Interindividual differences in tumor response and normal tissue toxicities are consistently observed with most chemotherapeutic agents or regimens. While many clinical variables have been associated with drug responses (e.g., age, gender, diet, drug-drug interactions), inherited variations in drug disposition (metabolism and transport) genes and drug target genes also likely contribute to the observed variability in cancer treatment outcome. Pharmacogenomic studies aim to elucidate the genetic bases for interindividual differences and to use such genetic information to predict the safety, toxicity, and/or efficacy of drugs. There exist several clinically relevant examples of the utility of pharmacogenomics that associate specific genetic polymorphisms in drug metabolizing enzymes (e.g., TPMT, UGT1A1, DPD), drug transporters (MDR1), and drug target enzymes (TS) with clinical outcomes in patients treated with commonly prescribed chemotherapy drugs, such as 5-fluorouracil and irinotecan (Camptosar; Pfizer Pharmaceuticals; New York, NY http://www.pfizer.com). Techniques to discover and evaluate the functional significance of these polymorphisms have evolved in recent years and may soon be applied to clinical practice and clinical trials of currently prescribed anticancer drugs as well as new therapeutic agents. This review discusses the current and future applications of pharmacogenomics in clinical cancer therapy and cancer drug development.
Pharmacology, Toxicology and Pharmaceutical Science
17
15%
Biochemistry, Genetics and Molecular Biology
15
14%
Unspecified
1
<1%
Other
5
5%
Unknown
27
24%
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 30 June 2026.
All research outputs
#7,241,762
of 33,949,960 outputs
Outputs from Oncologist
#1,782
of 4,822 outputs
Outputs of similar age
#32,763
of 218,040 outputs
Outputs of similar age from Oncologist
#7
of 17 outputs
Altmetric has tracked 33,949,960 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,822 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has gotten more attention than average, scoring higher than 62% 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 218,040 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 84% of its contemporaries.
We're also able to compare this research output to 17 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 52% of its contemporaries.
