Vià, Matteo Da

Abstract Background: Multiple myeloma (MM) is always preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). While these precursor conditions are asymptomatic, they are not entirely benign and carry a lifelong risk of progression to MM. Unlike other cancers defined by pathology, malignant transformation from MGUS or SMM to MM has so far relied on demonstration of clinical end-organ damage or high tumor cell burden (i.e. SLiM criteria, SV Rajkumar Lancet Onc 2014), as morphology and cytogenetics cannot reliably distinguish them. Methods: To identify genomic features underlying clinical behavior in MGUS and SMM, a total of 374 patients with SMM (n= 290) or MGUS (n=84) with available whole exome (whole exome sequencing, WES, n=190) or whole genome sequencing (whole genome sequencing WGS, n=184) were included in the study. Overall, none of the patients had evidence of SLiM or CRAB criteria at the time of the biopsy. Based on the center of origin and availability of WES and WGS, 227 and 97 patients were used to form our study training and validation set. The study was designed in two parts: 1) defining a new classification for MM precursor conditions; 2) integrating genomics to existing prognostic score to improve accuracy in identifying patients at imminent risk of progression. Overall, 68 patients in the training set were either lost to follow-up or enrolled in a clinical trial and they were only included in the classification part of the study. Results: By leveraging the distribution of established MM-defining genomic events (Maura et al. JCO 2024) in the training set, we developed a workflow that differentiates MGUS and SMM into two genomically distinct entities: one with evidence of neoplastic transformation (i.e., genomic MM) and one without (i.e., genomic MGUS). Overall, 39% of MGUS and 91% of SMM cases had genomic evidence of neoplastic transformation in the training set (i.e., genomic MM). When we applied the same workflow and classification to the validation set, 46% and 83% of MGUS and SMM had evidence of neoplastic transformation, respectively. Importantly, none of the patients classified as genomic-MGUS progressed to MM in either the training or validation cohorts, with a median follow-up of 40 and 61 months, respectively. Moreover, all patients with IMWG 2/20/20 high risk SMM were classified as genomic MM in both the training and validation set. Interestingly, 5 out of 62 (8%) patients enrolled in early intervention trials for high risk SMM were genomically classified as genomic-MGUS. Overall, these data demonstrated that the MM genomic background and neoplastic transformation can be acquired very early in time, even before the SMM phase, in line with what observed in solid tumors. To avoid overestimating the prognostic impact of myeloma-defining genomic events—which are, by definition, enriched in the genomic-MM group compared to genomic-MGUS—we restricted our prognostic analysis to patients in whom transformation has already occurred (genomic-MM). In fact, distinct genomic drivers may predict malignant transformation but not necessarily the risk of imminent progression to MM once transformation has occurred. After running 5-fold cross validations corrected for IMWG 2/20/20, only presence of RAS mutations, genomic events involving MYC, presence of neoplastic copy number variant (CNV) signatures and APOBEC mutagenesis were predictive of early progression in the training set. Adding the presence of high-risk myeloma-defining genomic events to the IMWG 2/20/20 model (i.e., genomic-IMWG) significantly improves the accuracy of predicting MM progression in both the training (c-index 0.69 vs. 0.74) and validation sets (c-index 0.74 vs. 0.79), compared to the IMWG 2/20/20 alone. Conclusion: By leveraging comprehensive genomic profiling integrated with the clinical IMWG 2/20/20 risk score, we propose a novel classification and prognostication system for MM precursor conditions, which will better define patients who may benefit from early therapeutic intervention versus watch-and-wait monitoring.

Multiple myeloma (MM) is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). While these precursor conditions are asymptomatic, they are not entirely benign and carry a lifelong risk of progression to MM. Unlike other cancers defined by pathology, malignant transformation from MGUS or SMM to MM has so far relied on demonstration of clinical end-organ damage as morphology and cytogenetics cannot reliably distinguish them. In this study, using genomic data from 374 patients with MGUS or SMM (277 training, 97 validation), to our knowledge, we demonstrate for the first time the ability to identify malignant transformation in MGUS and SMM. We introduce the concept of genomic MM and genomic MGUS to differentiate the subsets of MGUS and SMM that are biologically malignant with genomic features indistinguishable from MM from the subset that is premalignant and unlikely to progress to malignancy. Importantly, we find that most SMM has biological features of malignant transformation indistinguishable from MM. As expected, this subset that we consider having genomic MM is associated with a high risk of progression to MM although some patients remained progression-free beyond 5 years. Conversely, 60% of MGUS and 10% of SMM have no evidence of malignant transformation (genomic MGUS), with no progression during follow-up. Integration of genomic features with the 2/20/20 International Myeloma Working Group model significantly improved the prediction of progression among genomic MM. These findings support the use of genomic criteria to refine the classification and the risk stratification in myeloma precursor conditions.

Abstract Accurate prediction of risk of progression from smoldering (SMM) to active multiple myeloma (MM) is paramount to individualized early therapeutic strategies with minimum risk of overtreatment. Current risk stratification models do not account for evolving biomarker trajectories. We assembled the largest cohort to date of 2,270 SMM patients from six international centers with longitudinal clinical and biological data to train and validate the PANGEA 2.0 risk models. Four evolving biomarkers were significantly associated with shorter time-to-progression: M-protein increase ≥0.2g/dL, involved:uninvolved serum free light chain ratio increase ≥20, creatinine increase >25%, and hemoglobin decrease ≥1.5g/dL. PANGEA 2.0 outperforms established models including the 20/2/20 and IMWG models by more accurately predicting progression (C-statistics=0.69–0.84), even without biomarker history (C-statistics=0.69–0.83) or recent bone marrow biopsy. PANGEA 2.0 is an easy-to-use, open-access tool (https://ghobrial.shinyapps.io/pangea_2_calculator) to improve and individualize SMM risk stratification. Validation tools are available to compare PANGEA 2.0 to established models (https://ghobrial.shinyapps.io/pangea_validation).

Abstract Introduction: The bone marrow (BM) niche promotes multiple myeloma (MM) growth, survival and drug resistance. Therapies targeting both cancer cells and the microenvironment are highly effective. We were interested in identifying novel signaling pathways supporting MM pathogenesis through MM-BM crosstalk. The transmembrane receptor Roundabout 1 (ROBO1) plays a role in growth and dissemination of solid tumors, however its function in MM is unknown. Material and Methods: We analyzed ROBO1 expression in cell lines and primary samples via western blot, immunohistochemistry (IHC) and gene expression profiling. We used short hairpin RNA and CRISPR-Cas9 for ROBO1 knock down (KD) and knock out (KO), respectively. For protein structure-function and rescue studies, we stably expressed full-length (FL) or mutant ROBO1 devoid of extracellular (Cyt) or intracellular domain (DeltaCyt), including patient-derived G674* truncation, with a C-terminus FLAG tag. We used a 3D hydrogel encapsulation system to study proliferation; FLAG immunoprecipitation (IP) followed by mass spectrometry to identify ROBO1 interacting partners; and immunofluorescence to detect ROBO1 localization. To study tumor growth in vivo, we performed PET-CT of mice inoculated subcutaneously or intramedullary with WT or ROBO1 KO MM cells and retrieved tumors for RNA sequencing. To study dissemination and homing, KO and FL addback MM cells were injected intravenously in SCID mice. Mice were monitored for development of tumors or hindlimb paralysis and femora/tumors harvested once mice reached endpoint. Results: ROBO1 is highly expressed in MM cell lines and primary cells but low/absent in normal plasma cells and other hematologic cancer cell lines. ROBO1 KD is specifically cytotoxic for MM cells and ROBO1 KO decreases proliferation, a phenotype fully rescued by FL ROBO1. Compared to WT, ROBO1 KO significantly decreases intramedullary (mean tumor volume (MTV): 1323 vs 457 mm3, p value= 0.02) and extramedullary (MTV: 2684 vs 823 mm3, p value= 0.001) tumor growth in vivo. We further discovered that ROBO1 KO decreases adhesion of MM to BM endothelial and BMSC, which is fully rescued by FL ROBO1. In a disseminated mouse model, ROBO1 KO cells generate bone plasmacytoma with reduced BM invasion, as compared to the extensive BM infiltration observed with ROBO1 FL cells. Consistently, in primary samples from patients, we detected ROBO1 expression only in 1 out of 10 solitary plasmacytoma (dim staining) as compared to 14 out of 14 MM bone marrow biopsy samples tested (11 strong, 3 dim, p value= 0.0001). Mechanistically, we show for the first time that ROBO1 C-terminus is cleaved in a ligand-independent fashion; translocates to the nucleus; and is necessary and sufficient to rescue ROBO1 KO proliferative defect. Viceversa, mutants lacking the cytoplasmic domain, including the G674* truncation, act dominantly negative. Interactomic and RNA sequencing studies point to a previously unknown function of ROBO1 in RNA processing, setting the bases for future studies. Conclusions: We show for the first time that ROBO1 is necessary for MM growth and homing to the BM. Cleaved ROBO1 cytosolic domain translocates to the nucleus and is necessary and sufficient to rescue ROBO1 KO proliferative defect, possibly by participating in RNA processing. These data suggest that ROBO1 C-terminus may be a novel molecular target in MM. Citation Format: Giada Bianchi, Peter G. Czarnecki, Matthew Ho, Aldo M. Roccaro, Antonio Sacco, Yawara Kawano, Annamaria Gulla, Anil Aktas Samur, Tianzeng Cheng, Kenneth Wen, Yu-Tzu Tai, Maria Moscvin, Xinchen Wu, Gulden Camci-Unal, Matteo Claudio Da VIa, Niccolo Bolli, Ruben D. Carrasco, Irene M. Ghobrial, Kenneth C. Anderson. ROBO1 promotes homing, dissemination, and survival of multiple myeloma within the bone marrow microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB217.

Abstract The bone marrow (BM) microenvironment actively promotes multiple myeloma pathogenesis, and therapies targeting both cancer cells and the niche are highly effective. We were interested in identifying novel signaling pathways supporting multiple myeloma–BM cross-talk. Mutations in the transmembrane receptor Roundabout 1 (ROBO1) were recently identified in patients with multiple myeloma; however, their functional consequences are uncertain. Through protein structure–function studies, we discovered that ROBO1 is necessary for multiple myeloma adhesion to BM stromal and endothelial cells and that ROBO1 knockout (KO) compromises BM homing and engraftment in a disseminated mouse model. ROBO1 KO significantly decreases multiple myeloma proliferation in vitro and intra- and extramedullary tumor growth in vivo. Mechanistically, the ROBO1 C-terminus is cleaved in a ligand-independent fashion and is sufficient to promote multiple myeloma proliferation. Vice versa, mutants lacking the cytoplasmic domain, including the human-derived G674* truncation, act dominantly negative. Interactomic and RNA-sequencing studies suggest that ROBO1 may be involved in RNA processing, supporting further studies. Significance: ROBO1 is highly expressed in t(4;14) multiple myeloma and supports homing and dissemination to the BM niche. ROBO1 knockout causes reduced tumor growth in intramedullary and extramedullary myeloma animal models, while the ROBO1 C-terminus is cleaved in multiple fragments and it is necessary and sufficient to sustain myeloma proliferation.