PS1345 CIRCULATING TUMOR DNA AS A LIQUID BIOPSY IN SMOLDERING MULTIPLE MYELOMA TO IDENTIFY BIOMARKERS OF PROGRESSION
Authors: M. Manzoni, M. Lionetti, F. Pelizzoni, A. Pompa, B. Ziccheddu, V. Spina, A. Bruscaggin, D. Rossi, N. Bolli, L. Baldini, A. Neri
Journal: HemaSphere (2019)

Background: Easily accessible, real‐time genotyping is desirable for patients suffering from plasma cell (PC) disorders for diagnostic, prognostic and therapeutic purpose. Circulating cell‐free DNA (cfDNA) might be an accessible source of tumor material in patients with PC diseases to identify cancer‐gene somatic mutations. Accessing the peripheral blood (PB) has clear advantages in terms of the sampling procedure itself, and has the potential to better reflect tumor heterogeneity. Aims: To test cfDNA, compare it with bone marrow (BM) PC DNA, and develop a streamlined analysis of genomic smoldering multiple myeloma (SMM) biomarkers for a better risk stratification at diagnosis and earlier prediction of progression. Methods: The study was based on a series of 41 consecutive patients with PC [13 with monoclonal gammopathy of undetermined significance (MGUS), 28 with SMM], of whom the following material was collected: (1) cfDNA isolated from plasma, (2) tumor genomic DNA (gDNA) from CD138+ purified BM PCs for comparative purposes when it was possible, and (3) normal germline gDNA extracted from PB granulocytes, to exclude polymorphisms. A targeted resequencing gene panel including coding exons and splice sites of 14 genes (target region: 31 kb) was specifically designed to allow a priori the recovery of at least one clonal mutation in 68% of MM patients. Ultra‐deep next‐generation sequencing (NGS) of the gene panel was performed on MiSeq (Illumina) using the CAPP‐seq library preparation strategy (NimbleGen). The somatic function of VarScan2 was used to call non‐synonymous somatic mutations, and a stringent bioinformatic pipeline was developed and applied to filter out sequencing errors (detection limit 3x10–3). The sensitivity and specificity of plasma cfDNA genotyping were calculated in comparison with tumor gDNA genotyping as the gold standard. Ultra‐low pass whole‐genome sequencing (ULP‐WGS) was performed with a target coverage of 0.1x in tumor gDNA at diagnosis and in matched cfDNA at each time point. Analysis was performed using ichorCNA ( https://github.com/broadinstitute/ichorCNA ) to predict large‐scale copy number alterations and estimate the SMM tumor fraction. Results: cfDNA was detectable in plasma samples with a median of 5000 haploid genome‐equivalents/mL. The application of our targeted ultra‐deep NGS approach for plasma cfDNA genotyping resulted in ≥96% of the target region covered &gt;2000X in all plasma samples. Overall, 17/41 (41%) patients harbored somatic mutations that were detectable in plasma cfDNA. Only a small dataset of 16 patients were analyzed also in BM sample. cfDNA genotyping correctly identified 62% of mutations (n = 8/13) discovered in tumor PCs and overall the variant allele frequencies in plasma samples correlated with those in tumor biopsies. Notably, the remaining mutations not discovered in cfDNA had a low representation (under the VAF threshold of 8%) in the purified BM PCs. In none of the cases with paired BM sample, cfDNA genotyping identified additional somatic mutations not detected in the purified BM PCs. ULP‐WGS was performed on 11 samples with paired BM sample (5 MM, 4 SMM, 2 MGUS) and a panel of 14 normal controls: cancer fraction is of average 40.5% for BM samples and 4.5% for cfDNA samples and it seem to be associated with the clinical stage of the disease. Summary/Conclusion: Our results provide the proof of principle that cfDNA genotyping is a feasible, non‐invasive real‐time approach that could identify biomarkers of progression in SMM patients.