Combined Measurement of Plasma Cell Proliferation and Apoptosis in Multiple Myeloma.
Authors: Minarik Jiri , Scudla Vlastimil , Ordeltova Marta , Pika Tomas , Bacovsky Jaroslav , Steinbach Michael , Kumar Vipin , Van Ness Brian G 
Published: October 2019

Abstract 4884

Background

Plasma cell proliferation and apoptosis represent key factors in multiple myeloma (MM) expansion and tumor survival. Both the proliferative and the apoptotic index have been shown to be strong and independent prognosticators in MM. Moreover, they do not correlate with most standard prognostic factors, representing thus different inherent features of the myeloma clone. The aim of the study was to assess the combined measurement of proliferation and apoptosis, giving the best predictive value for long and short MM survivals.

Methods

We assessed a cohort of 181 patients with newly diagnosed multiple myeloma, treated using conventional chemotherapy (regimens MP, VBMCP, VAD, CyVAD). In all the patients we measured proliferative and apoptotic index at the time of diagnosis, before the start of treatment. The proliferative activity of myeloma plasmocytes in bone marrow aspirate was measured by flow- cytometry using propidium-iodide index (PC-PI), representing the percentage of plasma cells in S-phase of the cell cycle; apoptosis was assessed using flow cytometry using an annexin-V (PC-AI) index. Subsequent statistical analysis of the the Kaplan-Meier curves of overall survival was evaluated using the MATLAB routine. We assessed different PC-PI and PC-AI tresholds with the best separation of groups with good and poor prognosis, using the log rank procedure. Additional measures of performance were obtained looking at the success with which two groups selected using the PC-AI and PC-PI thresholds reflected short term and long term survivors.

Results

The median follow-up of the group was 25 months (range 1 – 117 months). At the time of analysis, 137 patients had died (76%). Plasma cell proliferative index varied in the range 1.2 – 4.2, with median 2.5; apoptotic index was in the range 1.4 – 24.5 with median 4.3. Patients were divided into 4 groups based on PC-PI and PC-AI thresholds and then keeping only those two groups that demonstrated the worst and best overall survival based on the survival analysis of PC-PI and PC-AI individually. The best discriminating values for patients with poor prognosis (n=20) were PC-PI > 3.0% and PC-AI < 4.75%, and for patients with good prognosis (n = 71) PC-PI ' 3.0% and PC-AI ≥ 4.75%, with median overall survival 8 months versus 40 months respectively, p = 0.0002. The precision of the correct prediction of individual patient prognosis based on this grouping was in the patients with short survival 0.70 and in long survivors 0.58. Due to an imbalanced number of patients especially with high proliferation we were unable to create a single significant combined index across the entire patient group. Moreover, the patients outside the defined ranges substantially influenced the sensitivity and especially the specificity of the test, suggesting that defining of the extreme groups using PC-PI and PC-AI creates a better prognosticator than the assessment of the whole cohort based on a single combined index.

Conclusion

Plasma cell proliferation and apoptosis reflect different processes of MM kinetics with the growth characteristics on one hand, and survival on the other. Their assessment as single factors provides valuable information about the biology of the clone and contributes to the estimation of overall survival. Their combined measurement, however, significantly separates two extreme groups of patients with different prognosis and may thus become a valuable auxiliary parameter in MM patients stratification.

Disclosures

No relevant conflicts of interest to declare.