Aberrations on TP53, either as deletions of chromosome 17p (del17p) or mutations, are associated with poor outcome in multiple myeloma (MM), but conventional detection methods currently in use underestimate their incidence, hindering an optimal risk assessment and prognostication of MM patients. We have investigated the altered status of TP53 gene by SNPs array and sequencing techniques in a homogenous cohort of 143 newly diagnosed MM patients, evaluated both at diagnosis and at first relapse: single-hit on TP53 gene, either deletion or mutation, detected both at clonal and sub-clonal level, had a minor effect on outcomes. Conversely, the coexistence of both TP53 deletion and mutation, which defined the so-called double-hit patients, was associated with the worst clinical outcome (PFS: HR 3.34 [95% CI: 1.37–8.12] p = 0.008; OS: HR 3.47 [95% CI: 1.18–10.24] p = 0.02). Moreover, the analysis of longitudinal samples pointed out that TP53 allelic status might increase during the disease course. Notably, the acquisition of TP53 alterations at relapse dramatically worsened the clinical course of patients. Overall, our analyses showed these techniques to be highly sensitive to identify TP53 aberrations at sub-clonal level, emphasizing the poor prognosis associated with double-hit MM patients.

Reliable strategies to capture patients at risk of progression from precursor stages of multiple myeloma (MM) to overt disease are still missing. We assembled a comprehensive collection of MM genomic data comprising 1,030 patients (218 with precursor conditions) that we used to identify recurrent coding and non-coding candidate drivers as well as significant hotspots of structural variation. We used those drivers to define and validate a simple 'MM-like' score, which we could use to place patients' tumors on a gradual axis of progression toward active disease. Our MM precursor genomic map provides insights into the time of initiation and cell-of-origin of the disease, order of acquisition of genomic alterations and mutational processes found across the stages of transformation. Taken together, we highlight here the potential of genome sequencing to better inform risk assessment and monitoring of MM precursor conditions.

Multiple myeloma (MM) is a plasma cell (PC) disorder characterized by skeletal involvement at the time of diagnosis. Recently, cell-free DNA (cfDNA) has been proven to recapitulate the heterogeneity of bone marrow (BM) disease. Our aim was to evaluate the prognostic role of cfDNA at diagnosis according to disease distribution, and to investigate the role of the MM microenvironment inflammatory state in supplying the release of cfDNA. A total of 162 newly diagnosed MM patients were screened using 18F-FDG PET/CT and assessed by ultra low-pass whole genome sequencing (ULP-WGS). High cfDNA tumor fraction (ctDNA) levels were correlated with different tumor mass markers, and patients with high ctDNA levels at diagnosis were more likely to present with metabolically active paraskeletal (PS) and extramedullary (EM) lesions. Moreover, we demonstrated that microenvironment cancer-associated fibroblast (CAFs)-mediated inflammation might correlate with high ctDNA levels. Indeed, a high cfDNA TF level at diagnosis predicted a poorer prognosis, independent of R-ISS III and 1q amplification; the inclusion of >12% ctDNA in the current R-ISS risk score enables a better identification of high-risk patients. ctDNA can be a reliable and less invasive marker for disease characterization, and can refine patient risk.

Clonal hematopoiesis of indeterminate potential (CHIP) refers to the phenomenon where a hematopoietic stem cell acquires fitness-increasing mutation(s), resulting in its clonal expansion. CHIP is frequently observed in multiple myeloma (MM) patients, and it is associated with a worse outcome. High-throughput amplicon-based single-cell DNA sequencing was performed on circulating CD34+ cells collected from twelve MM patients before autologous stem cell transplantation (ASCT). Moreover, in four MM patients, longitudinal samples either before or post-ASCT were collected. Single-cell sequencing and data analysis were assessed using the MissionBio Tapestri^® platform, with a targeted panel of 20 leukemia-associated genes. We detected CHIP pathogenic mutations in 6/12 patients (50%) at the time of transplant. The most frequently mutated genes were TET2, EZH2, KIT, DNMT3A, and ASXL1. In two patients, we observed co-occurring mutations involving an epigenetic modifier (i.e., DNMT3A) and/or a gene involved in splicing machinery (i.e., SF3B1) and/or a tyrosine kinase receptor (i.e., KIT) in the same clone. Longitudinal analysis of paired samples revealed a positive selection of mutant high-fitness clones over time, regardless of their affinity with a major or minor sub-clone. Copy number analysis of the panel of all genes did not show any numerical alterations present in stem cell compartment. Moreover, we observed a tendency of CHIP-positive patients to achieve a suboptimal response to therapy compared to those without. A sub-clone dynamic of high-fitness mutations over time was confirmed.

The complexity of Multiple Myeloma (MM) is driven by several genomic aberrations, interacting with disease-related and/or -unrelated factors and conditioning patients’ clinical outcome. Patient’s prognosis is hardly predictable, as commonly employed MM risk models do not precisely partition high- from low-risk patients, preventing the reliable recognition of early relapsing/refractory patients. By a dimensionality reduction approach, here we dissect the genomic landscape of a large cohort of newly diagnosed MM patients, modelling all the possible interactions between any MM chromosomal alterations. We highlight the presence of a distinguished cluster of patients in the low-dimensionality space, with unfavorable clinical behavior, whose biology was driven by the co-occurrence of chromosomes 1q CN gain and 13 CN loss. Presence or absence of these alterations define MM patients overexpressing either CCND2 or CCND1, fostering the implementation of biology-based patients’ classification models to describe the different MM clinical behaviors.

In recent years, liquid biopsy has emerged as a promising alternative to the bone marrow (BM) examination, since it is a minimally invasive technique allowing serial monitoring. Circulating multiple myeloma cells (CMMCs) enumerated using CELLSEARCH^® were correlated with patients’ prognosis and measured under treatment to assess their role in monitoring disease dynamics. Forty-four MM and seven smouldering MM (SMM) patients were studied. The CMMC medians at diagnosis were 349 (1 to 39,940) and 327 (range 22–2463) for MM and SMM, respectively. In the MM patients, the CMMC count was correlated with serum albumin, calcium, β2-microglobulin, and monoclonal components (p < 0.04). Under therapy, the CMMCs were consistently detectable in 15/40 patients (coMMstant = 1) and were undetectable or decreasing in 25/40 patients (coMMstant = 0). High-quality response rates were lower in the coMMstant = 1 group (p = 0.04), with a 7.8-fold higher risk of death (p = 0.039), suggesting that continuous CMMC release is correlated with poor responses. In four MM patients, a single-cell DNA sequencing analysis on residual CMMCs confirmed the genomic pattern of the aberrations observed in the BM samples, also highlighting the presence of emerging clones. The CMMC kinetics during treatment were used to separate the patients into two subgroups based on the coMMstant index, with different responses and survival probabilities, providing evidence that CMMC persistence is associated with a poor disease course.