Introduction Mantle cell lymphoma (MCL) is a rare subtype of aggressive non-Hodgkin's lymphoma in which the genomic factors determining the clinical behavior are not fully understood. The genetic heterogeneity in MCL motivates us to characterize the genetic landscape, to define pattern of clonal evolution, and to determine molecular subgroups.

Methods We performed whole-exome sequencing on 152 DNA samples derived from 134 MCL patients, which includes 123 untreated and 11 relapsed patients, and 16 with longitudinal samples. 95 patients received high dose cytarabine-based immunochemotherapy from BDH-MCL01 clinical trial (NCT02858804). 48 samples have matched RNA sequencing data for which 42 from untreated and 6 from relapsed patients. We used GATK, MutSig2CV, and GISTIC2.0 to identify driver genetic lesions, applied MutationalPatterns to define mutational signatures, and utilized ABSOLUTE and PhylogicNDT to determine pattern of clonal evolution. We applied NNMF consensus clustering to identify subgroups and evaluated association between genomic features and clinical outcomes.

Results The median non-silent mutational burden was 29 per sample (range 8-72). 34 recurrently mutated genes were identified, containing previously reported driver mutations (TP53, ATM, CCND1, KMT2D, NSD2, SMARCA4, ARID1A, NOTCH1, NOTCH2, BIRC3, TRAF2, UBR5) and novel mutations (SP140, SVEP1, LRP1B, LRP2, PCDH10). 7 copy number gain and 13 loss regions were detected as recurrent somatic copy number alterations (frequency>10%, q<0.1) (FigA). In multivariable Cox models of PFS and OS, TP53 mutation/del(17p13), SP140 mutation/del(2q36), and mutations in NOTCH1, PCDH10, and del(9p) showed prognostic value independent of MIPI risk and IGHV mutation status.

We defined the clonal status of genetic lesions and pattern of clonal evolution. Del(11q22) and del(9p) tend to be clonal while mutations in NSD2, LRP1B, CTNNA2 were more likely to be subclonal (q<0.05) (Fig B). Clonality analysis further enabled inference of temporal relationships between pairs of events. We further determined clonal evolution pattern by measuring the dynamic changes of fraction of cancer cells harboring each genetic lesion. 11 of 16 (69%) longitudinal samples had extreme clonal evolution (CCF change > 0.5), 4 with modest evolution (0.2 ≤ CCF change ≤ 0.5), 1 without evolution (CCF change < 0.2). Patients with extreme evolution had inferior survival than with those with modest and no evolution (median survival from first sampling was 47.5 months vs not reached, p=0.041, second sampling was 17.1 months vs not reached, p=0.023).

We classified MCL into four subsets based on genetic lesions, each with distinct gene expression profile and clinical behavior (Fig C, D). Cluster 1 (C1) and cluster 2-4 (C2-4) were associated with indolent and aggressive types of MCL. Consistent with different cellular origins for two types of MCL, C1 and C2-4 were enriched for gene expression signatures of memory and CCR6 negative light zone B cells, respectively. C1 featured mutated IGHV, CCND1 mutation, amp(11q13) and active BCR signaling. C2 was enriched with del (11q22), del (1p21), ATM mutation and had upregulation of genes involved in the NF-kB and DNA repair pathways while C3 was characterized by mutations in SP140, NOTCH1 and NSD2 and downregulation of gene expression in the NF-kB, BCR signaling, MYC and inflammatory pathways. Interestingly, C4 had the highest incidence of blastoid or pleomorphic MCL (23.7%, p=0.016) and harbored del(17p), del(13q), del(9p) and mutations in TP53 and TRAF2. This cluster carried enrichment of MYC pathway activation and hyperproliferation signatures. These unique gene expression signatures indicated that coordinate genomic factors captured biologic heterogeneity. Importantly, patients in these four clusters had distinct outcomes with median PFS of not reached for C1, 41.2 months for C2, 30.7 months for C3, and 16.1 months for C4 (log rank, p<0.001). The differences of OS and PFS remained significant when only considered 95 patients with high dose cytarabine-based immunochemotherapy.

Conclusion Our study provides a portrait of the MCL genetic landscape, uncovers pattern of clonal evolution in MCL, classifies patients with genetic features, links the cluster with gene expression and clinical outcome. The outcome-associated genetic signatures will guide the development of therapies in patients with the greatest need.

Disclosures

No relevant conflicts of interest to declare.

Author notes

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