C Denkert1, M Untch2, S Benz3, A Schneeweiss4, K E Weber5, S Schmatloch6, C Jackisch7, H P Sinn8, J Golovato3, T Karn9, F Marmé10, T Link11, J Budczies12, V Nekljudova5, W D Schmitt13, E Stickeler14, V Müller15, P Jank16, R Parulkar3, E Heinmöller17, J Z Sanborn3, C Schem18, B V Sinn13, P Soon-Shiong3, M van Mackelenbergh19, P A Fasching20, S Rabizadeh3, S Loibl21. 1. Institute of Pathology, Philipps-University Marburg and University Hospital Marburg (UK-GM), Marburg, Germany; Charité - Universitätsmedizin Berlin, Institute of Pathology, Berlin, Germany. Electronic address: carsten.denkert@uni-marburg.de. 2. Helios Klinikum Berlin-Buch, Department of Obstetrics and Gynaecology, Berlin, Germany. 3. NantOmics, LLC, Culver City, USA. 4. Nationales Centrum für Tumorerkrankungen, Universitätsklinikum und Deutsches Krebsforschungszentrum Heidelberg, Heidelberg, Germany. 5. German Breast Group (GBG), Neu-Isenburg, Germany. 6. Brustzentrum Kassel, Elisabeth Krankenhaus, Kassel, Germany. 7. Department of Obstetrics and Gynecology and Breast Cancer Center, Sana Klinikum Offenbach, Offenbach, Germany. 8. Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany; German Cancer consortium (DKTK), Heidelberg, Germany. 9. Klinik für Frauenheilkunde und Geburtshilfe, Goethe Universität, Frankfurt, Germany. 10. Universitätsfrauenklinik Mannheim, Mannheim, Germany. 11. Department of Gynecology and Obstetrics, Technische Universität Dresden, Dresden, Germany. 12. Charité - Universitätsmedizin Berlin, Institute of Pathology, Berlin, Germany; Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany; German Cancer consortium (DKTK), Heidelberg, Germany. 13. Charité - Universitätsmedizin Berlin, Institute of Pathology, Berlin, Germany. 14. Department of Gynecology, RWTH Aachen, Aachen, Germany. 15. Department of Gynecology, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany. 16. Institute of Pathology, Philipps-University Marburg and University Hospital Marburg (UK-GM), Marburg, Germany; Charité - Universitätsmedizin Berlin, Institute of Pathology, Berlin, Germany. 17. Pathologie Nordhessen, Kassel, Germany. 18. Mammazentrum Hamburg am Krankenhaus Jerusalem, Hamburg, Germany. 19. Universitätsklinikum Schleswig-Holstein, Klinik für Gynäkologie und Geburtshilfe, Kiel, Germany. 20. Department of Gynecology and Obstetrics, University Hospital Erlangen, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany. 21. German Breast Group (GBG), Neu-Isenburg, Germany; University of Frankfurt, Frankfurt am Main, Germany.
Abstract
BACKGROUND: 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. PATIENTS AND METHODS: Whole exome sequencing was carried out 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. RESULTS: 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 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 (P = 0.002) were significantly correlated with increased pathological complete response rates. The signatures S3 (HRD, P = 0.006) and S4 (tobacco, P = 0.011) were prognostic for reduced disease-free survival of patients with chemotherapy-resistant tumors. CONCLUSION: The results of this investigation suggest that the clinical behavior of a tumor, in particular, response to neoadjuvant chemotherapy and disease-free survival 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.
BACKGROUND: 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. PATIENTS AND METHODS: Whole exome sequencing was carried out 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. RESULTS: 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 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 (P = 0.002) were significantly correlated with increased pathological complete response rates. The signatures S3 (HRD, P = 0.006) and S4 (tobacco, P = 0.011) were prognostic for reduced disease-free survival of patients with chemotherapy-resistant tumors. CONCLUSION: The results of this investigation suggest that the clinical behavior of a tumor, in particular, response to neoadjuvant chemotherapy and disease-free survival 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.
Authors: Stian Knappskog; Hans P Eikesdal; Andreas Venizelos; Christina Engebrethsen; Wei Deng; Jürgen Geisler; Stephanie Geisler; Gjertrud T Iversen; Turid Aas; Hildegunn S Aase; Manouchehr Seyedzadeh; Eli Sihn Steinskog; Ola Myklebost; Sigve Nakken; Daniel Vodak; Eivind Hovig; Leonardo A Meza-Zepeda; Per E Lønning Journal: Genome Med Date: 2022-08-11 Impact factor: 15.266