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CYP3A7 allele predicts poor outcomes for lung and breast cancer, leukemia
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Patients with breast cancer, lung cancer or chronic lymphocytic leukemia who harbored the CYP3A7*1C form of the CYP3A7 gene experienced worse outcomes than patients without this alteration, according to study data.
The CYP3A7 gene encodes an enzyme that breaks down naturally occurring substances, such as estrogen and testosterone, as well as a variety of drugs used in cancer treatment. Thus, the CYP3A7*1C allele may affect the way anticancer drugs are metabolized, according to the researchers.
“One possibility is that these patients break down the drugs that they are given to treat their cancer too fast,” Olivia Fletcher, PhD, senior investigator at the Breast Cancer Now Toby Robins Research Center at The Institute for Cancer Research in London, said in a press release. “However, further independent studies that replicate our findings in larger numbers of patients and rule out biases are needed before we could recommend any changes to the treatment that patients with cancer and the CYP3A7*1C allele receive.”
Olivia Fletcher, PhD
CYP3A7 is normally turned on in an embryo, then turned off at birth. However, individuals with one or more copy of the gene (CYP3A7*1C) turn on their CYP3A7 gene in adult life.
Fletcher and colleagues sought to determine whether the CYP3A7*1C allele could predict outcomes in patients with certain cancers. To do so, they analyzed DNA samples from patients with breast cancer (n = 1,008), lung cancer (n = 1,128), and CLL (n = 347) for the presence for the single nucleotide polymorphism rs45446698, which is one of seven SNPs that cluster together to form the CYP3A7*1C allele.
Overall, 73 patients with breast cancer, 89 patients with lung cancer and 23 patients with CLL were carriers of the rare rs45446698-C allele.
Analyses adjusted for prognostic factors showed harboring the SNP increased risk for disease-specific mortality 74% among patients with breast cancer (HR = 1.74; 95% CI, 1.05-2.9) and 43% among patients with lung cancer (HR = 1.43; 95% CI, 1.09-1.87).
Further, the SNP increased the risk for disease progression among patients with CLL 62% (HR = 1.62; 95% CI, 1.05-2.5).
Researchers then stratified patients based on treatment with a cytotoxic agent that is metabolized by a CYP3A enzyme. Results showed the association between genotype and outcome appeared related to treatment with a CYP3A substrate (HR = 1.8; 95% CI, 1.36-2.39). However, the difference between outcomes among patients who were and were not (HR = 1.2; 95% CI, 0.87-1.65) treated with a CYP3A substrate only reached borderline statistical significance.
The DNA samples used in this study were originally collected for use in other studies, which the researchers identified as a limitation of their analysis.
Additional limitations included a lack of clinical information from each patient, the fact that samples were collected at different points in time, and the researchers’ inability to judge how quickly the patients broke down the therapeutics they received.
“Even though we did not see a statistically significant difference when stratifying patients by treatment with a CYP3A7 substrate, the fact that we see the same effect in three very different cancer types suggests to me that it is more likely to be something to do with treatment than the disease itself,” Fletcher said. “However, we are looking at ways of replicating these results in additional cohorts of patients and types of cancers.” – by Cameron Kelsall
Disclosure: Breast Cancer Now, Bloodwise, Cancer Research U.K., the Medical Research Council, the Cridlan Trust, the Helen Rollason Cancer Charity, and Sanofi-Aventis provided funding for this study. The researchers report no relevant financial disclosures.
Perspective
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Shannon Lynch, PhD, MPH
This article identifies CYP3A7*1C as a potential prognostic marker that can detect poor outcomes in several cancer types. The manuscript is interesting because it suggests that a rare allele, which is only carried by a small subset of the population, might have potential treatment implications across several cancer types.
The manuscript also is timely given that the use of genetic information to identify patient sub-populations at risk for poor cancer outcomes is becoming increasingly important in this emerging era of precision medicine.
Although these initial CYP3A7*1C findings show promise, reported associations will need to be replicated in other studies that include additional race/ethnic groups, more detailed information on treatment and a discussion of the effects of a patient’s cancer family history before they could be used more broadly for treatment optimization.
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