Page 312 - Haematologica Vol. 109 - July 2024

LETTER TO THE EDITOR
Validation of LymphGen classification on a 400-gene clinical next-generation sequencing panel in diffuse large B-cell lymphoma: real-world experience from a cancer center
Diffuse large B-cell lymphoma (DLBCL) is the most com- mon type of non-Hodgkin lymphoma and is characterized by high clinicopathologic heterogeneity.1 This has fueled several efforts at subclassification aiming to identify prog- nostic and clinically relevant subgroups. Currently, the most widely used classification is based on gene expression profiles, stratifying DLBCL according to the cell-of-origin (COO) into activated B-cell (ABC) and germinal center B-cell (GCB) subtypes.2-4 Patients with ABC-DLBCL have been reported to have less favorable responses to stan- dard therapy than those with GCB-DLBCL. Unfortunately, clinical studies based on this classification have repeat- edly failed to improve the outcome of DLBCL patients, suggesting that this simplified scheme is not sufficiently effective for clinical trial design.5 To address this problem, several recent studies have utilized high-resolution ge- nomic analysis to subcategorize patients based on genetic alteration profiles.6-8 This approach has uncovered broader biological heterogeneity than the ABC/GCB paradigm. In a recent National Cancer Institute (NCI) study, observations have been applied to develop a probabilistic classification algorithm, LymphGen, that enables the subclassification of DLBCL into 6 molecularly distinct groups: MCD, BN2, EZB, ST2, A53, and N1, with prognostic correlations.9,10 Biomo- lecular clusters defined by other studies have overlapped with those of the NCI study.11 However, all large-scale studies have primarily been performed using data derived by whole genome, whole exome sequencing, or a large comprehensive target next-generation sequencing (NGS) panel carried out as part of wider research endeavors. In contrast, in routine clinical practice, sequencing is neces- sarily targeted to limited sets of genes with a key role for immediate clinical management. In this study, therefore, we aimed to apply the published LymphGen algorithm to a validated clinical NGS assay: the Memorial Sloan Kettering Cancer Center’s (MSKCC) Integrated Mutation Profiling of Actionable Cancer Targets for Hematologic malignancies NGS panel (MSK-IMPACT HEME, herein referred to as IM- PACT), which is currently utilized in the management of patients with DLBCL in the clinical setting.
IMPACT is a clinical validated hybridization capture-based assay designed to detect genetic alterations, including single nucleotide variants (SNV), small insertions and de- letions (INDEL), and copy number alterations (CNA), impli- cated in the oncogenesis of hematopoietic malignancies (Online Supplementary Figure S1). The custom designed DNA probes target all protein-coding exons and the ad-
jacent 20bp of intronic sequence of 400 key oncogenes and tumor suppressor genes. IMPACT uses either saliva or nail clippings as a source of germline DNA to confi- dently identify somatic mutations in hematologic tumor cells. Details of the methodology and analytical code have been published previously.12,13 Published data from the NCI DLBCL cohort was used to evaluate the performance of LymphGen with only the genes in the IMPACT panel. Applying the LymphGen cluster allocation to the limited set of 400 genes on cases from the NCI cohort by filter- ing the NCI variant calling data into genes on the IMPACT panel demonstrated an overall accuracy of 92%, with 86% sensitivity and 98% specificity, using cluster allocation based on the original panel as ground truth (Figure 1A, B). In total, 58% of cases were ultimately classified into one of the 6 subtypes (or composite subtypes), which was only marginally below the 63% reported with the use of comprehensive methods, including whole exon, deep amplicon and RNA-sequencing in the original NCI report. The cases that were successfully classified included 11.7% MCD type, 12.7% BN2 type, 13.7% EZB type, 9.2% A53 type, 5.3% ST2 type, and 0.8% N1 type, compared to the original NCI LymphGen study which included 13.9% MCD type, 16.1% BN2 type, 13.2% EZB type, 6.6% A53 type, 4.7% ST2 type, and 2.8% N1 type (Figure 1C). Misclassification primarily encompassed cases deemed as unclassified (“Other”) by either the comprehensive NCI panel or the IMPACT panel, as shown in the confusion matrix (Figure 1A).
Similar to the NCI study, most cases of EZB subtypes were of the GCB COO; most cases of MCD and N1 subtypes were of ABC COO; and BN2 and A53 subtypes carried both GCB and ABC types, while cases in the ST2 subtype contained more GCB type than ABC type (Figure 1D). In our classification using the genes on the targeted IMPACT panel approach, within 58% of classified cases, 34% of cases were called with high confidence (“Core” group, >90% probability), while 19% of cases were called with lower confidence (“Extended” group, 50-90% probabil- ity) (Figure 1C). Compared to the original NCI allocation (47% “Core” and 10% “Extended” group cases), there is a slight reduction in calling confidence from the narrower IMPACT panel. The percentage of cases being classified in the “Core” group varies in subtypes, with the highest in N1 subtype and the lowest in ST2, which represents the confidence of classification in these subtypes (Figure 1E). In the “Core” group, classification accuracy by the IMPACT gene panel increased to 96%; sensitivity and specificity
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