Proliferation is a central independent prognostic factor and target for personalized and risk-adapted treatment in multiple myeloma

Abstract

Background: Proliferation of malignant plasma cells is a strong adverse prognostic factor in multiple myeloma and simultaneously targetable by available (e.g. tubulin polymerase inhibitors) and upcoming (e.g. aurora kinase inhibitors) compounds.

Design and methods: We assessed proliferation using gene expression-based indices in 757 samples including independent cohorts of 298 and 345 samples of CD138-purified myeloma cells from previously untreated patients undergoing high-dose chemotherapy, together with clinical prognostic factors, chromosomal aberrations, and gene expression-based high-risk scores.

Results: In the two cohorts, 43.3% and 39.4% of the myeloma cell samples showed a proliferation index above the median plus three standard deviations of normal bone marrow plasma cells. Malignant plasma cells of patients in advanced stages or those harboring disease progression-associated gain of 1q21 or deletion of 13q14.3 showed significantly higher proliferation indices; patients with gain of chromosome 9, 15 or 19 (hyperdiploid samples) had significantly lower proliferation indices. Proliferation correlated with the presence of chromosomal aberrations in metaphase cytogenetics. It was significantly predictive for event-free and overall survival in both cohorts, allowed highly predictive risk stratification (e.g. event-free survival 12.7 versus 26.2 versus 40.6 months, P < 0.001) of patients, and was largely independent of clinical prognostic factors, e.g. serum β₂-microglobulin, International Staging System stage, associated high-risk chromosomal aberrations, e.g. translocation t(4;14), and gene expression-based high-risk scores.

Conclusions: Proliferation assessed by gene expression profiling, being independent of serum-β₂-microglobulin, International Staging System stage, t(4;14), and gene expression-based risk scores, is a central prognostic factor in multiple myeloma. Surrogating a biological targetable variable, gene expression-based assessment of proliferation allows selection of patients for risk-adapted anti-proliferative treatment on the background of conventional and gene expression-based risk factors.

Figure 1.

Unsupervised hierarchical clustering of normal bone marrow plasma cells (dark green), polyclonal plasmablastic cells (yellow), memory B cells (light green), myeloma cell lines (red) and myeloma cells (white). Clustering based on (A) the GPI of Hose et al., (B) the index of Shaughnessy’s group and (C) the index of Bergsagel et al. The data for the HM2-group are shown (see Online Supplementary Design and Methods for details).

Figure 2.

Prognostic value of proliferation. Event-free (EFS) and overall survival (OS) for treated patients in our series (HM). (A) GPI^high (red) versus GPI^low (black) delineates significantly different survival. (B) Model comprising GPI^low (black), GPI^medium (blue) and a high proliferation group (GPI^high, red). Prognostic relevance of (C) β-2-microglobulin >3.5 mg/dL, (D) ISS-stage, (E) presence of t(4;14), and the high-risk scores of (F) Shaughnessy et al. and (G) Decaux et al.

Figure 3.

Gene expression-based proliferation index of memory B cells (MBC), polyclonal plasmablastic cells (PPC), normal bone marrow plasma cells (BMPC), myeloma cells (MMC) and myeloma cell lines (HMCL). MMC samples are subdivided into monoclonal gammopathy of undetermined significance (MGUS) and multiple myeloma (MM) I/II/III according to Durie-Salmon stage. Significant differences between BMPC and other samples are indicated by one asterisk (*), and between early (MGUS/MMI) and late (MMII/III) stages by two asterisks (**).

Figure 4.

Distribution of proliferation. Distribution of the GPI for newly-diagnosed patients within our series (HM1 and HM2; n=298) and the Little Rock-data (LR; n=345). Horizontal bars indicate the median GPI plus three standard deviations of normal plasma cells (BMPC) and the high proliferation group (HR) defined as the median GPI of myeloma cell samples plus two standard deviations.