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Somatic mutations in DLBCL
type.4-9 While germinal center B-cell-like (GCB) DLBCL is characterized by frequent translocations of the BCL2 gene, a key regulator of the intrinsic apoptotic pathway, or mutations of the epigenetic modifiers, CREBBP and EZH2, these abnormalities are rare in activated B-cell-like (ABC) DLBCL.10 In contrast, mutations in genes encoding pro- teins implicated in B-cell receptor signaling and the NFκB pathway, such as CD79b or MYD88, or genes involved in regulation of the cell cycle such as CDKN2A, contribute to the molecular pathogenesis of ABC DLBCL.11-14
While the prognostic impact of the distinct COO sub- types has been confirmed in several studies,2,3,15,16 the influ- ence of key genomic alterations on the clinical outcomes of DLBCL patients is less clear, particularly their added clinical prognostic value over the International Prognostic Index (IPI) and COO. Mutations of several genes, such as TP53, MYD88 or CDKN2A, have been shown to be asso- ciated with poor prognosis in DLBCL patients.11,17-19 Many of these alterations, such as loss of CDKN2A or mutations of MYD88, are significantly enriched within the prognos- tically inferior ABC subtype and their independent prog- nostic role needs to be confirmed.
A recent observational study by Reddy et al.19 retrospec- tively explored 150 genetic drivers of DLBCL in 1,001 patients and developed a genomic risk model comprising genetic alterations, COO DLBCL subtype, IPI score, and dual MYC and BCL2 expression, which had greater prog- nostic ability for overall survival than molecular or clinical factors (COO, MYC/BCL2 expression, IPI) alone.19 Additionally, the studies by Schmitz et al.8 and Chapuy et al.9 helped elucidate some of the reported clinical and genetic heterogeneity in transcriptionally defined COO subsets of front-line DLBCL.8,9 Using a set of common genetic alterations, both studies identified distinct molecu- lar subtypes and evaluated their clinical prognostic out- come. Both studies identified a number of common muta- tional profiles, including two distinct subsets of ABC (one enriched for mutations in MYD88 and CD79B, and anoth- er for BCL6 and NOTCH mutations) and a GCB subset enriched for BCL2 translocations and mutations in CREBBP and EZH2. Importantly, these clusters had distinct prognostic profiles, many reflecting the established prog- nostic impact of the dominant mutations in each group (e.g. worse prognosis for the BCL2 and MYD88 subsets).9
Here, we perform an integrated analysis to evaluate if somatic mutations in DLBCL provide clinical prognostic value over established clinical and biological risk factors, including COO and IPI. Using data from the phase III GOYA study, the largest (n=1,418) randomized clinical trial in patients with previously untreated DLBCL to date, we analyzed the mutational profile of DLBCL using a well- established, highly validated targeted next-generation sequencing (NGS) platform, and evaluated the prognostic impact of somatic mutations and their relationship with COO. A previous exploratory analysis in the GOYA study showed that patients with GCB DLBCL achieved a better outcome in terms of progression-free survival (PFS) than those with the ABC subtype, irrespective of treatment.3
Methods
Patient treatment and assessments
The GOYA study design has been described previously.3 Patients included in the study had previously untreated, histologi-
cally documented, CD20+ DLBCL; details of the inclusion criteria are available in the Online Supplementary Methods.
The study was conducted in accordance with the European Clinical Trial Directive (for European centers), the Declaration of Helsinki, and the International Conference on Harmonisation Guidelines for Good Clinical Practice. The protocol was approved by the ethics committees of participating centers and registered at clinicaltrials.gov identifier: NCT01287741. All patients provided writ- ten informed consent.
Staging investigations included computed tomography (CT) scanning and bone marrow biopsy. Tumor response and progres- sion were assessed by the investigator using regular clinical and laboratory examinations and CT scans. Response was evaluated according to the Revised Response Criteria for Malignant Lymphoma20 4-8 weeks after last study treatment, or at early dis- continuation.
Cell-of-origin analysis
Cell-of-origin classification was based on gene expression pro- filing using the NanoString Lymphoma Subtyping Research-Use- Only assay (NanoString Technologies Inc., Seattle, WA, USA). COO data were available in 933 patients. Reasons for non-avail- ability were: restricted Chinese export license (n=252), CD20+ DLBCL not confirmed by central pathology (n=102) and missing/inadequate tissue (n=131).
Immunohistochemical analyses
Pre-treatment tumor samples were analyzed by a central labo- ratory using the Ventana BCL2 (124) and MYC (Y69) investiga- tional use only immunohistochemical assays. The pre-specified scoring algorithm incorporated percentage of tumor cells stained and their intensity: BCL2 immunohistochemistry-positive was defined as moderate/strong cytoplasmic staining in ≥50% of tumor cells and MYC immunohistochemistry-positive was defined as nuclear staining at any intensity in ≥40% of tumor cells.
Targeted next-generation sequencing
Genomic DNA was extracted from diagnostic formalin-fixed, paraffin-embedded tissue sections containing ≥20% tumor cells. Samples were submitted to a central laboratory for NGS-based genomic profiling and processed as previously described.21,22 Adaptor-ligated DNA underwent hybrid capture for all coding exons of 465 cancer-related genes [FoundationOne HemeTM plat- form, Foundation Medicine Incorporated (FMI), MA, USA] (Online Supplementary Methods). NGS data were available for 499 of the 1,418 patients included in the intent-to-treat (ITT) population of the GOYA study; both NGS and COO were available in 482 patients. Information about known drug targets and ongoing clin- ical trials targeting individual mutations was queried on March 23, 2018, through an FMI internal database populated using data from clinicaltrials.gov and other publicly available sources.
Validation of mutational models
We sought to confirm the prognostic value of the mutational genomic risk model generated by Reddy et al.,19 Chapuy et al.,9 and Schmitz et al.,8 as described in the Online Supplementary Methods.
Statistical analysis
Only genetic alterations with known somatic and functional status were included in the statistical analysis.21 Univariate and multivariate Cox regression analyses were used to evaluate the prognostic effect of a genetic alteration if there were ≥10 progres- sion events in mutated patients or ≥40 patients in total with the mutation. Multivariate Cox regression analysis was performed to control for COO, IPI, treatment arm, number of planned
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