Exploring secondary extramedullary myeloma disease: a five-predictor scoring system with spotlight on double-hit cytogenetics.

BACKGROUND

Extramedullary myeloma disease (EMD) can present at disease relapse (secondary EMD, sEMD) and confers an aggressive clinical course. Identifying predictive markers for sEMD is crucial for clinical management.

METHODS

Our study, spanning February 2013 to October 2022, identified sEMD in 77 (12.5%) of 618 newly diagnosed multiple myeloma patients. We categorized sEMD patients into bone-related extramedullary (EM-B) and extraosseous extramedullary (EM-E) relapse groups, as well as into early and late relapse groups based on the median interval from initial MM diagnosis, and assessed their overall survival (OS). We investigated independent predictors for the development of sEMD and focused on double-hit (DH) myeloma, one of the predictors of sEMD. Through the analysis of single-cell RNA from DH myeloma samples, we explored the potential mechanisms by which it may contribute to sEMD.

RESULTS

Median OS post-sEMD diagnosis was 11 months, with no significant OS difference between EM-B and EM-E relapse groups. A median interval of 22 months from initial MM diagnosis to sEMD relapse divided the 77 sEMD patients into early and late relapse groups, with early sEMD associated with significantly inferior OS post-sEMD (5.0 vs 27.0 months, p = 0.028). Driven by the prognostic difference of early vs late sEMD relapse, we used a time-to-event model and identified five independent predictors: double-hit (DH) cytogenetics, ≥ 3 osteolytic lesions, IgD subtype, and non-autologous stem-cell transplantation (ASCT) status, each scoring one point, alongside EM-E scoring two points. These predictors informed an additive score, stratifying patients into low (0-2 points) and high (3-5 points) risk categories for sEMD, showing a significant difference in 3-year sEMD rates (6.6% vs 52.8%, p < 0.001). Moreover, the single-cell RNA sequencing of newly diagnosed DH myeloma samples uncovered significant mitogen-activated protein kinase (MAPK) activation in DH cells and exhaustion in CD8 + memory and NK effector cells. Potential therapeutic targets such as EZH2 have emerged from this analysis.

CONCLUSIONS

Our study introduces a five-predictor scoring system informed by the potential mechanisms underlying sEMD progression in DH myeloma, with the goal of delaying or possibly preventing sEMD.