Abstract: Prior studies have reported a significant, inverse association between adiponectin in human milk and offspring growth velocity. Less is known about this association in populations characterised by a loss of weight for age z ‐scores ( WAZs ) in early life. We investigated the association between maternal body composition and milk adiponectin in a sample of F ilipino mothers. We then tested for an association between milk adiponectin and size for age in their infants. A total of 117 F ilipino mothers nursing infants from 0 to 24 months were recruited from C ebu, P hilippines. Anthropometrics, interviews and milk samples were collected and analysed using standard protocols. Mean milk adiponectin in this sample was 7.47 ± 5.75 ng mL −1 . Mean infant WAZ and weight for length ( WLZ ) decreased with age. Maternal body composition was not associated with milk adiponectin content. Milk adiponectin had a significant, positive association with infant WAZ and WLZ . Prior reports have found an inverse association between milk adiponectin and infant WAZ . Here, we report that in lean populations with lower milk adiponectin, there is a positive association with infant WAZ , possibly reflecting pleiotropic biological functions of adiponectin for post‐natal growth. This study increases the understanding of normal biological variation in milk adiponectin and the consequences of low levels of milk adiponectin for offspring growth.

Abstract: Introduction: African American (AA) patients with Multiple Myeloma (MM) are diagnosed at younger ages and show an age-adjusted incidence twice as high as that seen in European Americans (EA); however, a study by Waxman et al found higher disease specific survival in AA. A recent study showed differences in chromosomal aberrations between AA and EA, but further work is needed to understand racial differences in cytogenetics through Fluorescent In Situ Hybridization (FISH) using an extensive array of probes. Methods: We identified 470 consecutive patients with MM from the University of Chicago Cancer Cytogenetics Laboratory from October 2003-January 2017. Of those, 127 (22%) patients had abnormal karyotypes and 343 were evaluated by FISH using a panel of 18 probes. Twenty-two patients who self-identified as Hispanic, Multiracial, Asian, or Indian were dropped from the analysis due to low numbers. For the remaining 311 patients, we obtained data on IGH translocations (partner genes included IGH/FGFR3 fusion [t(4;14)(p16.3;q32)]; IGH/CCND1 fusion [t(11;14)(q13;q32)] ; IGH/MAF fusion [t(14;16)(q32;q23)]); TP53 loss [17p13.1] ; CDKN2C loss [1p32.3]; CKS1B gain [1q21] ; ATM losss [(11)(q22.3)11(q22.3)]; trisomy of chromosomes 3, 7, 9, 12, and 15; and chromosome 13 loss or interstitial deletion of 13q. We grouped the FISH results as high (loss of TP53, loss of CDKN2C; CKS1B gain, IGH/MAF fusion), intermediate (IGH/FGFR3 fusion), or standard (Trisomies 3, 7, 9, 15; Gain of TP53, Gain of ATM, chromosome 13 loss) prognostic risk markers. Results: Of 311 patients, 172 (55.3%) are self-reported EA, 130 (41.8%) are AA. Compared with EA, AA patients were more likely to be females (44.8% vs. 59.2%, respectively) and older than 65 years at diagnosis (47.7% vs. 56.2% respectively). Overall, 6.3% of patients were younger than 45 years at diagnosis, but there was no racial difference in the proportion of young patients. Compared with EA, AA patients assessed with standard risk probes were less likely to have standard risk cytogenetic features (48% vs. 66%; p-value=0.02). AA patients showed a lower percentage of hyperdiploidy, 36.5% of AA patients assessed were positive for hyperdiploidy compared with 57.1% of assessed EA (p=0.02). Despite the lower proportion of AA with cytogenetic markers associated with favorable prognosis, there was no significant difference between EA and AA patients in the prevalence of adverse prognostic markers, such as TP53 deletion, IGH/MAF fusions, or CKS1B gain. However, we did observe that AA patients were more likely to have loss of CDKN2C (16.7% vs 3.6%, p=0.02). Conclusions: We found that compared with EA, AA patients are less likely to have cytogenetic features associated with favorable prognosis (i.e. hyperdiploidy), yet AA do not have a higher prevalence of high risk cytogenetics. These findings suggest that cytogenetics alone may not fully explain racial/ethnic differences in MM mortality. [Meytal Chernoff and Madina Sukhanova are co-first authors of this abstract.] Citation Format: Meytal B. Chernoff, Madina Sukhanova, Liz Stepniak, Wei Zhang, Brian C. Chiu. Racial differences in patterns of cytogenetic abnormalities in multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4233.

Abstract: Introduction: Multiple myeloma (MM) is more common in blacks compared to whites. Prior studies have shown that when blacks have equal access to anti-myeloma therapies as whites, they have similar or even superior relative survival. However, most of these studies included eras when proteasome inhibitors (PI) and immunomodulatory agents (IMiD) were not routinely used. In addition, it is unclear how pre-treatment high risk cytogenetic mutations (HRCM) affect response to therapy among races. We sought to assess differences in the frequencies and outcomes between blacks and whites stratified by cytogenetic risk in two cohorts of MM patients receiving modern treatment approaches. Methods: A retrospective chart review was conducted using the Multiple Myeloma Research Foundation (MMRF) CoMMpass registry (version IA13) and the University of Chicago cytogenetic database and medical records (UChicago). High risk cytogenetic mutations were defined as: deletion 17p/TP53, 1q gain, t(4;14), t(14;16), and t(14;20). The CoMMPass registry inferred cytogenetic changes from next-generation sequencing data; a deletion required that 21% of cells have at least a 1 copy deletion, a gain required that 23% of the cells have a 1 copy gain, and translocations required at least 30% of cells having the event. UChicago cytogenetics data were limited to analyses using fluorescent in situ hybridization on CD138+ selected bone marrow aspirate samples. Abstracted data included pre-treatment demographics, International Staging System (ISS), cytogenetics, induction regimen, autologous stem cell transplant (ASCT) and maintenance therapy use, and overall survival (OS). Comparisons were made using Chi-square or Fisher's exact test for categorical variables and Mann-Whitney U-test for continuous variables. Kaplan-Meier curves were used to display survival curves and Cox models were used to assess the association between cytogenetic mutations and outcomes. Baseline HRCM frequencies from the MMRF and UChicago were pooled; outcomes from the MMRF registry are provided here, and combined survival analysis with UChicago data will be presented. Results: We identified 639 MM patients (113 black and 526 white) in the MMRF CoMMpass registry and 110 (47 black and 63 white) in the UChicago database with complete baseline cytogenetic data available. Median age was 64.5 yrs for whites vs 63 yrs for blacks (p=0.2); 349/589 (59%) whites and 93/160 (58%) blacks were male (p=0.9). There was a similar distribution in the number of HRCMs between the two groups (p=0.7), and no statistical differences in individual HRCMs. In analyzing outcomes in the MMRF cohort, blacks and whites had similar pre-treatment ISS stage and bone marrow plasmacytosis. Blacks were less likely to receive triplet therapies, including combined PI/IMiD-based or alkylator-based triplet therapy (55% vs 73%, p 〈 0.001). First line ASCT was performed in 260/526 (49%) whites compared to 44/113 (39%) blacks (p=0.05). A triplet induction combined with first line ASCT was performed in 231/526 (44%) whites and 37/113 (33%) blacks (p=0.04). Of those who received ASCT, equal numbers received post-ASCT maintenance therapy (60% vs 59%, p=0.9). For the entire MMRF cohort, OS was shorter for blacks compared to whites (Hazard Ratio (HR) 1.59, 95% confidence interval (CI) 1.13-2.27, p=0.01) (Fig. 1A). Estimated 3-yr OS was 67% for blacks vs 76% for whites (p=0.05). In patients who specifically received a triplet regimen followed by ASCT (Fig. 1B), there was no difference in OS between races (HR 1.86, 95% CI 0.75-4.63, p=0.2). Among patients with no HRCM present at diagnosis, there was also no difference between races (p=0.6) (Fig. 2A). There was a trend toward inferior OS in blacks vs whites with one or more HRCMs, which did not reach significance (p=0.13) (Fig. 2B). Results from pooled analyses with the UChicago cohort will be presented at the ASH meeting. Conclusions: There was a similar distribution of HRCMs between blacks and whites. Utilization rates of both triplets and ASCT were higher for both races than previously reported; however, there was a higher use of triplet regimens and ASCT in whites vs blacks. Access to a combination of frontline triplet regimens and ASCT appears to mitigate disparities in outcomes for patients with standard risk cytogenetics, but it is unclear if this is true for those with HRCMs. This requires further investigation of the biological differences in MM among races. Disclosures Jakubowiak: Adaptive Biotechnologies: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; KaryoPharm Therapeutics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Millennium: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; SkyLineDx: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Juno: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees.