Despite producing a panoply of potential cancer-specific targets, the proteogenomic characterization of human tumors has yet to demonstrate value for precision cancer medicine. Integrative multi-omics using a machine-learning network identified master kinases responsible for effecting phenotypic hallmarks of functional glioblastoma subtypes. In subtype-matched patient-derived models, we validated PKCδ and DNA-PK as master kinases of glycolytic/plurimetabolic and proliferative/progenitor subtypes, respectively, and qualified the kinases as potent and actionable glioblastoma subtype-specific therapeutic targets. Glioblastoma subtypes were associated with clinical and radiomics features, orthogonally validated by proteomics, phospho-proteomics, metabolomics, lipidomics and acetylomics analyses, and recapitulated in pediatric glioma, breast and lung squamous cell carcinoma, including subtype specificity of PKCδ and DNA-PK activity. We developed a probabilistic classification tool that performs optimally with RNA from frozen and paraffin-embedded tissues, which can be used to evaluate the association of therapeutic response with glioblastoma subtypes and to inform patient selection in prospective clinical trials.
This research output has an Altmetric Attention Score of 148. 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 21 November 2024.
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#351,271
of 34,350,471 outputs
Outputs from Nature Cancer
#91
of 1,064 outputs
Outputs of similar age
#7,412
of 525,408 outputs
Outputs of similar age from Nature Cancer
#8
of 51 outputs
Altmetric has tracked 34,350,471 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,064 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 53.6. This one has done particularly well, scoring higher than 91% of its peers.
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We're also able to compare this research output to 51 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.
