Breast cancer is the second leading cause of cancer-related death in women, with nearly 450,000 deaths per year from the disease worldwide. However, women aged 15-39 at diagnosis have a poorer chance of surviving their cancer than older women* (although survival rates for the disease are generally high).
This difference is partly due to the higher incidence of adverse tumor types that occur in younger women, but age is an independent risk factor even after accounting for differences in tumor type and treatment.
A new study has found that inherited variation in a particular gene may be to blame for the lower survival rate of patients diagnosed with early-onset breast cancer.
The Southampton study - one of the largest ever undertaken into the link between genes and breast cancer survival in women aged 40 or under at diagnosis - looked at which factors, other than the features of the cancer tissue, might contribute to the poorer survival rate in younger women.
Authors conducted a metaanalysis of overall survival (OS) and disease-free survival (DFS) in 6042 patients from four cohorts. In young women, breast cancer is characterized by a higher incidence of adverse pathological features, unique gene expression profiles and worse survival, which may relate to germline variation.
To explore this hypothesis, researchers also performed survival analysis in 2315 patients aged ≤ 40 years at diagnosis. They identified two SNPs associated with early onset DFS, rs715212 (Pmeta = 3.54 × 10−5) and rs10963755 (Pmeta = 3.91 × 10−4) in ADAMTSL1. The effect of these SNPs is independent of classical prognostic factors and there is no heterogeneity between cohorts.
Most importantly, the association with rs715212 is noteworthy (FPRP <0.2) and approaches genome-wide significance in multivariable analysis. Expression quantitative trait analysis provides tentative evidence that rs715212 may influence AREG expression, although further functional studies are needed to confirm this association and determine a mechanism
The collaborative study is published in the journal Nature Communications. Lead author said that the findings could eventually be used to improve the accuracy of estimates of disease progression, helping clinicians and patients to choose the most effective treatments.
"In the short to medium-term, this genetic factor may be used to improve prognostic models. In the long-term, when more is known about the mechanism underlying this association and its relationship with treatment response, it may have an influence on approaches to the most effective breast cancer treatments."