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C.R. Bolen et al.
95%CI: 0.42-0.88; P<0.01), when corrected for COO, the model was no longer significant (HR: 0.77; 95%CI: 0.49- 1.2; P=0.27), indicating that it provided little additional benefit over the most commonly used gene expression profiling and fluorescence in situ hybridization assays, and that COO evaluation in combination with BCL2 and MYC translocation status may be a simpler approach with simi- lar overall prognostic relevance, although other genomic features such as TP53 or CREBBP may provide additional information that is worth considering. However, it should be noted that we were unable to apply the Reddy et al.19 model in its entirety due to some differences in gene avail- ability on the FMI platform, and for the fact that Reddy et al.19 evaluated the model in terms of overall survival, whereas our study evaluated it in terms of PFS.
The current study also demonstrated the molecular het- erogeneity of DLBCL, with the majority of the observed genetic alterations shared by COO subtypes; however, the frequency of mutations in 15 genes was enriched between GCB and ABC subtypes. In addition, approxi- mating the molecular clusters described by Schmitz et al.8 and Chapuy et al.9 revealed a consistent set of molecular subgroups, with some specific to either GCB (EZB-like, G3), ABC (MCD- or N1-like, G5), or Unclassified (BN2- like) COO subtypes, and others appearing to be inde- pendent of the tumor COO. Among the clusters defined by NMF, we observed a significantly worse prognosis for clusters G2, G3 and G5, consistent with Chapuy’s C2, C3 and C5 clusters.9 This is most likely driven by the enrich- ment of individual prognostic alterations among these subgroups (BCL2 and CREBBP in G3; TP53 and REL in G2), or by enrichment for the ABC subset (G5). By con- trast, our approximation of the Schmitz clusters identi- fied four sets of clusters with approximately equivalent prognosis, suggesting that the founder alterations used to define these clusters are not sufficient to identify patients with worse prognosis. Although we cannot directly reca- pitulate the clusters defined by Schmitz et al.8 and Chapuy et al.,9 both due to limitations of the FMI panel and because algorithms for classifying DLBCL samples are not publicly available, our results here show that we can suc- cessfully capture the molecular heterogeneity of DLBCL using this targeted mutational panel.
Since 2011, several studies have characterized the landscape of somatic mutations in DLBCL by whole exome NGS technologies5-7,26 or the FMI targeted exome-sequencing platform,4 and have identified recur- rent genetic alterations. Our study identified a relatively lower number of genetic alterations compared with whole-exome studies, but it was relatively consistent with the frequencies of mutations identified by Intlekofer et al.4 This is most likely because both our study and the study by Intlekofer et al. focused on mutations with known or likely somatic and functional status. FMI may also lack some alterations of potential relevance in DLBCL, including alterations in the human leukocyte antigen genes, potentially limiting the scope of this analy-
sis. In contrast, the relatively low prevalence of MYC translocations in this dataset may be reflective of an accrual bias during patient recruitment. Patients with these alterations, particularly in combination with BCL2 translocations (double-hit lymphoma) have been well characterized as having particularly aggressive disease and are generally more difficult to recruit for clinical tri- als. These patients may also benefit from more aggressive chemotherapy than G-/R-CHOP, which could also explain why these patients were not enrolled in GOYA.
Our data show that DLBCL contains mutations in a variety of potentially targetable pathways. In total, a majority (59%) of patients harbor ≥1 alteration in genes that would be eligible for potential targeted therapies approved in other indications (e.g. venetoclax for BCL2 translocations/amplifications, everolimus for PTEN loss, and ruxolitinib and tofacitinib for JAK2 mutations) and over 70% of patients would potentially qualify to be enrolled in ongoing clinical trials based on genomic infor- mation, according to the FMI clinical trial database. Genes enriched between GCB and ABC subtypes also included previously reported driver mutations and gene alterations that can be targeted by novel therapies, such as the gain of function mutation of EZH2 in the GCB DLBCL subtype,27 and the BCL2 translocations and ampli- fications.28 These mutations, along with COO subtype information, would be useful for the design of clinical tri- als involving combinations of novel targeted therapies.
In conclusion, using the largest prospective dataset in previously untreated DLBCL to date, we demonstrated the molecular heterogeneity of DLBCL, with potential treatment targets harbored by the distinct COO sub- types. Only alterations in BCL2 were significantly associ- ated with clinical outcome independent of COO and clin- ical factors, thereby demonstrating the strong prognostic value of COO for clinical outcome in DLBCL.
Data sharing
Qualified researchers may request access to individual patient level data through the clinical study data request platform. Further details on Roche's criteria for eligible studies are available here (https://vivli.org/members/ourmembers/). For further details on Roche's Global Policy on the Sharing of Clinical Information and how to request access to related clinical study documents, see here(https://www.roche.com/research_and_development/ who_we_are_how_we_work/clinical_trials/our_commitment_to_ data_sharing.htm).
Acknowledgments
The authors would like to thank the GOYA study team inves- tigators, coordinators, nurses and patients.
Funding
GOYA was supported by F. Hoffmann-La Roche Ltd, with sci- entific support from the Fondazione Italiana Linfomi. Editorial support was provided by Louise Profit, PhD (Gardiner-Caldwell Communications Ltd, Macclesfield, UK), and was funded by F. Hoffmann-La Roche Ltd.
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3. Vitolo U, Trneny M, Belada D, et al.
Obinutuzumab or rituximab plus cyclophosphamide, doxorubicin, vin- cristine, and prednisone in previously
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