Campbell, Peter J.

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.

To assess the possible role of increased insulin clearance in the pathogenesis of the dawn phenomenon, we compared plasma free-insulin concentrations, free-insulin clearance rates, and plasma glucose concentrations in eight subjects with insulin-dependent diabetes mellitus (IDDM) during infusion of insulin from midnight to 0800 h (0.15 mU · kg−1 · min−1) with a Biostator and a Harvard pump. During infusion of insulin with the Biostator, plasma free insulin decreased 40% (from 14 ± 1 to 9 ± 1 μU/ml, P < .01), insulin clearance increased 54% (from 11 ± 1 to 17 ± 2 ml/min, P < .05), and plasma glucose increased from 101 ± 4 to 217 ± 27 mg/dl, P < .01. During infusion of insulin with the Harvard pump, neither plasma free insulin (14 ± vs. 13 ± 1 μU/ml) nor free-insulin clearance (12 ± 2 vs. 13 ± 2 ml/min) changed significantly, but plasma glucose increased from 100 ± 3 to 167 ± 21 mg/dl, P < .01. The increases in plasma glucose during infusion of insulin with the Biostator and the Harvard pump were not significantly different (t = 1.44, P = .19). When insulin was delivered directly into test tubes with the Biostator and the Harvard pump, insulin concentrations in the test tubes decreased 46% over 8 h (P < .05) with the Biostator, whereas no decrease was observed with the Harvard pump. We conclude that the dawn phenomenon can occur without an increase in insulin clearance and that the apparent overnight increase in insulin clearance observed in studies with the Biostator iS artifactual.

To compare glucose counter regulatory mechanisms during short-term hypoglycemia and prolonged hypoglycemia, insulin was infused either intravenously (160 mil · M−2 · min) for 10 min or subcutaneously (15 mU · M−2 · min) for 12 h in normal volunteers. With each type of insulin infusion, hypoglycemia (∼50 mg/dl) was either allowed to develop or was prevented (control experiments) by the glucose-clamp technique. During prolonged hypoglycemia, both increased glucose production (1.55 ± 0.05 versus 0.33 ± 0.14 mg · kg−1 · min in control experiments at 12 h, P < 0.01) and suppressed glucose utilization (1.55 ± 0.06 versus 3.17 ± 0.15 mg · kg−1 · min in control studies at 12 h, P < 0.01) were involved in counterregulation. During short-term hypoglycemia, only increased glucose production (3.23 ± 0.33 versus 0.06 ± 0.03 mg · kg−1 · min in control experiments at 60 min) was involved, since glucose clearance actually increased (3.99 ± 0.20 versus 2.88 ± 0.02 ml · kg−1 · min in control experiments at 60 min, P < 0.01). Estimated portal venous insulin concentrations decreased 40% (basal 24 ± 3 versus 14 ± 1 mU/ml at 60 min, P < 0.01) in the short-term hypoglycemia experiments but remained at basal levels (basal 25 ± 1 versus ∼26 μU/min between 1 and 12 h) during prolonged hypoglycemia. Despite the fact that hypoglycemia was more gradually induced in the prolonged hypoglycemia model, peak counterregulatory hormone responses were at least as great as those during short-term hypoglycemia. Plasma free fatty acids and ketone bodies increased 150–200% above basal (both P < 0.01) with counterregulation during prolonged hypoglycemia but did not increase above basal levels with counterregulation during short-term hypoglycemia. Finally, plasma alanine remained unchanged during short-term hypoglycemia but decreased nearly 40% during prolonged hypoglycemia (basal 327 ± 20 versus 208 ± 21 μM at 12 h, P < 0.01). We conclude that glucose counterregulatory mechanisms differ during short-term and prolonged hypoglycemia. In the former, only an increase in glucose production mediated by suppression of insulin secretion and increased glucagon secretion is involved, whereas during prolonged hypoglycemia, both a suppression of glucose utilization, and an increase in glucose production are important. These latter changes in glucose production and utilization may be influenced by changes in circulating nonglucose substrates (e.g., alanine, free fatty acids, and ketone bodies) as well as by hormonal factors acting on both hepatic and extrahepatic tissues.

To ascertain whether the dawn phenomenon occurs in nondiabetic individuals and, if so, whether it is due to an increase in glucose production or a decrease in glucose utilization, we determined plasma concentrations of glucose, insulin, C-peptide, and counter regulatory hormones, as well as rates of glucose production, glucose utilization, and insulin secretion at one-halfhourly intervals between 1:00 and 9:00 a.m. in eight normal volunteers. After 5:30 a.m., plasma glucose, insulin, and C-peptide concentrations all increased significantly; rates of glucose production, glucose utilization, and insulin secretion also increased (all P < 0.05). Plasma cortisol, epinephrine, and norepinephrine increased significantly from nocturnal nadirs between 4:00 and 6:30 a.m. Plasma growth hormone, which had increased episodically between 1:00 and 4:30 a.m., decreased thereafter nearly 50% (P < 0.05). Plasma glucagon did not change significantly throughout the period of observation. These results indicate that a dawn-like phenomenon, initiated by an increase in glucose production, occurs in nondiabetic individuals. Thus, early morning increases in plasma glucose concentrations and insulin requirements observed in IDDM and NIDDM may be an exaggeration of a physiologic circadian variation in hepatic insulin sensitivity induced by antecedent changes in catecholamine and/or growth hormone secretion.