Genome-Wide Transcriptome Analysis Identifies Molecular Patterns of FDG-PET/CT Biomarkers in MM Patients from the Cassiopet Study

Background

Positron emission tomography (PET) using 18Fluorodeoxyglucose (FDG) provides independent prognostic informations in newly diagnosed multiple myeloma (NDMM) patients (Moreau et al, ASH 2019; Moreau et al, JCO 2017; Zamagni et al, Blood 2011). At baseline, FDG-PET/CT characteristics such as maximum standardized uptake value (SUV_max), presence of extramedullary disease (EMD), and paramedullary disease (PMD) define high-risk NDMM patients. Similarly, the presence of negative FDG-PET/CT at baseline has been associated with favorable outcome in NDMM patients (Abe et al, EJNMMI 2019; Moreau et al, ASH 2019). The aim of the present study was to identify MM molecular features associated with these functional imaging biomarkers.

Methods

A group of 136 patients from CASSIOPET, a companion study of the CASSIOPEIA cohort (ClinicalTrials.gov, number NCT02541383) were subjected to whole genome expression profiling using RNA sequencing (RNA-seq) on sorted bone marrow plasma cells in addition to FDG-PET/CT imaging at baseline. RNA-seq reads were aligned to hg38 reference genome with STAR and subjected to differential expression testing with DESeq2 with sample purity treated as a model covariate. High risk group with the GEP70 signature and classification from the seven molecular subgroups (CD-1, CD-2, HY, LB, MF, MS, and PR) were determined by weighted mean value of gene expression (Zhan et al, Blood 2006). Special attention was paid to genes associated with glucose metabolism and related to plasma cells proliferation. On FDG-PET/CT, SUV_max of areas of focally increased tracer uptake on bone was determined and the presence of EMD or PMD identified.

Results

FDG-PET/CT was positive in 108 patients out of 136 (79,4%), with 19 (14%) and 15 (11%) of them presenting PMD and EMD disease respectively. Expression level of glucose transporter GLUT1 was independent of these three imaging biomarkers (FDG-PET/CT positivity, EMD and PMD), while HK2 was downregulated in negative scans only (Fold Change = 2.1, p_adj=0.02). GLUT5 expression was associated with positive FDG-PET/CT (Fold Change = 3.5, p_adj = 8E-4). Both GLUT1 and HK2 weakly correlated with SUV_max (r=0.26 and 0.36, respectively). Of note, negative FDG-PET/CT were enriched for the LB group of patients, consistent with the lower incidence of MRI-defined bone lesions reported in this subgroup, and it remained independent of the GEP70 signature.

Furthermore, high risk GEP70 signature was associated with a SUV_max ≥ 4, and correlated with the presence of PMD (OR=3.2, CI=[0.95-10.6], p=0.03), but not with EMD (p=0.7).Conversely, there was no patient from the LB group with detected PMD on imaging, but 25% (2/8) showed EMD, suggesting that different biological features support both disease patterns.

Finally, positive PET/CT profiles seemed to display two distinct signatures with either high expression of proliferation genes (MKI67, PCNA, TOP2A, STMN1), or high expression of GLUT5 and lymphocyte antigens (CD19, CD30L, and CCR2), suggesting a different phenotype for this subgroup. This finding was independent of a high SUV_max.

Conclusion

Our study confirmed that negative FDG-PET/CT at baseline is associated with low HK2 expression while positive exams showed increased GLUT5 expression and proliferation markers. We describe a strong correlation between two imaging biomarkers (baseline SUV_max and PMD) and high risk signature and molecular subgroup with highly proliferative disease. On the contrary, EMD appeared independent of high risk signature or molecular subgroups. Additional studies will confirm and extend the correlation between imaging and clinical features of the disease and molecular characteristics of malignant plasma cells.