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Abstract Chimeric antigen receptor (CAR) T-cell therapy has demonstrated remarkable response rates in relapsed/refractory aggressive B-cell non-Hodgkin's lymphoma. However, durable remissions occur in only 40% of treated patients, highlighting mechanisms of therapeutic resistance and immune escape. While cytotoxicity is principally executed by CAR T-cells, monocytes shape CAR-T cell efficacy and orchestrate cytokine-driven immunity. In this study, we defined distinct metabolic profiles of T-cell and monocyte subsets based on clinical response. Single-cell RNA sequencing (scRNA-seq) and T-cell receptor sequencing (scTCR-seq) were performed on peripheral blood mononuclear cells at three timepoints: before lymphodepletion (BL), at peak CAR-T expansion (PK), and one-month post-infusion (M1). Data were processed with CellRanger v7.0.1 and analyzed with the immunopipe pipeline (Wang et al., 2025). Seurat v4.3.0 was utilized for unsupervised hierarchical clustering analysis; subsets identified included classical monocytes (CM), intermediate monocytes (IM), non-classical monocytes (NM), and monocytic myeloid derived suppressor cells (mMDSC). Metabolic profiles were compared across patients achieving ≥6-month complete remission (CR, n=16), primary refractory disease (PD1, n=4), or relapsed after a prior response (PD2, n=12). A total of 107035 T cells and 129981 monocytes from 77 serial samples in 32 patients were analyzed. CR patients had a higher T-cell:monocyte ratio than PD1/PD2 at all time points, especially at BL and PK (BL 1.2 vs 0.4, p=0.011; PK 1.3 vs 0.3, p=0.027). Clinical responses were compared with metabolic pathway analysis and identified oxidative phosphorylation (OXPHOS) as the dominant pathway. OXPHOS was consistently enriched in PD cohorts across T-cell subsets, particularly in PD1 vs CR at BL (mucosal-associated invariant T-cell (MAIT) and T peripheral memory (Tpm)), and at PK (CD4/CD8 memory precursor effector cells (MPEC) and activated MPECs (MPECa), CD4 T-helper 1 proliferating (Th1p), CD4 Th2 activated (Th2a), regulatory T-cell (Treg), CD8 naive senescent (CD8NS), CD8 T effector memory (Tem) tumor recirculating (TR), CD8 Tpm, CD8 T resident memory (Trm) TR and MAIT Tpm). By M1, OXPHOS enrichment in CD4/CD8MPECa, CD4Th2a, CD8NS, CD8TemTR reversed, now predominant in CR although CD8Tpm and CD8TrmTR remained enriched in PD1. In the monocyte subsets at BL, PD2 showed OXPHOS enrichment in CD163+ monocytes (mono), IM IL1, mMDSC SIRPA, mMDSC TGFβ, and CM IL6 subsets compared to PD1 and CR, while PD1 showed OXPHOS enrichment in IM CD38, CM TGFβ, and mMDSC HIF1A vs CR and PD2. This persisted at PK. By M1, the pattern reversed and mirrored that of T-cells, with CR patients showing OXPHOS enrichment in CD163+mono, CM IL6, CM TGFβ, IM CD38, mMDSC HIF1A, mMDSC SIRPA and mMDSC TGFβ, and additionally in CM EMT, CM p53, NM, NM CD36 vs PD1/PD2. Glycolysis/gluconeogenesis (GLY) was also enriched across subsets. In T-cells, PD1 vs CR showed GLY enrichment in CD4Th2a, CD8Tpm, CD8Tpm proliferating and MAIT Tpm at PK. In monocytes, GLY was enriched in PD1/2 vs CR at BL (CD163+mono, CM IL6) and PK (CD163+mono, IM CD18, mMDSC SIRPA). By M1, GLY metabolism was enriched in CR vs PD1/PD2 in CD163+mono, CM IL6, mMDSC SIRPA. Additional GLY enriched subsets at CR vs PD1 included CM, CM p53, EMT, IM CD38, IM IL1, mMDSC HIF1A, NM, NM CD36. Inositol phosphate metabolism (IP) was predominantly enriched in PD2 vs CR at BL (CD8NS, CD8Tcm, CD8Tpm activated), PK (CD4Th2, CD8NS, CD8Tem TR, CD8Tpm proliferating, γδT Tem) and M1 (CD4/CD8 MPECa, CD4 Th1/Th2, CD8NS, CD8Tpm, CD8 Tpm proliferating, Treg and MAIT Tpm). Notably, Treg was the only T-cell subset enriched for IP at PK in CR vs PD1/PD2. Additionally, the TCA cycle was enriched in PD1 Tregs and Th2 cells at BL and PK vs CR/PD2. A higher T-cell:monocyte ratio in CR vs PD1/PD2 supports prior evidence that elevated pre-lymphodepletion lymphocyte:monocyte ratios predict better outcomes. We identified distinct metabolic signatures in T-cells and monocytes between CR and PD1/PD2. OXPHOS enrichment in T-cells and monocytes at M1 in CR patients may reflect oxidative programming as a hallmark of sustained anti-tumor immunity. Conversely, GLY enrichment in PD1 T-cells at PK may reflect short-lived effector states lacking persistence. Overall, these findings highlight metabolic profiling as a promising predictive biomarker and therapeutic programming target to enhance CAR T-cell outcomes.

Abstract Introduction: Reporting patient outcomes by CAR-T treatment centers is part of the accreditation requirement under the FACT (Foundation for Accreditation of Cell Therapy) Immune Effector Cell (IEC) Program standard. Currently, this is a time-consuming and manual process, making it increasingly difficult to sustain with the growing CAR-T applications and patient volume. The objective of this study is to evaluate how a Large Language Model (LLM) can be used to automate the abstraction and summarization of medical record for CAR-T toxicities. Methods: Clinical data from patients treated with CAR-T between January 2018 and June 2025, including hematology clinical notes, lab results, flowsheets, vital signs, and medication administration record, were used as the source of patient information. The American Society of Transplant and Cell Therapy (ASTCT) CAR-T toxicity grading guideline for cytokine release syndrome (CRS) and immune effector cell associated neurologic syndrome (ICANS) were used to define these toxicities. With the large context window of the LLM (Gemini 2.5 pro), we created a prompt by embedding both the patient data and the ASTCT guidelines for CRS and ICANS, along with an outline of specific information we aimed to abstract from the data. Additionally, the LLM was instructed to provide contextual justification for the data it extracted from patient information. The LLM-generated output included event onset date, resolution date, maximum grade, date of maximum grade, and medications given for management. The CRS and ICANS outcome reports generated by the LLM were then compared to the IEC compliance program data. Any discrepancies identified were reviewed manually. Results: Among patients (pt) treated with CAR-T in the specified timeframe, 47 were selected as training cohort. This cohort included pt with toxicities events, no events, and a mix of events of varying grades. For the test cohort, 66 pts who received CAR-T from March to June 2025 were included. Demographics for the training and test cohorts are reflective of evolving clinical practice (training, test cohorts: median age 69, 65; male 55%, 74%; lymphoma/leukemia 66%, 48%; multiple myeloma 34%, 52%; CD19 CAR-T 46%, 50%). Compared to data from the IEC compliance program, the LLM-generated summaries for CRS events demonstrated an accuracy of 90%, precision 95%, sensitivity 100%, specificity 80%, F1 score 97%, and Matthew's correlation coefficient 87%. For ICANS event, the LLM achieved an accuracy of 91%, precision 92%, sensitivity 92%, specificity 90%, F1 score 92%, Matthew's correlation coefficient 83%. Maximum grade, for both CRS and ICANS, were identified with >90% accuracy. However, dates for CRS and ICANS were less accurate, with the lowest accuracy noted in identifying the event resolution date, 45% for CRS and 67% for ICANS. Medical records were reviewed for all discrepancies between the LLM and the IEC Compliance Program data. The most common discrepancy was a mismatch in event resolution date, determined to be due to differing criteria used by the compliance team and the LLM prompt. Of note, a few discrepancies were attributed to missed information by the IEC Compliance Team, which was correctly identified and categorised by the LLM. An updated LLM prompt (LLMv2) was developed and applied to the test cohort. In version 2, the prompt was revised to include clearer instructions on how to summarize CRS and ICANS events, as well as new instructions on additional data elements to be summarized. The performance of LLMv2 on this cohort for CRS event identification was 100% across all categories (accuracy, precision, sensitivity, specificity, F1 score, and Matthew's correlation coefficient). For ICANS the LLMv2 achieved accuracy of 96%, precision 69%, sensitivity 100%, specificity 93%, F1 score 82%, Matthew's correlation coefficient 80%. Accuracy in identifying event resolution date improved significantly from 64% to 99%. Conclusions: Our study demonstrates that LLMs can significantly reduce the time required to abstract and summarize CAR-T toxicities, while maintaining high accuracy. One limitation of our study is that it is based on data from a single institution. However, plans are already underway to evaluate the use of LLMs in a multi-institutional setting.

Abstract Introduction: Achieving rapid and deep hematological responses is essential for improving organ function and reducing early mortality in AL amyloidosis. While daratumumab has transformed the management of newly diagnosed disease, many daratumumab-treated patients will not clear amyloidogenic serum free light chains or will relapse. Chimeric antigen receptor (CAR) T-cell therapy is a highly active modality in multiple myeloma, capable of inducing deep and durable remissions. Whether this strategy can be safely and effectively adopted in AL amyloidosis remains an important unanswered question. Methods: This multicenter retrospective study involved 8 US academic medical centers within the US Multiple Myeloma Immunotherapy Consortium. We included patients with systemic AL amyloidosis who received BCMA-targeted CAR T therapy to treat AL amyloidosis with concurrent myeloma to investigate the safety, and efficacy of this approach. Results: Between September 2021 and March 2025, we identified 33 patients with AL amyloidosis treated with CAR T (n=9 ide-cel, n=24 cilta-cel). The median age was 69-years (IQR: 60, 72); 48% were female. Most patients were kappa light-chain isotype (61%, n=20), 4 patients (13%) had the t(11;14) translocation. Although baseline plasma cell burden was unknown in 2 cases, all patients had a concurrent diagnosis of myeloma, and 88% of patients had ≥20% bone marrow plasma cells (BPMC) at diagnosis. The median number of prior lines was 6 (range: 3-13), all patients had previous anti-CD38 exposure, and 27 patients (82%) had received previous autologous stem cell transplant. Regarding organ involvement, 11 patients (33%) had cardiac, 9 (27%) renal, 8 (24%) gastrointestinal, 3 (9%) peripheral nerve and 1 (3%) autonomic nerve involvement. Five patients had AL amyloid deposition without known organ involvement. Prior to CAR T, cardiac staging was unavailable or unknown in 19 cases. Of the remaining 14 cases, 6 cases were European Modification of Mayo 2004 stage 3A with no stage 3B cases. Prior to lymphodepletion the median BMPC was 6% (IQR: 1, 20). The overall rate of cytokine release syndrome (CRS) was 64% (Grade 1, G1: n=15, Grade 2, G2: n=4, Grade 3, G3: n=2), and immune cell associated neurological syndrome (ICANS) was 15% (G1: n=3, G3: n=2). The rate of CRS was 56% for ide-cel (G1: 33%, G2: 22%) and 67% for cilta-cel (G1: 50%, G2: 8%, G3: 8%). The median time to CRS onset was 1 day for ide-cel and 6 days for cilta-cel. The median duration of CRS was 1 day for ide-cel and 2 days for cilta-cel. The rate of ICANS was 11% for ide-cel (G1: n=1), and 16% for cilta-cel (G1: n=2, G3: n=2). There were no cases of non-ICANS neurotoxicity. Ten patients (30%) experienced infections (≥Grade 3 = 9%). The overall response rate (ORR) by AL amyloidosis response criteria (Palladini et al. 2012) was 91%, including n=5 very good partial responses (VGPRs) and n=24 complete responses (CRs). The ORR for ide-cel was 78% (n=6 CRs, n=1 VGPR), and for cilta-cel was 96% (n=18 CRs, n=4 VGPRs). Among responders, the median time to VGPR or better was 30 days (IQR: 29, 32). One cilta-cel recipient died of infection on day 17 prior to disease reassessment. At a median follow up of 17.8 months, the 12 and 18-month overall survival rates were 88% (95%CI: 76%-100%) and 83% (95%CI: 68%-100%), respectively. There were 5 deaths; 3 were related to underlying disease, 1 related to infection, and 1 unrelated. Seven patients were eligible for cardiac response assessment (NTproBNP>650 OR BNP>150) at the time of CAR T, and of those, three obtained a cardiac response (2 Cardiac PR, 1 Cardiac VGPR). Three patients were eligible for renal response assessment (>1g proteinuria/day) at the time of CAR T; of those, two obtained a renal PR. Conclusion: We demonstrate that commercial BCMA-targeted CAR T-cell therapy induces deep and rapid hematological responses in a cohort of heavily pretreated patients with AL amyloidosis. Although all patients exhibited overlapping features with concurrent multiple myeloma (≥10% plasma cells at diagnosis), CAR T-cell therapy was feasible to administer, with modest rates of CRS and only isolated cases of severe CRS or ICANS. Nearly all patients achieved a deep hematological response, which appeared to translate into meaningful organ improvement among those who were evaluable.

Abstract Introduction Cila-cel is associated with a 10-15% risk of delayed neurotoxicity (DNT) with rates of cranial nerve palsies (IEC-NP) and parkinsonism (IEC-PKS) seen at a rate of 10% and 1-4% respectively and can occur as early as 3-4 weeks after infusion. We and others have shown that high post-infusion peak absolute lymphocyte count (ALCpeak) of >3x10^9/L is associated with an increased risk of delayed neurotoxicity (Lim et al., ASCO 2025) whilst the risk was negligible (~1%) when ALCpeak fell below that threshold. Since December 2024, we implemented prophylactic administration of dexamethasone (PPX DEX) when ALC was >3x10^9/L (defined as high ALCpeak). Outcome of these patients are described here. Methods Analysis of clinical outcome included 230 pts treated between Feb 2022 and Nov 2024 as a historical cohort and 102 patients treated between Dec 2024 and May 2025 after the introduction of dexamethasone prophylaxis using an oral dose of 10mg twice a day for at least three days in the high ALCpeak cohort. Results No significant differences were seen between the new and historical cohort in pre-lymphodepletion disease burden (bone marrow plasma cell %, involved light chain or M-spike level), and rates of all/high-grade CRS or ICANS, IEC-HS and rates of tocilizumub use. Median follow-up in the new cohort of 102 pts was 3.6 months (95% CI 3.3-4.2). Eleven (10.8%) developed DNT [3 (2.9%) with IEC-PKS, 8 (7.8%) with IEC-NP]. High ALCpeak of >3x10^9/L was observed in 51 (50%) pts. Among pts with high ALCpeak, DNT was observed in 10 (20%) pts [3 (5.9%) with IEC-PKS, 7 (13.7%) with IEC-NP] whereas among 51 pts with ALCpeak <3x10^9/L, DNT was observed in 1 (2%) pt [1 (2%) with IEC-NP]. In the high ALCpeak cohort, 38 (75%) received DEX [6 (12%) for toxicity management, 32 (63%) PPX DEX]. Of the 38 pts treated with DEX, DNT was observed in 6 (16%) pts (2 (5.3%) IEC-PKS, 4 (10.5%) IEC-CNP). We next compared DNT rates between this new cohort of high ALCpeak pts receiving DEX (n=38) against the historical cohort with high ALCpeak (n=98). Estimated 90-day DNT by Kaplan-Meier method was (19.2% vs 20.5%; p=0.53): IEC-PKS (5.8% vs 7.2%; p=0.60) and IEC-NP (11.7% vs 13.3%; p=0.58). In patients with high ALCpeak, the use of DEX did not appear to significantly reduce the risk of DNT compared to historical controls (HR 0.76, 0.33-1.78), IEC-PKS (HR 0.67, 0.14-3.10) or IEC-NP (0.73, 0.24-2.23). We next compared ALC expansion over the first month post CAR-T infusion (area under the curve, AUC). Among the new cohort of 102 patients, no difference was seen in the AUC of pts who received DEX but did not develop DNT vs those who developed DNT (31.0 vs 57.9, p=0.28); No difference in AUC was seen in the new high ALCpeak cohort receiving DEX vs the historical cohort with high ALCpeak (36.0 vs 43.8, p=0.15) Of the eight cases of IEC-NP, 4 received PPX DEX. No noticeable differences were observed in the severity of presentation, laterality of cranial nerve involvement and rates of multiple cranial nerve involvement between these 4 cases who received PPX DEX and the 16 cases from the historical cohort. At the time of database freeze, 3 of the 4 cases had resolved and 1 was improving. Median time to complete symptom resolution was 38 days vs 69 days in the historical cohort. Of the three cases of IEC-PKS, 2 received PPX DEX. Median time to symptom onset for IEC-PKS was 46 days (vs. 24 days in historical cohort). Both cases had severe symptoms non-responsive to first line high-dose methylprednisolone, second line intrathecal chemotherapy and third line high-dose cyclophosphamide. Both pts subsequently died from sepsis 28 and 67 days post-cyclophosphamide. Conclusion While ALCpeak >3x10^9/L predicts risk of DNT in pts treated with cilta-cel, the use of PPX DEX does not appear to significantly reduce ALC expansion and does not appear to significantly reduce the risk of DNT, IEC-PKS or IEC-NP. Other strategies to reduce ALC or alter T cell functions may need to be considered.

Abstract Background Central nervous system involvement in multiple myeloma (CNS-MM) is a rare but highly aggressive manifestation. Limited data exists regarding its incidence, biology, treatment patterns, and outcomes. A deeper understanding of the features unique to CNS-MM will help inform risk stratification and management strategies. Methods We conducted a retrospective study of CNS-MM patients at our institution between January 2000 and December 2023. We identified 305 MM patients with pathology-proven extramedullary disease (EMD). CNS involvement was defined as the presence of parenchymal (brain or spine) or leptomeningeal involvement by MM. Univariate analysis was performed to compare the clinical characteristics between EMD patients with and without CNS-MM. Results Out of 305 patients with EMD, we identified 22 patients with CNS-MM. Common symptoms prompting evaluation of CNS-MM were headaches (32%), numbness or tingling (32%), weakness (27%), confusion (23%), falls (23%), and visual disturbances (14%). Among these patients, 17 (77%) had detectable disease in cerebrospinal fluid (CSF), 12 (55%) in the brain parenchyma, 4 (18%) in the spinal cord parenchyma and 6 (27%) in the leptomeninges. Of the CNS-MM patients, the median age at diagnosis of MM was 58.3 years and the median time to CNS-MM involvement was 16.2 months, with 3 (14%) patients having CNS involvement at diagnosis. The predictors of CNS-MM development were high-risk cytogenetics (OR 2.9, p=0.04) and presence of additional visceral organ involvement outside of the CNS (OR 3.4, p=0.03). EMD was multifocal in 20 CNS-MM patients (83%) and visceral organ involvement [most commonly lymphadenopathy (27%), solid organ (18%) and pleural fluid (14%)] was present in 14 (64%) of these patients, compared to 54% in EMD patients without CNS-MM. High-risk cytogenetics [del(17p), 1q gain/amplification, t(4;14), t(14;16), t(14;20)] were seen in 16 (73%) patients, most commonly 1q gain or amplification (40%), t(4;14) (23%), and del(17p) (18%). Five (23%) exhibited a double-hit profile. In comparison, 113 (40%) EMD patients without CNS-MM had high risk cytogenetics. The median overall survival (OS) from diagnosis of CNS-MM was 6 months (95%CI:1.26-36) compared to 15.6 months (95%CI: 12-18) from diagnosis of EMD in EMD patients without CNS-MM (p=0.05). Median OS from diagnosis of MM in the CNS-MM cohort was 36 months (95%CI: 22.8-NA) compared to 55.2 months (95%CI: 45.6-68.4) in EMD patients without CNS-MM (P=0.11). When excluding CAR-T or bispecific therapy recipients, median OS from diagnosis of MM for CNS-MM was 22 months versus 48 months in EMD patients without CNS-MM (P=0.02). Overall response rate in our CNS-MM cohort with first treatment for EMD was 32% compared to 48% in EMD patients without CNS-MM (p=0.04). In patients with CNS-MM, median progression-free survival (PFS) from CNS-MM diagnosis was 3.3 months (95%CI: 0.8-12) versus 3.9 months (95%CI: 3-5.1) in EMD patients without CNS involvement (p=0.2). Six (27%) CNS-MM patients received CAR-T; 3 received cilta-cel, 2 received ide-cel and one received a BCMA CAR-T on trial. Bispecific therapy was used in 4 (18%) patients, with 2 receiving Teclistamab and 2 Talquetamab. Three (14%) CNS-MM patients received both CAR-T and bispecific therapy. The median PFS on CAR-T therapy was 10.5 (95%CI: 5.6-NA) months and 12.7 (95%CI: 10.2-NA) months on bispecific therapy. The median OS from diagnosis of CNS-MM for patients who received CAR-T or bispecific therapy was 36 months (95%CI: 14.0-NA), compared to 1.2 months (95%CI: 0-14.4) for those who did not (p=0.002). Six (27%) patients with CNS-MM, all of whom had CSF involvement of disease, received intrathecal therapy; methotrexate in 3, cytarabine in 2, and one receiving both. Two of these patients demonstrated improvement in cerebrospinal fluid findings following intrathecal chemotherapy, in conjunction with other therapies. Patients who received intrathecal chemotherapy had a median OS measured from development of EMD of 10.8 (95%CI: 3.6-NA) months, compared to 15 months (95%CI: 4.8-NA) in those without IT chemotherapy (p=0.59). Conclusion Central nervous system involvement in MM is relatively uncommon and associated with dismal outcomes. High-risk cytogenetics and involvement of other visceral sites are associated with a higher risk of CNS involvement. Intrathecal therapy offers limited value and immune effector therapies represent efficacious options for treatment.

Abstract Introduction: The CAR-T therapies ide-cel and cilta-cel are approved for patients (pts) with relapsed/refractory multiple myeloma (RRMM). The aim of this study was to determine the incidence, subtypes, and associated risk factors for subsequent primary malignancies (SPMs) in MM pts treated with CAR-T therapy in the real-world setting. Methods: A retrospective, multicenter observational cohort study was conducted of pts who received CAR-T therapy between May 2021 and Dec 2024 at 15 centers within the US Multiple Myeloma Immunotherapy Consortium. Logistic models were used for univariable analyses of invasive SPMs (excluding non-melanoma skin cancers). Variables significant at p < 0.10 were included as candidate variables in the multivariable analysis. Time to event endpoints were analyzed using Kaplan-Meier curves. Results: Of n=1460 CAR-T recipients, median follow-up from the time of CAR-T infusion for the entire cohort, ide-cel, and cilta-cel pts was 13.1, 16.9, and 10 months, respectively. A total of 55 invasive SPMs were noted in 53 pts (SPM incidence 3.6%). The incidence rate of SPMs was 4.55 per 1,000 person-years, based on 53 SPMs occurring over 11,646.14 person-years (calculated from CAR-T to the SPM diagnosis, death, or last follow-up). Baseline characteristics were similar for pts with no SPM versus SPM including: age at CAR-T (median 67 vs 65), female (36% vs 43%), Black (13% vs 16%), prior autologous transplant (87% vs 80%), lenalidomide for ≥2 years (31% vs 27%), high risk cytogenetics (23% vs 29%), and known clonal hematopoiesis (7.5% vs 9.9%). Differences were observed in baseline characteristics among pts with SPM versus no SPM for ≥2 prior alkylator lines of therapy (LOT) (82% vs 60%, p=0.002) and median prior LOT (6 vs 5, p=0.008). There was a trend for more patients with SPMs being age ≥70 (35% vs 37%, p=0.074). Of the 53 SPMs, 26 (49%) were myeloid (MDS or AML), 19 (35.8%) were solid, 7 (13.2%) were of T-cell origin, and 1 was a B-cell lymphoma. Of the T-cell SPMs, three were of T-LGL, though one of the T-LGL pts later developed an invasive CNS T-cell lymphoma (CAR-negative). There were four cases of confirmed CAR-positive T-cell SPMs (all pts treated with cilta-cel), of which two were indolent T-cell lymphoma of the GI tract and two were cutaneous PTCL. There was no difference in total incidence of SPMs among pts who received ide-cel (total=4.4%; myeloid=2.2%, T-cell=0.04%) versus cilta-cel (total=3%; myeloid=1.4%; T-cell=0.5%) (p=0.21). Median OS from the time of CAR-T therapy was 40.8 months for pts without SPM compared to 27.6 months for pts with SPM (p=0.4). Median OS did not differ by myeloid, solid, and T-cell subgroup: 26.4, 37.2, and 24 months, respectively (p=0.21). Median time from CAR-T cell to SPM was 12 months overall, and by subtypes of myeloid, solid, and T-cell was 13.2, 9.6, and 9.6 months, respectively (p=0.74). There was no difference in time to any SPM among pts receiving ide-cel versus cilta-cel (p=0.61). An earlier time to diagnosis of myeloid SPM was observed for cilta-cel versus ide-cel (4.8 vs 20.4 months; p=0.003). Median OS from the time of diagnosis of any SPM, myeloid, solid, or T-cell SPM was 9.6, 7.2, 15.6, and not reached in months, respectively (p=0.006), demonstrating that pts diagnosed with myeloid subtype SPM had inferior OS from the time of their SPM diagnosis compared to other subtypes. The cause of death of 4/11 myeloid SPM pts was the myeloid SPM itself. In univariable analysis for the entire cohort, age ≥70 (p=0.079), ≥5 prior LOT (p=0.012), and ≥2 prior alkylator LOT (p<0.001) were associated with higher risk for SPM. In multivariable analysis, ≥2 LOT containing alkylators was associated with higher risk of SPM (p=0.005). For the univariable analysis of the myeloid subgroup, ≥2 prior alkylator LOT (p=0.016) and ≥2 years of lenalidomide maintenance (p=0.063) were associated with higher risk of SPM. In multivariable analysis, ≥2 years of lenalidomide (p=0.065) was associated with a trend toward increased risk of myeloid SPM. Conclusions: With a median follow up of 13.1 months, the incidence of developing a SPM following CAR-T in pts with RRMM was 3.6%, of which approximately half were myeloid malignancies. There was no difference in SPM incidence when comparing the two CAR-T products. Pts treated with ≥2 alkylator LOT had a higher risk of SPM in multivariable analysis and may warrant additional monitoring for SPM development.

Abstract Background: Gastrointestinal (GI) symptoms are frequent in patients (pts) with systemic light chain amyloidosis (AL), yet their clinical significance remains poorly defined. We investigated the role of symptomatic GI involvement in disease burden, survival, and organ-specific outcomes in a large single-center cohort. Methods From 2010–2025, 4,396 AL pts were evaluated at our center; 560 pts (13%) had provider-attributed symptomatic GI AL. Pts with localized AL or positive biopsy without GI symptoms were excluded (n=38). We analyzed relationships between GI symptoms, anatomic/histologic involvement, laboratory parameters, survival, and need for nutritional support using Wilcoxon rank-sum, Chi-square, Kaplan-Meier, and logistic regression tests. Results GI symptoms included early satiety (n=320/57%), diarrhea (n=189/34%), nausea (n=184/33%), abdominal pain (n=148/26%), dysphagia (n=119/21%), vomiting (n=75/13%), GI bleeding (n=74/13%), and heartburn (n=71/13%). Only nausea and GI bleeding were not associated with cardiac (n=366/65%) renal (n=274/49%) or hepatic (n=84/15%) AL, whereas dysphagia, early satiety and heartburn were more frequent with cardiac (all OR=1.7), abdominal pain and diarrhea with hepatic (OR=2 and 1.6, respectively), and vomiting with renal involvement (OR=2; all p<0.04). Autonomic involvement impacted GI symptoms, often without proof of parenchymal GI amyloid. Of the 124 pts with formal autonomic testing, only 44 (35%) had positive GI biopsies as compared to AL GI pts without proven autonomic involvement (240/436, 55%). Pts with autonomic involvement were more symptomatic than pts with positive GI biopsies, suffering more often from dysphagia (29% vs 19%), diarrhea (41% vs 32%), and gastroparesis (34% vs 9%, all p<0.001). We screened changes in body weight, calcium, VitB12, Hb, PO4, and albumin at diagnosis. Of the 175 pts with documented weight loss in this cohort, pts with GI AL lost more weight compared to those with other organ involvement (21% vs 14% of weight, p=0.002), and had lower phosphate (3.7 vs 4.0 mg/dL, p=0.06). In our cohort of pts with GI symptoms, 298 (53%) had a positive GI biopsy. Biopsy-proven anatomic involvement dictated symptoms (all p<0.05): Of the 20 pts with positive esophageal biopsy, dysphagia was present in 45%; only 33% of the pts without an esophageal biopsy had dysphagia. Similar patterns were seen for the 170 pts with a positive gastric biopsy (n=170) in terms of heartburn (21% vs 11%), for the 165 pts with positive small bowel biopsies in terms of abdominal pain (68% vs 32%), and for the 130 pts with positive colon biopsies and diarrhea (46% vs 33%). Specific histopathological patterns were prognostic. Mucosal involvement (n=161) was an independent risk factor for survival compared to submucosal (n=64) and vascular (n=102) involvement throughout the GI tract (HR 1.83; p=0.03). Three-layer GI infiltration was associated with inferior mOS (2.4 vs 5.1 vs 7.8 y for 3 vs 2 vs 1-layer involvement, HR 3.19/1.56/1; p<0.05). Counterintuitively, vascular involvement had the lowest risk of bleeding in all GI anatomic sites (p=0.02). In the colon, only mucosal involvement was associated with a higher risk of bleeding (OR=5; p=0.04). GI involvement in AL pts did not worsen prognosis (mOS 10.0/6.3y, p=0.02), and pts with isolated GI AL (n=74/13%) had an even better survival (55% surviving at 10 y). Cachexia (n=120; mOS 3.5 vs 7.8 y, p<0.001), need for nutritional support (n=36; mOS 0.9 vs 7.0 y, p<0.001), and diarrhea (mOS 5.8 vs 6.9 y, p=0.06) were risk factors for death. In pts with hematologic response (≥PR), bleeding did not recur within 3 y (n=27), but even with response, diarrhea (n=160) persisted in 39%. Resolution was less frequent without hematologic response (persistence in 69%, OR=3.5). Improvement was most often due to treatment of bacterial overgrowth (11/35 pts; 68%) and loperamide (54/59 pts; 91%). Conclusion In AL, meaningful GI involvement is defined by nausea, diarrhea, occurrence of bleeding, and malnutrition. These are primarily associated with mucosal infiltration. GI symptoms can occur in the face of autonomic involvement. While long-term persistence of GI bleeding is rare after serologic response, cachexia and persistent diarrhea drive morbidity, need for nutritional support, and poor survival.