Abdallah, Nadine

BackgroundSarcopenia increases with age and is associated with poor survival outcomes in patients with cancer. By using a deep learning–based segmentation approach, clinical computed tomography (CT) images of the abdomen of patients with newly diagnosed multiple myeloma (NDMM) were reviewed to determine whether the presence of sarcopenia had any prognostic value.MethodsSarcopenia was detected by accurate segmentation and measurement of the skeletal muscle components present at the level of the L3 vertebrae. These skeletal muscle measurements were further normalized by the height of the patient to obtain the skeletal muscle index for each patient to classify them as sarcopenic or not.ResultsThe study cohort consisted of 322 patients of which 67 (28%) were categorized as having high risk (HR) fluorescence in situ hybridization (FISH) cytogenetics. A total of 171 (53%) patients were sarcopenic based on their peri‐diagnosis standard‐dose CT scan. The median overall survival (OS) and 2‐year mortality rate for sarcopenic patients was 44 months and 40% compared to 90 months and 18% for those not sarcopenic, respectively (p < .0001 for both comparisons). In a multivariable model, the adverse prognostic impact of sarcopenia was independent of International Staging System stage, age, and HR FISH cytogenetics.ConclusionsSarcopenia identified by a machine learning–based convolutional neural network algorithm significantly affects OS in patients with NDMM. Future studies using this machine learning–based methodology of assessing sarcopenia in larger prospective clinical trials are required to validate these findings.

Abstract Overall Survival estimates from diagnosis are valuable for guiding treatment, but do not consider the years already survived. Conditional survival (CS) provides dynamic survival predictions over time. This study was conducted to estimate CS at 1–8 years from diagnosis and the impact of baseline prognostic factors on CS in multiple myeloma (MM) patients. This is a retrospective study including 2556 MM patients diagnosed between 2004–2019. CS (t|s) was defined as the probability of surviving t years given survival of s years. Median age was 64 years. Median follow-up was 6.2 years and median overall survival from diagnosis was 7.5 years. The 5-year CS estimates at s = 0, 1, 2, 3, and 5 years were 0.64, 0.61, 0.61, 0.61, and 0.58, respectively. On multivariate analysis, age ≥ 65 and proteasome inhibitor + immunomodulatory-based induction were associated with decreased survival and increased survival, respectively, retained at 5 years. The adverse impact of 1q gain/amplification, high-risk IgH translocation, and ISS-3 was significant at 1 and 3 years but not 5 years. Chromosome 17 abnormality was associated with decreased survival only at 1 year. Among MM patients, 5-year CS was stable at 1–5 years from diagnosis. The prognostic impact of high-risk cytogenetic factors decreased with additional years survived.

Abstract Purpose: The prevalence of pathogenic variants in BRCA1 and BRCA2 in populations other than Ashkenazi Jewish (AJ) is not well defined. We describe the racial and ethnic-specific prevalence of BRCA1/2 pathogenic variants and variants of uncertain significance (VUS) among individuals referred for genetic testing in a large urban comprehensive cancer center over a 20-year period. Methods: The population included 3,537 unrelated individuals who underwent genetic testing from January 1999 to October 2019 at the Karmanos Cancer Institute. We estimated the prevalence of pathogenic variants and VUS and evaluated associations with race and ethnicity for African American (AA), Arab, AJ and Hispanic individuals compared to Non-Hispanic Whites (NHW). We used multivariable models to adjust for other predictors of pathogenic variants. We also reported the most common pathogenic variants by racial and ethnic group. Results: The racial and ethnic breakdown of our population was: NHW (68.9%), AA (20.3%), AJ (2.5%), Arab (2.2%), Hispanic (1.0%), Asian Pacific Islander, Native American/Alaskan Native (4.7%), and <1% unknown. The overall prevalence of pathogenic variants in BRCA1/2 was 8.9% and the prevalence of VUS was 5.6%. Compared to NHW, there were no racial or ethnic differences in the rate of pathogenic variants. However, AA individuals were more likely to have VUS in BRCA1 (adjusted OR 2.43, 95% CI 1.38-4.28) and AJ more likely to have VUS in BRCA2 (adjusted OR 3.50, 95% CI 1.61-6.58).Conclusion: These results suggest the continued need for genetic testing and variant reclassification for individuals of all race and ethnic groups.

110 Background: Sarcopenia or a loss of muscle mass increases with aging and is associated with increased overall mortality in patients with cancer. Recent advances in machine learning–based CNN algorithms have allowed for the rapid processing of digital images to produce image classifications of body composition. Since incidence of MM is highly associated with aging, we sought to determine if the presence of sarcopenia, as determined by utilizing this machine learning–based CNN algorithm on CT images, had prognostic value in patients with NDMM. Methods: We identified all patients with NDMM from January 2003 to July 2019 who had a standard-dose CT scan that included the L3 vertebral level performed within 6 months of diagnosis. Using a machine learning–based CNN-algorithm, abdominal CT images were analyzed to measure muscle area. These measurements were normalized by dividing the area values by the height of the patient squared (m2) to obtain skeletal muscle index (SMI) values. Patients were categorized as sarcopenic according to international gender-specific consensus cutoffs for SMI (male: < 55 cm2/m2 and female: < 39 cm2/m2). Patients with the following FISH cytogenetics were considered high risk (HR): t(4;14), t(14;16), t(14;20), and deletion 17p/monosomy 17 whereas the remainder were standard risk (SR). Survival analysis was performed using the Kaplan-Meier method and compared via the log-rank method. Results: The study cohort consisted of 344 patients. 68 (20%) were categorized as HR based on FISH cytogenetics.187 (54%) patients were sarcopenic based on their peri-diagnosis standard-dose CT scan. Sarcopenic patients were more likely to have ISS-3 disease (45% vs. 30%; p =.023), be male (73% vs. 48%; p <.001), and be ≥ age 75 (27% vs. 14%; p =.002) compared to non-sarcopenic patients. The median OS for patients with HR FISH and ISS 2 / 3 disease was 40 months and 57 months respectively compared to 90 months and 119 months for those with SR FISH and ISS-1 disease respectively (FISH: p <.004; ISS: p <.001). The median OS for sarcopenic patients was 44 months compared to 90 months for those not sarcopenic (p <.001). The time to next therapy (TTNT) for sarcopenic patients was 39 months compared to 45 months for those not sarcopenic (p =.05). In a multivariable model, the presence of sarcopenia (HR 1.64, 95% CI, 1.05–2.56; p =.03) retained significance in the presence of HR FISH, ISS 2 / 3 disease, and age ≥ 75. Conclusions: Gender-specific sarcopenia identified by a machine learning–based CNN algorithm significantly affects OS in patients with NDMM and is independent of age, ISS stage, and cytogenetic status. Future studies utilizing this machine learning–based methodology of assessing sarcopenia in larger prospective clinical trials are required to validate these findings.

AbstractBackgroundThere is sparse clinical information on the racial and ethnic distribution of results of multigene panel testing among individuals at high risk for hereditary cancer.MethodsWe evaluated the results of multigene panel testing across eight clinical sites across the state of Michigan for individuals seen for genetic counseling from May 13, 2013 to October 31, 2019 at the Karmanos Cancer Institute's cancer genetics clinic. We estimated the prevalence of pathogenic variants and variants of uncertain significance (VUS) from genes other than BRCA1/2 among individuals of non‐Hispanic White (NHW), Black or African American (AA), Ashkenazi Jewish (AJ), Arab, Hispanic, and other ancestry.ResultsThe racial and ethnic distribution of 2419 individuals who had panel testing included 68.8% NHW, 22.1% AA, 2.3% Arab, 2.2% AJ, 1.0% Hispanic, and 3.6% other. Of these, 11.2% had pathogenic variants and 17.5% had VUS. After multivariable analyses, compared to NHW, AA were less likely to have pathogenic variants (OR 95% CI, 0.38, 0.24–0.59, p < 0.001). Both AA and Arabs were more likely to have VUS (OR 95% CI, 1.53, 1.18–1.98, p = 0.001 and OR 95% CI, 2.28, 1.17–4.43, p = 0.015, respectively). There were no significant differences for other groups. The most common pathogenic variants were CHEK2 (n = 65), MUTYH (n = 45), ATM (n = 28), and MSH2 (n = 22); the most common pathogenic variants by race and ethnicity were CHEK2 (NHW), MSH2 and MUTYH (AA), MSH2 (Arab), MSH6 and CHEK2 (AJ), and MLH1 (Hispanic); the most common pathogenic variants by primary cancer site were CHEK2 (breast), MSH2 (colon), BRIP1 and MUTYH (ovarian), and MSH2 and MSH6 (endometrial).ConclusionsUnderstanding the racial and ethnic distribution of pathogenic variants in multi‐gene panels has the potential to lead to better identification of individuals at risk for hereditary cancer.

AbstractCastleman disease (CD) is a rare lymphoproliferative disease characterized by diverse clinical and pathologic features. Due to its rarity, there are limited studies comparing currently available therapies. The role of autologous stem cell transplantation (ASCT) in CD has not yet been established. In this paper, we describe the clinical characteristics, treatment choices, and outcomes in 34 Mayo Clinic patients diagnosed with multicentric CD from July 1, 2003 to April 30, 2018. Eighteen patients (53%) also met the criteria for POEMS, including 14 with the osteosclerotic variant. The first‐line treatments included: steroid monotherapy (4), cytotoxic chemotherapy (6), rituximab alone (8) or with chemotherapy (2), anti‐IL6 treatment (3), and ASCT (10). The median follow‐up was 4.8 (range: 0.1–15.2) years. The 5‐ and 10‐year overall survival rates were 84% and 71%, respectively. Sixteen patients received high‐dose chemotherapy followed by ASCT during their disease course. Among those, 14 had multicentric CD associated with POEMS. There were no transplant‐related deaths. All patients had at least a partial response to ASCT, most of whom achieved a complete response. The favorable outcomes seen with ASCT in this cohort suggest that transplantation may have a role in multicentric CD, particularly for patients with multicentric CD associated with POEMS.

Abstract Background: MASS-FIX is a screening method for serum and urine monoclonal proteins in multiple myeloma and related plasma cell disorders, which uses immunoglobulin enrichment coupled with matrix-assisted laser desorption ionization time-of-flight mass-spectrometry (MALDI-TOF). In addition to superior sensitivity over conventional gel-based techniques, MASS-FIX can distinguish therapeutic monoclonal antibodies (MoAb) from patient's M protein. As the utilization of therapeutic MoAbs increases, it is essential to understand the persistence pattern of these therapeutic antibodies in the serum. We designed this study to evaluate the duration of daratumumab detection by MASS-FIX in the serum of treated patients. Methods: We used a prospectively maintained database at Mayo clinic to identify patients with multiple myeloma and related plasma cell disorders who were treated with a daratumumab-containing regimen anytime during their disease course and had serial MASS-FIX data available after discontinuation of daratumumab. A univariate analysis was performed to assess for factors that may impact the clearance of daratumumab. Results: We included 125 patients with plasma cell disorders who received daratumumab as first or subsequent line of treatment between March 15 th, 2016, and March 4 th, 2020. The median age was 60.2 years and 57% were male. The most common diagnoses were multiple myeloma (70%) and light chain amyloidosis (18%). Daratumumab-based treatments were initiated after a median of 28.8 (IQR: 6.4-76.3) months from initial diagnosis. The most common regimen used was daratumumab, bortezomib and dexamethasone (23%); 26% underwent transplant after daratumumab-based induction. The median duration of treatment with a daratumumab-based regimen was 208 (IQR: 99-479) days. The median follow-up from the time of daratumumab discontinuation was 457 (95% CI: 346-NR) days. By last follow up, daratumumab was not detected by MASS-FIX in 93 (74%) patients but remained detectable in 32 (26%) patients. The median time from daratumumab discontinuation to disappearance of daratumumab by MASS-FIX was 160 (IQR: 107-233) days. On univariate analysis, the presence of ≥0.5 grams of urine protein was associated with earlier disappearance of daratumumab on MASS-FIX [risk ratio (RR): 2.0, P=0.02). The median time from daratumumab discontinuation to disappearance of daratumumab on MASS-FIX was 116 (95%CI: 76-160) days in patients with urine protein ≥0.5 grams and 203 (95%CI: 162-216) days in patients with urine protein &lt;0.5 grams (P=0.02). There was no association between the time to disappearance of daratumumab by MASS-FIX and old age ≥70 (RR: 0.9, P=0.81], male gender (RR: 0.9, P=0.60), eGFR &lt;60 (RR: 1.0, P=0.98), daratumumab schedule (every 1/2 weeks vs &gt;2weeks) (RR: 1.0, P=0.97), treatment duration (&lt;200 days vs ≥200 days) ( RR: 1.0, P=0.95), or transplantation status (RR: 1.0, P=0.98). Conclusion: The therapeutic monoclonal antibody daratumumab remains detectable in the serum of treated patients by MASS-FIX for several months after discontinuation and the duration varies between individual patients. This data has implications for diagnostic and monitoring testing and may provide guidance for reuse of daratumumab in clinical trials and practice. Proteinuria is associated with earlier disappearance of daratumumab by MASS-FIX and may have implications in patients with amyloidosis and monoclonal immunoglobulin deposition disease (MIDD). Further studies are needed to identify additional factors associated with the timing of disappearance. Disclosures Murray: Mayo Clinic: Other: Has received patents for the Mass-Fix technology which has been licensed to the Binding Site with potential royalties.. Dispenzieri: Takeda: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Kapoor: Karyopharm: Consultancy; Cellectar: Consultancy; BeiGene: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Amgen: Research Funding; Ichnos Sciences: Research Funding; Regeneron Pharmaceuticals: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; AbbVie: Research Funding. Gertz: Akcea Therapeutics, Ambry Genetics, Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Karyopharm Therapeutics, Pfizer Inc (to Institution), Sanofi Genzyme: Honoraria; Ionis Pharmaceuticals: Other: Advisory Board; Akcea Therapeutics, Alnylam Pharmaceuticals Inc, Prothena: Consultancy; Aurora Biopharma: Other: Stock option; AbbVie Inc, Celgene Corporation: Other: Data Safetly & Monitoring. Dingli: Alexion: Consultancy; Novartis: Research Funding; Apellis: Consultancy; Janssen: Consultancy; Sanofi: Consultancy; GSK: Consultancy. Kumar: Antengene: Consultancy, Honoraria; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Merck: Research Funding; Roche-Genentech: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Oncopeptides: Consultancy; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Carsgen: Research Funding; Tenebio: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.

Abstract Purpose: Multiple myeloma (MM) is a plasma cell malignancy characterized by a collection of cytogenetic abnormalities that drive clinical presentation, response to treatment, and prognosis. The most common immunoglobulin heavy chain (IGH) translocation found in MM, t(11;14), results in CCND1 overexpression. Although t(11;14) is considered a standard risk cytogenetic abnormality, heterogeneity in patient outcomes and response to therapy within the t(11;14) group has been reported. In contrast to t(11;14) mantle cell lymphoma, where most cases (73%) have a typical, balanced t(11;14) rearrangement, only 47% of t(11;14) MM have a typical, balanced t(11;14) FISH pattern; the remaining 53% of MM are characterized by an atypical t(11;14) FISH result (Dalland, Genes Chromosomes Cancer, 2021). Here, we compared the genetic characteristics of typical vs. atypical t(11;14) MM and the association with other genomic abnormalities, CCND1 expression, IGH breakpoint location and patient outcomes. Methods: We performed a retrospective study of newly diagnosed t(11;14) MM patients seen at Mayo Clinic (N=411) or enrolled in the MMRF CoMMpass trial (N=167). The t(11;14) FISH results of the Mayo Clinic samples were segmented into two groups: typical CCND1/IGH signal pattern (n=179, 3 red, 3 green, 2 fusion signals) and atypical CCND1/IGH signal pattern (n=232, any FISH pattern deviating from typical). The CoMMpass cases had both RNAseq and long-insert WGS data and were analyzed to detect gene expression, structural and copy number variants and IGH breakpoint locations. These data were used to classify the t(11;14) as typical (n=63) or atypical (n=104) and whether there was a single t(11;14) fusion (n=107) or a gain of the t(11;14) fusion (n=60), and whether these cases were associated with changes in gene expression or breakpoint location. Differences between the groups were measured using χ2 and Wilcoxon tests. Survival curves were estimated using Kaplan Meier and compared using the Log-Rank test. Statistical significance was determined at p&lt;0.05. Results: Of the Mayo t(11;14) cohort, 232/411 (56%) had an atypical t(11;14) FISH pattern and 179/411 (44%) had a typical t(11;14) FISH pattern. Although an atypical t(11;14) FISH pattern was not significantly associated with monosomy 17/17p deletion, MYC rearrangements, 1q gain or ISS stage III, it was significantly associated with the presence of any trisomy in comparison to typical t(11;14) cases (40/222=18% vs.12/166=7%, p=0.002). Atypical t(11;14) cases had an increase in CCND1 gene expression compared to typical t(11;14) cases (median 375.0 RPKM vs. 266.4 RPKM, p&lt;0.0001) and cases with a gain of the t(11;14) fusion were associated with even greater CCND1 expression compared to cases with a single t(11;14) fusion (median 459.4 RPKM vs. 263.2 RPKM, p&lt;0.0001). We next evaluated whether the t(11:14) FISH pattern was associated with differences in IGH breakpoint locations. Nearly 80.0% of atypical t(11;14) cases had a breakpoint within the constant region of the IGH locus commonly reported for MM, while only 61.0% of the typical cases had constant region breakpoints (p=0.035); the remaining cases had breakpoints involving the VDJ region. We next evaluated the impact of atypical t(11;14) FISH on OS. In Mayo cases, OS was significantly shorter in patients with atypical FISH patterns compared to typical t(11;14) FISH patterns (6.9 years [95% CI: 5.1-7.8] vs. 9.0 years [95% CI: 7.0-11.6], p=0.019). Although atypical t(11;14) was associated with increased risk of death (RR 1.45, p=0.021), this finding was not retained in a multivariate model including high risk abnormalities such as age, ISS stage, 17p deletion and 1q gain demonstrating atypical t(11;14) is not an independent predictor of poor outcome when treated with standard therapies. Conclusions: Atypical t(11;14) FISH in MM is found in approximately half of t(11;14) cases, is associated with trisomies, higher CCND1 expression and is more likely to have a breakpoint involving the constant region of the IGH locus. The enrichment of VDJ breakpoints within typical t(11;14) MM is consistent with enrichment of VDJ IGH breakpoints in MCL, which are mostly characterized by typical t(11;14) FISH patterns. While not an independent predictor of outcome with standard therapies, it remains to be evaluated whether patients with typical or atypical t(11;14) have a differential response to novel agents, such as venetoclax. Disclosures Fonseca: Janssen: Consultancy; Novartis: Consultancy; Pharmacyclics: Consultancy; Sanofi: Consultancy; Merck: Consultancy; Juno: Consultancy; Caris Life Sciences: Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy; Aduro: Consultancy; OncoTracker: Consultancy, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy; AbbVie: Consultancy; Patent: Prognosticaton of myeloma via FISH: Patents & Royalties; Mayo Clinic in Arizona: Current Employment; Amgen: Consultancy; BMS: Consultancy; Celgene: Consultancy; Takeda: Consultancy; Bayer: Consultancy; Scientific Advisory Board: Adaptive Biotechnologies: Membership on an entity's Board of Directors or advisory committees. Bergsagel: Pfizer: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; GSK: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Genetech: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse. Kumar: Merck: Research Funding; Carsgen: Research Funding; Roche-Genentech: Consultancy, Research Funding; Beigene: Consultancy; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Antengene: Consultancy, Honoraria; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Sanofi: Research Funding.