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279 Genomic and Transcriptomic Profiling Reveals Distinct Subsets Associated with Outcomes in Mantle Cell Lymphoma

Program: Oral and Poster Abstracts
Type: Oral
Session: 621. Lymphoma—Genetic/Epigenetic Biology: Genetic and epigenetic profiling of malignant lymphomas
Hematology Disease Topics & Pathways:
Diseases, Mantle Cell Lymphoma, Non-Hodgkin Lymphoma, Technology and Procedures, Lymphoid Malignancies, genetic profiling, Clinically relevant, NGS, RNA sequencing
Saturday, December 5, 2020: 2:15 PM

Yuting Yan1,2*, Shuhua Yi, MD3*, Meiling Jin, PhD2*, Yi Wang4*, Ying Yu1*, Wang Jun5*, Dehui Zou, MD3*, Tingyu Wang1*, Zhen Yu, MD6*, Lanting Liu7*, Rui Cui, MD8*, Wei Liu9*, Ryu Lv10*, Weiwei Sui, MD11*, Wenyang Huang12*, Xiong Wenjie5*, Huijun Wang12*, Qi Sun12*, Mu Hao3*, Jianxiang Wang, MD6, Cheng Tao13*, Lugui Qiu, MD1 and Lili Wang, MD, PhD2

1National Clinical Research Center for Blood Diseases, State Key Laboratory of Experimental Hematology, Blood Diseases Hospital & Institute of Hematology, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
2Department of Systems Biology, Beckman Research Institute, City of Hope, Monrovia, CA
3State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, TIANJIN, China
4State Key Laboratory of Experimental Hematology, Institute of Hematology and Blood Disease Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
5Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
6State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
7Institute of Hematology and Blood Diseases Hospital Chinese Academy of Medical S, Tianjin, China
8Tianjin First Central Hospital, Tianjin, China
9State Key Laboratory of Experimental Hematology, Institute of Hematology & Blood, TIANJIN, China
10Lymphoma and Myeloma Center, Institute of Hematology & Blood Disease Hpspital,Cams &PUMC, Tianjin, China
11State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin City, China
12Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Tianjin, China
13Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences/Peking Union Medical College, tianjin, China

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.

*signifies non-member of ASH