A multiple myeloma classification system that associates normal B-cell subset phenotypes with prognosis

Abstract

Despite the recent progress in treatment of multiple myeloma (MM), it is still an incurable malignant disease, and we are therefore in need of new risk stratification tools that can help us to understand the disease and optimize therapy. Here we propose a new subtyping of myeloma plasma cells (PCs) from diagnostic samples, assigned by normal B-cell subset associated gene signatures (BAGS). For this purpose, we combined fluorescence-activated cell sorting and gene expression profiles from normal bone marrow (BM) Pre-BI, Pre-BII, immature, naïve, memory, and PC subsets to generate BAGS for assignment of normal BM subtypes in diagnostic samples. The impact of the subtypes was analyzed in 8 available data sets from 1772 patients' myeloma PC samples. The resulting tumor assignments in available clinical data sets exhibited similar BAGS subtype frequencies in 4 cohorts from de novo MM patients across 1296 individual cases. The BAGS subtypes were significantly associated with progression-free and overall survival in a meta-analysis of 916 patients from 3 prospective clinical trials. The major impact was observed within the Pre-BII and memory subtypes, which had a significantly inferior prognosis compared with other subtypes. A multiple Cox proportional hazard analysis documented that BAGS subtypes added significant, independent prognostic information to the translocations and cyclin D classification. BAGS subtype analysis of patient cases identified transcriptional differences, including a number of differentially spliced genes. We identified subtype differences in myeloma at diagnosis, with prognostic impact and predictive potential, supporting an acquired B-cell trait and phenotypic plasticity as a pathogenetic hallmark of MM.

Graphical abstract

Figure 1.

Expression of membrane markers, transcription factors, and B-cell subset-specific genes in normal BM tissue. (A) B cells of the BM were defined by flow cytometry as CD19⁺, CD45⁺, and CD3⁻ and were additionally divided by surface marker expression of CD10, CD20, CD27, CD38, and CD34, published in detail previously. The data quality of the differentiating B-cell subset compartments was validated as illustrated by normalized histograms of (A) the mean fluorescence intensities (MFIs) CD markers based on merged MFC reanalysis of pure sorted populations resulting from 7 independent sorting procedures. Broken lines represent MFI values for each sorted B-cell subset. (B) Principal component analysis of the MFI values for each sorted cell in all samples. The cells are coded with a color according to their original subset. The dots represent mean values for each sorted B-cell subset. (C) The most variable probe sets were used in unsupervised hierarchical clustering analysis of the surface markers (MME = CD10, CD34, CD38, CD27; PTPRC = CD45; MS4A = CD20, CD19) used for FACS. (D) B-cell differentiation–specific genes (n = 45), summarized from a literature review of transcriptional regulation of B lymphopoiesis. The colors at the top of panel D indicate the relative gene expression for each sample, with blue representing high and brown representing low.

Figure 2.

Meta-analysis of the prognostic impact of assigned BAGS subtypes. Progression-free survival (PFS) (A) and OS (B) were compared between BAGS subtypes for high-dose melphalan–treated patients in published prospective clinical trials. P values are results from log-rank tests. The subtype numbers given as n are the numbers of events/number of assigned patients with the subtypes in the meta–data set. The BAGS subtypes are color coded as in Figure 1.

Figure 3.

BAGS subtype boxplots with correlation to proliferation, melphalan resistance, and β-2 microglobulin. The individual adjusted PI risk profiling (A), melphalan drug resistance probability (index) (B), and β-2 microglobulin plasma level (C), respectively, per BAGS subtype cases from analysis of the meta–data set. The BAGS subtypes are color coded as in Figure 1.