Pharmacogenetic assessment of clinical outcome in patients with metastatic breast cancer treated with docetaxel plus capecitabine

Dong, Ningning; Yu, Jing; Wang, Chaoying; Zheng, Xiaohui; Wang, Zheng; Di, Lijun; Song, Gonghua; Zhu, Budong; Che, Li; Jia, Jun; Jiang, Hanfang; Zhou, Xinna; Wang, Xiaoli; Ren, Jun

doi:10.1007/s00432-012-1183-5

Cited by 23 publications

(10 citation statements)

References 34 publications

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“…CYP1A1 is likely involved in the metabolism of fluoropyrimidine [ 34 ]. Metastatic breast cancer patients carrying TT genotype may suffer a decreased progression-free survival when treated with capecitabine plus docetaxel [ 35 ] (LOE 3). The frequency of C allele in our cohort was 6.8 % (6.3 % in Exome chip data) and 3–4 % in the EUR/ExAC cohort (p = 2.4E−2, 5.7E−18).…”

Section: Resultsmentioning

confidence: 99%

Pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in Italian isolated populations

et al. 2016

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BackgroundBreast cancer is the most common cancer in women characterized by a high variable clinical outcome among individuals treated with equivalent regimens and novel targeted therapies. In this study, we performed a population based approach intersecting high-throughput genotype data from Friuli Venezia Giulia (FVG) isolated populations with publically available pharmacogenomics information to estimate the frequency of genotypes correlated with responsiveness to breast cancer treatment thus improving the clinical management of this disease in an efficient and cost effective way.MethodsA list of 80 variants reported to be related to the efficacy or toxicity of breast cancer drugs was obtained from PharmGKB database. Fourty-one were present in FVG, 1000G European (EUR) and ExAC (Non Finnish European) databases. Their frequency was extracted using PLINK software and the differences tested by Fisher’s exact test.ResultsStatistical analyses revealed that 13 out of the 41 (32 %) variants were significantly different in frequency in our sample as compared to the EUR/ExAC cohorts. For nine variants the available level of evidence (LOE) included polymorphisms related to cyclophosphamide, tamoxifen, doxorubicin, fluorpyrimidine and paclitaxel. In particular, for trastuzumab two variants were detected: (1) rs1801274-G within FCGR2A and associated with decreased efficacy (LOE 2B); (2) rs1136201-G located within ERBB2 and associated with increased toxicity (LOE 3). Both these two variants were underrepresented in the FVG population compared to EUR/ExAC population thus suggesting a high therapeutic index of this drug in our population. Moreover, as regards fluoropyrimidines, the frequency of two polymorphisms within the DPYD gene associated with drug toxicity (e.g., rs2297595-C allele and rs3918290-T allele, LOE 2A and 1, respectively) was extremely low in FVG population thus suggesting that a larger number of FVG patients could benefit from full dosage of fluoropyrimidine therapy.ConclusionsAll these findings increase the overall knowledge on the prevalence of specific variants related with breast cancer treatment responsiveness in FVG population and highlight the importance of assessing gene polymorphisms related with cancer medications in isolated communities.Electronic supplementary materialThe online version of this article (doi:10.1186/s12967-016-0778-z) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

Pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in Italian isolated populations

et al. 2016

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“…Notably, rs1048943 ( CYP1A1 ) has a MAF of 0.7 in PELs, being a missense variant and thus, a potential prognostic marker for survival outcome after docetaxel plus capecitabine chemotherapy in metastatic breast cancer patients [ 42 ]. Furthermore, rs7246981, a missense variant associated with ( CYP2F1 ) is found in high frequency (MAF = 0.6) only in PELs.…”

Section: Resultsmentioning

confidence: 99%

Exploring public genomics data for population pharmacogenomics

et al. 2017

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Racial and ethnic differences in drug responses are now well studied and documented. Pharmacogenomics research seeks to unravel the genetic underpinnings of inter-individual variability with the aim of tailored-made theranostics and therapeutics. Taking into account the differential expression of pharmacogenes coding for key metabolic enzymes and transporters that affect drug pharmacokinetics and pharmacodynamics, we advise that data interpretation and analysis need to occur in light of geographical ancestry, if implications for drug development and global health are to be considered. Herein, we exploit ePGA, a web-based electronic Pharmacogenomics Assistant and publicly available genetic data from the 1000 Genomes Project to explore genotype to phenotype associations among the 1000 Genomes Project populations.

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“…The association between “Urinary Bladder Neoplasms” and “Capecitabine” could be inferred through multiple paths as shown in Figure 3 . Among all paths between these two, the shortest path is Capecitabine-CYP1A1-Urinary Bladder Neoplasms, of which the association could be proved by literatures: (1) “CYP1A1 rs1048943 A > G (Ile462Val) polymorphism is a potential prognostic marker for survival outcome after docetaxel plus capecitabine chemotherapy” [ 34 ]; (2) active CYP1A1 and CYP1B1 overexpression is revealed in bladder cancer [ 35 ]; (3) the combination of Capecitabine and radiation therapy offers a promising treatment option for bladder cancer patients who are not candidates for surgery or cisplatin-based chemotherapy [ 36 ]; (4) a patient with metastatic bladder cancer responded well to second-line capecitabine with a clinically meaningful progression-free survival [ 37 ]. Through this validation chain, the inference that the breast and colorectal cancer drug, “Capecitabine” might be used for urinary bladder cancer could be made.…”

Section: Resultsmentioning

confidence: 99%

Cancer based pharmacogenomics network supported with scientific evidences: from the view of drug repurposing

et al. 2015

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BackgroundPharmacogenomics (PGx) as an emerging field, is poised to change the way we practice medicine and deliver health care by customizing drug therapies on the basis of each patient’s genetic makeup. A large volume of PGx data including information among drugs, genes, and single nucleotide polymorphisms (SNPs) has been accumulated. Normalized and integrated PGx information could facilitate revelation of hidden relationships among drug treatments, genomic variations, and phenotype traits to better support drug discovery and next generation of treatment.MethodsIn this study, we generated a normalized and scientific evidence supported cancer based PGx network (CPN) by integrating cancer related PGx information from multiple well-known PGx resources including the Pharmacogenomics Knowledge Base (PharmGKB), the FDA PGx Biomarkers in Drug Labeling, and the Catalog of Published Genome-Wide Association Studies (GWAS). We successfully demonstrated the capability of the CPN for drug repurposing by conducting two case studies.ConclusionsThe CPN established in this study offers comprehensive cancer based PGx information to support cancer orientated research, especially for drug repurposing.

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Pharmacogenetic assessment of clinical outcome in patients with metastatic breast cancer treated with docetaxel plus capecitabine

Abstract: CYP1A1 rs1048943 A>G (Ile462Val) polymorphism is a potential prognostic marker for survival outcome after docetaxel plus capecitabine chemotherapy in MBC patients. However, confirmatory study is needed to validate this finding.

Cited by 23 publications

References 34 publications

Pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in Italian isolated populations

Pharmacogenetics driving personalized medicine: analysis of genetic polymorphisms related to breast cancer medications in Italian isolated populations

Exploring public genomics data for population pharmacogenomics

Cancer based pharmacogenomics network supported with scientific evidences: from the view of drug repurposing

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