Bohra, Arwa

Abstract Introduction Surface proteins in cancer not only reflect tumor–microenvironment interactions but also serve as targets for diagnostic flow cytometry and precision therapies, including monoclonal antibodies and CAR-T cell therapies. A better understanding of plasma cell immunophenotypes could inform flow cytometric prognostic assays and development of targeted therapies. Methods RNA-seq and Seq-FISH data from CD138-enriched bone marrow plasma cells, along with corresponding clinical annotations, were obtained from the Multiple Myeloma Research Foundation-CoMMpass Study. A curated list of surface genes was assembled by integrating three sources: the Human Protein Atlas (plasma membrane and cell junction annotations), the Gene-Set Enrichment Analysis membrane-associated gene set (Ontology:0016020), and the Cell Surface Protein Atlas (validated high-confidence category). A total of 4,579 genes coding for cell surface proteins were identified. Genes below the 25th variance percentile were removed. PCA (≥90% variance) followed by k-means (k=2, silhouette) and confirmed by hierarchical clustering. A Plasma Cell Maturity (PBM) score was computed using singscore on 84 mature plasma cell–associated genes to compare cluster phenotypes. Pathway analysis was done using GSEA software for Hallmark pathways. Clinical biomarkers and survival kinetics were compared between the clusters. Results 761 newly diagnosed patients were included. (Age: 27-93 years, median overall survival/OS: 29 months/mo). Clustering revealed two groups which we termed Atypical/Aggressive Cluster 1 (C1, n=105, 13.8%) and Classical Cluster 2 (C2, n=656, 86.2%), based on the patterns and clinical characteristics. Among non-missing cases, high-risk disease per the International Myeloma Society–International Myeloma Working Group (IMS–IMWG) definition was observed in 27.7% of patients in C2 (n = 552) and 24.7% in C1 (n = 90) (p = 0.4).C1 exhibited enrichment for t(14;16)-MAF (OR = 2.6, 95% CI: 1.1–6.1, p = 0.04) and t(11;14)-CCND1 (OR = 1.7, CI: 1.01–2.8, p = 0.04). In contrast, hyperdiploidy was more common in C2 (OR for C1 = 0.6, CI: 0.4–0.9, p = 0.04). Elevated LDH was observed in C1 (OR = 2.6, CI: 1.6–4, p < 0.001). Median serum Beta-2 microglobulin was lower in C1.(p=0.009) Upregulated genes in C1 in decreasing order of log Fold Change(logFC): AHNAK, MT-ND1, EEF2, EZR, HLA-B, TXNIP, HLA-E, TRIB1, MCL1, RHOB, CD74, CFLAR, HLA-A, HERPUD1, RPSA, ERN1, HSP90AB1, RAPGEF2, ADGRE5, and LAPTM5. Downregulated genes in C1 in descending order of |logFC|: B2M, SDC1 (CD138), HSP90B1, SEL1L, CALR, CANX, PECAM1, SLAMF7, STT3A, TNFRSF17 (BCMA), FCRL5, STT3B, PALM2AKAP2, CD53, PARP1, CCR2, RPN1, CD38, EDNRB, and LMAN2. Upregulated pathways in C1: proliferation (MYC, E2F, PI3K/AKT/mTOR, KRAS, Wnt); evasion of apoptosis (p53, TGF-β, Notch, NF-κB, IL6/JAK/STAT3); Epithelial to Mesenchymal Transition (angiogenesis, apical junction); inflammatory (interferon, TNF-α, complement, IL2/STAT5); metabolic reprogramming (oxidative phosphorylation, lipid/cholesterol); and stress (DNA repair, unfolded protein response). The PBM score for C1 was significantly lower, suggesting a less differentiated phenotype. C1 patients had inferior survival (n = 93, median OS 43.9 mo, p = 0.04) compared to those in the C2 cluster (n = 559, median OS 102.5 mo). Patients in the C1 + IMS–IMWG high-risk status had the shortest survival (20.7 mo), compared to C1+low (50 mo), C2/high (68.3 mo), and C2+low (not reached). In a multivariable analysis, C1 status (HR = 1.93; 95% CI: 1.1–3.4, p = 0.02) was an independent predictor, along with older age (1.05), UAMS70 (1.02), EMC-92 (1.4). In C1, early (<18 mo) progression occurred in 76.3% (n=71) (p < 0.001). In patients receiving first line of treatment(LOT1), median PFS was 39.7 mo in C1vs. 47.3 mo in C2 (p=0.8). Among patients who received stem cell transplant in LOT1, the median survival for the C2 was 102.5 mo, compared to 44.5 mo for C1 (n = 52) (p = 0.01). Among non-SCT patients on Immunomodulator + Proteasome Inhibitor therapy, C1 (n=28) had shorter survival of 50.0 vs. 71.7 C2 (n=137; p =0.8). Conclusion Our transcriptomic analysis identified a higher-risk group of patients (C1) exhibiting downregulation of myeloma specific markers (CD38, CD138, BCMA, SLAMF7, FCRL5) and inferior outcomes. It is important to diagnose and find appropriate therapy for these patients as they don't obtain the same benefit from the current standard of therapy as the remaining patients.

Introduction: Myeloma response to treatment can be biochemical, pathological, or radiological, with pathological assessments being invasive. Next-generation blood flow (PBF) for assessment of circulating tumor plasma cells (CTCs) has shown promising results as a prognostic in Multiple Myeloma (MM) patients. CTC detection via PBF has a potential to serve as non-invasive method for assessing pathological burden of disease and response to treatment. Comparing CTC responses to the International Myeloma Working Group (IMWG) criteria will further help to understand PBF's utility in predicting response to therapy. Patients and Methods: The study conducted is a retrospective observational study. We included patients with MM treated at Mayo Clinic from 01/01/2011 to 12/31/2019 with CTC records available at the time of best response (BR) to frontline therapy. The CTC values were expressed as the number of plasma cell events per 150,000 Peripheral Blood Mononuclear Cells (CD38, CD138, CD19, CD45, Kappa, Lambda). The CTC levels were compared across all response(IMWG Criteria) groups at BR, and at baseline. The CTC response was expressed as % CTC decrease at BR from baseline. Time-to-event analyses utilized the Kaplan Meier method and Cox-proportional hazards models, with comparisons made using the log-rank test. Results: We identified 621 patients with CTC data at the time of BR to frontline therapy. Of these, 148 (24%) had baseline CTC data from diagnosis. The median age at diagnosis was 62.3 (27.2-83.7). The median follow-up was 66.15 months; the distribution of patients by treatment class is as follows- Alkylator: 0.8%, PI(Proteasome Inhibitor)+Cyclophosphamide: 27.4%, IMid: 12.7%, PI+IMid(Immunomodulator): 55.9%, PI+IMid+antiCD38: 3.2%; 378 patients (78.8%) underwent an autologous transplant. BR to initial therapy was sCR/stringent Complete Response (10, 1.6%), CR (230, 36.9%), VGPR/Very Good Partial Response (224, 36.1%), PR (123, 19.8%), MR/Minimal Response (12, 1.9%), SD/Stable Disease (14, 2.3%), PD/Progressive Disease (8, 1.3%). In the study, 64 patients (10.31%) had detectable CTCs at their BR. The distribution of CTCs across the different response categories was as follows: none (0%) in sCR, 3 patients (1.3%) in CR, 18 patients (8%) in VGPR, 24 patients (19.5%) in PR, 8 patients (66.7%) in MR, 6 patients (42.9%) in SD, and 5 patients (62.5%) in PD. The median CTC counts and their interquartile ranges for these categories showed significant variability: CR had a median of 46 (IQR: 28.5, 923), VGPR had 39.5 (IQR: 15.5, 111.25), PR had 47 (IQR: 22.75, 82.5), MR had 55 (IQR: 28.5, 85), SD had 96.5 (IQR: 22.25, 218.75), and PD had 317 (IQR: 57, 415). This Analysis of Variance (ANOVA) for response-wise distribution of CTC was <0.01. Response was dichotomized as PR and above for sCR, CR, VGPR, PR and less than PR for MR, SD and PD. Median Overall Survival(OS) for PR and above was 127.8 months (vs less than PR 56.7 months, p=0.01). Median OS for CTC+ at BR was 56.7 months (vs 134.8 for CTC negative, p=0.01). On multivariate analysis, presence of CTC at best response (Hazards Ratio = 2.9, n=1.1-2.9), RISS staging at diagnosis (Hazards Ratio = 2.35, n=1.5-3.05), less than PR (Hazards Ratio =1.8, 1.1-2.9) were independent predictors of inferior OS. In patients with data for CTC available at both baseline and at BR to frontline therapy (n=148), 110 had CTC detectable at diagnosis. Among patients in various response categories, a complete disappearance of CTCs was observed in sCR (n=3, 75.0%), CR (n=36, 69.2%), VGPR (n=38, 64.4%), and PR (n=14, 60.9%). CTC responses greater than 90% were noted in VGPR (n=3, 5.1%), PR (n=2, 8.7%), and SD (n=2, 40.0%). No CTC response was reported in sCR (1, 25.0%), CR (16, 30.8%), VGPR (2, 3.4% and 13, 22.0%), PR (3, 13.0% and both 2, 8.7%), SD (1, 20.0% and both 2, 40.0%), MR (1, 50.0%), and PD (1, 33.3% and 1, 50.0%, respectively). The median OS for those with a CTC response was 112.4 months vs 28.2 months for no response. (p=0.01). Conclusion: The presence of CTC at best response is an independent prognostic marker for inferior OS. Depth of response to frontline therapy correspond to a high rate of clearance of CTCs. Presence of CTC at best response provides independent prognostic value beyond the depth of response. A complete clearance of CTC at best response is associated with improved OS. CTC levels have not been corrected for WBC counts and may not be applicable in all settings.

Introduction: The current definition of plasma cell leukemia (PCL) is based on peripheral blood smear (PBS) demonstrating ≥5% plasma cells. However, PCL cases are enriched in translocation t(11;14), which often has a lympho-plasmacytoid appearance. Detection and quantification of circulating tumor plasma cells (CTC) through peripheral blood flow cytometry (PBF) has emerged as a promising approach for assessing disease burden and prognosis in multiple myeloma (MM) patients. While PBF is more sensitive, the potential threshold values on PBF that correspond with the PBS detection of circulating plasma cells (PBS-PC) remain undetermined. It is important to understand this comparison better to categorize PCL based on PBF. Patients and Methods: This is a retrospective cross-sectional diagnostic accuracy study. We reviewed results of patients diagnosed with plasma cell dyscrasia at the Mayo Clinic from January 2011 to December 2020. The presence of circulating tumor plasma cells (CTC) in encounters was evaluated using peripheral blood flow cytometry (PBF) and peripheral blood smear (PBS) for plasma cells (PBS-PC). PBS-PC was measured as a percentage of plasma cells (PC) in a 100-cell manual differential smear count, and PBF was expressed as the number of plasma cell events per 150,000 peripheral blood mononuclear cells (PBMCs) (Ficoll-isolated peripheral blood mononuclear cells using antibodies to CD38, CD138, CD19, CD45, kappa, lambda, sensitivity (Sn)=6.7x10-5). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of PBS with respect to PBF were calculated. For threshold analysis, four groups were defined: A = absent PBS-PC, C = ≥1% and <5%, D = ≥5%. Sensitivity and specificity of detecting PBS-PC (y-axis) for groups A vs. B, B vs. C, and C vs. D were plotted against CTC levels on PBF (x-axis) to determine the best cut-off. Area Under the Curve (AUC) was calculated to determine accuracy. Agreement analysis was done for internal validation and reliability assessment. Results: 6066 test records of CTC were reviewed. Circulating tumor plasma cells (CTC) by peripheral blood flow cytometry (PBF) were reported in 1610 (26.5%) instances, and peripheral blood smear for plasma cells (PBS-PC) in 226 (3.7%) tests. Peripheral blood smear (PBS) demonstrated a sensitivity of 9.3%, specificity of 99.5%, positive predictive value (PPV) of 86.7%, and negative predictive value (NPV) of 75.3% when compared to peripheral blood flow cytometry (PBF). The correlation between PBS-PC% and CTC was weakly positive (Spearman's rho=0.27, p<0.01). The median (Q1, Q3) of circulating tumor plasma cells (CTC) for group A (n=5840) was 0 (0, 0), group B (n=82) was 780 (97.75, 4012.75), group C (n=67) was 1801 (61.50, 8723.50), and group D (n=77) was 20518 (2296, 41349) (p-value <0.001). On post-hoc analysis, all pairs had significant differences in CTCs. To distinguish between A and B, a threshold of 32.5 for CTC demonstrated a sensitivity of 81.8% (AUC=87.8%), and to distinguish B and C, 1125 demonstrated a sensitivity of 59.4% (AUC=63.2%). To distinguish between C and D, 5875 for CTC demonstrated a sensitivity of 68.8% (AUC=74.6%). Agreement Analysis: The Bland-Altman plot demonstrates a slight positive bias between the Clonal Event % and %PBS-PC values (mean of difference = 0.28). The variability of differences increases with higher mean values, indicating a potential proportional bias. All predicted thresholds lie within the limits of agreement (LoA) (upper: 6.13, lower: -5.58) and are therefore reliable. The precision range (upper: 0.35, lower: 0.2) is narrower for the predicted thresholds. The methods should not be compared beyond a circulating tumor plasma cell (CTC) count of 9,195. Conclusion: Detection of circulating tumor plasma cells (CTC) by peripheral blood smear (PBS) is very specific but not sensitive and can be improved by peripheral blood flow cytometry (PBF) detection of CTC. Important clinical cutoffs by morphology (presence and ≥5%) have their counterparts by PBF (32 and 5875 out of 150,000 peripheral blood mononuclear cells (PBMC), respectively). The predicted thresholds are reliable. The study is retrospective and may not be generalizable across all demographics and disease severity. Circulating tumor plasma cell (CTC) values aren't absolute counts and may not be generalizable for low white blood cell (WBC) counts.

Background: Multiple myeloma (MM) involves the proliferation of monoclonal plasma cells (PCs) in the bone marrow. The plasma cell labeling index (PCLI), indicating the percentage of PCs in the S-phase, is a key prognostic factor in newly diagnosed multiple myeloma (NDMM) patients. Methods: A retrospective study at Mayo Clinic analyzed bone marrow Affymetrix microarray datasets from 136 NDMM patients (2001-2012). Data normalization and quality assessment were followed by differential gene expression analysis using limma-voom, adjusted for age, BMPC percentage, and disease stage (RISS). Selected genes were dichotomized by median and subjected to logistic regression for high/low PCLI. Data from 594 patients with a Proliferation Index at baseline was pooled from the MMRF (CoMMpass) dataset for validation after normalization across assays. Results: The baseline characteristics of the patients are as follows: 62 (46%) were female and 74 (54%) were male, with a mean age at diagnosis of 61.6 ± 11.5 years. RISS staging included 36 patients (26.5%) at stage 1, 32 (23.5%) at stage 2, 29 (21.32%) at stage 3, and 39 patients (28.67%) with unknown stage. PCLI distribution showed 113 patients (83.7%) with <2%, and 23 (16.3%) ≥2%. Differential Analysis: The differential analyses reveal several critical insights. In the primary continuous differential analysis, 21,367 genes were analyzed, identifying 654 as differentially expressed with an FDR-adjusted p-value ≤0.05. Of these, 481 genes were upregulated (top 5: SPC25, TRAT1, PBK, E2F8, ASPM) and 173 were downregulated (top 5: SPARC, CD24, MYOF, CXCL12, VCAM1). Univariate and multivariate stratified analyses showed significant findings: 668 genes in age stratification, 395 genes in BMPC% stratification, and 536 genes in RISS stratification. In multivariate analysis, 408 genes were significant with an FDR-adjusted p-value <0.05 for PCLI and ≥0.05 for BMPC%, age, and RISS. 3-Fold Internal Validation: 240 significant genes were identified in fold 1, 25 in fold 2, and 167 in fold 3, with 21 genes common across all folds (e.g., MCM10, GTSE1, UBE2S, NCAPG, FOXM1, STMN1, NEK2, CENPF, MND1, HJURP, E2F8, TOP2A, SKA1, CCNB2, CCNF, CHAF1A, PBK, EXO1, AURKB, CDCA2, DHFR). 19 genes were common in the sensitivity analysis by excluding RISS 3. 20 genes were common in categorical analysis (Categories <1%, 1-2%, 2-3%, 3-4%, >4%). 3 Gene-Based Proliferation Score (3GPS): On univariate logistic regression analysis of 21 genes for high/low PCLI, 17 significant genes were identified. In the step-wise multivariate analysis, CDCA2 (OR=11.56), DHFR (OR=9.6), and CENPF (OR=6.11) were significant. Log-odds were used as weights. For the high expression(median and above) of gene as 1 and low expression as 0: 3GPS=2.4*CDCA2+ 2.3*DHFR +1.8*CENPF A cut-off of 2.4 was chosen as CDCA2 had the highest positive concordance rate (90.91%) versus DHFR (86.36%) and CENPF (77.27%). External Validation: In the CoMMpass dataset, the sensitivity and specificity for the presence of high expression of any of the 3 genes with ≥2 Proliferation Index (PI) were 92.4% and 73.8%, respectively (AUC=83.1%). The median 3GPS was 0 for <2 PI (n=238) and 6.5 for ≥2 PI (n=356). The sensitivity and specificity for the 3GPS in predicting ≥2 PI were 82.6% and 93.6%, respectively (AUC=88.1%). Pathway Analysis: Significant pathways using Reactome include polo-like kinase mediated events in G2/M transition, condensation of prometaphase chromosomes in metaphase, resolution of sister chromatid cohesion in anaphase, and APC-Cdc20 mediated degradation of Nek2A for regulation of the cell cycle. p53 signaling, cancer pathways, and microtubule regulation were also mapped. Survival Analysis: In our cohort, for CDCA2 quartiles (Q)3 and Q4, for CENPF Q3 and Q4, and for DHFR Q4 were associated with inferior overall survival. 3GPS ≥2.4 was associated with inferior survival of 60.28 months versus 111.5 months for <2.4 (p<0.01). In the validation dataset, median survival was not reached at 100 months (vs. high 79.7, p<0.01). The multivariate Cox model found 3GPS score ≥2.4 as an independent predictor (HR=1.64, 95% CI: 1.23 - 2.19), along with ECOG status, ISS stage, gender, age, and whether the patient underwent Stem Cell Transplant. Conclusion: CDCA2, DHFR, and CENPF are associated with ≥ 2% PCLI. The 3GPS score can serve as a measure of gene-based proliferation index. Prospective validation is needed for clinical practice.

Abstract Patient-reported outcomes (PROs) are associated with treatment outcomes in multiple myeloma (MM) in the clinical trial setting. However, most PRO tools are time consuming, which hinders use in routine practice. Our institution incorporated a “Hematology Patient-Reported Symptom Screen” (HPRSS), a 3-item questionnaire for fatigue, pain, and quality of life (QOL). The main objective of this study was to evaluate the impact of these symptoms on progression-free survival (PFS) and overall survival (OS) in a real-world cohort of patients with newly diagnosed MM. This retrospective study included patients with MM diagnosed between April 2011 and December 2017, seen at Mayo Clinic (Rochester, MN), who completed the HPRSS. Patients rated their symptoms on a scale from 0 to 10. Clinically relevant symptoms were defined as scores ≥5 for pain and fatigue, and ≤5 for QOL. At diagnosis, 735 patients had scores for all domains. The median follow-up was 8.1 years. Age was associated with increased odds of fatigue and decreased QOL. Female sex and comorbidities were associated with fatigue and pain. Higher disease stage, anemia, lytic lesions, and increased plasma cell burden were associated with fatigue, pain, and decreased QOL. Clinically relevant fatigue, pain, and decreased QOL were associated with decreased PFS and OS. On multivariate analysis including age, International Staging System III, high-risk cytogenetics, and postinduction transplantation, fatigue and decreased QOL were independently associated with decreased OS. A composite HPRSS score stratified patients into 3 groups with distinct OS. Patient-reported symptoms are prognostic in patients with newly diagnosed MM. The prognostic values of fatigue and decreased QOL are independent of age, disease stage, and transplant status.

7515 Background: BCMA directed CAR T cells, antibody drug conjugates (ADCs), and T cell engagers (TCEs) each have distinct strengths and weaknesses. While these agents have shown unprecedented response rates and survival outcomes, no head-head comparisons exist. We assessed the relative efficacy of different BCMA-therapies in relapsed myeloma, with a focus on high-risk subgroups. Methods: Retrospective study of MM patients treated at Mayo Clinic with commercial or investigational BCMA targeted therapies between April 2018-June 2023. Results: 385 patients (ADC=59, TCE=134, CAR T=192) with a median follow up of 20-months. The median time from diagnosis was 6.1 years. The table shows disease, and treatment characteristics. Amongst ADCs and TCEs recipients, the median treatment duration was 1.9 and 3.5 months respectively, disease progression (64% and 79%) and intolerance (22% and 10%) were the most common reasons for discontinuation. The overall response rates were 27, 50, and 86% for ADCs, TCEs and CAR T, respectively. Compared to ADCs, CAR T was associated with improved PFS (adjusted HRPFS=0.29, 95%CI=0.20-0.43) and OS (aHROS=0.28, 95%CI=0.18-0.44) when adjusting for age, R-ISS, double hit high risk cytogenetic abnormalities (HRCAs), extramedullary disease (EMD, excluding paraskeletal plasmacytomas), triple class refractoriness, and the number of lines of therapy (LOTs) received in the preceding 1 year. Likewise compared to ADCs, TCEs were associated with superior PFS (aHRPFS=0.59, 95%CI=0.40-0.86) and OS (aHROS=0.60, 95%CI=0.39-0.93). Amongst patients with plasma cell leukemia (PCL) or EMD at the time of BCMA therapy (n=123), median PFS was poor irrespective of the therapeutic class at 1.3, 1.7 and 6.1 months for ADCs, TCEs and CAR T, respectively. Equally, for patients previously treated with BCMA therapy (n=58), median PFS was poor regardless of class at 1.9, 2.4 and 3 months for ADCs, TCEs and CAR T, respectively. Of 229 relapses the mode of relapse was known in 192 cases (84%), with 101 (52%) having EMD at relapse. Conclusions: While contingent on myriad other factors, patients able to receive BCMA-directed CAR T therapy experience superior survival compared to ADC and TCEs. EMD, PCL and BCMA-exposed populations are recalcitrant to BCMA-directed immunotherapy, and EMD is a common means of relapse. [Table: see text]

Abstract Three classes of BCMA-directed therapy (BDT) exist: antibody drug-conjugates (ADCs), CAR-T, and T-cell engagers (TCEs), each with distinct strengths and weaknesses. To aid clinicians in selecting between BDTs, we reviewed myeloma patients treated at Mayo Clinic with commercial or investigational BDT between 2018–2023. We identified 339 individuals (1-exposure = 297, 2-exposures = 38, 3-exposures = 4) who received 385 BDTs (ADC = 59, TCE = 134, CAR-T = 192), with median follow-up of 21-months. ADC recipients were older, with more lines of therapy (LOT), and penta-refractory disease. Compared to ADCs, CAR-T (aHR = 0.29, 95%CI = 0.20–0.43) and TCEs (aHR = 0.62, 95%CI = 0.43–0.91) had better progression-free survival (PFS) on analysis adjusted for age, the presence of extramedullary (EMD), penta-refractory disease, multi-hit high-risk cytogenetics, prior BDT, and the number of LOT in the preceding 1-year. Likewise, compared to ADCs, CAR-T (aHR = 0.28, 95%CI = 0.18–0.44) and TCEs (aHR = 0.60, 95%CI = 0.39–0.93) had superior overall survival. Prior BDT exposure negatively impacted all classes but was most striking in CAR-T, ORR 86% vs. 50% and median PFS 13-months vs. 3-months. Of relapses, 54% were extramedullary in nature, and a quarter of these cases had no history of EMD. CAR-T demonstrates superior efficacy and where feasible, should be the initial BDT. However, for patients with prior BDT or rapidly progressive disease, an alternative approach may be preferable.