NEW YORK (GenomeWeb) – The presence or absence of germline variants in and around the ADAMTSL1 gene may provide prognostic clues in early-onset breast cancer cases, according to an international team's new study published in Nature Communications today.
The researchers took a meta-analysis genome-wide association approach to finding germline variants with potential ties to overall survival and/or disease-free survival in more than 6,000 individuals with breast cancer. In women diagnosed with breast cancer when they were 40 years old or younger, the team narrowed in on germline ADAMTSL1 SNPs associated with disease-free survival independent of previously described prognostic variants.
Two more loci also showed ties to survival across all of the cases, though none of the loci reached genome-wide significant association with outcomes.
"The SNPs identified in this study have the potential to improve the accuracy of prognostic estimates and stratification of patients into treatment groups," corresponding and co-senior author William Tapper, a genetic epidemiology and bioinformatics researcher at the University of Southampton, and his colleagues wrote. "Moreover, the gene implicated by these SNPs may warrant further investigation as novel therapeutic targets and some are already under investigation for this purpose."
While tumor features are frequently used for selecting breast cancer treatments and attempting to predict disease outcomes, the team noted that not only somatic mutations, but also inherited variants in the germline, have been found to affect breast cancer risk, treatment response, and survival.
With that in mind, the researchers set out to find new germline genetic contributors to breast cancer prognosis, starting with array-based genotyping profiles for 4,739 breast cancer cases from studies undertaken in Australia, Finland, the UK, and Germany. They followed up on suspicious variants detected in the discovery stage of the study in a validation cohort involving 1,303 more breast cancer cases from the UK.
When the team folded in disease-free survival and overall survival outcomes, when available, it did not detect variants with genome-wide significant ties to survival. But a more targeted test for survival-related SNPs using dozens of variants identified through a literature search led to a dozen variants that appeared to affect survival.
Following the replication stages of the study — along with a stratified analysis focusing on a subset of 2,315 early cancer cases diagnosed at age 40 or younger — the researchers were left with the rs715212 and rs10963755 variants in ADAMTSL1.
Both common variants fall at sites with transcription factor motifs, they noted. Expression quantitative trait locus clues gleaned from GTEx data suggested at least one of the SNPs may influence expression of the AREG gene, though other lines of evidence suggested the locus may also impact ADAMTSL1 methylation.
The presence of these variants appeared to coincide with poorer outcomes in women with early-onset breast cancer, the authors explained, noting that "unique disease mechanisms may influence survival in younger women and provide some biological insight into why younger-onset breast cancer has a worse prognosis."
A pooled analysis of breast cancer cases from each stage of the study highlighted variants in and around the TXNRD1 and the CHST11 genes that also showed potential associations with breast cancer outcomes.
The authors cautioned that "none of the survival analyses were adjusted for treatment," and noted that there was not sufficient data available to include breast cancer cases from all of the cohorts in the some of the analyses, including the search for disease-free survival-associated sites.
"Further analysis with larger sample sizes and adjustment for additional clinicopathological factors including treatment (chemotherapy and hormone therapy) may provide more information that could further improve survival analysis," they wrote, adding that "functional studies involving breast cancer patients and including epigenetic mechanisms should be performed to provide more insights about the three association signals identified in the present study."