Kumar, Shaji

Although oncology care has evolved, outcome assessment remains a key challenge. Outcome measurement requires identification and adoption of a succinct list of metrics indicative of high-quality cancer care for use within and across healthcare systems. NCCN established an advisory committee, the NCCN Quality and Outcomes Committee, consisting of provider experts from NCCN Member Institutions and other stakeholders, including payers and patient advocacy, community oncology, and health information technology representatives, to review the existing quality landscape and identify contemporary, relevant cancer quality and outcomes measures by reevaluating validated measures for endorsement and proposing new measure concepts to fill crucial gaps. This manuscript reports on 22 measures and concepts; 15 that align with existing measures and 7 that are new.

AbstractThe diagnosis of primary plasma cell leukemia (pPCL) has been made by quantifying circulating plasma cells (cPCs) morphologically on a peripheral blood (PB) smear. However, this technique is not sufficiently sensitive. Multiparametric flow cytometry (MFC) provides a readily available and highly sensitive method to identify and quantify cPCs that could complement PB smear assessment. However, an optimal quantitative cutoff for cPCs by MFC to identify pPCL has not been established. Thus, a total of 591 patients newly diagnosed multiple myeloma (NDMM) patients who had their PB samples evaluated morphologically by PB smear, and immunophenotypically by MFC prior to beginning therapy were evaluated. The presence of ≥200 cPCs/μL by MFC (N = 25 or 5% of the total population) was chosen to identify patients with ≥5% cPCs by PB smear with a specificity of 99% and a sensitivity of 77%. For patients with ≥200 cPCs/μL by MFC compared to the remainder of the cohort, the median Time to next therapy (TTNT) was 18 vs 30 months and the median OS was 38 vs 70 months respectively. Thus, MFC assessment of PB can be utilized in conjunction with the morphological assessment of a PB smear to aid in improving the identification of pPCL among NDMM patients.

Abstract The most common genetic abnormality in multiple myeloma is the deletion of chromosome 13, seen in almost half of newly diagnosed patients. Unlike chronic lymphocytic leukemia, where a recurrent minimally deleted region including MIR15A/MIR16-1 has been mapped, the deletions in multiple myeloma predominantly involve the entire chromosome and no specific driver gene has been identified. Additional candidate loci include RB1 and DIS3, but while biallelic deletion of RB1 is associated with disease progression, DIS3 is a common essential gene and complete inactivation is not observed. The Vk*MYC transgenic mouse model of multiple myeloma spontaneously acquires del(14), syntenic to human chromosome 13, and Rb1 complete inactivation, but not Dis3 mutations. Taking advantage of this model, we explored the role in multiple myeloma initiation and progression of two candidate loci on chromosome 13: RB1 and MIR15A/MIR16-1. Monoallelic deletion of Mir15a/Mir16-1, but not Rb1, was sufficient to accelerate the development of monoclonal gammopathy in wild-type mice and the progression of multiple myeloma in Vk*MYC mice, resulting in increased expression of Mir15a/Mir16-1 target genes and plasma cell proliferation, which was similarly observed in patients with multiple myeloma. Significance: In the absence of a defined, minimally deleted region the significance of del(13) in multiple myeloma has remained controversial. Here we show that haploinsufficiency of Mir15a/Mir16-1, but not Rb1, upregulates the cell cycle–regulatory network, inducing monoclonal gammopathy in mice and promoting multiple myeloma progression in both mice and men. See related commentary by Walker, p. 16. This article is highlighted in the In This Issue feature, p. 5

SummaryWe sought to dissect the tumour microenvironment in a small cohort (N = 10) of patients with POEMS at diagnosis and after therapy using mass cytometry. We included 10 MGUS patients as controls. We identified 29 immune cell subsets in the CD45+ and CD3+ compartments. Double positive T cells and PD‐1 positive CD4 T cells were expanded and naïve CD4 T cells were decreased in the bone marrow of patients with newly diagnosed/progressing POEMS. These findings provide evidence for possible antigenic‐driven selection as a driver of disease pathogenesis in POEMS.

SummarymiR‐1258 is localised to the first intron of ZNF385B at chromosome 2q31.3. miR‐1258 promoter methylation was studied in 147 samples including 10 normal buffy coat, eight normal bone marrow plasma cells, 16 human myeloma cell lines (HMCLs), 20 MGUS, 63 diagnostic myeloma, and 30 relapsed myeloma samples by methylation‐specific PCR. In myeloma lines, miR‐1258 methylation, verified by pyrosequencing, was detected in 62·5% HMCLs but not normal controls, and expression of miR‐1258 correlated with that of ZNF385B. 5‐Aza‐2′‐deoxycytidine resulted in promoter demethylation and ZNF385B/miR‐1258 re‐expression. Luciferase assay confirmed programmed cell death ligand‐1 (PDL1) as a direct target of miR‐1258. Over‐expression of miR‐1258 in completely methylated myeloma cells led to reduced cellular proliferation and enhanced apoptosis, hence a tumour suppressor role, in addition to repression of PDL1. In primary samples, miR‐1258 methylation, with lower expression of miR‐1258, was detected in 49·2% diagnostic myeloma, imparting an inferior PFS (P = 0·034) in addition to 50·0% relapsed myeloma but not MGUS. Therefore, miR‐1258 is a tumour suppressor miRNA co‐regulated with its host gene, and frequently hypermethylated in active myeloma instead of MGUS, hence acquired during myeloma progression. Methylation‐mediated miR‐1258 silencing led to overexpression of PDL1 and inferior PFS, implicating miR‐1258 in the modulation of myeloma‐specific cytotoxicity.

Background: Novel agent induction and AHCT remains the preferred initial therapeutic strategy for transplant-eligible MM patients. Current prognostic tools in MM focus solely on disease-specific factors at diagnosis to determine patient prognosis-International Staging System (ISS) and revised-ISS (R-ISS). A major limitation to both, the ISS and R-ISS, is that they are not specific for HCT-eligible patients and do not take into account other patient factors that may enter into a decision to pursue AHCT. The data used to generate these staging systems were from broad populations with varying upfront treatment strategies and included patients who were ineligible for intensive therapy. Additionally, there is considerable interest in identifying the population that relapses early despite modern induction/AHCT approaches who are candidates for novel approaches for maintenance/consolidation. To address these problems, we used data from the Center for Blood and Marrow Transplant Research (CIBMTR) registry to identify disease-, patient-, and transplantation-specific variables that are associated with progression-free survival (PFS) in patients undergoing upfront AHCT (within 12 months of diagnosis). Methods: We used the outcomes of 2528 MM patients undergoing upfront AHCT from 2008-2017 reported to the CIBMTR. Patients were divided into training and validation sets with a 50% random split. High risk cytogenetics was defined as the presence of one or more of the following: t(4;14), t (14;16), t (14;20), del 13q, del 17p, 1q gain, or 1p deletion. We used a Cox multivariable model to identify factors prognostic of progression free survival (PFS) in a training subset. The regression coefficients of the final model was transformed into a risk score with an appropriate transformation. A weighted score using these factors was assigned to the training cohort (n = 917) and validation cohort (n=897) using subset that had all values that entered the final model. Kaplan-Meier estimates of the individual scores were used to classify patients into risk groups for both cohorts. Results: Baseline characteristics of these patients are shown in Table 1. No cytogenetic abnormality, VRD induction, pre-AHCT bone marrow plasma cells (BMPCs) <10% and 1 line of induction chemotherapy were assigned 0 points. Pre-AHCT BMPCs ≥10% (hazard ratio HR, 1.47; 95% CI, 1.19-1.83), use of ≥2 lines of induction chemotherapy prior to AHCT (HR 1.32; 95% CI 1.06-1.64), standard cytogenetic risk vs. no abnormality (HR 1.41; 95% CI 1.13-1.77) and induction regimens (non-VRD regimens vs. VRD) (HR 1.4, 95% CI 1.17-1.74) were associated with increased hazard of progression and assigned 1 point in the scoring system. Presence of high-risk cytogenetics vs. no abnormality (HR 1.87; 95% CI 1.45-2.42) was assigned 2 points, and the use of thalidomide and dexamethasone (TD) as an induction regimen (HR 2.19; 95% CI 1.48-3.2) was assigned 3 points. A two-category system was created based on the scoring: low risk (0-3) and high risk (4-6). The scoring system was prognostic for PFS when applied to both cohorts. High-risk group was found to have significantly higher risk of progression and/or death compared to low risk in training (HR 2.2; 95% CI 1.74-2.86; p<0.0001) and validation cohort (HR 1.7, 95% CI 1.30-2.22; p=0.0001) respectively (Table 2). The 3-year PFS in the training cohort was 60% (95% CI 56%-64%) in low risk and 27% (95% CI 17%- 36%) in high risk while in the validation cohort was 51% (95% CI 47%-55%) in low risk and 28% (95% CI 16%- 39%) in high risk (Figure 1A and 1B). Conclusions: We describe a prognostic model specifically for patients undergoing upfront AHCT in MM which can identify patients at very high risk for early relapse/progression. These patients should be ideal candidates for studies of immunotherapy or other interventions after AHCT aimed at reducing relapse. Disclosures Dhakal: Sanofi: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria; Takeda: Membership on an entity's Board of Directors or advisory committees. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding. Shah:Genentech, Seattle Genetics, Oncopeptides, Karoypharm, Surface Oncology, Precision biosciences GSK, Nektar, Amgen, Indapta Therapeutics, Sanofi: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: 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; Nkarta: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees; Teneobio: Consultancy, Membership on an entity's Board of Directors or advisory committees; University of California, San Francisco: Employment; Poseida: Research Funding; Indapta Therapeutics: Equity Ownership; Celgene, Janssen, Bluebird Bio, Sutro Biopharma: Research Funding. Qazilbash:Amgen: Consultancy, Other: Advisory Board; Autolus: Consultancy; Bioclinical: Consultancy; Genzyme: Other: Speaker. D'Souza:EDO-Mundapharma, Merck, Prothena, Sanofi, TeneoBio: Research Funding; Prothena: Consultancy; Pfizer, Imbrium, Akcea: Membership on an entity's Board of Directors or advisory committees. Hari:AbbVie: Consultancy, Honoraria; Cell Vault: Equity Ownership; Sanofi: Honoraria, Research Funding; Spectrum: Consultancy, Research Funding; Amgen: Research Funding; Kite: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; BMS: Consultancy, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding.

Background: Autologous hematopoietic cell transplantation (AHCT) is an effective treatment to achieve deep and durable remission in multiple myeloma (MM). Typically, AHCT is offered to patients <70 years of age, although the median age of diagnosis of MM is 70 years. We compared the outcomes of upfront AHCT across age groups for newly diagnosed MM in the era of novel therapies using the Center for International Blood and Marrow Transplant Research (CIBMTR) database. Methods: We analyzed the outcomes of 15,999 MM patients aged 20 years and older from the USA who received a single AHCT with melphalan conditioning within 12 months of diagnosis between 2013 and 2017 and reported to the CIBMTR. Multivariate analysis was performed for non-relapse mortality (NRM), relapse/progression (REL), progression-free survival (PFS) and overall survival (OS) using Cox proportional hazards model with age at transplant in decades as the main effect. Hazard ratio (HR) with 95% confidence intervals (CI) are reported. Because of the large sample size, a p-value of <0.01 was considered significant a priori. Results: Table 1 shows patient, disease and treatment characteristics by age group at diagnosis. All age groups had similar distribution of gender, race, ethnicity, Karnofsky performance score (KPS), comorbidity index (HCT-CI), stage III by Durie-Salmon/International Staging System. There was a higher proportion of high-risk cytogenetics in patients ≥70 years (30%), compared to age group 40-49 years (24%) and 20-39 years (20%) in this population. Older patients were more likely to be White compared to younger patients: 85% ≥70 compared to 64% 20-39 years. While 82% of the overall population received melphalan 200 mg/m2, 58% of the ≥70% received Mel 140 mg/m2. There were more ASCT performed in the ≥70-year age group in 2017 (28%) compared to 2013 (15%). Univariate outcomes by age groups shown in Table 2 revealed that 100-day NRM was higher in ≥70 years at 1% compared to younger patients (p <0.01) and 2-year OS was lower in ≥70 years at 86 (85-88)% compared to 60-69 years, 89 (88-89)% (p<0.01). When adjusted for other variables (Table 3), compared to reference age group of 60-69 years, patients ≥70 had similar NRM (HR 1.3, 95% CI 1, 1.7, p 0.06), REL (HR 1.03, 95% CI 0.9, 1.1, p 0.6), PFS (HR 1.06, 95% CI 1, 1.2, p 0.2), and OS (HR 1.2, 95% CI 1, 1.4, p 0.02). The leading cause of death across all age groups was primary disease. Among the ≥70 years cohort, melphalan dose was a surrogate for worse outcomes including NRM at 100 days (Mel 140, 1 (1-2)% vs Mel 200 0 (0-1)%, p 0.003, PFS at 2 years Mel 140 64 (60-67)% vs Mel 200 69 (66-73)%, p 0.003, and OS at 2 years (Mel 140 85 (82-87)% vs Mel 200 89 (86-91)%, p 0.01) (Figure). Conclusions: This is the largest study of AHCT in older adults with MM. More MM patients ≥70 years are being transplanted in the US over time. While our data may highlight referral and access biases regarding which older patients may be referred for ASCT, our results confirm that patients ≥70 years can undergo transplant safely and achieve similar benefits as 60-69 years' old patients. Our results also suggest that melphalan 200 mg/m2 may be given safely in the ≥70 years population. While melphalan conditioning dose 140 mg/m2 in the ≥70 group is associated with worse outcomes, this is likely a surrogate for higher frailty and comorbidities in this cohort of patients. Our analysis confirms that AHCT has similar benefits in terms of disease control (REL and PFS) in both young and older MM patients. This benefit is seen even in a contemporaneous era where proteasome inhibitors and/or immunomodulator drugs are used in upfront treatment. Thus, AHCT remains a safe consolidation therapy across all age groups of MM patients. Disclosures Hari: Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Research Funding; Janssen: Consultancy, Honoraria; Kite: Consultancy, Honoraria; Amgen: Research Funding; Spectrum: Consultancy, Research Funding; Sanofi: Honoraria, Research Funding; Cell Vault: Equity Ownership; AbbVie: Consultancy, Honoraria. Kumar:Janssen: Consultancy, Research Funding; Takeda: Research Funding; Celgene: Consultancy, Research Funding. Shah:Poseida: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Nkarta: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene, Janssen, Bluebird Bio, Sutro Biopharma: Research Funding; University of California, San Francisco: Employment; Genentech, Seattle Genetics, Oncopeptides, Karoypharm, Surface Oncology, Precision biosciences GSK, Nektar, Amgen, Indapta Therapeutics, Sanofi: Membership on an entity's Board of Directors or advisory committees; Indapta Therapeutics: Equity Ownership; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Teneobio: Consultancy, Membership on an entity's Board of Directors or advisory committees. Qazilbash:Genzyme: Other: Speaker; Bioclinical: Consultancy; Amgen: Consultancy, Other: Advisory Board; Autolus: Consultancy. D'Souza:EDO-Mundapharma, Merck, Prothena, Sanofi, TeneoBio: Research Funding; Prothena: Consultancy; Pfizer, Imbrium, Akcea: Membership on an entity's Board of Directors or advisory committees.

Background Venetoclax (Ven) is a selective, small molecule inhibitor of anti-apoptosis protein Bcl-2 that has antitumoral activity against multiple myeloma (MM), notably those with translocation t(11;14). Dexamethasone (d) has shown to enhance the expression of BCL-2 and pro-apoptotic protein Bim, shifting its binding towards Bcl-2 and sensitizing MM cells to Ven. This Phase 1/2 open-label trial is evaluating the safety and efficacy of the combination of Ven+d as a therapeutic approach to improve clinical outcomes in patients with t(11;14) Relapsed/Refractory (R/R) MM. Methods This ongoing study (NCT01794520) has 2 distinct phases. Phase 1 (P1) consisted of separate dose escalation, safety expansion, and Ven+d combination cohorts. The phase 2 (P2) portion is an expansion cohort of Ven+d to further evaluate its efficacy. The safety and efficacy of the Ven+d cohorts from P1 and P2 are reported here. Eligible patients (pts) were adults with t(11;14) R/R MM ≥18 years of age. Key eligibility criteria for the Ven+d cohort in P1 included prior treatment with a proteasome inhibitor (PI) and an immunomodulatory drug (IMID), and an ECOG score ≤1. In P2, eligibility included an ECOG score ≤2, disease progression on or within 60 days from the last dose on previous treatment and having received at least two lines of therapy with a PI, IMID, daratumumab, and glucocorticoids. Additional inclusion criteria for both phases included measurable disease and adequate bone marrow function in all pts, and the presence of t(11;14) determined by fluorescence in-situ hybridization. In both phases, pts received oral Ven 800 mg/day + oral d 40 mg (20 mg for pts ≥75 years of age) on days 1, 8, and 15 of each 21-day cycle. In P1, preliminary efficacy was assessed as the overall response rate (ORR), time to progression (TTP), progression free survival (PFS), and duration of response (DOR) of Ven+d based on the 2011 International Uniform Response Criteria for MM. Efficacy in P2 further evaluated ORR, very good partial response (VGPR) or better, PFS, DOR, TTP, and overall survival (OS) using 2016 IMWG response criteria. Results In P1, as of 15thApril, 2019, 20 pts were enrolled (17 [85%] male; median age, 63 years [range, 46-77]). The median number of prior therapies received was 2.5 (range: 1-7). Nineteen pts (95%) discontinued the study (18 due to progressive disease and 1 underwent transplant). The treatment-emergent adverse events (TEAEs) are summarized in the Table. Most frequent TEAEs were insomnia (45%), hypophosphatemia (40%), hyperglycemia (35%), diarrhea (35%), and thrombocytopenia (30%). Predominant Grade 3 or 4 TEAEs included neutropenia (21%), lymphopenia (29%), and hypophosphatemia (20%). The most common serious TEAE was tumor lysis syndrome (TLS) (10%). No deaths were reported in the treatment-emergent period. ORR was achieved by 13 (65%) and ≥VGPR was achieved by 6 (30%) pts respectively. Partial response (PR) was observed in 7 (35%) pts and stable disease (SD) in 4 (20%) pts. Median time to first response was 1.4 mos (95% CI: 0.7, 2.8). The DOR was 13.1 mos (95% CI: 10.9, 21.9). Median PFS and TTP were both 12.4 mos (95% CI 3.6, 20.9). In P2, as of March 18, 2019, 31 pts were enrolled (18 [58%] male; median age, 65 years [range, 48-80]). The median number of prior therapies received were 5 (range: 1-9). Eight (26%) pts discontinued the study (6 deaths, 1 withdrew consent, 1 due to physician's decision). The most frequent TEAEs reported were diarrhea (32%), nausea (26%) and lymphopenia (32%). The most frequent Grade 3 or 4 TEAEs were lymphopenia (32%), thrombocytopenia (11%), and hypertension (10%). Most common serious TEAE was sepsis (10%). Six (19%) deaths were reported (5 due to progressive disease and 1 due to adverse event). In the intention to treat population, the median TTR was 0.7 mos (range: 0.6-1.5). ORR was achieved by 14 (45%) and >VGPR was observed in 8 (26%) pts. PR was observed in 6 (13%) pts and SD in 8 (26%) pts. Median PFS, DOR, and OS were not reached at the time of data analysis. The 9-mo estimates for PFS, DOR, and OS were 57% (95% CI: 19% 82%), 66% (95% CI: 16%, 91%), and 71% (95% CI: 44%, 87%) respectively. Conclusion In both phases of this study, Ven+d was efficacious and demonstrated tolerable safety in pts with t(11;14) R/R MM. These results support further investigation of Ven combinations in this pt population. This combination is also being investigated in the ongoing Phase 3 trial M13-494 (CANOVA) in t(11;14) positive R/R MM. Disclosures Kaufman: Takeda: Consultancy; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Bristol-Myers Squibb: Consultancy; Incyte: Consultancy; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria; AbbVie: Consultancy; Winship Cancer Institute of Emory University: Employment; Amgen: Consultancy; TG Therapeutics: Consultancy. Gasparetto:Celgene: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; Janssen: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; BMS: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed . Schjesvold:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; MSD: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; SkyliteDX: Honoraria. Moreau:Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Facon:Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees. Boise:Genentech Inc.: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria, Research Funding. Alzate:AbbVie Inc: Employment, Other: Stock/stock options. Macartney:AbbVie Inc: Employment, Other: Stock/stock options. Pesko:AbbVie: Employment, Other: Stock/stock options. Salem:AbbVie: Employment, Other: Stock/stock options. Ross:AbbVie: Employment, Other: Stock/stock options. Hong:Genentech Inc.: Employment, Equity Ownership; Roche: Equity Ownership. Maciag:AbbVie: Employment, Other: Stock/stock options. Pauff:AbbVie Inc: Employment, Other: may own stock or stock options. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding. OffLabel Disclosure: Venetoclax is a BCL-2 inhibitor that is FDA-approved in some indications. This presentation will focus on venetoclax for treatment in multiple myeloma, which is not an approved indication.

Introduction: With the expanding use of CAR-T cell therapy, which is associated with serious adverse effects (AEs), there is a need to characterize the patient's experience over time to guide patient/provider education, and help optimize symptom management. This study reports on longitudinal evaluation of patient-reported quality of life (QOL) and symptom burden of CAR-T cell therapy compared with established forms of cellular therapy i.e autologous stem cell transplant (autoSCT) and allogeneic SCT (alloSCT). Methods: Patients with hematologic malignancies were prospectively recruited in three cohorts: CAR-T, autoSCT and alloSCT. The primary endpoint was change in QOL from baseline, using the FACT-G questionnaire. Secondary endpoints were patient-reported AEs (PRO-AEs) using 7 items from the PRO-CTCAE and assessment of cognition/memory using the NeuroQOLv2 questionnaire. PRO-CTCAE data was graded using a composite score (combining frequency, severity, and interference) and rates, using a method adjusting for pre-existing baseline symptoms, were compared using Fisher's exact test. We also evaluated the time profile of PRO-AEs using the Toxicity over Time (ToxT) approach, a longitudinal approach to AE analysis (Thanarajasingam Lancet Onc 2016). Patients completed questionnaires at baseline, week 2 and monthly thereafter. Results: From 07/2018 to 06/2019, 93 patients were recruited (CAR-T: 20; autoSCT: 37; alloSCT: 36). At data cut-off, week 2 and months 1, 2 and 3 data were available in 74, 62, 46 and 35 patients, respectively. There was no difference in patient age across the 3 groups (median age 63, range 23-77; p=0.26). Baseline QOL by FACT-G total score (mean=83.4, SD=14.7; p=0.77), side effect bother by FACT-G GP5 (66/93 [71%] a little bit or less; p=0.72), activities and function (70/93 [75%] fairly normal activities or no limitations; p=0.68) and cognition by NeuroQOL t-score (mean=52.2, SD=8.13; p=0.39) were similar across 3 groups at baseline. The CAR-T group experienced significantly less worsening in QOL (FACT-G) than both autoSCT and alloSCT groups (Fig. 1a). Worsening in overall QOL nadired at week 2, after which QOL gradually returned to baseline in all groups. When comparing changes from baseline in overall QOL, statistically significant differences between groups were evident at week 2 (CAR-T vs autoSCT p<0.001; vs alloSCT p<0.001), month 1 (CAR-T vs autoSCT p=0.02; vs alloSCT p=0.003), month 2 (CAR-T vs autoSCT p=0.02; vs alloSCT p=0.001) and month 3 (CAR-T vs autoSCT p=NS; vs alloSCT p=0.03). Results for physical (Fig. 1b) and functional well-being (WB) were similar, with significantly less QOL worsening at week 2 in CAR-T vs autoSCT and alloSCT groups. The most common PRO-AEs (Table 1) in the CAR-T group were decreased appetite (59%), diarrhea (53%) and fatigue (44%). There was no statistically significant difference in the PRO-AEs between CAR-T and autoSCT groups. However, patients undergoing alloSCT had significantly higher proportion of PRO-AEs vs the CAR-T group, except for neuropathy and sad feelings. AutoSCT and alloSCT groups had significant worsening of FACT-G side effect bother (GP5) at week 2, which was significantly different from that of the CAR-T group, following which the side effect bother gradually returned to baseline. (Fig. 1c) This was the first application of ToxT to PRO-CTCAE data (graphs not shown). Bar charts of maximum grade frequency and stream plots of mean grade over time demonstrate that mouth sores, fatigue, diarrhea and decreased appetite peak at week 2 and improve by month 3, and are of lesser severity in the CAR-T vs autoSCT and alloSCT groups. The trajectory of maximum grade across all PRO-AEs was similar by group as overall side effect burden by FACT-G GP5. Heatmap visualization demonstrated significant intra-patient variability and allowed inspection of data completeness. No difference in cognition and memory was observed across the three groups over the first three months. (Fig. 1d) Conclusion: This study is the first to our knowledge to provide comprehensive PRO data comparing QOL, patient-reported AEs and cognition in CAR-T cell therapy vs. auto- and alloSCT, and the first application of ToxT to PRO-CTCAE data. Short-term QOL, including physical and functional WB domains was better in the CAR-T group vs. SCT groups. These data can serve as a guide for patient education and symptom management in CAR-T cell therapy. Co-senior authors: SKK & ACD Disclosures Paludo: Celgene: Research Funding; Celgene: Research Funding; Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding. Gertz:Johnson and Johnson: Speakers Bureau; Celgene: Consultancy; Appellis: Consultancy; Amyloidosis Foundation: Research Funding; DAVA oncology: Speakers Bureau; Physicians Education Resource: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Medscape: Consultancy, Speakers Bureau; Prothena Biosciences Inc: Consultancy; Teva: Speakers Bureau; Research to Practice: Consultancy; Annexon: Consultancy; Alnylam: Consultancy; International Waldenstrom Foundation: Research Funding; Ionis/Akcea: Consultancy; Spectrum: Consultancy, Research Funding; i3Health: Other: Development of educational programs and materials; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; Springer Publishing: Patents & Royalties. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Ansell:Trillium: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding. Bennani:Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Adicet Bio: Other: Advisory board; Adicet Bio: Other: Advisory board; Purdue Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Seattle Genetics: Other: Advisory board; Seattle Genetics: Other: Advisory board; Kite Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board; Kite Pharma: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

Introduction: Interferon regulatory factor 4 (IRF4) is a transcription factor involved in B cell activation and differentiation into plasma cells, as well as B-cell lineage neoplasia. Diverse genetic abnormalities and dysregulated expression of IRF4 have been documented in various hematologic malignancies, including multiple myeloma (MM). IRF4 is also identified as a major downstream target of CRBN/IKZF to regulate MYC expression, representing a primary mechanism underlying anti-MM action of IMiDs. However, it remains unclear how the expression and function of IRF4 are regulated in MM cells. Materials and Methods: DNAseq, whole exome RNAseq (WES), and label-free analyses of quantitative proteomics and post-translational modifications (PTMs) mapping were conducted to examine genetic aberrations, transcriptional dysregulation, or protein and PTM alterations in primary patient samples and drug-naive vs -resistant cell lines. Flow cytometry, qPCR, and Western blot analysis were utilized to monitor apoptosis or mRNA and protein levels of target genes. Stable transfection with wild-type or mutated IRF4 was carried out to evaluate its function. Analysis of the MM genome-wide GEP databases (R2: Genomics Analysis and Visualization Platform) was performed to validate the clinical significance of IRF4 and its target genes in MM patients. Results: MM cells that acquired bortezomib (btz) resistance (PS-R) exhibited a marked increase in protein levels of multiple key components of the canonical and non-canonical NF-κB signaling cascades, in association with increased NF-κB transcriptional activity. Pharmacological inhibition of NF-κB using several compounds (e.g., Bay 11-7082, parthenolide, triptolide) significantly increased btz sensitivity in PS-R cells and their parental U266 cells, as well as other MM cell lines. These events were accompanied by down-regulation of various genes, including NF-κB-dependent genes and those whose relationship with NF-κB remains uncertain. The latter included IRF4, MYC, MCL1, BIRC2/cIAP1, SQSTM1/p62, among others. Of note, overexpression of wild-type IRF4 sharply reduced sensitivity of drug-naive cells to btz alone or in combination with NF-κB inhibitors. However, IRF4 overexpression did not prevent inactivation of NF-κB and down-regulation of the NF-κB-dependent genes (e.g., Bcl-xL, TNFAIP3/A20), suggesting that IRF4 acts downstream of NF-κB. Surprisingly, IRF4 overexpression failed to restore expression of MYC, a well-established target of IRF4, while largely reversed expression of cIAP1 and Mcl-1 at both mRNA and protein levels. Moreover, inhibitors of either IAP (birinapant/TL32711) or Mcl-1 (S63845) overcame btz-resistance conferred by IRF4 overexpression. DNAseq unveiled multiple IRF4 SNPs located in introns and exons (both 3'-UTR and coding region) of chromosome 6. WES revealed that IRF4 was highly expressed in primary bone marrow and extramedullary samples of MM patients (2~10 folds over normal donors). But no difference at mRNA and protein levels of IRF4 was observed between drug-naive and -resistant cell lines. The global PTM mapping identified two lysine residues (K59 and K399) that were highly ubiquitinated in PS-R cells (p = 0.0447 and p = 0.0004, vs U266 cells). Interestingly, ectopic expression of IRF4 mutants (e.g., K59N, K123R) lost the cytoprotective capability of their wild-type counterpart, in association with failure to reverse down-regulation of cIAP1 and Mcl-1. This observation argues that these point mutations are loss-of-function, which might explain better prognosis of patients carrying IRF4 mutations (including K59N and K123R) than wild-type IRF4 as reported previously. Last, the MM GEP database analysis validated the correlation between IRF4 and Mcl-1 or cIAP expression, as well as the adverse effect of their dysregulation on overall survival of MM patients. Conclusion: IRF4 is highly expressed in MM cells, likely via an NF-κB-dependent mechanism. IRF4 acts downstream of the NF-κB signaling pathways, which in turn directly targets cIAP1 and Mcl-1, rather than MYC, to confer drug resistance. IRF4 could be mutated in MM patients, while the point mutations, at least at certain lysine sites, seem to be loss-of-function and thus predict better outcome. Together, these findings suggest that the oncogenic function of IRF4 might be governed at genetic, transcriptional, and PTM levels in MM cells. Disclosures Kumar: Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.