Round Table Discussion on Optimal Clinical Trial Design in Precursor Multiple Myeloma.

SUMMARY: While the current approach to precursor hematologic conditions is to "watch and wait," this may change with the development of therapies that are safe and extend survival or delay the onset of symptomatic disease. The goal of future therapies in precursor hematologic conditions is to improve survival and prevent or delay the development of symptomatic disease while maximizing safety. Clinical trial considerations in this field include identifying an appropriate at-risk population, safety assessments, dose selection, primary and secondary trial endpoints including surrogate endpoints, control arms, and quality-of-life metrics, all of which may enable more precise benefit-risk assessment.

Design and Rationale of Prolonged Nightly Fasting for Multiple Myeloma Prevention (PROFAST): Protocol for a Randomized Controlled Pilot Trial.

BACKGROUND: Obesity is an established, modifiable risk factor of multiple myeloma (MM); yet, no lifestyle interventions are routinely recommended for patients with overweight or obesity with MM precursor conditions. Prolonged nightly fasting is a simple, practical dietary regimen supported by research, suggesting that the synchronization of feeding-fasting timing with sleep-wake cycles favorably affects metabolic pathways implicated in MM. We describe the design and rationale of a randomized controlled pilot trial evaluating the efficacy of a regular, prolonged nighttime fasting schedule among individuals with overweight or obesity at high risk for developing MM or a related lymphoid malignancy. OBJECTIVE: We aim to investigate the effects of 4-month prolonged nightly fasting on body composition and tumor biomarkers among individuals with overweight or obesity with monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), or smoldering Waldenström macroglobulinemia (SWM). METHODS: Individuals with MGUS, SMM, or SWM aged ≥18 years and a BMI of ≥25 kg/m2 are randomized to either a 14-hour nighttime fasting intervention or a healthy lifestyle education control group. Participants' baseline diet and lifestyle patterns are characterized through two 24-hour dietary recalls: questionnaires querying demographic, comorbidity, lifestyle, and quality-of-life information; and wrist actigraphy measurements for 7 days. Fasting intervention participants are supported through one-on-one telephone counseling by a health coach and automated SMS text messaging to support fasting goals. Primary end points of body composition, including visceral and subcutaneous fat (by dual-energy x-ray absorptiometry); bone marrow adiposity (by bone marrow histology); and tumor biomarkers, specifically M-proteins and serum free light-chain concentrations (by gel-based and serum free light-chain assays), are assessed at baseline and after the 4-month study period; changes therein from baseline are evaluated using a repeated measures mixed-effects model that accounts for the correlation between baseline and follow-up measures and is generally robust to missing data. Feasibility is assessed as participant retention (percent dropout in each arm) and percentage of days participants achieved a ≥14-hour fast. RESULTS: The PROlonged nightly FASTing (PROFAST) study was funded in June 2022. Participant recruitment commenced in April 2023. As of July 2023, six participants consented to the study. The study is expected to be completed by April 2024, and data analysis and results are expected to be published in the first quarter of 2025. CONCLUSIONS: PROFAST serves as an important first step in exploring the premise that prolonged nightly fasting is a strategy to control obesity and obesity-related mechanisms of myelomagenesis. In evaluating the feasibility and impact of prolonged nightly fasting on body composition, bone marrow adipose tissue, and biomarkers of tumor burden, this pilot study may generate hypotheses regarding metabolic mechanisms underlying MM development and ultimately inform clinical and public health strategies for MM prevention. TRIAL REGISTRATION: ClinicalTrials.gov NCT05565638; http://clinicaltrials.gov/ct2/show/NCT05565638. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/51368.

Mass spectrometry-detected MGUS is associated with obesity and other novel modifiable risk factors in a high-risk population.

ABSTRACT: Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant condition of multiple myeloma with few known risk factors. The emergence of mass spectrometry (MS) for the detection of MGUS has provided new opportunities to evaluate its risk factors. In total, 2628 individuals at elevated risk for multiple myeloma were enrolled in a screening study and completed an exposure survey (PROMISE trial). Participant samples were screened by MS, and monoclonal proteins (M-proteins) with concentrations of ≥0.2 g/L were categorized as MS-MGUS. Multivariable logistic models evaluated associations between exposures and MS outcomes. Compared with normal weight (body mass index [BMI] of 18.5 to <25 kg/m2), obesity (BMI of ≥30 kg/m2) was associated with MS-MGUS, adjusting for age, sex, Black race, education, and income (odds ratio [OR], 1.73; 95% confidence interval [CI], 1.21-2.47; P = .003). High physical activity (≥73.5 metabolic equivalent of task (MET)-hours per week vs <10.5 MET-hours per week) had a decreased likelihood of MS-MGUS (OR, 0.45, 95% CI, 0.24-0.80; P = .009), whereas heavy smoking and short sleep had increased likelihood of MS-MGUS (>30 pack-years vs never smoker: OR, 2.19; 95% CI, 1.24-3.74; P = .005, and sleep <6 vs ≥6 hours per day: OR, 2.11; 95% CI, 1.26-3.42; P = .003). In the analysis of all MS-detected monoclonal gammopathies, which are inclusive of M-proteins with concentrations of <0.2 g/L, elevated BMI and smoking were associated with all MS-positive cases. Findings suggest MS-detected monoclonal gammopathies are associated with a broader range of modifiable risk factors than what has been previously identified. This trial was registered at www.clinicaltrials.gov as #NCT03689595.

Blood-based tests for multicancer early detection (PATHFINDER): a prospective cohort study.

BACKGROUND: Multicancer early detection (MCED) blood tests can detect a cancer signal from circulating cell-free DNA (cfDNA). PATHFINDER was a prospective cohort study investigating the feasibility of MCED testing for cancer screening. METHODS: In this prospective cohort study done in oncology and primary care outpatient clinics at seven US health networks, a convenience sample of adults aged 50 years or older without signs or symptoms of cancer consented to MCED testing. We collected blood, analysed cfDNA, and returned results to participants' doctors. If a methylation signature indicative of cancer was detected, predicted cancer signal origin(s) informed diagnostic assessment. The primary outcome was time to, and extent of, diagnostic testing required to confirm the presence or absence of cancer. This trial is registered at ClinicalTrials.gov, NCT04241796, and is completed. FINDINGS: Between Dec 12, 2019, and Dec 4, 2020, we recruited 6662 participants. 4204 (63·5%) of 6621 participants with analysable results were women, 2417 (36·5%) were men, and 6071 (91·7%) were White. A cancer signal was detected in 92 (1·4%) of 6621 participants with analysable results. 35 (38%) participants were diagnosed with cancer (true positives) and 57 (62%) had no cancer diagnosis (false positives). Excluding two participants whose diagnostic assessments began before MCED test results were reported, median time to diagnostic resolution was 79 days (IQR 37-219): 57 days (33-143) in true-positive and 162 days (44-248) in false-positive participants. Most participants had both laboratory tests (26 [79%] of 33 with true-positive results and 50 [88%] of 57 with false-positive results) and imaging (30 [91%] of 33 with true-positive results and 53 [93%] of 57 with false-positive results). Fewer procedures were done in participants with false-positive results (17 [30%] of 57) than true-positive results (27 [82%] of 33) and few had surgery (one with a false-positive result and three with a true-positive result). INTERPRETATION: This study supports the feasibility of MCED screening for cancer and underscores the need for further research investigating the test's clinical utility. FUNDING: GRAIL.

Personalised progression prediction in patients with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma (PANGEA): a retrospective, multicohort study.

BACKGROUND: Patients with precursors to multiple myeloma are dichotomised as having monoclonal gammopathy of undetermined significance or smouldering multiple myeloma on the basis of monoclonal protein concentrations or bone marrow plasma cell percentage. Current risk stratifications use laboratory measurements at diagnosis and do not incorporate time-varying biomarkers. Our goal was to develop a monoclonal gammopathy of undetermined significance and smouldering multiple myeloma stratification algorithm that utilised accessible, time-varying biomarkers to model risk of progression to multiple myeloma. METHODS: In this retrospective, multicohort study, we included patients who were 18 years or older with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma. We evaluated several modelling approaches for predicting disease progression to multiple myeloma using a training cohort (with patients at Dana-Farber Cancer Institute, Boston, MA, USA; annotated from Nov, 13, 2019, to April, 13, 2022). We created the PANGEA models, which used data on biomarkers (monoclonal protein concentration, free light chain ratio, age, creatinine concentration, and bone marrow plasma cell percentage) and haemoglobin trajectories from medical records to predict progression from precursor disease to multiple myeloma. The models were validated in two independent validation cohorts from National and Kapodistrian University of Athens (Athens, Greece; from Jan 26, 2020, to Feb 7, 2022; validation cohort 1), University College London (London, UK; from June 9, 2020, to April 10, 2022; validation cohort 1), and Registry of Monoclonal Gammopathies (Czech Republic, Czech Republic; Jan 5, 2004, to March 10, 2022; validation cohort 2). We compared the PANGEA models (with bone marrow [BM] data and without bone marrow [no BM] data) to current criteria (International Myeloma Working Group [IMWG] monoclonal gammopathy of undetermined significance and 20/2/20 smouldering multiple myeloma risk criteria). FINDINGS: We included 6441 patients, 4931 (77%) with monoclonal gammopathy of undetermined significance and 1510 (23%) with smouldering multiple myeloma. 3430 (53%) of 6441 participants were female. The PANGEA model (BM) improved prediction of progression from smouldering multiple myeloma to multiple myeloma compared with the 20/2/20 model, with a C-statistic increase from 0·533 (0·480-0·709) to 0·756 (0·629-0·785) at patient visit 1 to the clinic, 0·613 (0·504-0·704) to 0·720 (0·592-0·775) at visit 2, and 0·637 (0·386-0·841) to 0·756 (0·547-0·830) at visit three in validation cohort 1. The PANGEA model (no BM) improved prediction of smouldering multiple myeloma progression to multiple myeloma compared with the 20/2/20 model with a C-statistic increase from 0·534 (0·501-0·672) to 0·692 (0·614-0·736) at visit 1, 0·573 (0·518-0·647) to 0·693 (0·605-0·734) at visit 2, and 0·560 (0·497-0·645) to 0·692 (0·570-0·708) at visit 3 in validation cohort 1. The PANGEA models improved prediction of monoclonal gammopathy of undetermined significance progression to multiple myeloma compared with the IMWG rolling model at visit 1 in validation cohort 2, with C-statistics increases from 0·640 (0·518-0·718) to 0·729 (0·643-0·941) for the PANGEA model (BM) and 0·670 (0·523-0·729) to 0·879 (0·586-0·938) for the PANGEA model (no BM). INTERPRETATION: Use of the PANGEA models in clinical practice will allow patients with precursor disease to receive more accurate measures of their risk of progression to multiple myeloma, thus prompting for more appropriate treatment strategies. FUNDING: SU2C Dream Team and Cancer Research UK.

Targeting the fatty acid binding proteins disrupts multiple myeloma cell cycle progression and MYC signaling.

Multiple myeloma is an incurable plasma cell malignancy with only a 53% 5-year survival rate. There is a critical need to find new multiple myeloma vulnerabilities and therapeutic avenues. Herein, we identified and explored a novel multiple myeloma target: the fatty acid binding protein (FABP) family. In our work, myeloma cells were treated with FABP inhibitors (BMS3094013 and SBFI-26) and examined in vivo and in vitro for cell cycle state, proliferation, apoptosis, mitochondrial membrane potential, cellular metabolism (oxygen consumption rates and fatty acid oxidation), and DNA methylation properties. Myeloma cell responses to BMS309403, SBFI-26, or both, were also assessed with RNA sequencing (RNA-Seq) and proteomic analysis, and confirmed with western blotting and qRT-PCR. Myeloma cell dependency on FABPs was assessed using the Cancer Dependency Map (DepMap). Finally, MM patient datasets (CoMMpass and GEO) were mined for FABP expression correlations with clinical outcomes. We found that myeloma cells treated with FABPi or with FABP5 knockout (generated via CRISPR/Cas9 editing) exhibited diminished proliferation, increased apoptosis, and metabolic changes in vitro. FABPi had mixed results in vivo, in two pre-clinical MM mouse models, suggesting optimization of in vivo delivery, dosing, or type of FABP inhibitors will be needed before clinical applicability. FABPi negatively impacted mitochondrial respiration and reduced expression of MYC and other key signaling pathways in MM cells in vitro. Clinical data demonstrated worse overall and progression-free survival in patients with high FABP5 expression in tumor cells. Overall, this study establishes the FABP family as a potentially new target in multiple myeloma. In MM cells, FABPs have a multitude of actions and cellular roles that result in the support of myeloma progression. Further research into the FABP family in MM is warrented, especially into the effective translation of targeting these in vivo.

Multiple myeloma is a type of blood cancer for which only a few treatments are available. Currently, only about half the patients with multiple myeloma survive for five years after diagnosis. Because obesity is a risk factor for multiple myeloma, researchers have been studying how fat cells or fatty acids affect multiple myeloma tumor cells to identify new treatment targets. Fatty acid binding proteins (FABPs) are one promising target. The FABPs shuttle fatty acids and help cells communicate. Previous studies linked FABPs to some types of cancer, including another blood cancer called leukemia, and cancers of the prostate and breast. A recent study showed that patients with multiple myeloma, who have high levels of FABP5 in their tumors, have worse outcomes than patients with lower levels. But, so far, no one has studied the effects of inhibiting FABPs in multiple myeloma tumor cells or animals with multiple myeloma. Farrell et al. show that blocking or eliminating FABPs kills myeloma tumor cells and slows their growth in a dish (in vitro) and in some laboratory mice. In the experiments, the researchers treated myeloma cells with drugs that inhibit FABPs or genetically engineered myeloma cells to lack FABPs. They also show that blocking FABPs reduces the activity of a protein called MYC, which promotes tumor cell survival in many types of cancer. It also changed the metabolism of the tumor cell. Finally, the team examined data collected from several sets of patients with multiple myeloma and found that patients with high FABP levels have more aggressive cancer. The experiments lay the groundwork for more studies to determine if drugs or other therapies targeting FABPs could treat multiple myeloma. More research is needed to determine why inhibiting FABPs worked in some mice with multiple myeloma but not others, and whether FABP inhibitors might work better if combined with other cancer therapies. There were no signs that the drugs were toxic in mice, but more studies must prove they are safe and effective before testing the drugs in humans with multiple myeloma. Designing better or more potent FABP-blocking drugs may also lead to better animal study results.

Prevalence of monoclonal gammopathies and clinical outcomes in a high-risk US population screened by mass spectrometry: a multicentre cohort study.

BACKGROUND: Prevalence estimates for monoclonal gammopathy of undetermined significance (MGUS) are based on predominantly White study populations screened by serum protein electrophoresis supplemented with immunofixation electrophoresis. A prevalence of 3% is reported for MGUS in the general population of European ancestry aged 50 years or older. MGUS prevalence is two times higher in individuals of African descent or with a family history of conditions related to multiple myeloma. We aimed to evaluate the prevalence and clinical implications of monoclonal gammopathies in a high-risk US population screened by quantitative mass spectrometry. METHODS: We used quantitative matrix-assisted laser desorption ionisation-time of flight (MALDI-TOF) mass spectrometry and EXENT-iQ software to screen for and quantify monoclonal gammopathies in serum from 7622 individuals who consented to the PROMISE screening study between Feb 26, 2019, and Nov 4, 2021, and the Mass General Brigham Biobank (MGBB) between July 28, 2010, and July 1, 2021. M-protein concentrations at the monoclonal gammopathy of indeterminate potential (MGIP) level were confirmed by liquid chromatography mass spectrometry testing. 6305 (83%; 2211 from PROMISE, 4094 from MGBB) of 7622 participants in the cohorts were at high risk for developing a monoclonal gammopathy on the basis of Black race or a family history of haematological malignancies and fell within the eligible high-risk age range (30 years or older for PROMISE cohort and 18 years or older for MGBB cohort); those over 18 years were also eligible if they had two or more family members with a blood cancer (PROMISE cohort). Participants with a plasma cell malignancy diagnosed before screening were excluded. Longitudinal clinical data were available for MGBB participants with a median follow-up time from serum sample screening of 4·5 years (IQR 2·4-6·7). The PROMISE study is registered with ClinicalTrials.gov, NCT03689595. FINDINGS: The median age at time of screening was 56·0 years (IQR 46·8-64·1). 5013 (66%) of 7622 participants were female, 2570 (34%) male, and 39 (<1%) unknown. 2439 (32%) self-identified as Black, 4986 (65%) as White, 119 (2%) as other, and 78 (1%) unknown. Using serum protein electrophoresis with immunofixation electrophoresis, the MGUS prevalence was 6% (101 of 1714) in high-risk individuals aged 50 years or older. Using mass spectrometry, we observed a total prevalence of monoclonal gammopathies of 43% (1788 of 4207) in this group. We termed monoclonal gammopathies below the clinical immunofixation electrophoresis detection level (<0·2 g/L) MGIPs, to differentiate them from those with higher concentrations, termed mass-spectrometry MGUS, which had a 13% (592 of 4207) prevalence by mass spectrometry in high-risk individuals aged 50 years or older. MGIP was predominantly of immunoglobulin M isotype, and its prevalence increased with age (19% [488 of 2564] for individuals aged <50 years, 29% [1464 of 5058] for those aged ≥50 years, and 37% [347 of 946] for those aged ≥70 years). Mass-spectrometry MGUS prevalence increased with age (5% [127 of 2564] for individuals aged <50 years, 13% [678 of 5058] for those aged ≥50 years, and 18% [173 of 946] for those aged ≥70 years) and was higher in men (314 [12%] of 2570) compared with women (485 [10%] 5013; p=0·0002), whereas MGIP prevalence did not differ significantly by gender. In those aged 50 years or older, the prevalence of mass spectrometry was significantly higher in Black participants (224 [17%] of 1356) compared with the controls (p=0·0012) but not in those with family history (368 [13%] of 2851) compared with the controls (p=0·1008). Screen-detected monoclonal gammopathies correlated with increased all-cause mortality in MGBB participants (hazard ratio 1·55, 95% CI 1·16-2·08; p=0·0035). All monoclonal gammopathies were associated with an increased likelihood of comorbidities, including myocardial infarction (odds ratio 1·60, 95% CI 1·26-2·02; p=0·00016 for MGIP-high and 1·39, 1·07-1·80; p=0·015 for mass-spectrometry MGUS). INTERPRETATION: We detected a high prevalence of monoclonal gammopathies, including age-associated MGIP, and made more precise estimates of mass-spectrometry MGUS compared with conventional gel-based methods. The use of mass spectrometry also highlighted the potential hidden clinical significance of MGIP. Our study suggests the association of monoclonal gammopathies with a variety of clinical phenotypes and decreased overall survival. FUNDING: Stand Up To Cancer Dream Team, the Multiple Myeloma Research Foundation, and National Institutes of Health.

A comprehensive review of the impact of obesity on plasma cell disorders.

Multiple myeloma (MM) remains an incurable plasma cell malignancy. Although little is known about the etiology of MM, several metabolic risk factors such as obesity, diabetes, poor nutrition, many of which are modifiable, have been linked to the pathogenesis of numerous neoplasms including MM. In this article, we provide a detailed summary of what is known about the impact of obesity on the pathogenesis of MM, its influence on outcomes in MM patients, and discuss potential mechanisms through which obesity is postulated to influence MM risk and prognosis. Along with advancements in treatment modalities to improve survival in MM patients, focused efforts are needed to prevent or intercept MM at its earliest stages. The consolidated findings presented in this review highlight the need for clinical trials to assess if lifestyle modifications can reduce the incidence and improve outcomes of MM in high-risk populations. Data generated from such studies can help formulate evidence-based lifestyle recommendations for the prevention and control of MM.

Regular Aspirin Use and Mortality in Patients with Multiple Myeloma.

BACKGROUND: Inflammation is important in multiple myeloma pathogenesis, and regular aspirin use has been shown to confer a reduced risk of multiple myeloma. The influence of aspirin on survival after multiple myeloma diagnosis is unknown. METHODS: We identified 436 men and women diagnosed with multiple myeloma between 1980 and 2016 in the Health Professionals Follow-up Study and the Nurses' Health Study who reported aspirin intake biennially on follow-up questionnaires. Using multivariable Cox proportional hazards regression models, we estimated HRs and 95% confidence intervals (CI) associated with the effect of aspirin use on multiple myeloma-specific and overall mortality. RESULTS: Compared with nonusers, participants who used aspirin after diagnosis had a multivariable HR for multiple myeloma-specific mortality of 0.61 (95% CI, 0.46-0.79) and for overall mortality of 0.63 (95% CI, 0.49-0.80), after adjustment for age at diagnosis, year of diagnosis, sex, body mass index, prediagnosis aspirin use, and number of comorbidities. For postdiagnosis aspirin quantity, we observed a modest trend of reduction in multiple myeloma-specific and all-cause mortality with increasing number of 325-mg tablets of aspirin per week, although the CIs for 1 to <6 and ≥6 tablets overlapped. Results were not materially different before or after the availability of novel therapies (before vs. after the year 2000). Prediagnosis frequency or duration of aspirin use was not significantly associated with multiple myeloma-specific or overall mortality. CONCLUSIONS: These findings support the use of aspirin as a complementary strategy to enhance multiple myeloma survival. IMPACT: Confirmation in samples that have comprehensive clinical information is encouraged.

The PATHFINDER Study: Assessment of the Implementation of an Investigational Multi-Cancer Early Detection Test into Clinical Practice.

To examine the extent of the evaluation required to achieve diagnostic resolution and the test performance characteristics of a targeted methylation cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test, ~6200 participants ≥50 years with (cohort A) or without (cohort B) ≥1 of 3 additional specific cancer risk factors will be enrolled in PATHFINDER (NCT04241796), a prospective, longitudinal, interventional, multi-center study. Plasma cfDNA from blood samples will be analyzed to detect abnormally methylated DNA associated with cancer (i.e., cancer "signal") and a cancer signal origin (i.e., tissue of origin). Participants with a "signal detected" will undergo further diagnostic evaluation per guiding physician discretion; those with a "signal not detected" will be advised to continue guideline-recommended screening. The primary objective will be to assess the number and types of subsequent diagnostic tests needed for diagnostic resolution. Based on microsimulations (using estimates of cancer incidence and dwell times) of the typical risk profiles of anticipated participants, the median (95% CI) number of participants with a "signal detected" result is expected to be 106 (87-128). Subsequent diagnostic evaluation is expected to detect 52 (39-67) cancers. The positive predictive value of the MCED test is expected to be 49% (39-58%). PATHFINDER will evaluate the integration of a cfDNA-based MCED test into existing clinical cancer diagnostic pathways. The study design of PATHFINDER is described here.

The COronavirus Pandemic Epidemiology (COPE) Consortium: A Call to Action.

The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; COVID-19) pandemic presents challenges to the real-time collection of population-scale data to inform near-term public health needs as well as future investigations. We established the COronavirus Pandemic Epidemiology (COPE) consortium to address this unprecedented crisis on behalf of the epidemiology research community. As a central component of this initiative, we have developed a COVID Symptom Study (previously known as the COVID Symptom Tracker) mobile application as a common data collection tool for epidemiologic cohort studies with active study participants. This mobile application collects information on risk factors, daily symptoms, and outcomes through a user-friendly interface that minimizes participant burden. Combined with our efforts within the general population, data collected from nearly 3 million participants in the United States and United Kingdom are being used to address critical needs in the emergency response, including identifying potential hot spots of disease and clinically actionable risk factors. The linkage of symptom data collected in the app with information and biospecimens already collected in epidemiology cohorts will position us to address key questions related to diet, lifestyle, environmental, and socioeconomic factors on susceptibility to COVID-19, clinical outcomes related to infection, and long-term physical, mental health, and financial sequalae. We call upon additional epidemiology cohorts to join this collective effort to strengthen our impact on the current health crisis and generate a new model for a collaborative and nimble research infrastructure that will lead to more rapid translation of our work for the betterment of public health.

Dissecting racial disparities in multiple myeloma.

Multiple myeloma (MM) is a fatal plasma cell dyscrasia with a median overall survival of 5 to 10 years. MM progresses from the more common but often subclinical precursor states of monoclonal gammopathy of undetermined significance (MGUS), and smoldering multiple myeloma (SMM) to overt MM. There are large racial disparities in all stages of the disease. Compared with Whites, Blacks have an increased MGUS and MM risk and higher mortality rate, and have not experienced the same survival gains over time. The roots of this disparity are likely multifactorial in nature. Comparisons of Black and White MGUS and MM patients suggest that differences in risk factors, biology, and clinical characteristics exist by race or ancestry, which may explain some of the observed disparity in MM. However, poor accrual of Black MGUS and MM patients in clinical and epidemiological studies has limited our understanding of this disparity and hindered its elimination. Disparities in MM survival also exist but appear to stem from inferior treatment utilization and access rather than underlying pathogenesis. Innovative and multidisciplinary approaches are urgently needed to enhance our understanding of disparities that exist at each stage of the MM disease continuum and facilitate their elimination.

Prediagnosis dietary pattern and survival in patients with multiple myeloma.

Inflammation and endogenous growth factors are important in multiple myeloma (MM) pathogenesis. Although diets that modulate these biologic pathways may influence MM patient survival, studies have not examined the association of dietary patterns with MM survival. We conducted pooled prospective survival analyses of 423 MM patients from the Nurses' Health Study (1986-2016) and the Health Professionals Follow-up Study (1988-2016) using Cox regression models. We used data from repeated food frequency questionnaires (FFQ) to compute dietary patterns as of the last prediagnosis FFQ, including the Alternate Healthy Eating Index (AHEI)-2010, alternate Mediterranean Diet, Dietary Approaches to Stop Hypertension, Prudent, Western and empirical dietary inflammatory patterns and empirical dietary indices for insulin resistance and hyperinsulinemia. During follow-up, we documented 295 MM-related deaths among 345 total deaths. MM-specific mortality was 15-24% lower per one standard deviation (SD) increase (e.g., toward healthier habits) in favorable dietary pattern scores. For example, the multivariable-adjusted hazard ratio [HR] and 95% confidence interval [CI] per 1-SD increase in AHEI-2010 score were 0.76, 0.67-0.87 (p < 0.001). In contrast, MM-specific mortality was 16-24% higher per 1-SD increase (e.g., toward less healthy habits) in "unhealthy" diet scores; for example, the multivariable-adjusted HR, 95% CI per 1-SD increase in Western pattern score were 1.24, 1.07-1.44 (p = 0.005). Associations were similar for all-cause mortality. In conclusion, our consistent findings for multiple dietary patterns provide the first evidence that MM patients with healthier prediagnosis dietary habits may have longer survival than those with less healthy diets.

Research-based PAM50 signature and long-term breast cancer survival.

PURPOSE: Multi-gene signatures provide biological insight and risk stratification in breast cancer. Intrinsic molecular subtypes defined by mRNA expression of 50 genes (PAM50) are prognostic in hormone-receptor positive postmenopausal breast cancer. Yet, for 25-40% in the PAM50 intermediate risk group, long-term risk remains uncertain. Our study aimed to (i) test the long-term prognostic value of the PAM50 signature in pre- and post-menopausal breast cancer; (ii) investigate if the PAM50 model could be improved by addition of other mRNAs implicated in oncogenesis. METHODS: We used archived FFPE samples from 1723 breast cancer survivors; high quality reads were obtained on 1253 samples. Transcript expression was quantified using a custom codeset with probes for > 100 targets. Cox models assessed gene signatures for breast cancer relapse and survival. RESULTS: Over 15 + years of follow-up, PAM50 subtypes were (P < 0.01) associated with breast cancer outcomes after accounting for tumor stage, grade and age at diagnosis. Results did not differ by menopausal status at diagnosis. Women with Luminal B (versus Luminal A) subtype had a > 60% higher hazard. Addition of a 13-gene hypoxia signature improved prognostication with > 40% higher hazard in the highest vs lowest hypoxia tertiles. CONCLUSIONS: PAM50 intrinsic subtypes were independently prognostic for long-term breast cancer survival, irrespective of menopausal status. Addition of hypoxia signatures improved risk prediction. If replicated, incorporating the 13-gene hypoxia signature into the existing PAM50 risk assessment tool, may refine risk stratification and further clarify treatment for breast cancer.

Elucidating Under-Studied Aspects of the Link Between Obesity and Multiple Myeloma: Weight Pattern, Body Shape Trajectory, and Body Fat Distribution.

BACKGROUND: Although obesity is an established modifiable risk factor for multiple myeloma (MM), several nuanced aspects of its relation to MM remain unelucidated, limiting public health and prevention messages. METHODS: We analyzed prospective data from the Nurses' Health Study and Health Professionals Follow-Up Study to examine MM risk associated with 20-year weight patterns in adulthood, body shape trajectory from ages 5 to 60 years, and body fat distribution. For each aforementioned risk factor, we report hazard ratios (HRs) and 95% confidence intervals (CIs) for incident MM from multivariable Cox proportional-hazards models. RESULTS: We documented 582 incident MM cases during 4 280 712 person-years of follow-up. Persons who exhibited extreme weight cycling, for example, those with net weight gain and one or more episodes of intentional loss of at least 20 pounds or whose cumulative intentional weight loss exceeded net weight loss with at least one episode of intentional loss of 20 pounds or more had an increased MM risk compared with individuals who maintained their weight (HR = 1.71, 95% CI = 1.05 to 2.80); the association was statistically nonsignificant after adjustment for body mass index. We identified four body shape trajectories: lean-stable, lean-increase, medium-stable, and medium-increase. MM risk was higher in the medium-increase group than in the lean-stable group (HR = 1.62, 95% CI = 1.22 to 2.14). Additionally, MM risk increased with increasing hip circumference (HR per 1-inch increase: 1.03, 95% CI = 1.01 to 1.06) but was not associated with other body fat distribution measures. CONCLUSIONS: Maintaining a lean and stable weight throughout life may provide the strongest benefit in terms of MM prevention.

miRNAs and Long-term Breast Cancer Survival: Evidence from the WHEL Study.

BACKGROUND: There is substantial variation in breast cancer survival rates, even among patients with similar clinical and genomic profiles. New biomarkers are needed to improve risk stratification and inform treatment options. Our aim was to identify novel miRNAs associated with breast cancer survival and quantify their prognostic value after adjusting for established clinical factors and genomic markers. METHODS: Using the Women's Healthy Eating and Living (WHEL) breast cancer cohort with >15 years of follow-up and archived tumor specimens, we assayed PAM50 mRNAs and 25 miRNAs using the Nanostring nCounter platform. RESULTS: We obtained high-quality reads on 1,253 samples (75% of available specimens) and used an existing research-use algorithm to ascertain PAM50 subtypes and risk scores (ROR-PT). We identified miRNAs significantly associated with breast cancer outcomes and then tested these in independent TCGA samples. miRNAs that were also prognostic in TCGA samples were further evaluated in multiple regression Cox models. We also used penalized regression for unbiased discovery. CONCLUSIONS: Two miRNAs, 210 and 29c, were associated with breast cancer outcomes in the WHEL and TCGA studies and further improved risk stratification within PAM50 risk groups: 10-year survival was 62% in the node-negative high miR-210-high ROR-PT group versus 75% in the low miR-210- high ROR-PT group. Similar results were obtained for miR-29c. We identified three additional miRNAs, 187-3p, 143-3p, and 205-5p, via penalized regression. IMPACT: Our findings suggest that miRNAs might be prognostic for long-term breast cancer survival and might improve risk stratification. Further research to incorporate miRNAs into existing clinicogenomic signatures is needed.

Physical Activity Change in an RCT: Comparison of Measurement Methods.

Objectives: We aimed to quantify the agreement between self-report, standard cut-point accelerometer, and machine learning accelerometer estimates of physical activity (PA), and exam- ine how agreement changes over time among older adults in an intervention setting. Methods: Data were from a randomized weight loss trial that encouraged increased PA among 333 postmenopausal breast cancer survivors. PA was estimated using accelerometry and a validated questionnaire at baseline and 6-months. Accelerometer data were processed using standard cut-points and a validated machine learning algorithm. Agreement of PA at each time-point and change was assessed using mixed effects regression models and concordance correlation. Results: At baseline, self-report and machine learning provided similar PA estimates (mean dif- ference = 11.5 min/day) unlike self-report and standard cut-points (mean difference = 36.3 min/ day). Cut-point and machine learning methods assessed PA change over time more similarly than other comparisons. Specifically, the mean difference of PA change for the cut-point versus machine learning methods was 5.1 min/day for intervention group and 2.9 in controls, whereas it was ≥ 24.7 min/day for other comparisons. Conclusions: Intervention researchers are facing the issue of self-report measures introducing bias and accelerometer cut-points being insensi- tive. Machine learning approaches may bridge this gap.