Prognostic value of integrated cytogenetic, somatic variation, and copy number variation analyses in Korean patients with newly diagnosed multiple myeloma

• DOI: 10.1371/journal.pone.0246322
• Publication Date: 2021-02-07T18:30:55Z
• Authors: Nuri Lee; Sung-Min Kim; Youngeun Lee; Dajeong Jeong; Jiwon Yun; Sohee Ryu; Sung-Soo Yoon; Yong-Oon Ahn; Sang Mee Hwang; Dong Soon Lee
• Keywords: Male; DNA Copy Number Variations; Science; Q; R; Genetic Variation; Middle Aged; Prognosis; Survival Analysis; Cytogenetics; 03 medical and health sciences; 0302 clinical medicine; Karyotyping; Republic of Korea; Exome Sequencing; Medicine; Humans; Female; Genetic Testing; Multiple Myeloma; Research Article; Aged

Background To investigate the prognostic value of gene variants and copy number variations (CNVs) in patients with newly diagnosed multiple myeloma (NDMM), an integrative genomic analysis was performed.

Methods Sixty-seven patients with NDMM exhibiting more than 60% plasma cells in the bone marrow aspirate were enrolled in the study. Whole-exome sequencing was conducted on bone marrow nucleated cells. Mutation and CNV analyses were performed using the CNVkit and Nexus Copy Number software. In addition, karyotype and fluorescent in situ hybridization were utilized for the integrated analysis.

Results Eighty-three driver gene mutations were detected in 63 patients with NDMM. The median number of mutations per patient was 2.0 (95% confidence interval [CI] = 2.0–3.0, range = 0–8). MAML2 and BHLHE41 mutations were associated with decreased survival. CNVs were detected in 56 patients (72.7%; 56/67). The median number of CNVs per patient was 6.0 (95% CI = 5.7–7.0; range = 0–16). Among the CNVs, 1q gain, 6p gain, 6q loss, 8p loss, and 13q loss were associated with decreased survival. Additionally, 1q gain and 6p gain were independent adverse prognostic factors. Increased numbers of CNVs and driver gene mutations were associated with poor clinical outcomes. Cluster analysis revealed that patients with the highest number of driver mutations along with 1q gain, 6p gain, and 13q loss exhibited the poorest prognosis.

Conclusions In addition to the known prognostic factors, the integrated analysis of genetic variations and CNVs could contribute to prognostic stratification of patients with NDMM.