Genomic and transcriptomic profiling reveals distinct molecular subsets associated with outcomes in mantle cell lymphoma

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Abstract

Mantle cell lymphoma (MCL) is a phenotypically and genetically heterogeneous malignancy in which the genetic alterations determining clinical indications are not fully understood. Here, we performed a comprehensive whole-exome sequencing analysis of 152 primary samples derived from 134 MCL patients, including longitudinal samples from 16 patients and matched RNA-Seq data from 48 samples. We classified MCL into 4 robust clusters (C1–C4). C1 featured mutated immunoglobulin heavy variable (IGHV), CCND1 mutation, amp(11q13), and active B cell receptor (BCR) signaling. C2 was enriched with del(11q)/ATM mutations and upregulation of NF-κB and DNA repair pathways. C3 was characterized by mutations in SP140, NOTCH1, and NSD2, with downregulation of BCR signaling and MYC targets. C4 harbored del(17p)/TP53 mutations, del(13q), and del(9p), and active MYC pathway and hyperproliferation signatures. Patients in these 4 clusters had distinct outcomes (5-year overall survival [OS] rates for C1–C4 were 100%, 56.7%, 48.7%, and 14.2%, respectively). We also inferred the temporal order of genetic events and studied clonal evolution of 16 patients before treatment and at progression/relapse. Eleven of these samples showed drastic clonal evolution that was associated with inferior survival, while the other samples showed modest or no evolution. Our study thus identifies genetic subsets that clinically define this malignancy and delineates clonal evolution patterns and their impact on clinical outcomes.

Authors

Shuhua Yi, Yuting Yan, Meiling Jin, Supriyo Bhattacharya, Yi Wang, Yiming Wu, Lu Yang, Eva Gine, Guillem Clot, Lu Chen, Ying Yu, Dehui Zou, Jun Wang, An T. Phan, Rui Cui, Fei Li, Qi Sun, Qiongli Zhai, Tingyu Wang, Zhen Yu, Lanting Liu, Wei Liu, Rui Lyv, Weiwei Sui, Wenyang Huang, Wenjie Xiong, Huijun Wang, Chengwen Li, Zhijian Xiao, Mu Hao, Jianxiang Wang, Tao Cheng, Silvia Bea, Alex F. Herrera, Alexey Danilov, Elias Campo, Vu N. Ngo, Lugui Qiu, Lili Wang