Tumor Specific cfDNA Predicts Treatment Response of Multiple Myeloma Patients

Introduction: Great progress achieved in treatment of multiple myeloma (MM) over the past decade changed overall perception of importance of minimal residual disease (MRD) assessment. Since new drugs induce deep responses, MRD must be evaluated using sensitive techniques, such as allele specific PCR (ASO-PCR), next-generation sequencing (NGS) or flow cytometry. MM is a genetically heterogeneous cancer of plasma cells characterized by multiple focal lesions in the bone marrow (BM). Hence, a single-site biopsy can create a sampling bias. In spite of this, BM samples are typically used for MRD analysis, but currently an alternative approach called liquid biopsies, which utilizes body fluids for analysis of various molecules and cells, is intensively studied. Cell-free DNA (cfDNA) as one type of the molecule which can be analyzed using liquid biopsy approach showed promising results previously. In our study, patient-specific, clonotypic rearrangement of immunoglobulin heavy chain (IgH) gene, identified in bone marrow samples, was used for qPCR analysis of cfDNA samples from peripheral blood. We demonstrate that dynamics and quantity of patient-specific, clonotypic IgH rearrangement found in cfDNA can predict the outcomes and response of MM patients. Methods: Total of 45 patients enrolled in the study. Samples of BM were collected at diagnosis, and CD138+ cell fraction was sorted using magnetic activated cell sorting. At diagnosis and at three-month intervals, samples of peripheral blood (PB) were collected for cfDNA extraction and analysis until a patient reached complete remission (CR). If CR was not reached, samples were collected for 24 months after diagnosis. Two more samples of PB were collected (CR+3, CR+6) if patients reached CR. Patient-specific VDJ rearrangement was identified using previously described PCR method from genomic DNA extracted from CD138+ cell fraction; based on the results, patient-specific primers and probes were designed for use in ASO-qPCR. Obtained data were evaluated by absolute and relative frequencies of categorical variables and median (minimum-maximum) of quantitative variables. Results: First, we assessed time to CR. Patients were classified according to the quantity of cfDNA measured at time of diagnosis into three groups: negative, PNQ (= positive non-quantifiable) and positive. As PNQ had a similar profile to negative-classified samples (in K-M plot), PNQ were grouped together with negative results except extremely high val