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Mendeley readers
Attention Score in Context
| Title |
Molecular features that predict the response to antimetabolite chemotherapies
|
|---|---|
| Published in |
Cancer & Metabolism, October 2017
|
| DOI | 10.1186/s40170-017-0170-3 |
| Pubmed ID | |
| Authors |
Mahya Mehrmohamadi, Seong Ho Jeong, Jason W. Locasale |
| Abstract |
Antimetabolite chemotherapeutic agents that target cellular metabolism are widely used in the clinic and are thought to exert their anti-cancer effects mainly through non-specific cytotoxic effects. However, patients vary dramatically with respect to treatment outcome, and the sources of heterogeneity remain largely unknown. Here, we introduce a computational method for identifying gene expression signatures of response to chemotherapies and apply it to human tumors and cancer cell lines. Furthermore, we characterize a set of 17 antimetabolite agents in various contexts to investigate determinants of sensitivity to these agents. We identify distinct favorable and unfavorable metabolic expression signatures for 5-FU and Gemcitabine. Importantly, we find that metabolic pathways targeted by each of these antimetabolites are specifically enriched in its expression signatures. We provide evidence against the common notion about non-specific cytotoxic functions of antimetabolite drugs. This study demonstrates through unbiased analyses that the activities of metabolic pathways likely contribute to therapeutic response. |
Mendeley readers
The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 42 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 21% |
| Student > Bachelor | 5 | 12% |
| Researcher | 5 | 12% |
| Student > Postgraduate | 3 | 7% |
| Student > Doctoral Student | 2 | 5% |
| Other | 6 | 14% |
| Unknown | 12 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 8 | 19% |
| Agricultural and Biological Sciences | 6 | 14% |
| Engineering | 3 | 7% |
| Immunology and Microbiology | 3 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 5% |
| Other | 5 | 12% |
| Unknown | 15 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 16 October 2017.
All research outputs
#7,293,771
of 23,006,268 outputs
Outputs from Cancer & Metabolism
#79
of 206 outputs
Outputs of similar age
#118,076
of 323,064 outputs
Outputs of similar age from Cancer & Metabolism
#2
of 4 outputs
Altmetric has tracked 23,006,268 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 206 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one has gotten more attention than average, scoring higher than 59% 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 323,064 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 62% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.