Alessandro Pastore1, Vindi Jurinovic2, Robert Kridel3, Eva Hoster2, Annette M Staiger4, Monika Szczepanowski5, Christiane Pott6, Nadja Kopp7, Mark Murakami7, Heike Horn4, Ellen Leich8, Alden A Moccia3, Anja Mottok3, Ashwini Sunkavalli9, Paul Van Hummelen9, Matthew Ducar9, Daisuke Ennishi3, Hennady P Shulha3, Christoffer Hother3, Joseph M Connors3, Laurie H Sehn3, Martin Dreyling1, Donna Neuberg7, Peter Möller10, Alfred C Feller11, Martin L Hansmann12, Harald Stein13, Andreas Rosenwald8, German Ott14, Wolfram Klapper5, Michael Unterhalt1, Wolfgang Hiddemann15, Randy D Gascoyne3, David M Weinstock7, Oliver Weigert16. 1. Department of Internal Medicine III, University Hospital of the Ludwig-Maximilians-University Munich, Munich, Germany. 2. Department of Internal Medicine III, University Hospital of the Ludwig-Maximilians-University Munich, Munich, Germany; Institute for Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-University Munich, Munich, Germany. 3. Department of Lymphoid Cancer Research and the Centre for Lymphoid Cancer, British Columbia Cancer Agency, Vancouver, BC, Canada. 4. Department of Clinical Pathology, Robert-Bosch-Krankenhaus, Stuttgart, Germany; Dr Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany; University of Tübingen, Tübingen, Germany. 5. Haematopathology Section, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany. 6. Second Medical Department, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany. 7. Dana-Farber Cancer Institute, Boston, MA, USA. 8. Institute of Pathology, University of Würzburg, and Comprehensive Cancer Center Mainfranken, Würzburg, Germany. 9. Center for Cancer Genome Discovery, Boston, MA, USA; Dana-Farber Cancer Institute, Boston, MA, USA. 10. Institute of Pathology, University of Ulm, Ulm, Germany. 11. Department of Pathology, University Hospital of Schleswig-Holstein, Lübeck, Germany. 12. Senckenberg Institute of Pathology, Goethe University, Frankfurt am Main, Germany. 13. Berlin Reference Center for Lymphoma and Haematopathology, Berlin, Germany. 14. Department of Clinical Pathology, Robert-Bosch-Krankenhaus, Stuttgart, Germany. 15. Department of Internal Medicine III, University Hospital of the Ludwig-Maximilians-University Munich, Munich, Germany; Clinical Cooperative Group Leukemia, Helmholtz-Center Munich, Munich, Germany; German Cancer Consortium (DKTK), Heidelberg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany. 16. Department of Internal Medicine III, University Hospital of the Ludwig-Maximilians-University Munich, Munich, Germany; Clinical Cooperative Group Leukemia, Helmholtz-Center Munich, Munich, Germany; German Cancer Consortium (DKTK), Heidelberg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany. Electronic address: oliver.weigert@med.uni-muenchen.de.
Abstract
BACKGROUND: Follicular lymphoma is a clinically and genetically heterogeneous disease, but the prognostic value of somatic mutations has not been systematically assessed. We aimed to improve risk stratification of patients receiving first-line immunochemotherapy by integrating gene mutations into a prognostic model. METHODS: We did DNA deep sequencing to retrospectively analyse the mutation status of 74 genes in 151 follicular lymphoma biopsy specimens that were obtained from patients within 1 year before beginning immunochemotherapy consisting of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). These patients were recruited between May 4, 2000, and Oct 20, 2010, as part of a phase 3 trial (GLSG2000). Eligible patients had symptomatic, advanced stage follicular lymphoma and were previously untreated. The primary endpoints were failure-free survival (defined as less than a partial remission at the end of induction, relapse, progression, or death) and overall survival calculated from date of treatment initiation. Median follow-up was 7·7 years (IQR 5·5-9·3). Mutations and clinical factors were incorporated into a risk model for failure-free survival using multivariable L1-penalised Cox regression. We validated the risk model in an independent population-based cohort of 107 patients with symptomatic follicular lymphoma considered ineligible for curative irradiation. Pretreatment biopsies were taken between Feb 24, 2004, and Nov 24, 2009, within 1 year before beginning first-line immunochemotherapy consisting of rituximab, cyclophosphamide, vincristine, and prednisone (R-CVP). Median follow-up was 6·7 years (IQR 5·7-7·6). FINDINGS: We established a clinicogenetic risk model (termed m7-FLIPI) that included the mutation status of seven genes (EZH2, ARID1A, MEF2B, EP300, FOXO1, CREBBP, and CARD11), the Follicular Lymphoma International Prognostic Index (FLIPI), and Eastern Cooperative Oncology Group (ECOG) performance status. In the training cohort, m7-FLIPI defined a high-risk group (28%, 43/151) with 5-year failure-free survival of 38·29% (95% CI 25·31-57·95) versus 77·21% (95% CI 69·21-86·14) for the low-risk group (hazard ratio [HR] 4·14, 95% CI 2·47-6·93; p<0·0001; bootstrap-corrected HR 2·02), and outperformed a prognostic model of only gene mutations (HR 3·76, 95% CI 2·10-6·74; p<0·0001; bootstrap-corrected HR 1·57). The positive predictive value and negative predictive value for 5-year failure-free survival were 64% and 78%, respectively, with a C-index of 0·80 (95% CI 0·71-0·89). In the validation cohort, m7-FLIPI again defined a high-risk group (22%, 24/107) with 5-year failure-free survival of 25·00% (95% CI 12·50-49·99) versus 68·24% (58·84-79·15) in the low-risk group (HR 3·58, 95% CI 2·00-6·42; p<0.0001). The positive predictive value for 5-year failure-free survival was 72% and 68% for negative predictive value, with a C-index of 0·79 (95% CI 0·69-0·89). In the validation cohort, risk stratification by m7-FLIPI outperformed FLIPI alone (HR 2·18, 95% CI 1·21-3·92), and FLIPI combined with ECOG performance status (HR 2·03, 95% CI 1·12-3·67). INTERPRETATION: Integration of the mutational status of seven genes with clinical risk factors improves prognostication for patients with follicular lymphoma receiving first-line immunochemotherapy and is a promising approach to identify the subset at highest risk of treatment failure. FUNDING: Deutsche Krebshilfe, Terry Fox Research Institute.
BACKGROUND:Follicular lymphoma is a clinically and genetically heterogeneous disease, but the prognostic value of somatic mutations has not been systematically assessed. We aimed to improve risk stratification of patients receiving first-line immunochemotherapy by integrating gene mutations into a prognostic model. METHODS: We did DNA deep sequencing to retrospectively analyse the mutation status of 74 genes in 151 follicular lymphoma biopsy specimens that were obtained from patients within 1 year before beginning immunochemotherapy consisting of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). These patients were recruited between May 4, 2000, and Oct 20, 2010, as part of a phase 3 trial (GLSG2000). Eligible patients had symptomatic, advanced stage follicular lymphoma and were previously untreated. The primary endpoints were failure-free survival (defined as less than a partial remission at the end of induction, relapse, progression, or death) and overall survival calculated from date of treatment initiation. Median follow-up was 7·7 years (IQR 5·5-9·3). Mutations and clinical factors were incorporated into a risk model for failure-free survival using multivariable L1-penalised Cox regression. We validated the risk model in an independent population-based cohort of 107 patients with symptomatic follicular lymphoma considered ineligible for curative irradiation. Pretreatment biopsies were taken between Feb 24, 2004, and Nov 24, 2009, within 1 year before beginning first-line immunochemotherapy consisting of rituximab, cyclophosphamide, vincristine, and prednisone (R-CVP). Median follow-up was 6·7 years (IQR 5·7-7·6). FINDINGS: We established a clinicogenetic risk model (termed m7-FLIPI) that included the mutation status of seven genes (EZH2, ARID1A, MEF2B, EP300, FOXO1, CREBBP, and CARD11), the Follicular Lymphoma International Prognostic Index (FLIPI), and Eastern Cooperative Oncology Group (ECOG) performance status. In the training cohort, m7-FLIPI defined a high-risk group (28%, 43/151) with 5-year failure-free survival of 38·29% (95% CI 25·31-57·95) versus 77·21% (95% CI 69·21-86·14) for the low-risk group (hazard ratio [HR] 4·14, 95% CI 2·47-6·93; p<0·0001; bootstrap-corrected HR 2·02), and outperformed a prognostic model of only gene mutations (HR 3·76, 95% CI 2·10-6·74; p<0·0001; bootstrap-corrected HR 1·57). The positive predictive value and negative predictive value for 5-year failure-free survival were 64% and 78%, respectively, with a C-index of 0·80 (95% CI 0·71-0·89). In the validation cohort, m7-FLIPI again defined a high-risk group (22%, 24/107) with 5-year failure-free survival of 25·00% (95% CI 12·50-49·99) versus 68·24% (58·84-79·15) in the low-risk group (HR 3·58, 95% CI 2·00-6·42; p<0.0001). The positive predictive value for 5-year failure-free survival was 72% and 68% for negative predictive value, with a C-index of 0·79 (95% CI 0·69-0·89). In the validation cohort, risk stratification by m7-FLIPI outperformed FLIPI alone (HR 2·18, 95% CI 1·21-3·92), and FLIPI combined with ECOG performance status (HR 2·03, 95% CI 1·12-3·67). INTERPRETATION: Integration of the mutational status of seven genes with clinical risk factors improves prognostication for patients with follicular lymphoma receiving first-line immunochemotherapy and is a promising approach to identify the subset at highest risk of treatment failure. FUNDING: Deutsche Krebshilfe, Terry Fox Research Institute.
Authors: Pablo Mozas; Andrea Rivero; Alfredo Rivas-Delgado; Ferran Nadeu; Juan Gonzalo Correa; Carlos Castillo; Alex Bataller; Tycho Baumann; Eva Giné; Julio Delgado; Neus Villamor; Elías Campo; Laura Magnano; Armando López-Guillermo Journal: Ann Hematol Date: 2021-02-25 Impact factor: 3.673
Authors: Romain Guièze; Vivian M Liu; Daniel Rosebrock; Alexis A Jourdain; María Hernández-Sánchez; Aina Martinez Zurita; Jing Sun; Elisa Ten Hacken; Kaitlyn Baranowski; Philip A Thompson; Jin-Mi Heo; Zachary Cartun; Ozan Aygün; J Bryan Iorgulescu; Wandi Zhang; Giulia Notarangelo; Dimitri Livitz; Shuqiang Li; Matthew S Davids; Anat Biran; Stacey M Fernandes; Jennifer R Brown; Ana Lako; Zoe B Ciantra; Matthew A Lawlor; Derin B Keskin; Namrata D Udeshi; William G Wierda; Kenneth J Livak; Anthony G Letai; Donna Neuberg; J Wade Harper; Steven A Carr; Federica Piccioni; Christopher J Ott; Ignaty Leshchiner; Cory M Johannessen; John Doench; Vamsi K Mootha; Gad Getz; Catherine J Wu Journal: Cancer Cell Date: 2019-09-19 Impact factor: 31.743