ALBERT

Description: Introduction: Multiple myeloma (MM) is a plasma cell neoplasm associated with heterogeneous somatic alterations. Despite the development of novel anti-myeloma agents that have significantly prolonged patient survival, disease relapse remains a daunting problem. Our goal was to employ whole-exome sequencing (WES) to better describe the mutational landscape in MM beyond the tumor cell and identify genomic factors that might predict relapse. WES was performed using autograft samples obtained from MM patients that were then treated with high dose melphalan and autologous hematopoietic cell transplant (HCT). We identified a panel of genes that were most frequently mutated in all patients and then identified those genes mutated with greater frequency in patients that relapsed. A relapse burden signature was generated based upon the genes that were most frequently mutated genes in relapsed patients. Finally, the relapse burden signature was correlated with patient progression-free survival (PFS) and overall survival (OS) following autologous HCT. Methods. DNA was extracted from one ml of cryopreserved, mobilized hematopoietic cell product obtained from patients (N=93) that underwent HCT and was provided by the Case Comprehensive Cancer Center Hematopoietic Biorepository Core. Targeted sequencing was performed using the Tempus xE whole exome platform (Tempus, Chicago, IL). Variants were identified using a variant allele frequency (VAF) ≥0.1 for each sample. Variants were tabulated for each gene in each patient. Patients were grouped according to their relapse status; "No Relapse" (N=39) and "Relapse" (N=54) which corresponded to their post-HCT outcome. Relapse time was defined as time from transplant to event. Variants identified in each gene and patient group were counted and ranked. A relapse burden signature was defined and included twenty-two genes over-represented in the relapse group compared to the non-relapse group by 〉 10%. Genes in the relapse burden signature were subjected to gene set enrichment analysis (GSEA) and cross referenced against Gene Ontology (GO) categories. PFS and OS were defined as the time from transplant until the event of interest, with censoring at time of last follow up. Patients were regrouped according to their mutation burden in the relapse signature genes ("High burden" defined as 〉=six signature genes with variants) and their OS and PFS were analyzed with an R package (survival) to generate Kaplan-Meier curves and statistical significance based on a Chi-square test between low and high burden patients. Results: In total, 3,523 genes were identified as containing variants. Table 1 lists the top thirty genes that were identified and ranked based upon total number of mutations (mutational count) and most frequently mutated in relapsed and non-relapsed patients (sample count). We then identified those genes that were more frequently mutated by at least 10% in relapsed patients compared to non-relapsed patients (Fig. 1A). GSEA revealed that the relapse burden gene signature was associated with protein O-linked glycosylation, glycan processing, Golgi lumen and innate immune response activating cell surface receptor signaling pathways (Table 2). Interestingly, multiple mucin family members (Muc2, Muc3A, Muc12 and Muc19) were represented in the relapse burden signature. GO analysis indicated that the individual mucin genes were associated with the same signaling pathways that had been associated with the relapse burden signature by GSEA (Table 3). Importantly, a high relapse burden signature was correlated with a statistically significant reduction in both PFS and OS (Fig. 1B, C). Conclusion: Taken together, our results support the feasibility of WES to generate a relapse burden signature that predicts the risk of MM patients for relapse following HCT. Moreover, the mutational landscape associated with relapse, i.e. the specific genes mutated, has provided insights on the mechanisms of relapse. It is noteworthy that the relapse burden signature genes identified here were mutated at a much greater frequency than genes associated with clonal hematopoiesis of indeterminate potential (CHIP). The identification of patient subgroups at heightened risk of relapse can better guide treatment decisions. Future studies will be conducted to evaluate the effect of pathways identified here on myeloma cell survival and to validate actionable therapeutic targets. Disclosures Malek: Bluespark: Research Funding; Takeda: Other: Advisory board , Speakers Bureau; Medpacto: Research Funding; Janssen: Other: Advisory board, Speakers Bureau; Sanofi: Other: Advisory board; Clegene: Other: Advisory board , Speakers Bureau; Amgen: Honoraria; Cumberland: Research Funding. Caimi:Amgen: Other: Advisory Board; Bayer: Other: Advisory Board; Verastem: Other: Advisory Board; Kite pharmaceuticals: Other: Advisory Board; Celgene: Speakers Bureau; ADC therapeutics: Other: Advisory Board, Research Funding. de Lima:Celgene: Research Funding; BMS: Other: Personal Fees, advisory board; Incyte: Other: Personal Fees, advisory board; Kadmon: Other: Personal Fees, Advisory board; Pfizer: Other: Personal fees, advisory board, Research Funding.

Description: Background High dose chemotherapy followed by autologous stem cell transplantation (ASCT) plays an important role in the treatment of transplant-eligible multiple myeloma (MM) patients and yields deep responses, prolongs progression-free survival (PFS) and overall survival (OS). Daratumumab (Dara), a humanized monoclonal antibody that binds to CD38+ on the surface of myeloma cells and is increasingly used upfront to treat MM. Up to 75% of mobilized CD34+ hematopoietic progenitors also express CD38 and, hence exposure to Dara may potentially impact stem cell mobilization, and, given the extended half-life of Dara, also impair engraftment. The Cassiopeia trial (Moreau, P. 2019) showed the utility of Dara in combination with bortezomib and thalidomide as upfront treatment for MM without a negative impact on stem cell collection yield. Similarly, the Griffin trial (Voorhees, PM, 2020) demonstrated the safety of upfront Dara when combined with bortezomib and lenalidomide also with no impact on stem cell collection or engraftment. However, others(Al Saleh, A. 2019) reported delayed neutrophil engraftment in patients treated with Dara. Given the conflicting findings of these studies and scarcity of data on the direct impact of Dara on erythroid and myeloid progenitors, we investigated the effect of Dara on stem cell collection yield, graft composition and time to engraftment among patients who underwent ASCT. Methods We evaluated all patients with MM who underwent ASCT at our institute between 2017-2020 and excluded patients undergoing 2nd transplant or tandem ASCT. Disease risk stratification was assessed as per International Staging System (ISS) for MM. Treatment response prior to transplant was assessed as per response criteria definitions by International Myeloma Working Group (IMWG). Stem cells were collected according to institutional protocol and prior to cryopreservation, 1x105 peripheral blood cells are plated in duplicate in semi-solid media- MethoCult™ H4434 (Stem Cell Technologies, Vancouver, BC) and cultured in 37°C, 5% CO2 following which CFU-GM (colony forming unit- granulocyte macrophage) and BFU-E (burst forming units- erythroid) colonies are scored on day 14 based on morphological recognition, and reported as 104 colonies per kg of recipient weight. CFU-C (colony forming unit combined) is calculated by combining BFU-E and CFU-GM. Results Patients (N=108) that underwent ASCT between 2017-2020 were identified and demographic data are summarized (Table 1). Sixteen patients received Dara as part of upfront treatment prior to stem cell collection. Median age was 62 years old for the entire group with no significant age difference between patients who received Dara vs. those who did not receive. Similarly, there was no difference in race, ISS stage, pre-transplant response, plerixafor or lenalidomide use between the groups. Pts who received Dara were more likely to have received more than one chemotherapy regimen prior to transplant (62.5% vs. 30%, p-value=0.014). Although, total and day 1 collection of CD34+ stem cells was lower in the Dara treated group (7.18 x 106/kg) compared to Dara untreated (8.78 x 106/kg), the difference was not statistically significant. (p-value=0.151). Stem cell product composition based on measurement of BFU-E, CFU-GM and CFU-C colonies were similar independent of Dara use. Prior exposure to Dara was also not predictive of day 1 stem cell collection failure (defined as 〈 5x106 CD34+ cells/kg) as determined by multivariate analysis. Median time to absolute neutrophil count (ANC) recovery (defined as ANC 〉1500) was 12 days in both groups (p-value=0.09). Median time to platelet recovery (defined as platelet count 〉20k) was 12 days in the Darauntreated group vs. 13 days Dara treated group (p-value=0.06). Discussion In this single institute experience, there was a trend towards lower CD34+ collection as well as lower progenitor scoring with Dara use but was not statistically significant and also there was no difference in time to ANC or platelet recovery. The majority of patients in this study received plerixafor for mobilization, which might abrogate the effect of Dara and lenalidomide on the graft and stem cell collection. Further studies to investigate the impact of Dara on CD38+ mobilized hematopoietic cells is warranted. Disclosures Manjappa: Pfizer: Research Funding. Caimi:Amgen: Other: Advisory Board; Bayer: Other: Advisory Board; Verastem: Other: Advisory Board; Celgene: Speakers Bureau; Kite pharmaceuticals: Other: Advisory Board; ADC therapeutics: Other: Advisory Board, Research Funding. de Lima:BMS: Other: Personal Fees, advisory board; Incyte: Other: Personal Fees, advisory board; Kadmon: Other: Personal Fees, Advisory board; Celgene: Research Funding; Pfizer: Other: Personal fees, advisory board, Research Funding. Malek:Clegene: Other: Advisory board , Speakers Bureau; Janssen: Other: Advisory board, Speakers Bureau; Sanofi: Other: Advisory board; Amgen: Honoraria; Medpacto: Research Funding; Cumberland: Research Funding; Bluespark: Research Funding; Takeda: Other: Advisory board , Speakers Bureau.

Description: Randomized clinical trials (RCT) are imperative for testing novel cancer therapies and advancing the science of cancer care. Exclusion criteria are employed to minimize toxicity and maximize benefit. However, the selection process introduces a deviation between enrolled patients (pts) and the real world population. Estimating how much the selected population deviates from the MM cohort at large may increase inclusiveness and could help define barriers to recruiting to MM studies. There has been significant advancement in treating Multiple Myeloma (MM) during the last decade. Over 16 FDA-approved anti-myeloma regimens are now available. We selected the recent 6 RCTs (ASPIRE, TOURMALNE-MM01, ELOQUENT-2, ENDEAVOR, POLLUX and CASTOR studies) which were pharma-sponsored landmark trials that provided the basis for FDA approval of a new agent or established a new indication for formerly FDA-approved drug. We intended to quantify the gap between the trial population and real world by examining the eligibility criteria of these trials compared against a single institution database. Methods: Pts with relapsed MM initiating second or later line of therapy containing lenalidomide (Len) or bortezomib (Bor) were identified retrospectively. The 3-week period before the index treatment date was used to apply the eligibility criteria of the mentioned 6 trials. Pts who received Len-containing regimens were tested as to be enrolled on trials with Len/Dex control arm (ASPIRE, TOURMALINE-MM1, POLLUX, and ELOQUENT-2) and pts who had Bor-containing regimens were reviewed to be enrolled on Bor/Dex trials (CASTOR and ENDEAVOR). Pts were classified as "Trial eligible" or "Trial ineligible", accordingly. Pts were followed up longitudinally from the index treatment date until death, loss to follow-up, or the end of the study period (Jan, 2018). Ten frequently used eligibility criteria were studied (Fig-1). History of other malignancies, except skin and prostate cancer, was defined as any cancer requiring therapy other than anti-myeloma regimen in the 3 years prior to the index treatment date. Current infection referred to the use of any medication other than acyclovir, ciprofloxacin or Bactrim. Shoelace algorithm was used to calculate area under the curve of the polygon graphs. Results: 516 pts were studied between 2010 and 2018; 153 pts were excluded due to missing values, while 224 and 136 pts were treated with Len-containing and Bor-containing regimens, respectively. Overall, the trial-eligible cohort was more likely to have autologous stem cell transplant and to have had longer treatment-free period before index treatment date (p-value: 0.012). There was a substantial variation in the ineligibility rate for these 6 RCTs among the study population (Fig-1). The most common items that excluded a patient from a RCT were: Other malignancies, current infection and renal dysfunction. Within the Len cohort the trial-specific Glomerular Filtration Rate (GFR) threshold for renal function was highest in ASPIRE trial (Cr clearance〉 50 ml/min) causing high rate of exclusion (29% vs. 8% in other trials). Only TOURMOULINE-MM01 and ASPIRE trials had bor-refractory status as the exclusion criteria leading to 36% ineligibility rate. The differences between the trial-eligible and trial-ineligible pts stratified by trial are listed in Table-1 and 2 for trials with Len and Bor as the control arms, respectively. The median follow-up for the Len and Bor cohort was 31 and 30 months, respectively. The trial-ineligible pts had significantly worse OS (2-year survival rate 69% vs. 82%, P-value: 0.001) and 43% higher chance of death (hazard ratio 1.43, 90% confidence interval (CI): 1.08-2.02) compared with trail-eligible cohort. Conclusion: Here we assessed the eligibility criteria of 6 landmark MM studies and showed that ineligibility rates were quite different amongst these trials suggesting significant limitations in cross-trial comparison. Furthermore, trial-eligibility per se was associated with improved survival. We therefore proposed a quantitative deviation score calibrating the generalizability of the results of these trials to a single institution cohort. Such a tool can lead to efforts to broaden eligibility criteria and possibly narrow the gap between reported clinical trial efficacy and the observed effectiveness in real-world MM pts. Disclosures de Lima: Kadmon: Other: Personal Fees, Advisory board; Incyte: Other: Personal Fees, advisory board; BMS: Other: Personal Fees, advisory board; Celgene: Research Funding; Pfizer: Other: Personal fees, advisory board, Research Funding. Malek:Medpacto: Research Funding; Takeda: Other: Advisory board , Speakers Bureau; Bluespark: Research Funding; Cumberland: Research Funding; Sanofi: Other: Advisory board; Janssen: Other: Advisory board, Speakers Bureau; Clegene: Other: Advisory board , Speakers Bureau; Amgen: Honoraria.

Description: Introduction: Immunomodulatory drugs (IMiDs) are being frequently used as an integral part of induction regimen as well as maintenance after Bone Marrow Stem cell Transplant (BMSCT) therapy as backbone of therapy for patients with plasma cell neoplasm (PCN) including Multiple Myeloma (MM). Therapy is often complicated by dermatologic adverse effects which may herald a favorable prognosis suggesting a more robust immune stimulation by this class of drugs. The incidence of IMiD-associated rash is up to 27% in some reports and can range from mild to moderate to severe and life threatening skin toxicity including Steven-Johnsons syndrome and toxic epidermal necrolysis. IMiD-associated skin eruptions are thought to result from differential T cell immune modulation. The optimal management strategy for IMiD induced rash is unknown. The European Myeloma Network recommends topical corticosteroids and antihistamines for localized skin reactions. For severe reactions, a desensitization protocol with prolonged 6-week steroid taper is recommended based on a case series of five patients that developed delayed cutaneous adverse effects to IMiD [Lee MJ et al]. Dexamethasone used concomitantly with IMiD as part of the treatment regimen does not decrease the occurrence of skin rash as shown by Sviggum et al. The likely explanation is that concurrent dexamethasone is not effectively able to exert immunosuppressive activity to mitigate the occurrence of cutaneous reactions. Hence, a prolonged, daily steroid protocol is required for effective desensitization. Therefore, we designed a standardized 3-week steroid rash prophylaxis protocol with a low dose daily corticosteroid tapering regimen that allows desensitization and reinstitution of the same IMiD. We assessed the impact of this desensitization regimen on clinical outcomes, by comparing patients with versus without dermatologic manifestations. Methods: Dermatologic adverse effects associated with IMiDs in our study were managed by a single oncologist using a standardized approach. A total of 87 patients were evaluated, 24 patients in the rash group vs 63 controls. A cohort of age- and gender-matched without rash (n = 63) was randomly selected from the institutional database. The effects of rash on overall and progression free survival (OS and PFS) were further estimated using Cox regression controlling for the effects of age and gender. Results: Median time to development of rash after IMiD initiation was 28 days (range 2-232 days). The incidence of rash was 27.6% (95% CI: 19.3%-37.8%). All patients were managed by temporary treatment interruption and upon clearance of rash, re-institution of the same IMiD concomitantly with a standardized 3-week steroid rash prophylaxis protocol (prednisone at 10 mg daily for 10 days, followed by 5 mg daily for 10 days, followed by 5 mg on alternate days for 10 days). As a result, all patients were able to restart the same IMiD with none re-experiencing any dermatologic adverse effect afterward. Comparing to controls without rash, there was no significant difference in PFS (p=0.769) or OS (p=0.24) in the multivariable regression model. Conclusions: Proposed 3-week corticosteroid regimen showed 100% success rate in re-instituting IMiDs without recurrence of skin rashes in our cohort. The results of our study indicate that the 30-day prednisone course is practical, well tolerated, effectively desensitizes and allows re-institution of IMiD enabling patients to enjoy comparable outcomes to those without skin rash. Whether development of rash correlates with improved outcomes is unknown. Here, outcomes were similar in both cohorts. Disclosures Caimi: Celgene Corp: Other: Incyte Corporation - Ownership - Pharmacyclics, Inc. - Ownership - Celgene Corp. - Other, Speakers Bureau; ADC Therapeutics: Research Funding; Genentech: Research Funding. de Lima:BMS: Other: Personal Fees, advisory board; Celgene: Research Funding; Pfizer: Other: Personal fees, advisory board, Research Funding; Incyte: Other: Personal Fees, advisory board; Kadmon: Other: Personal Fees, Advisory board. Malek:Bluespark: Research Funding; Takeda: Other: Advisory board , Speakers Bureau; Medpacto: Research Funding; Cumberland: Research Funding; Amgen: Honoraria; Clegene: Other: Advisory board , Speakers Bureau; Sanofi: Other: Advisory board; Janssen: Other: Advisory board, Speakers Bureau.

Description: Multiple Myeloma (MM) is a cancer of terminally-differentiated plasma cells residing in the bone marrow. Myeloma cells frequently secrete monoclonal proteins that can be used to assess tumor volume and patient response to therapy. Monoclonal proteins are measured by gel electrophoresis and subsequent immunofixation of the observed M-spike for protein typing. However, this a time-consuming process that may take up to 3-5 days that delays physician-patient decision-making, determining response to treatment and can be a significant psychological stressor for patients. Hence, there is an unmet need to develop a more rapid, point-of-care method to determine M-spike levels. Gamma gap is the difference between total serum protein and albumin and includes a variety metabolic proteins, i.e., transferrin, as well as immunologic proteins, e.g., non-involved immunoglobulins, in addition to the M-spike. Since estimation of the non-M-spike portion of the gamma gap cannot be achieved on routine patient care, the gamma gap cannot serve as an accurate surrogate for M-spike protein levels. Here, we hypothesized that an artificial intelligence (AI) algorithm utilizing readily available clinical and laboratory data along with previous and same-day lab variables can accurately predict M-spike levels without the need for serum electrophoresis. Methods: A total of 171 MM patients with 1,472 observations were included in the study, where the upper limit of the observed M-spike was 3.5 gr/dL. Correlation of the observed M-spike with gamma gap was assessed by two correlation methods using the Pearson and Spearman tests. Forty three clinical and lab variables (including total serum protein and albumin) as predictors of M-spike were fed into the machine learning model. Two lagged variables as the last two preceding M-spike values by the same subject were included. When needed, imputation for missing values was applied through interpolation from subject-level linear trend analysis. The random forest model was used, where regression forests are an ensemble of different regression trees and are used for nonlinear multiple regression. The default number of trees was set to be n = 500, and the number of variables considered at each split after random selection was 13. The goal of using a large number of trees was to train enough that each feature had a chance to appear in several models. The data was randomly split into a training set (80%) and a test set (20%), and a regression tree was built with the training set and then validated using the test set. Bootstrapping was used to generate a collection of data sets (n=500), leading to a random forest of regression trees. Results and estimates were combined across trees. Importance was measured by leaving a covariate out of models, and comparing performance with its inclusion. All analyses were performed using R v3.6.2 and its libraries. Results: Median age of the study cohort was 73 years old, range: 42-96), and 44% were male. The median M-spike value was (0.7 gr/dL, range: 0.1-3.5). Fig. 1 shows the number of observations and magnitude distribution for M-spike levels among the patients included in our study. The correlation of the calculated gamma gap and observed M-spike levels was assessed by two methods (Fig.2). The Pearson coefficient was 0.43 for M-spike levels 1 gr/dL, respectively (Fig.2a). The Spearman coefficient was 0.41 for M-spike levels 1 suggesting a low overall correlation overall, especially for M-spike levels

Description: Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant, clonal plasma cell disorder, characterized by the presence of a monoclonal (M) protein in serum,