Gene Expression Profiling (GEP) of Purified Plasma Cells at Baseline and 48hr after-Dexamethasone (D) or Thalidomide (T) Improve Outcome Predicition of Baseline GEP Alone in Patients with Multiple Myeloma (MM) Treated with Total Therapy 2 (TT2).
Authors: Burington Bart , Shaughnessy John , Barlogie Bart , John Crowley 
Published: April 2020

Abstract
The prognosis of patients with MM varies widely. High risk is best captured by cellular and molecular genetic features. Objective: to determine whether predictive power of baseline GEP and metaphase cytogenetic abnormalities (CA) could be improved by availability of GEP data obtained 48hr after single agent D or T, pre-therapy. A total of 668 patients were enrolled on TT2, 323 randomized to T and 345 without T (ASCO 05). When randomized to T/no T, Baseline and 48 hr GEP samples were obtained from 32/41 receiving a test dose of T/D vs 10/14 receiving full VAD+T/VAD regimen. A total of 97 baseline/early treatment GEP pairs were analyzed. Combined baseline expression and 48hr expression changes of 151 genes predicted EFS at a false discovery rate (FDR) of 10%. The table compares baseline EFS high-risk dysregulation to the direction of 48 hour changes, confering improved EFS. Decreases over 48 hours are associated with improved EFS in 74 of 78 genes (upregulated expression confers poor survival at baseline). In the remaining 4, perturbation in the direction of an additional increase may be a marker of early response. With EFS-associated genes, we trained 15 EFS prediction models using baseline expression and 15 prediction models using the change in expression between baseline and 48 hours. Training sets were random splits of 97 patients and baseline and change models separately predicted an EFS risk index in the remaining validation patients (standardized to a variance of 1). Risk indices were compared to an indicator of cytogenetic abnormalities (CA) among validation patients using multivariate proportional hazards analyses. The table shows median hazard ratios and p-values for competing predictors in 15 validation sets. Without cytogenetics, combined GEP baseline and change indices were significant predictors in all 15 validation sets (median combined P-value of 0.002). The table shows median performing GEP model of 15 in a multivariate analysis including cytogenetics for all 97 patients. 48 hour changes in gene expression in newly diagnosed myeloma patients can significantly predict EFS in validated prediction models, alone and in combination with baseline GEP. After adjustment for baseline and 48-hour GEP change indices, metaphase cytogenetics is no longer a significant predictor in independent patient samples.
Baseline EFS risk and 48 hour changes associated with good outcome in 151 EFS-associated genes. Improved EFS Decrease (HR&gt;=1 Increase (HR &lt;1) Baseline High Risk Downregulated (HR&lt;1) 6 67 Upregulated (HR&gt;+ 1) 74 4 Median Hazard Ratios and P-values for Multivariate Models in 15 Validation Sets HR P # of p-values below .05 (of 15) GEP baseline Risk 2.1 0.037 10 EP 48 hr change risk 1.9 0.052 7 CA 1.6 0.310 0 Median validation set overall P-value 0.0003 Median GEP EFS baseline/48 hour EFS prediction model n=97 HR P GEP baseline Risk 2.0 0.004 GEP 48 hr change risk 2.6 0.001 CA 1.4 0.330