Pearce, Kathryn E.

Abstract Background The use of autonomous mobile robots (AMRs) to move materials/supplies is long-standing in manufacturing/warehouse settings and is expanding into hospitals and clinical laboratories. The recently launched Proxie robot (Collaborative Robotics i.e. Cobot) is an AMR that can autonomously move existing carts between defined locations. However, AMRs pose new challenges compared to traditional lab automation. The aims of this study were to: i) perform functional validation to verify Proxie*s manufacturer performance specifications within the laboratory, ii) assess the risk of using Proxie to deliver laboratory specimens, and iii) pilot the use of the Proxie robot to autonomously deliver loaded carts from the Pathology case intake area to the sorting station at Mayo Clinic Laboratories. Methods Functional validation of Proxie consisted of verifying manufacturer’s performance specifications for the following robot parameters (5 test runs): maximum speed, emergency-stop, and ability to maintain localization, travel autonomously, stop and/or avoid moving/fixed objects, and park/unpark. Risk assessment for the robotic use case was performed by a multi-disciplinary team utilizing an AMR risk assessment tool developed by the institutional robotics group. Hazards were categorized as mechanical, electrical, noise, ergonomic, environmental, material/substance or combination risks. Injury severity, exposure(frequency), and avoidance scores were assigned to each hazard to determine negligible-, low-, medium-, high- or very high-risk levels. Proxie’s workstream was evaluated weekly over four weeks by measuring number of cart deliveries, total time/miles traveled, % autonomous deliveries(goal >80%), % on-time deliveries, average±standard deviation(SD) time (min:sec±min:sec) for delivery/return trips, and dwell times at intake/sorting stations. Results Manufacturer’s performance specifications were verified in 100% of test runs. Proxie traveled at human walking speed, stopped within 1 second of emergency stop being enabled, maintained localization, and traveled autonomously for =5 consecutive workflow cycles. Proxie navigated through spaces =4’ wide along fixed pathways and stopped safely when encountering obstacles. Proxie navigated around people and carts in the main 6’ hallway if they were blocking <2’ hallway width. For objects blocking >2’, Proxie stopped and resumed motion after the object moved. After task completion, Proxie side-shifted into the AMR parking space stopping no closer than 7.8” from any object. Twenty-four potential hazards were identified through the risk assessment tool with all risk levels scored as negligible or low. Proxie completed 304 cart deliveries/returns operating 17:35 hours and traveling 11.5 miles during the pilot. The % autonomous deliveries for week 1-4 was 82%,88%,91% and 88%, respectively with =99% on-time deliveries. Delivery from pathology case intake to sorting station averaged 5:43±0:25 min and return trips averaged 3:32±0:34. Proxie dwell times were 13:10±0:33 and 37:34±0:23 min at the pathology intake and sorting stations, respectively. Conclusions The Proxie AMR was capable of successfully and autonomously moving carts with laboratory specimens between the pathology intake and sorting stations of the laboratory during the pilot study. Adding Proxie to this workstream translated to eliminating 5,800 steps and 4 hours 24 min of human cart-pushing per week. Incorporating Proxie into laboratory operations as a cart-moving AMR would increase efficiency and allow laboratory staff to focus on technical, non-repetitive work.

Complex structural chromosome abnormalities such as chromoanagenesis have been reported in acute myeloid leukemia (AML). They are usually not well characterized by conventional genetic methods, and the characterization of chromoanagenesis structural abnormalities from short-read sequencing still presents challenges. Here, we characterized complex structural abnormalities involving chromosomes 2, 3, and 7 in an AML patient using an integrated approach including CRISPR/Cas9-mediated nanopore sequencing, mate pair sequencing (MPseq), and SNP microarray analysis along with cytogenetic methods. SNP microarray analysis revealed chromoanagenesis involving chromosomes 3 and 7, and a pseudotricentric chromosome 7 was revealed by cytogenetic methods. MPseq revealed 138 structural variants (SVs) as putative junctions of complex rearrangements involving chromosomes 2, 3, and 7, which led to 16 novel gene fusions and 33 truncated genes. Thirty CRISPR RNA (crRNA) sequences were designed to map 29 SVs, of which 27 (93.1%) were on-target based on CRISPR/Cas9 crRNA nanopore sequencing. In addition to simple SVs, complex SVs involving over two breakpoints were also revealed. Twenty-one SVs (77.8% of the on-target SVs) were also revealed by MPseq with shared SV breakpoints. Approximately three-quarters of breakpoints were located within genes, especially intronic regions, and one-quarter of breakpoints were intergenic. Alu and LINE repeat elements were frequent among breakpoints. Amplification of the chromosome 7 centromere was also detected by nanopore sequencing. Given the high amplification of the chromosome 7 centromere, extra chromosome 7 centromere sequences (tricentric), and more gains than losses of genomic material, chromoanasynthesis and chromothripsis may be responsible for forming this highly complex structural abnormality. We showed this combination approach’s value in characterizing complex structural abnormalities for clinical and research applications. Characterization of these complex structural chromosome abnormalities not only will help understand the molecular mechanisms responsible for the process of chromoanagenesis, but also may identify specific molecular targets and their impact on therapy and overall survival.

Abstract Objectives Fluorescence in situ hybridization (FISH) for plasma cell neoplasms (PCNs) requires plasma cell (PC) identification or purification strategies to optimize results. We compared the efficacy of cytoplasmic immunoglobulin FISH (cIg-FISH) and fluorescence-activated cell sorting FISH (FACS-FISH) in a clinical laboratory setting. Methods The FISH analysis results of 14,855 samples from individuals with a suspected PCN subjected to cytogenetic evaluation between 2019 and 2022 with cIg-FISH (n = 6917) or FACS-FISH (n = 7938) testing were analyzed. Results Fluorescence-activated cell sorting–FISH increased the detection rate of abnormalities in comparison with cIg-FISH, with abnormal results documented in 54% vs 50% of cases, respectively (P < .001). It improved the detection of IGH::CCND1 (P < .001), IGH::MAF (P < .001), IGH::MAFB (P < .001), other IGH rearrangements (P < .001), and gains/amplifications of 1q (P < .001), whereas the detection rates of IGH::FGFR3 fusions (P = .3), loss of 17p (P = .3), and other abnormalities, including hyperdiploidy (P = .5), were similar. Insufficient PC yield for FISH analysis was decreased between cIg-FISH and FACS-FISH (22% and 3% respectively, P < .001). Flow cytometry allowed establishment of ploidy status in 91% of cases. In addition, FACS-FISH decreased analysis times, workload efforts, and operating costs. Conclusions Fluorescence-activated cell sorting–FISH is an efficient PC purification strategy that affords significant improvement in diagnostic yield and decreases workflow requirements in comparison with cIg-FISH.

Abstract Purpose: Multiple myeloma (MM) is a plasma cell (PC) malignancy with an increasing incidence in the United States. Fluorescence in situ hybridization (FISH) is currently the gold-standard diagnostic assay to detect recurrent genomic abnormalities of prognostic and therapeutic significance in MM. Hyperdiploid MM, a standard risk abnormality, is characterized by gains of odd-numbered chromosomes including chromosome 15. While gains of chromosome 15 have been reported in approximately 53% of standard risk MM patients (Chretien, Blood, 2015), losses of chromosome 15 are rarely reported. Enumeration of chromosome 15 centromere is detected using the alpha satellite FISH probe. We previously discovered ~9% of cases had false-negative chromosome 15 FISH results when compared to Mate Pair Sequencing (MPseq) (Smadbeck, BCJ, 2019). To our knowledge, no previous studies have reported a reduced performance of the alpha satellite D15Z4 FISH probe in PC FISH studies. A false-negative result for D15Z4 could result in an underreporting of trisomy 15 and overreporting of monosomy 15. Here, we investigated the incidence of false-negative D15Z4 FISH results by examining the presence of monosomy 15 from patients with a monoclonal gammopathy. Methods: We identified 1231 samples from patients with a monoclonal gammopathy who had undergone uniform testing to identify MM-specific cytogenetic abnormalities. DNA from bone marrow samples was genotyped on the Precision Medicine Research Array and biogeographical ancestry was assessed using the Geographic Population Structure Origins tool (Elhaik, Nat Commun, 2014; Home DNA 2016). FISH of immunoglobulin (cIg)-stained PCs was performed as described (Baughn, BCJ, 2018). Chromosome 15 centromere probe (Vysis CEP 15 D15Z4, Abbott Molecular, Abbott Park, IL) was used for chromosome 15 enumeration. Samples were divided into two groups: Cases with or without evidence of monosomy 15 by FISH. Mann-Whitney U test was applied to compare difference between groups for data deviating from normal distribution. A Chi-squared test evaluating the differences across these two groups was used. Results: We identified monosomy 15 in 31 cases (2.5% of cohort). Monosomy 15 was observed in nearly 100% of both the PC (cIg+) and non-PC (cIg-) populations, by contrast to the other recurrent PC-specific genomic abnormalities which were restricted to only the PC population. All samples with a banded analysis revealed most metaphases had two normal chromosome 15s demonstrating that the D15Z4 FISH probe failed to correctly enumerate the number of chromosome 15 centromere signals. Of the samples with a monosomy 15 result, the median African ancestry was 76.2% (95% percentiles: 77.5%-89.0%), while the median African ancestry of the non-monosomy 15 cohort was 2.3% (95% percentiles: 0%-87.7%) (). Although not all patients with >50% African ancestry had evidence of monosomy 15, 26/31 (83.9%) of patients with monosomy 15 had >50% African ancestry. Accordingly, patients with African ancestry (similarity ≥ 0.70) had 8.02-fold (95% confidence interval: 3.73-17.25, P = 9.92 X10 -8) increased possibility to have monosomy 15. Of cases with monosomy 15, 22 (71.0%) had an IGH rearrangement with the most prevalent IGH partner being CCND1. The incidence of t(11;14) was greater in the monosomy 15 group (13/31:41.9%), in contrast to the non-monosomy 15 group (330/1200=27.5%) (P = 0.12). Conclusions: We report a polymorphic variant of the chromosome 15 centromere resulting in a false-negative FISH result using the D15Z4 FISH probe. Surprisingly, the false-negative FISH result was not uniformly distributed among patients and was highly enriched in individuals of African ancestry. This may be due to a variation of the chromosome 15 alpha satellite in some individuals that prevents the D15Z4 FISH probe from sufficiently binding (O'Keefe, Genome Research, 2000). Although this study focused on identification of monosomy 15, the incidence of a false-negative result is likely greater than we have reported in this study since we did not evaluate cases that had a true trisomy 15 that was reported as normal chromosome 15 enumeration by FISH. This study highlights a critical need to ensure diagnostic reagents have equal performance for all patients independent of their ancestry. Evaluation of genomic events using unbiased approaches such as whole genome sequencing may circumvent some of these limitations. Disclosures Elhaik: DDC: Consultancy. Baird: DDC: Current Employment. Kumar: Antengene: Consultancy, Honoraria; Bluebird Bio: Consultancy; Beigene: Consultancy; BMS: Consultancy, Research Funding; Tenebio: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Novartis: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Carsgen: 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 The basis for acquired resistance to JAK inhibition in patients with JAK2-driven hematologic malignancies is not well understood. We report a patient with a myeloproliferative neoplasm (MPN) with a BCR activator of RhoGEF and GTPase (BCR)–JAK2 fusion with initial hematologic response to ruxolitinib who rapidly developed B-lymphoid blast transformation. We analyzed pre-ruxolitinib and blast transformation samples using genome sequencing, DNA mate-pair sequencing (MPseq), RNA sequencing (RNA-seq), and chromosomal microarray to characterize possible mechanisms of resistance. No resistance mutations in the BCR-JAK2 fusion gene or transcript were identified, and fusion transcript expression levels remained stable. However, at the time of blast transformation, MPseq detected a new IKZF1 copy-number loss, which is predicted to result in loss of normal IKZF1 protein translation. RNA-seq revealed significant upregulation of genes negatively regulated by IKZF1, including IL7R and CRLF2. Disease progression was also characterized by adaptation to an activated B-cell receptor (BCR)–like signaling phenotype, with marked upregulation of genes such as CD79A, CD79B, IGLL1, VPREB1, BLNK, ZAP70, RAG1, and RAG2. In summary, IKZF1 deletion and a switch from cytokine dependence to activated BCR-like signaling phenotype represent putative mechanisms of ruxolitinib resistance in this case, recapitulating preclinical data on resistance to JAK inhibition in CRLF2-rearranged Philadelphia chromosome-like acute lymphoblastic leukemia.

Abstract Purpose: Structural variants (SV) of the MYC gene region are common in multiple myeloma and influence disease progression. However, the prognostic significance of different MYC SVs in multiple myeloma has not been clearly established. Experimental Design: We conducted a retrospective study of multiple myeloma comparing MYC SV subtypes identified by next-generation sequencing (NGS) and FISH to MYC expression and disease survival using 140 cases from Mayo Clinic and 658 cases from the MMRF CoMMpass study. Results: MYC SVs were found in 41% of cases and were classified into nine subtypes. A correlation between the presence of a MYC SV and increased MYC expression was identified. Among the nine MYC subtypes, the non-immunoglobulin (non-Ig) insertion subtype was independently associated with improved outcomes, while the Ig insertion subtype, specifically involving the IgL gene partner, was independently associated with poorer outcomes compared with other MYC SV subtypes. Although the FISH methodology failed to detect approximately 70% of all MYC SVs, those detected by FISH were associated with elevated MYC gene expression and poor outcomes suggesting a different pathogenic role for FISH-detected MYC subtypes compared with other MYC subtypes. Conclusions: Understanding the impact of different MYC SVs on disease outcome is necessary for the reliable interpretation of MYC SVs in multiple myeloma. NGS approaches should be considered as a replacement technique for a more comprehensive evaluation of the multiple myeloma clone.

Abstract Objectives Prognostically relevant chromosomal abnormalities in chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) are routinely identified by fluorescence in situ hybridization (FISH) on peripheral blood or bone marrow specimens. We studied the prevalence of chromosomal abnormalities on extramedullary tissues involved by CLL/SLL and evaluated their association with prominent proliferation centers (PPCs). Methods FISH for recurrent abnormalities in CLL/SLL was performed on formalin-fixed, paraffin-embedded biopsy sections. PPCs were identified on H&E-stained sections. Available FISH results on peripheral blood or bone marrow specimens were also reviewed. Results Recurrent FISH abnormalities were detected in 69% of 320 CLL/SLL biopsy specimens studied, including +12 (35%), 13q– (24%), 11q– (15%), 17p– (6%), 6q– (2%), and IGH/BCL2 (0.9%). Forty-three patients had abnormal blood or bone marrow FISH analyses, of whom 7 (16%) had discordant +12 and/or 13q–, and 3 (7%) had discordant 17p– or 11q–. Morphology was positive (17%), negative (78%), or equivocal (6%) for PPCs on 247 evaluable biopsy specimens, a finding not significantly associated with FISH results (P = .7). Conclusions Trisomy 12 is overrepresented in tumoral CLL/SLL involvement, compared with the known predominance of 13q– in blood. Discrepancies between leukemic and tissue FISH findings are occasionally encountered. FISH results do not correlate with the presence of PPCs.

AbstractPlasma cell neoplasms (PCN) and mantle cell lymphoma (MCL) can both harbor t(11;14)(q13;q32) (CCND1/IGH), usually resulting in cyclin D1 overexpression. In some cases, particularly at low levels of disease, it can be morphologically challenging to distinguish between these entities in the bone marrow (BM) since PCN with t(11;14) are often CD20‐positive with lymphoplasmacytic cytology, while MCL can rarely have plasmacytic differentiation. We compared the difference in CCND1/IGH by fluorescence in situ hybridization (FISH) in PCN and MCL to evaluate for possible differentiating characteristics. We identified 326 cases of MCL with t(11;14) and 279 cases of PCN with t(11;14) from either formalin‐fixed, paraffin‐embedded tissue or fresh BM specimens. The “typical,” balanced CCND1/IGH FISH signal pattern was defined as three total CCND1 signals, three total IGH signals, and two total fusion signals. Any deviation from the “typical” pattern was defined as an “atypical” pattern, which was further stratified into “gain of fusion” vs “complex” patterns. There was a significantly higher proportion of cases that showed an atypical FISH pattern in PCN compared with MCL (53% vs 27%, P < .0001). There was also a significantly higher proportion of cases that showed a complex FISH pattern in PCN compared with MCL (47% vs 17%, P < .0001). We confirmed these findings using mate‐pair sequencing of 25 PCN and MCL samples. PCN more often have a complex CCND1/IGH FISH pattern compared with MCL, suggesting possible differences in the genomic mechanisms underlying these rearrangements in plasma cells compared with B cells.

Purpose: Acute myeloid leukemia (AML) is the most common acute leukemia in adults, affecting approximately 20,000 patients annually in the United States. AML genetic subtypes, as defined by the World Health Organization (WHO), are identified through fluorescence in situ hybridization (FISH), conventional chromosome analysis, and sequencing techniques. Mate pair sequencing (MPseq) is a next generation sequencing (NGS) technology optimized to detect genome wide structural variants and copy number alterations at high resolution. Our study goal was to investigate the prognostic value of MPseq in comparison to FISH, chromosome, and sequencing studies in the evaluation of AML patients. Methods: We performed a prospective study using blood and bone marrow samples from 105 patients with a diagnosis of AML, using MPseq, along with chromosome, FISH, and NGS or PCR studies to detect small mutations. Cytogenetic and molecular genetic results were correlated with MPseq findings. We also analyzed the MPseq data for chromoplexy, chromothripsis, and progressive complexity. Junction and copy number burden, the incidence of structural variation in the genome and the percent of the genome with aberrant copy number, were evaluated. Overall survival statistics were stratified by AML subtypes and observed anomalies. Results: Although structural variants in AML were characterized at a high resolution using MPseq when compared to conventional cytogenetic methods, risk stratification using current European Leukemia Net (ELN) guidelines was not improved by MPseq. The cohorts involving 5q and/or 7q deletions exhibited high levels of genomic complexity when compared to normal karyotype AML (NK-AML). The incidence of copy number gains, losses and junctions was greatest in 5q and 7q co-deletions (5q/7q) (16.5, 25.0, 69.3) and 5q deletions (5q) (9.8, 16.7, 31.6) subtypes compared to 7q deletions (3.4, 7.0, 6.7) and NK-AML (2.6, 4.3, 3.8) (p&lt;0.001) subtypes. Chromoplexy, chromothripsis, and progressive structural complexity were detected in most samples with 5q deletions and 5q/7q co-deletions, but absent in samples with 7q or NK-AML. Biallelic inactivation of TP53 by sequencing mutation and/or deletion was common in the 5q/7q co-deletion (14/18 cases) and 5q deletion cohorts (7/10 cases), rare in the 7q deletion cohort (1/11 cases), and absent in the NK-AML (n=44) cohort. The median OS was significantly worse for patients with 5q/7q deletions (122.5 days) and 5q deletions (248 days) compared to NK-AML (413.5 days; p&lt;0.001 and p=0.017, respectively) and between 5q/7q deletions and 7q deletions (370.5 days; p&lt;0.001). No significant difference was observed between 5q/7q and 5q deletion subtypes, between NK and 7q deletion subtypes and between 5q and 7q deletion subtypes. The median OS was also significantly shorter for patients with TP53 alterations compared to patients with normal TP53 status. Patients with chromoplexy, chromothripsis and/or progressive structural complexity identified by MPseq had a significantly shorter median OS compared to patients without these features. (p&lt;0.0001) Discussion: Risk stratifications based on current guidelines using cytogenetic and sequencing results were not adjusted due to MPseq results, which is not surprising when primary abnormalities are observed by conventional cytogenetic methods. NK-AML cases did not appear to benefit from a high resolution genomic evaluation. However, MPseq added value when structural variation required additional characterization, detecting novel rearrangements, such as a KAT6A/SORBS3 fusion. Lastly, we recognized common mischaracterizations made by conventional chromosome studies - including missed TP53 deletions in 7 cases, 5q/7q deletions misinterpreted as monosomies, cryptic NUP98 rearrangements, and unappreciated genomic complexity correlating with poor OS. These mischaracterizations challenge the use of conventional chromosome studies as a gold standard without accompanying FISH or MPseq studies. MPseq, similar to other structural methodologies such as optical mapping and long read sequencing, should be considered important complements to standard cytologic techniques given the important additional genomic information obtained. The additional structural variant characterization will be critical in paving the way for genomic discovery with the overall goal of improving prognostication for patient care. Figure Disclosures Vasmatzis: WholeGenome LLC.: Other: Owner; Mayo Clinic: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Background: Multiple myeloma (MM) remains an incurable plasma cell (PC) malignancy. Despite improvements in clinical outcomes, variability in treatment response exists. Some patients experience innate resistance, while others develop resistance over the course of treatment. Identifying signatures of treatment response and resistance is essential to predicting effective treatment strategies. Given the phenotypic clonal heterogeneity observed in MM, we hypothesize that resistant and sensitive subpopulations have unique phenotypic signatures. We used mass cytometry (CyTOF) to characterize primary MM samples and correlated their phenotypic signatures with treatment response. Methods: We characterized 102 primary MM samples by CyTOF using 37 antibodies (see figure). Frozen whole BM specimens were thawed, stained with antibodies, barcoded, and analyzed on a Helios mass cytometer. Data was processed using Cytobank or Pathsetter and analyzed using t-distributed stochastic neighbor embedding (t-SNE) algorithm. T-SNE plots for CD45+ cells were created using lineage defining markers. T-SNE plots of neoplastic PCs (CD138+,CD3-,CD16-,CD19-,cytoplasmic kappa or lambda+) were created using all remaining markers. A differential analysis of each sample's clusters was performed against all other events. Z-score values, representing marker changes from the differential analysis, for each cluster were used to group similar clusters across all samples, allowing us to compare sub populations of PCs between patients (see figure). From these groups of clusters with similar changes in markers, we calculated the proportion of cells with increases or decreases in markers for each sample. Results were compared to IMWG 90-day response criteria using a random forest model. Results: We performed mass cytometry on 102 samples from 68 unique MM patients. Median age was 66 years (range 34-95) with a 1.5:1 male:female ratio. 37 (36%) had NDMM, 55 (54%) had RRMM, 2 (2%) had SMM and 8 cases (8%) had unknown status. FISH studies revealed 47 (46%) had hyperdiploidy without a recurrent primary IgH rearrangement, 31 (30%) had t(11;14), 13 (13%) had t(4;14), 5 (5%) had 14;16 or 14;20, 3 (3%) had hyperhaploidy and 3 (3%) had an undefined primary. 54 (53%) had 1q gain/amp, 22 (22%) had TP53 deletion, 22 (22%) had a MYC rearrangement and 71% had high mSMART risk. Nearly all patients received an immunomodulatory compound, a proteasome inhibitor and dexamethasone. 2 (2%) had complete response (CR), 10 (9.8%) very good partial response (VGPR), 36 (35%) had partial response (PR), 14 (14%) had minimal response (MR), 13 (13%) had stable disease (SD) and 17 (17%) had progressive disease (PD). Characterization of CD45+ cells identified a relatively conserved and reproducible map from each patient. Notable differences included an ~2-fold reduction in the percentage of total B cells (CD45+,CD3-,CD19+)/total CD45+ cells in cases with high risk mSMART, RRMM and TP53 deletion compared to cases with standard risk, NDMM or normal TP53 status. Similar B-cell reductions were found in RRMM vs. NDMM samples from matched-patients. In contrast to the conserved t-SNE structure of the CD45+ population, the neoplastic PC population displayed dramatically reduced t-SNE structural consistency. Heterogeneity between patient samples and between the same patient samples over time was observed. We focused our analysis on 22 patients with serial samples. The proportion of each t-SNE group present in each patient sample was calculated and then correlated to the 90-day response metric. We identified a phenotypic group whose proportion increased in relation to disease progression (R2=0.85). This group had elevated BCL-2, pSTAT3, CD56 levels and reduced CD45 and CD81 levels. Evaluating individual markers, we found an increase in the proportion of cells with elevated BCL-2, pS6, Ki67, and IKZF1 levels in relation to disease progression. We also observed an increase in the proportion of cells with reduced pCREB levels and a reduction in the proportion of cells with reduced CD147 levels in relation to disease progression. Conclusions: We have utilized CyTOF to characterize phenotypic and functional markers in MM cells on a single cell level and can identify unique subgroups that change in relation to disease progression. Future analysis will correlate phenotypic signatures with ISS stage, mSMART risk, cytogenetic abnormality and type of treatment. Figure 1 Disclosures Kumar: Kite Pharma: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; MedImmune: Research Funding; Karyopharm: Consultancy; Merck: Consultancy, Research Funding; Carsgen: Other, Research Funding; Cellectar: Other; Novartis: Research Funding; Adaptive Biotechnologies: Consultancy; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genecentrix: Consultancy; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Tenebio: Other, Research Funding; BMS: Consultancy, Research Funding; Dr. Reddy's Laboratories: Honoraria.