Drug-Metabolizing Enzyme Polymorphisms Predict Clinical Outcome in a Node-Positive Breast Cancer Cohort

2005 ◽  
Vol 23 (24) ◽  
pp. 5552-5559 ◽  
Author(s):  
Angela DeMichele ◽  
Richard Aplenc ◽  
Jeffrey Botbyl ◽  
Theresa Colligan ◽  
Lisa Wray ◽  
...  

Purpose Adjuvant chemotherapy cures only a subset of women with nonmetastatic breast cancer. Genotypes in drug-metabolizing enzymes, including functional polymorphisms in cytochrome P450 (CYP) and glutathione S-transferases (GST), may predict treatment-related outcomes. Patients and Methods We examined CYP3A4*1B, CYP3A5*3, and deletions in GST μ (GSTM1) and θ (GSTT1), as well as a priori–defined combinations of polymorphisms in these genes. Using a cohort of 90 node-positive breast cancer patients who received anthracycline-based adjuvant chemotherapy followed by high-dose multiagent chemotherapy with stem-cell rescue, we estimated the effect of genotype and other known prognostic factors on disease-free survival (DFS) and overall survival (OS). Results Patients who carried homozygous CYP3A4*1B and CYP3A5*3 variants and did not carry homozygous deletions in both GSTM1 and GSTT1 (denoted low-drug genotype group) had a 4.9-fold poorer DFS (P = .021) and a four-fold poorer OS (P = .031) compared with individuals who did not carry any CYP3A4*1B or CYP3A5*3 variants but had deletions in both GSTT1 and GSTM1 (denoted high-drug genotype group). After adjustment for other significant prognostic factors, the low-drug genotype group retained a significantly poorer DFS (hazard ratio [HR] = 4.9; 95% CI, 1.7 to 14.6; P = .004) and OS (HR = 4.8; 95% CI, 1.8 to 12.9; P = .002) compared with the high- and intermediate-drug combined genotype group. In the multivariate model, having low-drug genotype group status had a greater impact on clinical outcome than estrogen receptor status. Conclusion Combined genotypes at CYP3A4, CYP3A5, GSTM1, and GSTT1 influence the probability of treatment failure after high-dose adjuvant chemotherapy for node-positive breast cancer.

2010 ◽  
Vol 16 (15) ◽  
pp. 3988-3997 ◽  
Author(s):  
Charles Dumontet ◽  
Maryla Krajewska ◽  
Isabelle Treilleux ◽  
John R. Mackey ◽  
Miguel Martin ◽  
...  

1993 ◽  
Vol 11 (2) ◽  
pp. 351-359 ◽  
Author(s):  
T E Witzig ◽  
J N Ingle ◽  
D J Schaid ◽  
L E Wold ◽  
J F Barlow ◽  
...  

PURPOSE AND METHODS To help clarify the clinical utility of flow-cytometric parameters, we performed flow cytometry on archival paraffin-embedded primary breast cancers from 502 patients treated on two adjuvant chemotherapy protocols performed by the North Central Cancer Treatment Group (NCCTG) and Mayo Clinic. DNA ploidy and percent S-phase (%S) were examined in univariate and Cox model multivariate analyses along with tumor size, menopausal and estrogen receptor status, Quetelet's index (QI), number of positive nodes and nodes examined, and Fisher and nuclear grades. RESULTS Ploidy analysis showed that 40% of tumors were DNA diploid and 60% were DNA nondiploid (12% tetraploid and 48% aneuploid). There was no difference in relapse-free survival (RFS) (P = .82) or overall survival (OS) (P = .78) between the ploidy groups. Tetraploid patients had the longest RFS and OS of any group, but this did not achieve statistical significance. The %S was computed in 98% of cases and the medians were 9.0% for all patients, 6.4% for diploid patients, and 11.7% for nondiploid patients (P < .0001). By use of a %S greater than 12.3 as a prognostic variable in a univariate analysis, there was a significant difference in the RFS (P = .02) and OS (P = .007) of patients with low- versus high-proliferative tumors. However, when the %S was adjusted for clinical characteristics in the multivariate analysis, it was not a significant factor for RFS (P = .23) or OS (P = .36). CONCLUSION These results indicate that DNA content and %S measurements by flow cytometry are not clinically useful independent prognostic factors in women with resected node-positive breast cancer administered adjuvant chemotherapy.


2012 ◽  
Vol 99 (6) ◽  
pp. E64-E74 ◽  
Author(s):  
Thomas Filleron ◽  
Andrew Kramar ◽  
Florence Dalenc ◽  
Marc Spielmann ◽  
Pierre Fumoleau ◽  
...  

2021 ◽  
Author(s):  
Yogeshkumar Malam ◽  
Mohamed Rabie ◽  
Konstantinos Geropantas ◽  
Susanna Alexander ◽  
Simon Pain ◽  
...  

2019 ◽  
Vol 17 (1) ◽  
pp. 47-56 ◽  
Author(s):  
Zachary Veitch ◽  
Omar F. Khan ◽  
Derek Tilley ◽  
Domek Ribnikar ◽  
Xanthoula Kostaras ◽  
...  

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