Vij, Ravi

Abstract Although the human genome encodes a vast repertoire of noncoding RNAs that regulate gene expression, the noncoding genome remains underexplored due to technical challenges. Specifically, during transcriptomic sequencing data alignment, the overlap between noncoding and coding loci can create ambiguous read alignments that are subsequently discarded from downstream analysis. For this reason, most of the noncoding genome is excluded from standard genomic annotations used for sequencing alignment. To address this challenge and enable concurrent profiling of the coding and noncoding transcriptome, we systematically integrated standard coding (GENCODE) and noncoding (LncBook) genome annotations, preserving coding gene annotations and removing overlapping noncoding regions. The resulting integrated genome annotation expanded the number of annotated noncoding genes from 40,785 to 138,296 while preserving all coding genes and reducing ambiguous read assignment. To evaluate the utility of our integrated genome annotation for uncovering novel, biologically relevant noncoding RNAs (ncRNAs), we realigned CD138-positive bulk RNA-seq (N = 942) and CD138-negative single-cell RNA-seq (N = 478) data from the MMRF CoMMpass study, generating a comprehensive coding-noncoding atlas of the myeloma bone marrow microenvironment with noncoding genes representing 51% of highly variable genes and displaying significant cell type specificity. Tumor expression profiling based on this integrated profiling identified 15 clusters, including two enriched for amp(1q21) or t(4;14) and associated with shorter progression-free survival (PFS). Differential expression and systematic filtering yielded 19 candidate high-risk ncRNAs, including previously uncharacterized ENSG00000310209 , which was associated with poor PFS (HR = 1.141, P = 0.0025), increased IRF4 activity, Wnt pathway activation, CCL5 signaling, and the accumulation of anergic-like CD8+ T cells. These findings establish integrated coding-noncoding analysis as a strategic approach for discovering functional ncRNAs from transcriptomic sequencing data.

Abstract The B-cell maturation antigen (BCMA)–targeting bispecific T-cell engager pavurutamab (AMG 701) directs the cytotoxic T-cell response toward multiple myeloma (MM) cells. This phase 1/1b, open-label, dose-exploration and dose-expansion study evaluated the safety, tolerability, and efficacy of pavurutamab monotherapy in patients with triple-class relapsed/refractory MM (RRMM). Pavurutamab (5-18 000 μg) was administered IV weekly with step-up dosing in week 1. Overall, 172 patients received at least 1 dose of pavurutamab; 73 received the recommended phase 2 dose (RP2D; 18 000 μg), with 2 different step-up dosing regimens in phase 1b. Twelve patients had dose-limiting toxicities, which included cytokine release syndrome (CRS) and increased transaminases; none of which occurred at the RP2D. The most frequently reported treatment-emergent adverse events included CRS (74.4%), anemia (61.0%), neutropenia (47.1%), and hypophosphatemia (45.3%). Grade ≥3 infections were noted in 60 patients (34.9%). The overall response rate (ORR) was 46.5% among all patients and 65.8% (very good partial response [VGPR] or better, 60.3%) among 73 patients treated at the RP2D. At median follow-up of 17.2 months, median duration of response (DOR) was 36.6 months (95% confidence interval [CI], 22.3 to not estimable). Median progression-free survival (PFS) for all patients was 5.5 months (95% CI, 2.8-10.1) and 16.8 months (95% CI, 5.0 to not estimable) with the RP2D. Pavurutamab exposure generally increased in a dose-proportional manner, with high soluble BCMA levels correlating with lower exposure level. The acceptable safety profile, pharmacokinetics, and preliminary efficacy of pavurutamab supports anti-BCMA T-cell engager therapy in heavily pretreated patients with RRMM. This trial was registered at www.clinicaltrials.gov as NCT03287908.

Abstract The CoMMpass study (NCT01454297) is a prospective, longitudinal observational study involving 1,141 newly diagnosed multiple myeloma (NDMM) patients. Bone marrow aspirates from the study participants were collected for comprehensive molecular characterization of tumor (using bulk RNA sequencing and whole genome sequencing) and tumor immune microenvironment using 3’ single-cell RNA sequencing (scRNA-seq). To support exploration of this rich multi-omic dataset, we developed CoMMpass Explorer (CE), an intuitive interactive platform that enables real-time analysis of clinical and genomic data from CoMMpass. A central feature of CE is cohort building, where users can filter and stratify patients by clinical, genomic, and survival data elements to create custom cohorts for analysis. CE provides five main views: Overall Summary for clinical feature distribution, Kaplan-Meier curves, and multivariate Cox proportional hazards models; Mutational Profile for visualizing and comparing somatic mutations; Tumor Profile for bulk differential expression and gene set enrichment; Immune Microenvironment for comparing cell type abundance and cell cycle dynamics between cohorts using scRNA-seq data; and Pseudo-Bulk, which aggregates single-cell expression by cell type to enable cohort-level comparisons of transcriptional programs using DEseq2. CE reproduces prior CoMMpass studies, including WEE1 expression being associated with poorer progression-free survival (Simhal, et al.) and different mutation frequencies between African American and European American patients (Manojlovic, et al.). We further demonstrate CE’s utility by interrogating the 2025 Consensus Genomic Staging (CGS) risk classification system (Avet-Loiseau, et al). We compared CGS high-risk (HR, n=249) vs. CGS standard-risk (SR, n=573) patients. HR patients have significantly worse progression-free survival, overall survival, and time to second-line therapy compared with SR patients. Univariate models recapitulated expected differences in the clinical features that define CGS risk. Bulk tumor RNA-seq and ssGSEA highlighted a more proliferative and genomically unstable transcriptional program in HR group, with upregulation of angiogenesis and cell-cycle-related pathways. In the immune microenvironment, monocytes were more abundant in the SR group. Pseudo-bulk RNA-seq of plasma cells showed overexpression of ANXA1, NSD2, IGF1R, MAF and related genes in HR. CE democratizes access to the CoMMpass multi-omic resource, allowing researchers to interrogate clinical and molecular heterogeneity. By enabling hypothesis generation and replication of published results, CE serves as a valuable tool for identifying prognostic biomarkers and meaningful patterns in gene expression, mutation profiles, and the immune microenvironment. Citation Format: Wanxing Zhang, Chaitanya R. Acharya, Steven M. Foltz, David E. Avigan, Samir Parekh, Ravi Vij, Shaji Kunnathu Kumar, Taxiarchis Kourelis, Sagar Lonial, Hearn Cho, Ioannis S. Vlachos, Sacha Gnjatic, Li Ding, Manoj Bhasin, George Mulligan. CoMMpass Explorer: An interactive platform to explore clinical and genomic data from newly diagnosed multiple myeloma patients from the landmark CoMMpass observational study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5504.

Abstract Background: Multiple myeloma is the second most common adult blood cancer and remains incurable, despite recent advances. The IMWG/IMS recently published updated risk criteria, Consensus Genomic Staging (CGS), combining genomic events with clinical measures to identify high-risk patients (Avet-Loiseau, et al. JCO 2025). We applied CGS risk criteria to baseline samples from the Multiple Myeloma Research Foundation CoMMpass Study (NCT01454297), a prospective, longitudinal observational study that enrolled more than1100 participants between 2011-2017. Methods: We assessed patient risk following CGS criteria. Criteria 1: del(17p), with a cutoff of >20% clonal fraction, and/or TP53 mutation. Criteria 2: an IgH translocation including t(4;14), t(14;16), or t(14;20) along with 1q+ and/or del(1p32). Criteria 3: monoallelic del(1p32) along with 1q+ or biallelic del(1p32). Criteria 4: beta-2 microglobulin >= 5.5 mg/L with normal creatinine. Patients meeting one or more criteria were classified as High Risk. To test if risk showed association with genetic ancestry, we grouped patients into those with high African genetic ancestry and those with low African genetic ancestry. Genetic ancestry was measured using ADMIXTURE in comparison to 1000 Genomes. Results: We evaluated the CGS risk status of 877 CoMMpass patients, finding 69.2% (573/828) to be Standard Risk (SR) and 30.8% (255/828) to be High Risk (HR). HR patients showed worse progression-free survival (median PFS 26.3 months vs. 42.5 months; log rank test, p < 0.0001) and overall survival (median OS 63.9 months vs. median not reached; p < 0.0001). 10.6% (91/858) of patients met Criteria 1, 10.7% (93/873) met Criteria 2, 5.6% (49/877) met Criteria 3, and 8.7% (73/835) met Criteria 4. We found 14.2% (123/867) of patients to have high African-like genetic ancestry (AFR-high) and 85.8% (744/867) to have low African-like genetic ancestry (AFR-low). We observed significantly fewer HR patients within the AFR-high group (20%, 23/115) than in the AFR-low group (32.4%, 231/712) (Fisher’s exact test, p = 0.0065). The AFR-high group met HR criteria at a lower rate across all criteria, but only with Criteria 3 was the difference significant (p-value = 0.03). Higher levels of creatinine in AFR-high patients may have impacted meeting the normal creatinine requirement of Criteria 4. Conclusions: HR patients comprise 30.8% of CoMMpass subjects and show significantly worse PFS and OS than SR patients. AFR-high patients met HR criteria at a lower rate than AFR-low patients according to the CGS criteria. Clinical trials that utilize CGS criteria to determine patient eligibility may be challenged to enroll a representative patient population, including AFR-high patients. Screening and eligibility criteria should be carefully considered to mitigate potential enrollment disparities. Citation Format: Steven M. Foltz, Chaitanya R. Acharya, Alexander Gout, Yuxin Jin, David E. Avigan, Ravi Vij, Shaji Kunnathu Kumar, Sagar Lonial, Hearn Cho, Katie Wozniak, Jonathan J. Keats, Craig Cole, John D. Carpten, George J. Mulligan. Multiple myeloma risk classification of CoMMpass using Consensus Genomic Staging identifies differences between patients with high and low African genetic ancestry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3887.

Abstract Multiple myeloma is a malignancy of clonally expanded plasma cells shaped by complex interactions with the immune microenvironment (IME). To investigate immune correlates of treatment response and disease progression, we conducted multi-omics profiling including CD138neg single-cell RNA sequencing of 243 bone marrow samples from 102 patients (631,226 cells) and CD138pos bulk RNA and whole-genome sequencing from 209 samples. In longitudinal analyses, interferon-γ signaling associated with markers of impaired T-cell memory after autologous stem cell transplant, whereas naïve B-cell abundance and immunoglobulin diversity correlated with improved progression-free survival (HR = 0.48; P = 2.3e−4). At disease progression, multiple myeloma cells upregulated cancer–testis antigens (CTAg) and immune effector genes, with concurrent B-cell depletion, enrichment of myeloid-derived suppressor cell expression, and phenotypic T-cell exhaustion. These findings highlight dynamic immune–tumor interactions, identifying naïve B-cell reconstitution as a biomarker of durable response and CTAgs as potential targets for high-risk disease at progression. Significance: Longitudinal profiling of multiple myeloma and the IME revealed dynamic immune–tumor interactions across the disease course. Altered expression in CD8+ T cells limited memory phenotype after transplant, whereas naïve B-cell recovery associated with sustained treatment response. At progression, CTAg expression associated with immunosuppression, revealing novel mechanisms of immune dysregulation.

Abstract Introduction Understanding the tumor immune microenvironment (TIME) in multiple myeloma (MM) is critical for identifying prognostic biomarkers and therapeutic targets. We hypothesized that specific immune cell populations within the bone marrow TIME are associated with clinical outcomes and could enhance patient stratification. To this end, we conducted the largest CyTOF-based immune profiling study to date in MM, profiling >300 million bone marrow immune cells from patients enrolled in the CoMMpass study. Methods We analyzed >1,000 bone marrow samples from ~700 newly diagnosed MM patients enrolled in the MMRF CoMMpass study (NCT01454297), using a harmonized protocol and 41-antibody CyTOF panel at five academic centers. The majority were baseline samples (n=671), with additional samples spanning up to 3.5 years post-diagnosis (n>300). Each site contributed ~200 samples on average. The cohort included 40% females, with a median age of 63 years and BMI of 27.8. ISS stages were evenly distributed (I: 36%, II: 36%, III: 29%), and 84% had ECOG 0-1. Autologous stem cell transplant was performed in 58% of patients, and 22% received maintenance therapy. Results We profiled 311 million single cells across the cohort, identifying major immune compartments: Neutrophils (36.0%), CD4 T cells (19.7%), NK cells (9.9%), monocytes (7.6%), B cells (5.7%), and CD8 T cells (5.6%). Less abundant populations included dendritic cells, γδ T cells, plasmablasts, and pDCs. In our preliminary analysis with multivariate cox regression modeling, we identified clinical factors including stem cell transplant, ISS stage, and ECOG status, as independent predictors of overall survival (OS). After adjusting for age and sex, higher proportions of naïve B cells, pDCs, and γδ T cells were independently associated with improved OS, while CD4+ T cell abundance was positively associated with prolonged progression-free survival (PFS). In contrast, elevated neutrophil proportions were significantly linked to inferior OS and demonstrated a trend toward shorter PFS. Longitudinal immune profiling in more than 200 patients identified a gradual accumulation of naïve B cells and a pronounced post-treatment rise in CD45+ plasmablasts, highlighting persistent B cell activity as a candidate mechanism for sustained therapeutic efficacy. Conclusion This study presents the largest immune proteomic atlas in MM to date, linking TIME composition to clinical outcomes. A favorable immune landscape was marked by preserved humoral immunity (naïve B cells, plasmablast expansion), enrichment of pDCs and γδ T cells, and lower neutrophil abundance, collectively associated with improved survival outcomes. These findings lay the groundwork for immune-guided prognostication and highlight new opportunities for therapeutic targeting in MM. Ongoing analyses aim to further resolve baseline and longitudinal immune dynamics in relation to treatment response.

Abstract Introduction: Multiple Myeloma (MM) is a complex hematologic malignancy, where patients often display one or more potentially high risk cytogenetic alterations associated with poor outcomes. Traditional high risk cytogenetics events in myeloma, such as NSD2 t(4;14) translocations, gain of 1q21, or deletion of 17p13, have often been studied in isolation, but emerging evidence suggests the combination of these high risk alterations has a greater negative prognostic impact than any on their own. This has been recently reflected in risk stratification guidelines from IMS and IMWG, which consider certain events, such as t(4;14), as high risk only in combination with gain of 1q21 or deletion of 1p32. Still, the mechanisms through which multi-hit high risk events disrupt the microenvironment and promote poor outcomes remains unclear. We hypothesize that myelomas with multiple high risk alterations remodel the immune environment to promote tumor progression and immune escape. Methods: To study the role of multi-hit high risk cytogenetics on the immune microenvironment, we analyzed CD138-bone marrow aspirate single-cell RNA sequencing (scRNAseq) data from 337 newly diagnosed MM patients from the MMRF CoMMpass study, generated as part of the Immune Atlas initiative. Cytogenetic alterations for these patients were derived from whole-genome and whole-exome sequencing of CD138+ bone marrow aspirates from the MMRF CoMMpass cohort. Patients were classified as multi-hit high-risk MM if they exhibited either (i) two high-risk cytogenetic events, including NSD2 t(4;14), MAF t(14;16), del(17p13), or (ii) one high-risk event with gain of 1q21. Results: Based on cytogenetic information, 33 patients in the Immune Atlas cohort were classified as 'multi-hit’ high-risk, while 34 patients had only a single high-risk alteration. These multi-hit high risk patents displayed significantly worse progression free survival compared to standard risk patients, adjusting for age, therapy, and ASCT (HR=2.34, p<7.2e-5), while single-hit patients showed a non-significant trend towards worse outcomes (HR=1.51, p=0.071). The most frequent multi-hit risk event in the cohort was NSD2 t(4;14) in combination with 1q21, observed in 23 patients. Compositional analysis of the immune populations in the scRNAseq data revealed that relative to both standard and single-hit high risk patients, multi-hit high risk patients displayed significant reductions in IFN-I stimulated CD4+ and CD8+ T cell populations, marked by decreased expression for antiviral response markers such as ISG15, XAF1, and IFI44L. Enrichment of inflammatory CD16+ non-classical monocytes was also observed. Further analysis of the most frequent multi-hit risk event, NSD2 with 1q21, revealed distinct enrichment of late-activated cytotoxic HLA+ CD8+T cells and cytotoxic CD4+.T cells. Neither alteration was observed in patients with single-hit NSD2 or 1q21. Further analysis on the interactions between high risk events revealed distinct transcriptomic profiles dependent on the high risk events involved, particularly in multi-hit events involving mutations or deletions of TP53 or gain of 1q21. Reduction in IFN-I signaling across various immune populations was primarily restricted to multi-hit risk events involving gain of 1q21. Conversely, patients with biallelic loss of TP53 displayed significant enrichment of these same IFN-I populations. Given this contrast in IFN-I signaling spanning multiple immune subtypes, we hypothesized that the malignant myeloma cells might similarly display altered IFN-I activity. Utilizing CD138+ myeloma bulk RNA sequencing data from CoMMpass, we found that IFN-I response scores strongly correlated between paired scRNA immune and bulk RNAseq tumor datasets (R2: 0.75, p=1.63e-32). Across 660 patients with bulk RNAseq and cytogenetic data, we confirmed significant reductions in IFN-I response scores in tumor cells in multi-hit high risk involving 1q21, and significant enrichment in those with complete loss of TP53 relative to standard-risk MM. Conclusions: Overall, we do observe that MM patients with multiple high risk cytogenetic alterations display distinct immunologic traits relative to standard risk or single-hit high risk patients in addition to significantly worse outcomes. Furthermore, we find variability in the immune alterations observed based on the cytogenetic events involved, further illustrating the heterogeneity in how MM shapes the immune microenvironment.

Abstract Background Etentamig is a second-generation B-cell maturation antigen (BCMA) x CD3 bispecific antibody that has shown promising efficacy and a favorable safety profile in heavily pretreated patients with relapsed/refractory multiple myeloma (RRMM). Etentamig possesses a unique combination of 2 high-affinity BCMA binding domains, coupled to a low-affinity CD3 binding domain that have been shown to reduce the negative impact of soluble BCMA (sBCMA), decrease risk for cytokine release syndrome (CRS), and drive sustained T-cell activation with reduced immune exhaustion in preclinical models of MM (Blood 2023;142 [suppl 1]:4666). Here, we describe correlative biomarker analyses from Phase 1 (NCT03933735) and Phase 1b (NCT05650632) clinical trials of etentamig in RRMM designed to assess the impact of sBCMA on clinical response and pharmacodynamic changes in proinflammatory cytokines, and T-cell redistribution, activation, proliferation, and exhaustion. Methods Peripheral blood and serum samples from patients with RRMM enrolled in Phase 1 and Phase 1b open-label studies who received etentamig monotherapy were collected at baseline, on treatment, and at disease progression. The Phase 1b study consisted of dose-optimization (DO) and dose-expansion (DE) phases. During DO, patients received a single step-up dose (SUD) of intravenous etentamig (2 or 4 mg) on Cycle (C) 1 Day (D) 1, followed by the target dose of 60 mg on D4. In DE, based on DO findings, patients received the recommended etentamig SUD (2 mg) on C1D1, followed by 60 mg on D4 with modified dexamethasone predosing. Samples were analyzed by flow cytometry for immune cell populations, Luminex® for cytokines, and electrochemiluminescence for sBCMA. Peripheral blood mononuclear cells and bone marrow mononuclear cells (BMMC) at baseline and on-treatment were subjected to single-cell Cellular Indexing of Transcriptomes and Epitopes sequencing (scCITEseq) and single-cell T-cell receptors (scTCR) / B-cell receptors clonality analyses. Results While baseline serum sBCMA levels did not correlate with clinical response to etentamig at the selected dose level of 60 mg every 4 weeks (Q4W) with 2 mg SUD, a reduction in sBCMA levels over time was associated with best International Myeloma Working Group response. Etentamig treatment led to a rapid and transient increase of proinflammatory cytokines and promoted T-cell redistribution, activation, and proliferation. Maximum reduction in peak levels of CRS-related cytokines, including (interleukin [IL]-6, IL-8, IL-10, tumor necrosis factor–a), were observed in DE compared with DO and 60 mg Q4W without SUD. Peak induction levels of proinflammatory cytokines during C1 correlated with occurrence of CRS (≥Grade [G] 1) as well as clinical response across dose levels. A modified dexamethasone premedication schedule of 2 mg/60 mg Q4W cohort for C1 resulted in significantly reduced baseline levels of IL-6 and key macrophage-associated cytokine/chemokines (eg, monocyte chemoattractant protein-1 and macrophage inflammatory protein-3 beta). Incidence of CRS was lowest in the 2 mg/60 mg Q4W cohort (26% G1, 4% G2, 0% ≥G3). Higher T-cell to myeloma cell ratio in BMMCs at baseline correlated with better response to etentamig. scCITEseq and scTCR analysis revealed that at baseline, responders also had greater CD8+ T-cell cytotoxic activities, increased TCR clonality, and elevated inflammatory signatures in T-cells from both peripheral blood and bone marrow. Etentamig at a dosage of 60 mg Q4W resulted in significant clonal expansion of CD8+ effector T-cells and enhanced gene expression signatures related to activation and cytotoxicity in both CD8+ T effector and natural killer cells. Along treatment cycles, responders maintained their T-cell fitness, high clonality, and low T-cell exhaustion levels. Frequency of baseline CD4+ or CD8+ T-cell exhaustion (programmed cell death receptor 1+/ T cell immunoglobulin and mucin-domain containing-3 +) did not impact clinical response at optimal dose level of 2 mg/60 mg Q4W etentamig. Conclusions Responses to etentamig were independent of baseline sBCMA levels and resulted in rapid and transient proinflammatory cytokine production that promoted robust T-cell redistribution, activation, and proliferation indicating that the optimal dose of etentamig (2 mg/60 mg Q4W) maximizes its clinical potential as a convenient, safe, and effective therapy for MM.

Abstract Multiple myeloma (MM) is an incurable malignancy of clonally expanded plasma cells shaped by complex interactions with the immune microenvironment. To investigate immune factors driving treatment response and resistance, we conducted multi-omics profiling including CD138 neg single-cell RNA sequencing of 243 bone marrow samples from 102 patients (631,226 cells) and CD138 pos bulk RNA and whole-genome sequencing from 209 samples. Longitudinal analyses revealed that interferon gamma signaling impairs T cell memory after autologous stem cell transplant, while naïve B cell abundance and immunoglobulin diversity correlated with improved progression-free survival (HR = 0.48, p = 2.3e -4 ). At disease progression, MM cells upregulated cancer-testis antigens and immune effector genes, with concurrent B cell depletion, enrichment of myeloid-derived suppressor cell genes in monocytes, and T cell exhaustion. These findings highlight dynamic immune-tumor interactions, identifying naïve B cell reconstitution as a biomarker of durable response, and cancer-testis antigens as potential targets for high-risk disease at progression. Statement of Significance Longitudinal profiling of multiple myeloma and the immune microenvironment revealed dynamic immune-tumor interactions across the disease course. Dysfunctional CD8⁺ T cells limited memory formation post-transplant, while naïve B recovery associated with sustained treatment response. At progression, cancer-testis antigen expression associated with immunosuppression, revealing novel mechanisms of immune escape.

AbstractBackgroundAcute lymphoblastic leukemia (ALL) in adults is aggressive, with long‐term outcomes impacted by treatment resistance and toxicity. CD52 is expressed in most cases of B‐ and T‐lineage ALL. Alemtuzumab, a humanized immunoglobulin G1 monoclonal antibody that targets CD52, was identified as a potential agent to improve treatment efficacy without increasing toxicity.MethodsIn this phase 1/2 study (Cancer and Leukemia Group B [CALGB] 10102, NCT00061945), a course of single‐agent alemtuzumab was intercalated into CALGB 19802 backbone chemotherapy after the third course of intensive chemotherapy in those who were CD52+ at diagnosis. Phase 1 tested three dose levels of subcutaneous alemtuzumab (10, 20, and 30 mg 3 times weekly for 4 weeks/12 doses) and demonstrated that 30 mg was tolerable. Phase 2 established feasibility.ResultsThe study enrolled 295 evaluable patients (115 in phase 1, 180 in phase 2); 206 (69.8%) were CD52+. Among evaluable CD52+ patients, 43.7% (90/206) completed the first three treatment modules; 97.8% (88 of 90) were treated with alemtuzumab. Alemtuzumab was associated with cytomegalovirus viremia, which occurred in 23.3% (14 of 60) of patients during and 29.2% (19 of 65) after alemtuzumab treatment. With a median follow‐up of 101.2 months, median overall survival (OS) was 26.3 months (3‐year rate, 44%; 5‐year rate, 36%; 10‐year rate, 31%). Landmark analysis at the start of the fourth course of treatment demonstrated no difference in OS or disease‐free survival between patients who did and who did not receive alemtuzumab.ConclusionAlemtuzumab was feasible to administer in adults with ALL receiving intensive chemotherapy, but was without evidence of benefit.