Citations

Currently, there are no internationally accepted consensus guidelines for pathologic evaluation of posttherapy pancreatectomy specimens. The Neoadjuvant Therapy Working Group of Pancreatobiliary Pathology Society was formed in 2018 to review grossing protocols, literature, and major issues and to develop recommendations for pathologic evaluation of posttherapy pancreatectomy specimens. The working group generated the following recommendations: (1) Systematic and standardized grossing and sampling protocols should be adopted for pancreatectomy specimens for treated pancreatic ductal adenocarcinoma (PDAC). (2) Consecutive mapping sections along the largest gross tumor dimension are recommended to validate tumor size by histology as required by the College of American Pathologists (CAP) cancer protocol. (3) Tumor size of treated PDACs should be measured microscopically as the largest dimension of tumor outer limits that is bound by viable tumor cells, including intervening stroma. (4) The MD Anderson grading system for tumor response has a better correlation with prognosis and better interobserver concordance among pathologists than does the CAP system. (5) A case should not be classified as a complete response unless the entire pancreas, peripancreatic tissues, ampulla of Vater, common bile duct, and duodenum adjacent to the pancreas are submitted for microscopic examination. (6) Future studies on tumor response of lymph node metastases, molecular and/or immunohistochemical markers, as well as application of artificial intelligence in grading tumor response of treated PDAC are needed. In summary, systematic, standardized pathologic evaluation, accurate tumor size measurement, and reproducible tumor response grading to neoadjuvant therapy are needed for optimal patient care. The criteria and discussions provided here may provide guidance towards these goals.

AbstractIntroductionHarboring two copies of the apolipoprotein E (APOE) ε2 allele strongly protects against Alzheimer's disease (AD). However, the effect of this genotype on gray matter (GM) volume in cognitively unimpaired individuals has not yet been described.MethodsMulticenter brain magnetic resonance images (MRIs) from cognitively unimpaired ε2 homozygotes were matched (1:1) against all other APOE genotypes for relevant confounders (n = 223). GM volumes of ε2 genotypic groups were compared to each other and to the reference group (APOE ε3/ε3).ResultsCarrying at least one ε2 allele was associated with larger GM volumes in brain areas typically affected by AD and also in areas associated with cognitive resilience. APOE ε2 homozygotes, but not APOE ε2 heterozygotes, showed larger GM volumes in areas related to successful aging.DiscussionIn addition to the known resistance against amyloid‐β deposition, the larger GM volumes in key brain regions may confer APOE ε2 homozygotes additional protection against AD‐related cognitive decline.

SummaryBackgroundTofacitinib is an oral, small molecule Janus kinase inhibitor for the treatment of ulcerative colitis. We present final data from OCTAVE Open, an open‐label, long‐term extension study.AimsThe primary objective of OCTAVE Open was to assess the safety and tolerability of long‐term tofacitinib in patients with ulcerative colitis; evaluating efficacy was a secondary objective.MethodsEligible patients included OCTAVE Induction 1&2 non‐responders and OCTAVE Sustain completers/treatment failures. Patients in remission at OCTAVE Open baseline received tofacitinib 5 mg b.d.; all others received 10 mg b.d. Incidence rates (unique patients with events/100 patient‐years) for adverse events of special interest were calculated; ≤7.0 years of observation. Efficacy endpoints derived from Mayo score were reported ≤36 months (last scheduled endoscopy visit).ResultsIn OCTAVE Open, 769 of 944 patients (81.5%) initially received tofacitinib 10 mg b.d. Among all patients (2440.8 patient‐years of exposure), incidence rates (IRs; 95% confidence intervals) for deaths and adverse events of special interest were: deaths, 0.25 (0.09‐0.54); serious infections, 1.61 (1.14‐2.20); herpes zoster (non‐serious and serious), 3.16 (2.47‐3.97); opportunistic infections, 0.87 (0.54‐1.33); major adverse cardiovascular events, 0.16 (0.04‐0.42); malignancies (excluding non‐melanoma skin cancer), 1.03 (0.67‐1.52); non‐melanoma skin cancer, 0.75 (0.45‐1.19); deep vein thrombosis, 0.04 (0.00‐0.23); pulmonary embolism, 0.21 (0.07‐0.48). At Month 36, 66.9% and 40.3% showed clinical response, 64.6% and 37.1% had endoscopic improvement, and 58.9% and 33.7% maintained or achieved remission, with tofacitinib 5 and 10 mg b.d. respectively.ConclusionTofacitinib demonstrated consistent safety up to 7.0 years. Data collected up to Month 36 support long‐term efficacy beyond the 52‐week maintenance study.

AbstractIntroductionCaregivers of patients with frontotemporal lobar degeneration (FTLD) spectrum disorders experience tremendous burden, which has been associated with the neuropsychiatric and behavioral features of the disorders.MethodsIn a sample of 558 participants with FTLD spectrum disorders, we performed multiple‐variable regressions to identify the behavioral features that were most strongly associated with caregiver burden, as measured by the Zarit Burden Interview, at each stage of disease.ResultsApathy and disinhibition, as rated by both clinicians and caregivers, as well as clinician‐rated psychosis, showed the strongest associations with caregiver burden, a pattern that was consistent when participants were separated cross‐sectionally by disease stage. In addition, behavioral features appeared to contribute most to caregiver burden in patients with early dementia.DiscussionCaregivers should be provided with early education on the management of the behavioral features of FTLD spectrum disorders. Interventions targeting apathy, disinhibition, and psychosis may be most useful to reduce caregiver burden.

Abstract Background Multiple myeloma (MM) evolves from monoclonal gammopathy of undetermined significance (MGUS), a clinically detectable but asymptomatic premalignant phase seen in ~3% of the general population 50 years of age or older. The prevalence of MGUS has not been described in a population at high risk of developing MM, specifically Black/African American (AA) individuals or first-degree relatives of patients with hematologic malignancies (HM). In 2019, we launched the first nationwide US screening study for individuals at high risk of MM to help better identify what population would benefit most from screening and early intervention for precursor MM stages. We aim to assess the prevalence of MGUS in a population at high risk of MM and characterize clinical variables of individuals who screen positive. Here, we report interim screening data on the first 2,960 participants. Methods Individuals aged 40 or older with an additional MM risk factor are eligible to be screened in the PROMISE Study. High-risk individuals include Black/AAs and those with a first-degree relative diagnosed with a hematologic malignancy or a precursor condition to MM. Blood from all participants was analyzed via serum protein electrophoresis, immunofixation, and Optilite® to measure the serum free light chains (sFLC), IgG, IgA and IgM. Results were returned to all participants, and those who tested positive for a monoclonal gammopathy (MGUS/SMM) were referred to a hematologist for clinical follow-up and invited to periodically complete epidemiologic exposure and psychosocial questionaries, including a 4-item cancer worry questionnaire and the RAND 36-item Short Form Survey (SF-36). To investigate the use of the higher-sensitivity matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) with the Optilite® IgG, IgA, IgM and sFLC results as a screening test for all participants, we rescreened 1,092 samples from PROMISE. The Binding Site Group proprietary software was used for the analysis of the combined MS/Optilite® results, allowing for the detection and quantification of M-protein. Heavy-Chain MGUS (HC-MGUS) was defined by the presence of one or more paired heavy and light chain monoclonal peaks detected by MS. Pairing was based on mass to charge ratio of identified peaks. To enrich the PROMISE cohort with Black/AA individuals, we identified and screened 1,868 Black/AA additional individuals from the Mass General Brigham (MGB) Biobank who met the PROMISE enrollment criteria. Screening was performed by MS/Optilite®, and results have not been returned to participants. Results We screened 2,960 participants with the combined MS/Optilite® approach. We report here the prevalence of HC-MGUS and plan on presenting the estimated rate of light chain MGUS in our cohort, at the meeting. We detected HC-MGUS in 9.6% (95% CI: 8.6-11%) of our cohort, with a prevalence of 10% (95% CI: 8.3-12%) in the PROMISE cohort and 9.4% (95% CI: 8.1-11%) in the MGB cohort (Table 1 and Figure 1). HC-MGUS prevalence increased with age in high-risk individuals from 4.9% (CI: 3.3-6.9%) for participants aged 40-49 to 13% (CI: 10-17%) in the 70-79 range (P < 1.2E-5). Among monoclonal HC-MGUS, we found 65% IgG, 18% IgM, and 18% IgA. M-spike was quantified in 97% of samples. Median M-spike concentration was, 0.058g/dL (max. 2.6g/dL) for IgG, 0.0043g/dL (max. 0.6g/dL) for IgM, and 0.067g/dL (max. 0.8g/dL) for IgA. In the Promise cohort, no significant change in cancer worry was observed across the pre- and post-screening interval among participants who screened positive (P = 0.52). Health-related quality of life, as measured by the SF-36, was not significantly different in screen-positive vs. screen-negative individuals for any of the eight subscales (all P > 0.20). Conclusions We present the largest dataset on monoclonal gammopathy prevalence and screening in individuals at high risk for MM, and more specifically the largest cohort of Black/AA, using a novel high-sensitivity testing approach. Our results confirm that older adults who are Black/AA or have a first-degree relative with an HM have a high prevalence MGUS and may benefit from precision screening approaches to allow for early detection and clinical intervention. Preliminary data on cancer worry and quality of life indicates that the psychosocial burden of screening in this population is likely minimal. Figure 1 Figure 1. Disclosures Sakrikar: The Binding Site: Current Employment. Krause: The Binding Site: Current Employment. Barnidge: The Binding Site: Current Employment. Bustoros: Takeda: Consultancy, Honoraria; Janssen, Bristol Myers Squibb: Honoraria, Speakers Bureau. Perkins: The Binding Site: Current Employment. Harding: The Binding Site: Current Employment, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties. Kapoor: Ichnos Sciences: Research Funding; Amgen: Research Funding; Pharmacyclics: Consultancy; Takeda: Research Funding; Sanofi: Consultancy; Regeneron Pharmaceuticals: Research Funding; AbbVie: Research Funding; BeiGene: Consultancy; Sanofi: Research Funding; Karyopharm: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy. Mo: Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Epizyme: Consultancy; Eli Lilly: Consultancy; Janssen: Honoraria; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees. Murray: The Binding Site: Patents & Royalties: Potential Royalties for use of mass spectrometry in M-protein detection. Getz: Scorpion Therapeutics: Consultancy, Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees; IBM, Pharmacyclics: Research Funding. Marinac: JBF Legal: Consultancy; GRAIL Inc: Research Funding. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy.

Abstract Background: Autologous stem cell transplantation (ASCT) in multiple myeloma (MM) has been shown to improve survival compared to conventional chemotherapy alone. However, the ability to perform ASCT relies, in part, on collecting a sufficient number (#) of CD34+ hematopoietic stem cells (HSCs), typically from peripheral blood. The ideal HSC mobilization regimen would enable collection of optimal #s of HSCs (5-6x10 6 CD34+ cells/kg) within the minimum # of apheresis sessions possible. Yet, despite currently available G-CSF (G) based mobilization regimens and multiple apheresis days, many remain unable to collect optimal #s of HSCs. Motixafortide (M) is a novel CXCR4 inhibitor, with high affinity (IC 50 0.54-4.5 nM) and long receptor occupancy (>48 hours). Methods: In this prospective, phase 3, double blind, placebo controlled, multicenter trial, 122 patients were randomized (2:1) to receive either M+G or placebo (P)+G for HSC mobilization prior to ASCT for MM. All patients received G (10 mcg/kg) on days 1-5 (and 6-8, if needed). Patients received either M (1.25 mg/kg, subcutaneous injection) or P on day 4 (and 6, if needed). Apheresis began day 5, with the primary (PEP) and secondary (SEP) endpoints of collecting ≥6x10 6 CD34+ cells/kg in up to 2 apheresis days or 1 day, respectively. Apheresis continued on days 6-8 if needed. Total CD34+ cells/kg were analyzed on site to determine if patients mobilized to the goal and all samples were subsequently sent for assessment by central laboratory. Patients that did not collect ≥2x10 6 CD34+ cells/kg by day 8 proceeded to rescue mobilization. The # of CD34+ cells infused was determined independently by each investigator according to local practice (minimum ≥2x10 6 CD34+ cells/kg). Analyses of the PEP/SEPs were performed on an intent-to-treat basis. Results: Demographics between the 2 treatment arms were similar. Mobilization with M+G resulted in 92.5% of patients collecting ≥6x10 6 CD34+ cells/kg within 2 apheresis days vs 26.2% with P+G (Odds Ratio (OR) 53.3, 95% CI 14.12-201.33, p<0.0001). Furthermore, 88.8% of patients with M+G collected ≥6x10 6 CD34+ cells/kg in 1 apheresis day vs 9.5% with P+G (OR 118.0, 95% CI 25.36-549.35, p<0.0001); and 96.3% with M+G collected ≥2x10 6 CD34+ cells/kg within 1 apheresis day vs 64.3% with P+G (OR 18.9, 95% CI 4.47-80.04, p<0.0001). The PEP and SEPs were confirmed as statistically significant by central laboratory (all respective p-values <0.0001). The median # of HSCs mobilized in 1 apheresis day with M+G was 10.80x10 6 CD34+ cells/kg vs 2.14x10 6 CD34+ cells/kg with P+G. The # of cells infused was determined independently by each investigator according to local practice. Median time to neutrophil engraftment was 12 days in both arms (HR 0.94, 95% CI 0.62-1.41, p=0.75). Median time to platelet engraftment was 18 days (range: 17-19) with M+G and 17 days (range: 17-18) with P+G (HR 0.89, 95% CI 0.59-1.34, p=0.57). Graft durability at day 100 post-ASCT was 92.2% in the M+G arm and 91.9% in the P+G arm (OR 1.04, 95% CI 0.2-4.5, p=0.96). Overall, adverse events were reported in 98.8% (Grade 3/4: 68.8%) of patients with M+G vs 95.2% (Grade 3/4: 42.9%) with P+G, with cytopenias in the post-ASCT period prior to engraftment accounting for the majority of Grade 3/4 AEs in both arms, as expected. The most common AEs related to M included: local injection site reactions (any grade: 70.0%, Grade 3/4: 11.3%); and systemic reactions such as pruritis (33.8%), flushing (32.5%) and urticaria (12.5%). Additionally, mobilization with M+G resulted in a 10.5x increase in mean absolute # of CD34+CD45RA-CD123loCD38-CD90+CD49f+ primitive HSCs collected vs P+G (p<0.0001). Multicolor FACS and scRNA sequencing of CD34+ HSCs from both arms will be reported in a separate ASH abstract. Conclusions: A single injection of M on top of G significantly increased the proportion of patients mobilizing ≥6x10 6 CD34+ cells/kg for ASCT (92.5%) vs G (26.2%) in up to 2 apheresis days (p<0.0001), while enabling 88.8% to collect ≥6x10 6 CD34+ cells/kg in just 1 apheresis (p<0.0001, Figure 1A). Despite the higher # of cells mobilized by M+G, the # of CD34+ cells/kg infused was determined independently by each investigator according to local practice with comparable engraftment kinetics and graft durability between the 2 arms. Finally, M+G mobilized 10.5x more immunophenotypically primitive CD34+ HSCs capable of durable multilineage hematopoietic engraftment vs P+G (p<0.0001, Figure 1B). Figure 1 Figure 1. Disclosures Crees: BioLineRx Ltd.: Research Funding. Larson: TORL biotherapeutics: Current holder of individual stocks in a privately-held company; Bioline: Research Funding; Abbvie: Research Funding; BMS: Research Funding; Celgene: Research Funding; GSK: Research Funding; Janssen: Research Funding; Juno: Research Funding; Novartis: Research Funding; Pfizer: Research Funding; Takeda: Research Funding. Illés: Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees. Stiff: Incyte: Research Funding; Cellectar: Research Funding; Seagen: Research Funding; Gamida Cell: Research Funding; Cellectar: Research Funding; Actinium: Research Funding; Bristol Myers Squibb: Research Funding; BioLineRX: Research Funding; Macrogenics: Research Funding; CRISPR Therapeutics: Consultancy, Honoraria; Amgen: Research Funding; Janssen: Research Funding; Kite, a Gilead Company: Research Funding; Karyopharm: Consultancy, Honoraria; MorphoSys: Consultancy, Honoraria. Sborov: Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Consultancy; Sanofi: Consultancy; SkylineDx: Consultancy. Pereira: Jazz Pharmaceutical: Membership on an entity's Board of Directors or advisory committees. Mikala: Novartis: Consultancy; Takeda: Consultancy; Abbvie: Consultancy; Krka: Consultancy; Janssen: Consultancy; Amgen: Consultancy; Celgene: Consultancy. Holtick: Celgene: Honoraria; Sanofi: Honoraria. Qazilbash: Amgen: Research Funding; Oncopeptides: Other: Advisory Board; Bristol-Myers Squibb: Other: Advisory Board; Biolline: Research Funding; Angiocrine: Research Funding; NexImmune: Research Funding; Janssen: Research Funding. Hardy: American Gene Technologies, International: Membership on an entity's Board of Directors or advisory committees; Kite/Gilead: Membership on an entity's Board of Directors or advisory committees; InCyte: Membership on an entity's Board of Directors or advisory committees. Vainstein: BioLineRx LTD: Current Employment. Sorani: BioLineRx LTD: Current Employment. Gliko-Kabir: BioLineRx Ltd.: Current Employment. Goldstein: BioLineRx Ltd.: Current Employment. Kadosh: BioLineRx Ltd.: Current Employment.

Abstract Introduction: Multiple Myeloma (MM) is an incurable plasma cell malignancy commonly preceded by the asymptomatic stage smoldering multiple myeloma (SMM). MM is characterized with significant genomic heterogeneity of chromosomal gains and losses (CNVs), translocations, and point mutations (SNVs); alterations that are also observed in SMM patients. However, current SMM risk models rely solely on clinical markers and do not accurately capture progression risk. While incorporating some genomic biomarkers improves prediction, using all MM genomic features to comprehensively stratify patients may increase risk stratification precision in SMM. Methods: We obtained a total of 214 patient samples at SMM diagnosis. We performed whole-exome sequencing on 166 tumors; of these, RNA sequencing was performed on 100. Targeted capture was done on 48 additional tumors. Upon binarization of DNA features, we performed consensus non-negative matrix factorization to identify distinct molecular clusters. We then trained a random forest classifier on translocations, SNVs, and CNVs. The predicted clinical outcomes for the molecular subtypes were further validated in an independent SMM cohort of 74 patients. Results: We identified six genomic subtypes, four with hyperdiploidy (>48 chromosomes, HMC, HKR, HNT, HNF) and two with IgH translocations (FMD, CND) (Table 1). In multivariate analysis accounting for IMWG (20-2-20) clinical risk stages, high-risk (HMC, FMD, HKR) and intermediate-risk (HNT, HNF) genetic subtypes were independent predictors of progression (Hazards ratio [HR]: 3.8 and 5.5, P = 0.016 and 0.001, respectively). The low-risk, CND subtype harboring translocation (11;14) was enriched for the previously defined CD-2 MM signature defined by the B cell markers CD20 and CD79A (FDR = 0.003 ), showed upregulation of CCND1, E2F1, and E2F7 (FDR = 0.01, 0.0004, 0.08), and was enriched for G2M checkpoint, heme metabolism, and monocyte cell signature (FDR = 0.003, 0.003, 0.003, respectively). The FMD subtype with IgH translocations (4;14) and (14;16) was enriched for P53, mTORC1, unfolded protein signaling pathways and plasmacytoid dendritic cell signatures (FDR = 0.01, 0.005, 0.008, respectively). The HKR tumors were enriched for inflammatory cytokine signaling, MYC target genes, T regulatory cell signature, and the MM proliferative (PR) signatures (FDR = 0.02, 0.03, 0.007, 0.02, respectively). The APOBEC mutational signature was enriched in HMC and FMD tumors (P = 0.005), while there was no statistical difference across subtypes in the AID signature. The median follow-up for the primary cohort is 7.1 years. Median TTP for patients in HMC, FMD, and HKR was 3.8, 2.6, and 2.2 years, respectively; TTP for HNT and HNF was 4.3 and 5.2, respectively, while it was 11 years in CND patients (P = 0.007). Moreover, by analyzing the changes in MM clinical biomarkers over time, we found that patients from high-risk subgroups had higher odds of developing evolving hemoglobin and monoclonal protein levels over time (P = 0.01 and 0.002, respectively); Moreover, the absolute increase in M-protein was significantly higher in patients from the high-risk genetic subtypes at one, two, and five years from diagnosis (P = 0.001, 0.03, and 0,01, respectively). Applying the classifier to the external cohort replicated our findings where intermediate and high-risk genetic subgroups conferred increased risk of progression to MM in multivariate analysis after accounting for IMWG staging (HR: 5.5 and 9.8, P = 0.04 and 0.005, respectively). Interestingly, within the intermediate-risk clinical group in the primary cohort, patients in the high-risk genetic subgroups had increased risk of progression (HR: 5.2, 95% CI 1.5 - 17.3, P = 0.007). In the validation cohort, these patients also had an increased risk of progression to MM (HR: 6.7, 95% CI 1.2 - 38.3, P = 0.03), indicating that molecular classification improves the clinical risk-stratification models. Conclusion: We identified and validated in an independent dataset six SMM molecular subgroups with distinct DNA alterations, transcriptional profiles, dysregulated pathways, and risks of progression to active MM. Our results underscore the importance of molecular classification in addition to clinical evaluation in better identifying high-risk SMM patients. Moreover, these subgroups may be used to identify tumor vulnerabilities and target them with precision medicine efforts. Figure 1 Figure 1. Disclosures Bustoros: Janssen, Bristol Myers Squibb: Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria. Casneuf: Janssen: Current Employment. Kastritis: Amgen: Consultancy, Honoraria, Research Funding; Takeda: Honoraria; Pfizer: Consultancy, Honoraria, Research Funding; Genesis Pharma: Honoraria; Janssen: Consultancy, Honoraria, Research Funding. Walker: Bristol Myers Squibb: Research Funding; Sanofi: Speakers Bureau. Davies: Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Dimopoulos: Amgen: Honoraria; BMS: Honoraria; Takeda: Honoraria; Beigene: Honoraria; Janssen: Honoraria. Bergsagel: Genetech: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Patents & Royalties: human CRBN mouse; GSK: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Yong: BMS: Research Funding; Autolus: Research Funding; Takeda: Honoraria; Janssen: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; GSK: Honoraria; Amgen: Honoraria. Morgan: BMS: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees. Getz: IBM, Pharmacyclics: Research Funding; Scorpion Therapeutics: Consultancy, Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy.

Abstract Background: CD34+ hematopoietic stem and progenitor cell (HSPC) dose during hematopoietic cell transplantation (HCT) remains one of the most reliable clinical parameters to predict quality of engraftment. A minimum HSPC dose of 2-2.5x10 6 CD34+ cells/kg is considered necessary for reliable engraftment, while optimal doses of 5-6x10 6 CD34+ cells/kg are associated with faster engraftment, as well as fewer transfusions, infections, and antibiotic days. CXCR4 inhibition significantly improves the number (#) of CD34+ HSPCs mobilized for HCT, when added to G-CSF (G). Motixafortide (M), a novel CXCR4 antagonist, is a potent mobilizer of HSPCs recently evaluated in the phase 3, double blind, placebo controlled, multicenter GENESIS Trial as a mobilizing agent prior to autologous HCT (ASCT) in multiple myeloma (MM). Methods: Patients received G (10 mcg/kg) on days 1-5 (and days 6-8, if needed). On day 4 (and day 6, if needed), patients received either M (1.25 mg/kg) or placebo (P). Apheresis began day 5, with up to 4 days of apheresis if needed. The primary and secondary endpoints were collection of ³6x10 6 CD34+ cells/kg in up to 2 days of apheresis or 1 day, respectively. The # of CD34+ cells/kg infused was determined independently by each investigator according to local practice, but a minimum of ³2x10 6 CD34+ cells/kg was required. A post-hoc analysis was performed pooling data from both arms to evaluate time to platelet engraftment (TPE) (≥20x10 9/L without transfusions x7 days) and neutrophil engraftment (TNE) (ANC ≥0.5x10 9/L x3 days) based on total # of CD34+ cells/kg and # of specific CD34+ HSPC subsets infused. CD34+ HSPC immunophenotyping was performed via multicolor fluorescence-activated cell sorting (FACS). TPE/TNE was analyzed using Kaplan-Meier curves and Cox proportional hazards model. Results: 114 MM patients underwent apheresis, ASCT and were evaluable (M+G N=77; P+G N=37). M+G mobilization yielded a median of 10.8x10 6 CD34+ cells/kg collected in 1 apheresis vs 2.3x10 6 CD34+ cells/kg with P+G (p<0.0001). M+G also resulted in mobilization of higher #s of relevant CD34+ HSPC subsets vs P+G, including 5.6 fold more HSCs (CD45RA-CD123loCD38+CD90+CD49f+) (p<0.0001), 3.5 fold more multipotent progenitors (MPPs) and common myeloid progenitors (CMPs) (CD45RA-CD123loCD38+CD90-CD49f+) (p=0.0004) and 5.6 fold more granulocyte and macrophage progenitors (GMPs) (CD45RA+CD123loCD38+/-CD10-) (<0.0001). The median # of infused HSPCs in both arms was <6x10 6 CD34+ cells/kg (Table 1), with similar TPE of 17-18 days (HR 0.89, 95% CI 0.59-1.34, p=0.57) and TNE of 12 days (HR 0.94, 95% CI 0.62-1.41, p=0.75). However, pooled analysis of all patients (N=114) revealed infusion of ³6x10 6 CD34+ cells/kg was associated with faster median TPE of 16 days vs 18 days with <6x10 6 CD34+ cells/kg (HR 0.63, 95% CI 0.41-0.96, p=0.03) (Figure 1A). Further analysis demonstrated an inverse correlation between increasing CD34+ cells/kg infused and TPE (Pearson r=-0.2789, p=0.0027). In addition, pooled analysis of 36 patients (M+G N=24; P+G N=12) using extended multicolor FACS revealed infusion of higher #s (>75 th percentile) of combined CD34+ HSC, MPP, CMP and GMP subsets was associated with faster TPE of 12 days vs 19 days with lower #s of these subsets (p=0.003) (Figure 2A). Furthermore, higher #s (>75 th percentile) of GMPs was individually associated with faster TPE of 13 days vs 19 days with lower GMP cell doses (p=0.0116) (Figure 2C). TNE was not impacted by increasing doses of total CD34+ HSPCs or any specific CD34+ HSPC subset (all p>0.05) (Figures 1B, 2B and 2D). Conclusions: M+G mobilization enabled significantly more CD34+ cells to be collected in 1 apheresis (median 10.8x10 6 CD34+ cells/kg) vs P+G (2.3x10 6 CD34+ cells/kg), as well as 3.5-5.6 fold higher #s of HSCs, MPPs, CMPs and GMPs (all p-values <0.0004). This high # of CD34+ cells/kg mobilized with M+G enables the potential infusion of ≥6x10 6 CD34+ cells/kg and cryopreservation of cells for later use. A dose response was observed with significant correlation between faster TPE and infusion of higher #s of total CD34+ HSPC doses (³6x10 6 CD34+ cells/kg) and combined HSC, MPP, CMP and GMP subsets. Additionally, infusion of higher #s of CD34+ GMP subsets was independently associated with faster TPE, suggesting these more committed progenitors may play a critical role in early engraftment. Figure 1 Figure 1. Disclosures Crees: BioLineRx Ltd.: Research Funding. Retting: BioLineRx Ltd.: Research Funding. Larson: TORL biotherapeutics: Current holder of individual stocks in a privately-held company; Abbvie, Bioline, BMS, Celgene, GSK, Janssen, Juno, Novartis, Pfizer, Takeda: Research Funding. Illes: Novartis, Janssen, Pfizer, Roche: Other: Travel, Accommodations, Expenses; Takeda, Seattle Genetics: Research Funding; Janssen, Celgene, Novartis, Pfizer, Takeda, Roche: Consultancy. Stiff: CRISPR: Consultancy; Gamida-Cell, Atara, Amgen, Incyte, Takeda, Macrogenetics, Eisai: Research Funding. Sborov: SkylineDx: Consultancy; GlaxoSmithKline: Consultancy; Sanofi: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees. Pereira: Jazz Pharmaceutical: Membership on an entity's Board of Directors or advisory committees. Mikala: Abbvie: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Krka: Consultancy; Novartis: Consultancy; Takeda: Consultancy. Holtick: Sanofi: Honoraria; Celgene: Honoraria. Qazilbash: Janssen: Research Funding; Oncopeptides: Other: Advisory Board; Biolline: Research Funding; Bristol-Myers Squibb: Other: Advisory Board; NexImmune: Research Funding; Amgen: Research Funding; Angiocrine: Research Funding. Hardy: Kite/Gilead: Membership on an entity's Board of Directors or advisory committees; American Gene Technologies, International: Membership on an entity's Board of Directors or advisory committees; InCyte: Membership on an entity's Board of Directors or advisory committees. Sorani: BioLineRx LTD: Current Employment. Shemesh-Darvish: BioLineRx LTD: Current Employment. Vainstein: BioLineRx LTD: Current Employment; Enlivex: Consultancy. Kadosh: StatExcellence: Current holder of individual stocks in a privately-held company; BioLineRx: Honoraria.