© The Author(s) 2021.Follicular lymphoma (FL) is the second most common non-Hodgkin lymphoma (NHL, 20–30%) after diffuse large B-cell lymphoma (DLBCL). Despite the introduction of rituximab and the high response rate to first-line treatment, approximately 20% of the FL patients relapse or progress within 2 years of receiving first-line therapy. Therefore, the major challenge is finding biomarkers that identify high-risk patients at diagnosis.This work was partially supported by the Instituto de Salud Carlos III (ISCIII), Spanish Ministry of Economy and Competitiveness PI15/01393, PI18/00410, CIBERONC-CB16/12/00233, and “Una manera de hacer Europa” (Innocampus; CEI-2010-1-0010)”, the Education Council or Health Council of the Junta de Castilla y León (CAS102P17, GRS 1180/A/15), Spanish Association Against Cancer (AECC; PROYE18020BEA), and Gilead Sciences (GLD17/00334). CJ, MES, and AMe are supported by the ISCII (CD19/00030, CPII18/00028, and FI19/00320). MGA, IPC, and CJ were supported by the Spanish Society of Hematology Foundation (FEHH). All Spanish funding is co-sponsored by the European Union FEDER program

Alcoceba, Miguel

Alonso-Álvarez, Sara

Antón, Alicia

Balanzategui, Ana

Blanco, Pedro

Blanco, Óscar

Caballero, Maria Dolores

Chillón, M. del Carmen

Díaz, Luis G.

Esteban, Carmen

García-Alvarez, María

García-Sanz, Ramón

González, Marcos

González-Calle, Verónica

Gutiérrez, Norma Carmen

Jiménez, Cristina

Maldonado, Rebeca

Martín, Alejandro

Medina, Alejandro

Prieto-Conde, Isabel

Puig, Noemi

Rodríguez, Marta

Sarasquete, María Eugenia

Tamayo, Pilar

Blood Cancer Journal

English

Digital.CSIC

García-Álvarez et al. Blood Cancer Journal           (2021) 11:11 https://doi.org/10.1038/s41408-020-00395-y Blood Cancer JournalCORRESPONDENCE Open Ac ce s sGenetic complexity impacts the clinical outcome offollicular lymphoma patientsMaría García-Álvarez1, Sara Alonso-Álvarez2, Isabel Prieto-Conde 1, Cristina Jiménez1, M. Eugenia Sarasquete 1,M. Carmen Chillón1, Alejandro Medina 1, Ana Balanzategui1, Rebeca Maldonado1, Alicia Antón1, Marta Rodríguez3,Oscar Blanco3, Luis G. Díaz4, Pilar Tamayo4, Pedro Blanco5, Carmen Esteban6, Verónica González-Calle1, Noemí Puig1,Norma Gutiérrez1, Alejandro Martín1, Ramón García-Sanz 1, Marcos González1, M. Dolores Caballero1 andMiguel Alcoceba 1Dear Editor,Follicular lymphoma (FL) is the second most commonnon-Hodgkin lymphoma (NHL, 20–30%) after diffuselarge B-cell lymphoma (DLBCL). Despite the introductionof rituximab and the high response rate to first-linetreatment, approximately 20% of the FL patients relapseor progress within 2 years of receiving first-line therapy.Therefore, the major challenge is finding biomarkers thatidentify high-risk patients at diagnosis.Qu et al. reported an association between increasedgenomic complexity, a concept based on copy-numberaberrations (CNAs) and copy neutral loss of hetero-zygosity (cnLOH), and poor outcome in FL [1]. However,the concept of genetic complexity based on the number ofmutated genes has not been analyzed in FL patients yet.The aim of the present study was to analyze in detail thegenetic landscape and genetic complexity by next-generation sequencing (NGS), defined by the number ofmutated genes, in a FL series to improve our under-standing of the biology of FL and its impact on the clinicaloutcome of the patients. See Supplementary Materials fordetails of methods.A total of 83 FL grade I–IIIA patients diagnosed at theUniversity Hospital of Salamanca between January 2000and December 2017 were retrospectively included. Thestudy was approved by the local Ethical Committee, inaccordance with Spanish law and the Declaration ofHelsinki. Written informed consent was obtained from allthe patients. Clinical characteristics of the cohort aredescribed in Table 1.We explored in patients who received rituximab-basedimmunochemotherapy (R-ICT, n= 47) the influence ofclinical-biological variables at diagnosis on the followingclinical endpoints: (i) complete response rate at30 months (CR30) [2], defined as complete response30 months after the first day of induction treatment; (ii)failure-free survival (FFS), defined as less than a partialresponse at the end of induction, relapse, progression, ordeath [3]; and (iii) overall survival (OS), defined as thetime from the date of diagnosis of FL to that of death fromany cause.We identified 56 mutated genes in our FL series and548 somatic nonsynonymous variants. FL patients har-bored a median of 5 mutated genes (range 1–12) and 6mutations (range 1–18) per case in our series. Fourteengenes were mutated with a frequency greater than 10%:CREBBP 63.9% (n= 53), KMT2D/MLL2 55.4% (n= 46),BCL2 41% (n= 34), TNFRSF14 27.7% (n= 23), EZH222.9% (n= 19), STAT6 19.3% (n= 12), ARID1A 18.1%(n= 15), FOXO1 18.1% (n= 15), CARD11 14.5% (n= 12),EP300 14.5% (n= 12), GNA13 13.2% (n= 11), IRF8 12%(n= 10), SMARCA4 12% (n= 10), and HIST1H1E 10.8%(n= 9) (Supplementary Fig. S1), being a subset of muta-tions clustered at known domains or hotspots (Supple-mentary Fig. S2).The clinical impact of the 14 mutated genes with fre-quency >10% were explored. We first compared theclinical characteristics at diagnosis between groups toavoid potential biases in the analyses. CREBBP mutationswere more frequently observed in younger FL patients© The Author(s) 2021OpenAccessThis article is licensedunder aCreativeCommonsAttribution 4.0 International License,whichpermits use, sharing, adaptation, distribution and reproductionin any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate ifchangesweremade. The images or other third partymaterial in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to thematerial. Ifmaterial is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtainpermission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Correspondence: Ramón. García-Sanz (rgarcias@usal.es)1Department of Hematology, University Hospital of Salamanca (HUS/IBSAL),CIBERONC and Cancer Research Institute of Salamanca-IBMCC (USAL-CSIC),Salamanca, Spain2Department of Hematology, Central University Hospital of Asturias (HUCA),Oviedo, SpainFull list of author information is available at the end of the articleBlood Cancer Journal1234567890():,;1234567890():,;1234567890():,;1234567890():,;(<60 years, P < 0.05). No other differences were observedfor individual gene mutations regarding clinical char-acteristics of patients.Regarding the clinical endpoints, mutations in EZH2were significantly associated with the presence of CR at30 months (100% vs. 53.3%, P <0.05). Considering FFS,those FL patients with FOXO1 mutations (25% vs. 68%, P<0.05) showed significantly shorter FFS at 5 years than theremaining patients. No other gene mutations were asso-ciated with CR30, FFS, or OS at 5 years.All seven genes included in the m7-FLIPI clinical-genetic risk model described by Pastore et al. [3] weretargeted by our NGS design, and therefore this modelcould be applied in 74 patients (89%). This score reclas-sified 17 high-risk FLIPI patients (23%) into the low-riskgroup. In our series, lower number of cases in CR30 (33%vs. 71%, P > 0.05), shorter FFS at 5 years (36% vs. 74%,P > 0.1), and shorter OS at 5 years (64% vs. 82%, P > 0.1)were found in high-risk m7-FLIPI patients although thedifferences were not statistically significant (Supplemen-tary Fig. S3). In this series, FLIPI index was able to dis-tinguish two groups with different OS at 5 years (69% vs.88%, P < 0.05) (Supplementary Fig. S3).In relation to genetic complexity, we observed a con-tinuous FFS decrease as the number of mutated genesincreased. Thus, we identified two groups with differentFFS: 53 patients (63.9%) with ≤5 mutated genes and 30patients (36.1%) with >5 mutated genes, which exactlymatches with the median number of mutated genes andthe result of the ROC analysis.These two groups did not show significant differences inclinical characteristics including histological grade, FLIPI,and treatment requirement among others (SupplementaryTable S1). By contrast, mutated genes showed a differentdistribution in both groups, underlining the high fre-quency of BCL2 (63% vs. 28%, P < 0.01), TNFRSF14 (43%vs. 19%, P < 0.05), ARID1A (30% vs. 11%, P < 0.05),FOXO1 (33% vs. 9%, P < 0.05), GNA13 (27% vs. 6%, P <0.05), IRF8 (27% vs. 4%, P < 0.01), andMEF2B (23% vs. 0%,P < 0.01) genes in group with >5 mutated genes.A strong association was observed between >5 mutatedgenes and a lower number of cases in CR at 30 months ascompared to ≤5 mutated genes (29% vs. 83%, P < 0.01).Moreover, patients with >5 mutated genes had a higherrisk of treatment failure, since these patients showedshorter FFS at 5 years than those with ≤5 mutated genes(30% vs. 82%, P < 0.001) (Fig. 1A). Finally, patients with >5mutated genes displayed shorter OS at 5 years thanpatients with ≤5 mutated genes (58% vs. 88%, P < 0.05)(Fig. 1B).In the multivariate analysis, including FLIPI and m7-FLIPI as co-variables besides those statistically significantin univariate analysis, the only variable independentlyassociated with shorter FFS was having >5 mutated genesTable 1 Clinical characteristics of FL patients (n= 83).Variable Training cohort n (%)Age, years (median, range) 62.5 (19–86)Sex F/M 46/37Histological gradea1 30 (38.0)2 40 (50.6)3A 9 (11.4)FLIPIa0-1 (Low risk) 24 (32.0)2 (Intermediate risk) 17 (22.7)3-5 (High risk) 34 (45.3)Ann ArboraI 10 (14.1)II 9 (12.7)III 7 (9.9)IV 45 (63.4)First-line therapyNever treated 10 (12.0)Palliative care 4 (4.8)Rituximab-based ICT 47 (56.6)R-CHOP 33 (39.8)R-Bendamustine 3 (3.6)R-CVP 3 (3.6)R-FC 4 (4.8)R-Lenalidomide 4 (4.8)CT without rituximab 13 (15.7)CHOP 11 (13.3)Other 2 (2.4)Radiotherapy alone or with rituximab 6 (7.2)Rituximab alone 3 (3.6)Maintenance with rituximaba 37 (53.6)Response after induction therapyaCR 37 (53.6)PR 28 (40.6)NR/failure 4 (5.8)CR30a 33 (47.8)aHistological grade was available for 79 (95%) patients; FLIPI was available for 75(90%) patients; Ann Arbor was available for 71 (86%) patients; Maintenance,response and CR30 were calculated for 69 (83%) patients. CHOP cyclopho-sphamide, doxorubicin, vincristine, prednisone; CR complete response, CR30complete response 30 months after the date induction treatment began, CTchemotherapy, CVP cyclophosphamide, vincristine, prednisone; FLIPI FL Inter-national Prognosis Index, ICT immunochemotherapy, NR no response, PR partialresponse, R rituximab.García-Álvarez et al. Blood Cancer Journal           (2021) 11:11 Page 2 of 4Blood Cancer Journal(HR: 5.5, 95% CI: 2.1–14.6) (Supplementary Table S2). Interms of OS, to present >5 mutated genes (HR: 5.4, 95%CI: 1.5–19.6) and high-risk FLIPI (HR: 7.2, 95% CI:1.3–39.1) at the time of diagnosis were independentlyassociated with shorter OS (Supplementary Table S2).In the present study, the mutational landscape analysishas allowed to identify 14 highly recurring mutated genesconsidered as drivers or early events in FL pathogenesis,which are consistent with previous reports [4–7]. Inaddition, we evaluated the m7-FLIPI clinicogenetic riskmodel in a real-world cohort of 47 R-ICT-treated patients,allowing the reclassification of 50% high-risk FLIPIpatients in low-risk group, similar to the original series[3]. The m7-FLIPI showed no statistically significant dif-ferences in terms of FFS or OS between high-risk andlow-risk patients in our series, probably due to the size ofstudy cohort. However, the FLIPI index distinguishedgroups with different OS in this series. Moreover, in linewith our results, other studies have also found no asso-ciation of m7-FLIPI with different outcomes in real-worldand clinical trial populations [5, 8].In this work, we showed for the first time the associa-tion of genetic complexity, defined by the number ofmutated genes, and FL outcome, independently of FLIPI.Genetic complexity in our study was defined as >5mutated genes among 66 and it was associated with apoor outcome assessed by low number of cases in CR at30 months, poor FFS, and short OS. In a very recent work,an increased genomic complexity defined by the numberof CNAs was associated with worse FFS and OS in FL [1].The impact of the number of mutations or the number ofCNAs in the clinical course of patients has been reportedin other hematological malignancies [9, 10].Even associated to genetic complexity, we pointed outthe association of FOXO1 mutations with adverse out-come. FOXO1 mutations had already been correlated toworse FFS in FL [3], and worse OS in DLBCL [11], andthey were found at high prevalence in relapsed/refractoryFL [12], thus supporting its adverse role in FL outcome.Finally, EZH2 mutations were associated to the persis-tence of complete response after 30 months from therapyinitiation (CR30), although they were equally distributedbetween genetic complexity groups, thus suggesting asubgroup of patients with better prognosis independentlyof the genetic complexity. This is in line with prior studiesthat associate EZH2 mutations with favorable prognosisin FL [13–15].In summary, our study has increased the knowledge ofthe FL biology through the characterization of the muta-tional landscape of a representative series of FL patients,  ≤5 mutated genes (n=30)      >5 mutated genes (n=17) Failure-free survival (%) Time (months) 5 years P < 0.00130%82%≤5 mutated genes (n=30)       >5 mutated genes (n=17) Overall survival (%) Time (months) 5 years 58%88%P = 0.019A. B. Fig. 1 Genetic complexity and FL clinical outcome. Kaplan-Meier analysis of (A) failure-free survival and (B) overall survival by number of mutatedgenes in FL patients treated with R-ICT (n= 47). The vertical dashed line indicates 5-year follow-up.García-Álvarez et al. Blood Cancer Journal           (2021) 11:11 Page 3 of 4Blood Cancer Journaland allowed to confirm the dependence of the tumorgerminal center B-cell on alterations in genes involved inepigenetic modification, signaling, and transcription fac-tors. Our results identified genetic alterations associatedwith prognosis in a cohort treated with chemoimmu-notherapy based on rituximab. The most outstandingresult, however, was that genetic complexity related withlower number of CR30 cases, worse FFS, and shortenedOS, independently of FLIPI. Although the small number ofpatients could limit some analysis and further validation isrequired, we have shown that genetic complexity con-stitutes a promising robust tool that may be incorporatedinto risk predictive models, and may improve risk classifi-cation of FL to help in the development of new risk-adapted therapies.AcknowledgementsThis work was partially supported by the Instituto de Salud Carlos III (ISCIII),Spanish Ministry of Economy and Competitiveness PI15/01393, PI18/00410,CIBERONC-CB16/12/00233, and “Una manera de hacer Europa” (Innocampus;CEI-2010-1-0010)”, the Education Council or Health Council of the Junta deCastilla y León (CAS102P17, GRS 1180/A/15), Spanish Association AgainstCancer (AECC; PROYE18020BEA), and Gilead Sciences (GLD17/00334). CJ, MES,and AMe are supported by the ISCII (CD19/00030, CPII18/00028, and FI19/00320). MGA, IPC, and CJ were supported by the Spanish Society ofHematology Foundation (FEHH). All Spanish funding is co-sponsored by theEuropean Union FEDER program. The authors wish to thank Alba Rodríguez,Montserrat Hernández-Ruano, Estrella Arnés, Inmaculada Sánchez, Rocío Corraland Francisco Boix (University Hospital of Salamanca, Spain) for their technicalsupport, and Sara Bonilla, for helping with the mutation plots. The authors arealso very grateful to the patients who participated in this study.Author details1Department of Hematology, University Hospital of Salamanca (HUS/IBSAL),CIBERONC and Cancer Research Institute of Salamanca-IBMCC (USAL-CSIC),Salamanca, Spain. 2Department of Hematology, Central University Hospital ofAsturias (HUCA), Oviedo, Spain. 3Department of Pathology, University Hospitalof Salamanca (HUS/IBSAL), Salamanca, Spain. 4Department of NuclearMedicine, University Hospital of Salamanca (HUS/IBSAL), Salamanca, Spain.5Department of Otorhinolaryngology, University Hospital of Salamanca (HUS/IBSAL), Salamanca, Spain. 6Department of General and Gastrointestinal Surgery,University Hospital of Salamanca (HUS/IBSAL), Salamanca, SpainAuthor contributionsM.G.A. and M.A. conceived and designed the study. M.G.A., S.A.A., I.P.C., C.J.,A.Me., A.B., R.M., and A.A. produced the molecular results. M.R. and O.B. werethe pathologists involved in the pathological and histological review of thecases. M.A. and M.G.A. analyzed the data, performed the statistical analyses,and wrote the first draft of the manuscript. S.A.A. and V.G.C. incorporated theclinical data into the database, and checked data for inconsistencies. M.E.S. andM.C.C. provided statistical support. S.A.A., L.G.D., P.T., P.B., C.E., V.G.S., N.P., N.G., A.M., R.G.S., M.G., and M.D.C. provided patient samples and/or clinical data. A.M.,R.G.S., M.G., and M.D.C. reviewed the final manuscript. M.G., M.A., and M.D.C.obtained funding for the study. R.G.S., the head of the group, produced thefinal revision of the manuscript and gave final approval its publication.Conflict of interestThe authors report grants PI15/01393, PI18/00410, CAS102P17, GRS1180/A/15,GLD17/00334, CIBERONC-CB16/12/00233, PROYE18020BEA during the conductof the study, and from Gilead Sciences (GLD15/00348, GLD16/00162, GLD18/00117), Incyte, Janssen, Celgene, and Amgen outside the submitted work. M.G.A., I.P.C., C.J., M.E.S., A.Me., and V.G.C. are or were supported by the Spanishgovernment (ISCIII and/or FEHH). Consulting fees and/or non-financial supportwere reported from Abbvie (M.G., M.A., M.D.C.), Amgen (N.P., M.D.C.), BindingSite (N.P.), Bristol-Myers Squibb (V.G.C., N.P., A.M., R.G.S., M.D.C.), Eusa Pharma (A.M.), Gilead (A.M., M.G., M.D.C.), iQone Healthcare (A.M.), Incyte (R.G.S.), Janssen(V.G.C., N.P., A.M., R.G.S., M.G., M.D.C., M.A.), Kite (M.D.C.), Kyowa Kirin (A.M.), MSD(M.D.C.), Novartis (S.A.A., M.D.C.), Prothena (V.G.C.), Roche (A.M., M.G., M.D.C., M.A.), Servier (A.M., M.D.C.), Takeda (N.P., R.G.S., M.D.C.), and Weber (N.P.). Theremaining authors have no relevant conflicts of interest to disclose. R.G.S. is thepresident of the Spanish Society of Hematology.Publisher’s noteSpringer Nature remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations.Supplementary Information accompanies this paper at (https://doi.org/10.1038/s41408-020-00395-y).Received: 25 August 2020 Revised: 19 November 2020 Accepted: 27November 2020References1. Qu, X. et al. Genomic alterations important for the prognosis in patients withfollicular lymphoma treated in SWOG study S0016. Blood 133, 81–93 (2019).2. Shi, Q. et al. Thirty-month complete response as a surrogate end point in first-line follicular lymphoma therapy: an individual patient-level analysis of mul-tiple randomized trials. J. Clin. Oncol. 35, 552–560 (2017).3. Pastore, A. et al. Integration of gene mutations in risk prognostication forpatients receiving first-line immunochemotherapy for follicular lymphoma: aretrospective analysis of a prospective clinical trial and validation in apopulation-based registry. Lancet Oncol. 16, 1111–1122 (2015).4. Green, M. R. et al. Hierarchy in somatic mutations arising during genomicevolution and progression of follicular lymphoma. Blood 121, 1604–1611(2013).5. Krysiak, K. et al. Recurrent somatic mutations affecting B-cell receptor signalingpathway genes in follicular lymphoma. Blood 129, 473–483 (2017).6. Korfi, K., Ali, S., Heward, J. A. & Fitzgibbon, J. Follicular lymphoma, a B cellmalignancy addicted to epigenetic mutations. Epigenetics 12, 370–377 (2017).7. Kuppers, R. & Stevenson, F. K. Critical influences on the pathogenesis offollicular lymphoma. Blood 131, 2297–2306 (2018).8. Lockmer, S. et al. M7-FLIPI is not prognostic in follicular lymphoma patientswith first-line rituximab chemo-free therapy. Br. J. Haematol. 188, 259–267(2020).9. Puente, X. S. et al. Non-coding recurrent mutations in chronic lymphocyticleukaemia. Nature 526, 519–524 (2015).10. Prieto-Conde, M. I. et al. Identification of relapse-associated gene mutations bynext-generation sequencing in low-risk acute myeloid leukaemia patients. Br.J. Haematol. 189, 718–730 (2020).11. Trinh, D. L. et al. Analysis of FOXO1 mutations in diffuse large B-cell lymphoma.Blood 121, 3666–3674 (2013).12. Umakanthan, J. M. et al. Phase I/II study of dasatinib and exploratory genomicanalysis in relapsed or refractory non-Hodgkin lymphoma. Br. J. Haematol. 184,744–752 (2019).13. Bodor, C. et al. EZH2 mutations are frequent and represent an early event infollicular lymphoma. Blood 122, 3165–3168 (2013).14. Weigert, O. & Weinstock, D. M. The promises and challenges of using genemutations for patient stratification in follicular lymphoma. Blood 130,1491–1498 (2017).15. Huet, S. et al. EZH2 alterations in follicular lymphoma: biological and clinicalcorrelations. Blood Cancer J. 7, e555 (2017).García-Álvarez et al. Blood Cancer Journal           (2021) 11:11 Page 4 of 4Blood Cancer Journal

Genetic complexity impacts the clinical outcome of follicular lymphoma patients

https://digital.csic.es/bitstream/10261/261439/1/Genetic%20complexity%20impacts_Garc%c3%ada_PV_Art2021.pdf

Genetic complexity impacts the clinical outcome of follicular lymphoma patients

Abstract

Similar works

Full text

Available Versions

Digital.CSIC