Emily R. Kansler, Akanksha Verma, Erin M. Langdon, Theresa Simon-Vermot, Alexandra Yin, William Lee, Marc Attiyeh, Olivier Elemento, Richard M. White
Abstract
Cancer genomes evolve in both space and time, which contributes to the genetic heterogeneity that underlies tumor progression and drug resistance. In human melanoma, identifying mechanistically important events in tumor evolution is hampered due to the high background mutation rate from ultraviolet (UV) light. Cross-species oncogenomics is a powerful tool for identifying these core events, in which transgenically well-defined animal models of cancer are compared to human cancers to identify key conserved alterations.
We use a zebrafish model of tumor progression and drug resistance for cross-species genomic analysis in melanoma. Zebrafish transgenic tumors are initiated with just 2 genetic lesions, BRAF(V600E) and p53(-/-), yet take 4-6 months to appear, at which time whole genome sequencing demonstrated >3,000 new mutations. An additional 4-month exposure to the BRAF inhibitor vemurafenib resulted in a highly drug resistant tumor that showed 3 additional new DNA mutations in the genes BUB1B, PINK1, and COL16A1. These genetic changes in drug resistance are accompanied by a massive reorganization of the transcriptome, with differential RNA expression of over 800 genes, centered on alterations in cAMP and PKA signaling. By comparing both the DNA and mRNA changes to a large panel of human melanomas, we find that there is a highly significant enrichment of these alterations in human patients with vemurafenib resistant disease.
Our results suggest that targeting of alterations that are conserved between zebrafish and humans may offer new avenues for therapeutic intervention. The approaches described here will be broadly applicable to the diverse array of cancer models available in the zebrafish, which can be used to inform human cancer genomics.
Pharmacology, Toxicology and Pharmaceutical Science
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2%
Other
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Unknown
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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 29 September 2017.
All research outputs
#5,454,715
of 26,378,648 outputs
Outputs from BMC Genomics
#2,030
of 11,427 outputs
Outputs of similar age
#100,301
of 430,902 outputs
Outputs of similar age from BMC Genomics
#63
of 231 outputs
Altmetric has tracked 26,378,648 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,427 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 82% 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 430,902 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 231 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 72% of its contemporaries.
