67P - Developing a prediction model for response to lenalidomide treatment in refractory/relapsed multiple myeloma patients

Date 11 September 2017
Event ESMO 2017 Congress
Session Poster display session
Topics Myeloproliferative Neoplasms
Haematologic Malignancies
Presenter Yeun-Jun Chung
Citation Annals of Oncology (2017) 28 (suppl_5): v1-v21. 10.1093/annonc/mdx361
Authors Y. Chung, S. Yim, S. Jung
  • Precision Medicine Research Center, The Catholic University of Korea, College of Medicine, 06591 - Seoul/KR

Abstract

Background

Despite improvements in treatment for Multiple myeloma (MM) achieved by novel drugs such as proteasome inhibitors (PIs) and immunomodulatory drugs (IMiDs), most patients will ultimately relapse or become refractory to their current treatment. Therefore, it is important to understand the mechanisms of therapeutic resistance in relapsed/refractory MM (RRMM) for improving treatment outcome. Recently, it was reported that serum or plasma of MM patients showed sufficiently stable miRNA signatures with prognostic impacts in MM cohorts, which can be used as minimally invasive markers for predicting and monitoring treatment outcomes. However, the expression patterns and biological implications of miRNAs are still unclear in RRMM patients receiving lenalidomide with dexamethasone (Len-dex).

Methods

We investigated the expression of serum miRNAs by genomewide miRNA array analysis and explored their predictive values in RRMM patients receiving Len-dex.

Results

We explored the associations of miRNAs with treatment outcome of Len-dex treatment and prognosis in 55 RRMMs (25 good responders and 30 poor responders) and built a prediction model for treatment response. Three miRNAs (miR-29c-3p, miR-30c-5p, and miR-331-3p) were found to be significantly down-regulated in poor responders. In survival analysis, lower expression of the three miRNAs was significantly associated with shorter time to progression (TTP) or poorer overall survival (OS). Eight clinical factors were also associated with TTP or OS. By combining the miRNA markers and clinical markers, we designed a a prediction model for response to lenalidomide treatment in RRMM patients. Our model showed better prediction power (AUC=0.855, sensitivity 84%, specificity 76%, and accuracy 81%) than international staging system (ISS) based prediction.

Conclusions

Our results suggest the potential of circulating miRNAs as minimally invasive markers for treatment response and prognosis in RRMM patients.

Clinical trial identification

Legal entity responsible for the study

This study was approved by the Institutional Review Board of The Catholic University of Korea and conducted in accordance with the Declaration of Helsinki.

Funding

None

Disclosure

All authors have declared no conflicts of interest.