The complexity of breast cancer (BC) at the clinical, morphological and molecular level has been well demonstrated. Molecular profiling, which reveals the intrinsic biology among subtypes, has significantly advanced the management of this disease. However, previous studies have provided very limited molecular data on Chinese BC patients.
We performed capture-based targeted sequencing on plasma samples using a panel consisting of 102 BC related genes, spanning 249 kb of human genome, to interrogate the genomic landscape of 236 female Chinese BC patients and compared our results to the TCGA data set. Only genes covered by the panel and occurring in more than 10% patients from at least one subgroup were compared and contrasted between the two cohorts. The Chinese and the TCGA cohort had a median age of 48 and 58, respectively.
Our cohort consisted of 55% triple negative breast cancer (TNBC), 10% luminal A, 27% luminal B and 8% HER2 positive BC. 53% of patients were post-menopausal. 190 patients had mutations found from this panel, resulting in a positive detection rate of 81%. Of the 46 patients with no mutation detected from this panel, 24 had TNBC. Collectively, we identified 921 mutations spanning 89 genes. First, we compared and contrasted mutation spectrum among the 4 subtypes. TP53mutations were more commonly seen in TNBC patients (p < 0.01), whereas FGF3, FGF4, FGF19and CCND1amplification were more likely to occur in patients with Lumina A or Luminal B BC (p = 0.002). Next, we compared the mutation spectrum of our cohort to TCGA dataset, and for luminal B breast cancer and TNBC, Chinese patients had significantly more PI3KCA mutation found. Furthermore, Chinese luminal A (p < 0.01) and luminal B (p < 0.01) patients had significantly higher TP53mutation frequency and Chinese HER2 positive BC patients (p < 0.01) had significantly lower TP53mutation frequency than TCGA dataset. In addition, we also identified 10 pathogenic or likely pathogenic BRCA1/2 mutations from this cohort, resulting in a prevalence rate of 4.2%.
We identified distinctive genomic patterns associated with Chinese breast cancer patients compared to TCGA data, suggesting the importance of mutation-based stratification according to ethnic status.
The authors.
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All authors have declared no conflicts of interest.