Identification of clinical implications and potential prognostic models of chromatin regulator mutations in multiple myeloma

Author:

Zhang LinaORCID,Zhang Run,Wang Jing,Chen Ying,Qiao Chun,Shi Qinglin,Jin Yuanyuan,Shen Xuxing,Li Jianyong,Chen LijuanORCID

Abstract

Abstract Background With the rapid development of next-generation sequencing (NGS) technologies, researchers are making efforts to reveal the genomic landscape of multiple myeloma (MM). However, the clinical significance of many mutations remains poorly defined due to the genetic heterogeneity of MM. To systematically explore the clinical implications of gene mutations and build practical prognostic models, we performed DNA sequencing in newly diagnosed MM patients. Methods MM cells were purified from bone marrow aspirates using CD138 microbeads and subjected to sequencing with a 387-gene Panel. Nomogram was developed using Cox’s proportional hazards model, and candidate variables were screened by stepwise regression. Internal validation was carried out by the bootstrap method. Results Between July 2016 and December 2020, a total of 147 patients were included in our study. We found patients with a higher mutational load had a significantly shorter progress-free survival (PFS) (19.0 vs. 32.0 months, P = 0.0098) and overall survival (OS) (3-year OS rates were 66.1% and 80.0%, P = 0.0290). Mutations in chromatin regulators (CRs) including KMT2C (14.3%), KMT2D (14.3%), EP300 (11.6%) and ARID gene family (31.3%) were highly frequent in newly diagnosed MM patients. Interestingly, proteins encoded by these genes could form a complex called KMT2C/D COMPASS (KCDCOMs). Patients with mutations of ARID gene family had a significantly shorter PFS (15.5 vs. 34.0 months, P = 0.0003) and OS (3-year OS rates were 64.9% and 81.0%, P = 0.0351) than patients without ARID gene mutations. Incorporating ARID gene mutations into the current staging system could successfully improve their prognostic performance. The PFS and OS nomogram models (including 1q21 copies, ARID gene mutations, extramedullary disease, mutational load and TP53 mutations) showed good predicting performance in both training and validation sets. Conclusion Our findings emphasized the importance of CRs mutations in newly diagnosed MM patients and indicated the mutations affecting KCDCOMs might promote the development of MM. High mutational load and harboring mutations in the ARID gene family were novel predictors of adverse prognosis in MM. Prognostic models based on gene mutations were commendably prognostic evaluation methods that could provide a reference for clinical practices.

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Genetics (clinical),Developmental Biology,Genetics,Molecular Biology

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