T Karn1, C Denkert2, K E Weber3, U Holtrich4, C Hanusch5, B V Sinn6, B W Higgs7, P Jank2, H P Sinn8, J Huober9, C Becker5, J-U Blohmer6, F Marmé8, W D Schmitt6, S Wu7, M van Mackelenbergh10, V Müller11, C Schem12, E Stickeler13, P A Fasching14, C Jackisch15, M Untch16, A Schneeweiss17, S Loibl3. 1. Goethe University, Frankfurt, Germany. Electronic address: t.karn@em.uni-frankfurt.de. 2. University Hospital, Marburg, Germany. 3. German Breast Group, Neu-Isenburg, Germany. 4. Goethe University, Frankfurt, Germany. 5. Rotkreuzklinikum, Munich, Germany. 6. Charite University, Berlin, Germany. 7. AstraZeneca, Gaithersburg, USA. 8. University Hospital, Heidelberg, Germany. 9. University Hospital, Ulm, Germany. 10. University Hospital, Kiel, Germany. 11. University Hospital, Hamburg, Germany. 12. Mammazentrum, Hamburg, Germany. 13. University Hospital, Aachen, Germany. 14. University Hospital Comprehensive Cancer Center, Friedrich-Alexander University, Erlangen, Germany. 15. Sana Klinikum, Offenbach, Germany. 16. Helios Kliniken Berlin-Buch, Berlin, Germany. 17. National Center of Tumor Diseases, Heidelberg, Germany.
Abstract
BACKGROUND: The predictive value of tumor mutational burden (TMB), alone or in combination with an immune gene expression profile (GEP), for response to neoadjuvant therapy in early triple negative breast cancer (TNBC) is currently not known, either for immune checkpoint blockade (ICB) or conventional chemotherapy. PATIENTS AND METHODS: We obtained both whole exome sequencing and RNA-Seq data from pretreatment samples of 149 TNBC of the recent neoadjuvant ICB trial, GeparNuevo. In a predefined analysis, we assessed the predictive value of TMB and a previously developed immune GEP for pathological complete remission (pCR). RESULTS: Median TMB was 1.52 mut/Mb (range 0.02-7.65) and was significantly higher in patients with pCR (median 1.87 versus 1.39; P = 0.005). In multivariate analysis, odds ratios for pCR per mut/Mb were 2.06 [95% confidence intervals (CI) 1.33-3.20, P = 0.001] among all patients, 1.77 (95% CI 1.00-3.13, P = 0.049) in the durvalumab treatment arm, and 2.82 (95% CI 1.21-6.54, P = 0.016) in the placebo treatment arm, respectively. We also found that both continuous TMB and immune GEP (or tumor infiltrating lymphocytes) independently predicted pCR. When we stratified patients in groups based on the upper tertile of TMB and median GEP, we observed a pCR rate of 82% (95% CI 60% to 95%) in the group with both high TMB and GEP in contrast to only 28% (95% CI 16% to 43%) in the group with both low TMB and GEP. CONCLUSIONS: TMB and immune GEP add independent value for pCR prediction. Our results recommend further analysis of TMB in combination with immune parameters to individually tailor therapies in breast cancer.
BACKGROUND: The predictive value of tumor mutational burden (TMB), alone or in combination with an immune gene expression profile (GEP), for response to neoadjuvant therapy in early triple negative breast cancer (TNBC) is currently not known, either for immune checkpoint blockade (ICB) or conventional chemotherapy. PATIENTS AND METHODS: We obtained both whole exome sequencing and RNA-Seq data from pretreatment samples of 149 TNBC of the recent neoadjuvant ICB trial, GeparNuevo. In a predefined analysis, we assessed the predictive value of TMB and a previously developed immune GEP for pathological complete remission (pCR). RESULTS: Median TMB was 1.52 mut/Mb (range 0.02-7.65) and was significantly higher in patients with pCR (median 1.87 versus 1.39; P = 0.005). In multivariate analysis, odds ratios for pCR per mut/Mb were 2.06 [95% confidence intervals (CI) 1.33-3.20, P = 0.001] among all patients, 1.77 (95% CI 1.00-3.13, P = 0.049) in the durvalumab treatment arm, and 2.82 (95% CI 1.21-6.54, P = 0.016) in the placebo treatment arm, respectively. We also found that both continuous TMB and immune GEP (or tumor infiltrating lymphocytes) independently predicted pCR. When we stratified patients in groups based on the upper tertile of TMB and median GEP, we observed a pCR rate of 82% (95% CI 60% to 95%) in the group with both high TMB and GEP in contrast to only 28% (95% CI 16% to 43%) in the group with both low TMB and GEP. CONCLUSIONS:TMB and immune GEP add independent value for pCR prediction. Our results recommend further analysis of TMB in combination with immune parameters to individually tailor therapies in breast cancer.
Authors: Khalid El Bairi; Harry R Haynes; Elizabeth Blackley; Susan Fineberg; Jeffrey Shear; Sophia Turner; Juliana Ribeiro de Freitas; Daniel Sur; Luis Claudio Amendola; Masoumeh Gharib; Amine Kallala; Indu Arun; Farid Azmoudeh-Ardalan; Luciana Fujimoto; Luz F Sua; Shi-Wei Liu; Huang-Chun Lien; Pawan Kirtani; Marcelo Balancin; Hicham El Attar; Prerna Guleria; Wenxian Yang; Emad Shash; I-Chun Chen; Veronica Bautista; Jose Fernando Do Prado Moura; Bernardo L Rapoport; Carlos Castaneda; Eunice Spengler; Gabriela Acosta-Haab; Isabel Frahm; Joselyn Sanchez; Miluska Castillo; Najat Bouchmaa; Reena R Md Zin; Ruohong Shui; Timothy Onyuma; Wentao Yang; Zaheed Husain; Karen Willard-Gallo; An Coosemans; Edith A Perez; Elena Provenzano; Paula Gonzalez Ericsson; Eduardo Richardet; Ravi Mehrotra; Sandra Sarancone; Anna Ehinger; David L Rimm; John M S Bartlett; Giuseppe Viale; Carsten Denkert; Akira I Hida; Christos Sotiriou; Sibylle Loibl; Stephen M Hewitt; Sunil Badve; William Fraser Symmans; Rim S Kim; Giancarlo Pruneri; Shom Goel; Prudence A Francis; Gloria Inurrigarro; Rin Yamaguchi; Hernan Garcia-Rivello; Hugo Horlings; Said Afqir; Roberto Salgado; Sylvia Adams; Marleen Kok; Maria Vittoria Dieci; Stefan Michiels; Sandra Demaria; Sherene Loi Journal: NPJ Breast Cancer Date: 2021-12-01
Authors: Kim R M Blenman; Michal Marczyk; Thomas Karn; Tao Qing; Xiaotong Li; Vignesh Gunasekharan; Vesal Yaghoobi; Yalai Bai; Eiman Y Ibrahim; Tristen Park; Andrea Silber; Denise M Wolf; Emily Reisenbichler; Carsten Denkert; Bruno V Sinn; Mariya Rozenblit; Julia Foldi; David L Rimm; Sibylle Loibl; Lajos Pusztai Journal: Clin Cancer Res Date: 2022-06-13 Impact factor: 13.801