Reconstructing tumor history in breast cancer: signatures of mutational processes and response to neoadjuvant chemotherapy.
Different endogenous and exogenous mutational processes act over the evolutionary history of a malignant tumor, driven by abnormal DNA editing, mutagens or age-related DNA alterations, among others, to generate the specific mutational landscape of each individual tumor. The signatures of these mutational processes can be identified in large genomic datasets. We investigated the hypothesis that genomic patterns of mutational signatures are associated with the clinical behavior of breast cancer, in particular chemotherapy response and survival, with a particular focus on therapy-resistant disease.Whole-exome-sequencing was performed in 405 pretherapeutic samples from the prospective neoadjuvant multicenter GeparSepto study. We analyzed 11 mutational signatures including biological processes such as APOBEC-mutagenesis, homologous-recombination-deficiency (HRD), mismatch-repair-deficiency, and also age-related or tobacco-induced alterations.Different subgroups of breast carcinomas were defined mainly by differences in HRD-related and APOBEC-related mutational signatures and significant differences between hormone-receptor (HR) negative and HR-positive tumors as well as correlations with age, Ki-67 and immunological parameters were observed. We could identify mutational processes that were linked to increased pathological complete response (pCR) rates to neoadjuvant chemotherapy with high significance. In univariate analyses for HR-positive tumors signatures, S3 (HRD, p<0.001) and S13 (APOBEC, p=0.001) as well as exonic mutation rate (EMR) (p=0.002) were significantly correlated with increased pCR rates. The signatures S3 (HRD, p=0.006) and S4 (tobacco, p=0.011) were prognostic for reduced DFS of patients with chemotherapy-resistant tumors.The results of this investigation suggest that the clinical behavior of a tumor, in particular response to neoadjuvant chemotherapy and DFS of therapy-resistant tumors, could be predicted by the composition of mutational signatures as an indicator of the individual genomic history of a tumor. After additional validations, mutational signatures might be used to identify tumors with an increased response rate to neoadjuvant chemotherapy and to define therapy-resistant subgroups for future therapeutic interventions.