270,052 outputs
Outputs of similar age from BMC Genomics
#6
of 21 outputs
Altmetric has tracked 13,104,802 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,728 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 51% 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 270,052 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 52% of its contemporaries.
We're also able to compare this research output to 21 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 66% of its contemporaries.