Blood Cancer Journal

Background: Translocation t(11;14) defines a biologically distinct subset of multiple myeloma (MM) enriched for BCL2 dependency. Treatment with venetoclax, selective BCL2 inhibitor, has shown varied responses in clinical trials and retrospective cohorts. Efficacy of venetoclax-based combination therapies and optimal timing of treatment in t(11;14) MM patients remain incompletely characterized. Methods: We have compared the overall survival of t(11;14) MM patients who received Venetoclax (N = 97) at any moment in time, to those who never did (N =284), in the largest retrospective cohort (N = 381) reported to date. We used longitudinal fluorescence in situ hybridization (FISH) to assess cytogenetic evolution and genomic complexity. We performed transcriptomic profiling of CD138 enriched tumors using RNA sequencing in a subset of samples and gene expression signatures (UAMS/HALLMARKS) were used to define molecular subtypes. Ex vivo drug sensitivity assays integrated with paired RNA sequencing were used to identify subtype specific therapeutic vulnerabilities and rational venetoclax based combination strategies. Results: Venetoclax exposure was associated with an improvement of median overall survival by nearly four years compared to non VEN exposed patients (p = 0.0003). Longitudinal cytogenetic analysis demonstrated stability of the primary t(11;14) translocation over time, while secondary abnormalities tend to accumulate, including those harboring high-risk secondary cytogenetic abnormalities such as del13q, amp/gain1q21, del17p, and del1p, resulting in increasing genomic complexity with disease progression. Transcriptomic analyses identified selective enrichment of CD1/CD2 signature (associated with t(11;14) NDMM) by single sample gene set enrichment analysis as a marker of prolonged progression free survival. However, patients with more than five prior lines of therapy were enriched for transcriptionally complex biology characterized by CD1/CD2 with either proliferative/hypermetabolic or inflammatory transcriptional programming which were associated with inferior outcomes with VEN based treatment. Ex vivo drug sensitivity profiling revealed subtype specific vulnerabilities, identifying daratumumab, lenalidomide, ixazomib, and panobinostat as rational partners for venetoclax depending on transcriptional context. Conclusion: Venetoclax-based therapy significantly improved overall survival in t(11;14) MM. Clinical benefit, defined by improved progression free survival, was greatest when venetoclax was administered earlier, preceding the emergence of transcriptomic reprogramming that reduces BCL2 dependency. These findings support transcriptomic biomarker guided, subtype specific venetoclax based treatment strategies to optimize outcomes in patients with t(11;14) MM.

Mantle cell lymphoma (MCL) is a B-cell non-Hodgkin lymphoma characterized by heterogeneous clinical courses despite a common pathobiological initiating event. In this work we explore the genomic variants that characterize MCL and integrate transcriptomic data to comprehensively describe MCL biology. We performed whole exome sequencing (WES) on 28 tumor-normal pairs (lymph node and skin, respectively), as well as whole genome sequencing (WGS) and RNA sequencing on subsets of samples. We used established DNA and RNA analysis pipelines to detect single-nucleotide variants (SNV) and indels, structural variants, copy-number alterations, and RNA fusions. The canonical t(11;14)(q13;q32) CCND1::IGH translocation was detected in 8 of 10 WGS samples. Structural variant analysis additionally identified recurrent rearrangements involving KMT2A and PAFAH1B2. SNV and indel analyses revealed frequent mutations in ATM, TP53, CCND1, IGH, and NOTCH1. ATM exhibited diverse variant classes, including missense mutations, frameshift mutations, deletions, and duplications, while all detected NOTCH1 mutations were predicted loss-of-function frameshift variants. Copy-number analysis identified recurrent losses affecting DNA damage response genes, including TP53 and ATM, and recurrent gains involving transcriptional regulators and oncogenic signaling genes. Integrated pathway analysis demonstrated enrichment of transcriptional misregulation, DNA repair, PI3K/AKT signaling, and interleukin signaling pathways. We also identified recurrent alterations in candidate genes, including ASXL1, suggesting additional mechanisms of epigenetic dysregulation in MCL. Together, these findings provide a comprehensive description of somatic alterations in MCL and demonstrate that diverse genomic lesions converge on common pathways involved in genomic instability, transcriptional regulation, and tumor survival.

Multiple myeloma (MM) is a plasma cell malignancy that frequently harbors activating mutations in NRAS and KRAS oncogenes. Previous clinical trials targeting the Ras/MAPK oncogenic pathway with MEK inhibitors (MEKi) were met with limited efficacy, and newer generation of Ras inhibitors (RASi) have not been specifically evaluated in MM patients. To investigate the vulnerabilities of Ras-mutant MM to targeted therapies, we examined the sensitivity of a panel of human MM cell lines to the RASi RMC-6236 (daraxonrasib) and the MEKi trametinib. Although Ras-mutant MM cells are responsive to oncogenic Ras signaling and are sensitive to RAS inhibition, their sensitivity to MEK inhibition is heterogeneous. Mechanistic studies revealed that c-Myc protein is destabilized by MEK inhibition only in MEKi-sensitive MM cells but not in MEKi-resistant cells, and pharmacological and genetic stabilization of c-Myc is sufficient to confer MEKi resistance. In contrast, Ras inhibition reduced c-Myc protein across all MM cell lines tested, regardless of their dependency on the MAPK pathway, and c-Myc expression was insufficient to promote RASi resistance. Together, these findings demonstrate that c-Myc protein stability differentiates the response of Ras-mutant MM cells to Ras and MEK inhibition, and suggest that direct targeting of the Ras oncoprotein, rather than its downstream MAPK pathway, may present a more effective strategy.

Clonal hematopoiesis (CH) can predict treatment outcomes in solid cancers, but the prevalence and clinical impact of CH in previously untreated, aggressive large B-cell lymphomas (LBCL) remains poorly characterized. Moreover, CH may be detected in cell-free DNA (cfDNA)-based biomarker assays, but the longitudinal dynamics of CH mutations during and after immunochemotherapy in LBCL remain unknown. Hence, we characterized the spectrum of CH mutations in 247 patients with high-risk primary LBCL from three phase II clinical trials. We identified CH mutations in 23% of patients. Compared with healthy controls, TET2 mutations were enriched in peripheral blood (PB) samples of LBCL patients (P=0.01). CH clone size showed high concordance between PB and cfDNA (R2=0.59, P<0.0001) but was not associated with circulating tumor DNA (ctDNA) concentration (P-values 0.25-0.86). In contrast with prior reports in the context of recurrent lymphoma, CH mutation status was not associated with overall survival (OS) (P=0.78) or progression-free survival (PFS) (P=0.89) in our primary LBCL cohort. CH clones showed variable longitudinal dynamics during immunochemotherapy, with 18% of evaluable patients developing mutant CH clones, mostly with TP53/PPM1D mutations. Together, CH mutations can be readily detected in cfDNA of lymphoma patients, but they do not predict survival in primary high-risk LBCL.

Pre-infusion cerebrospinal fluid (CSF) proteomics may enable risk stratification for immune effector cell-associated neurotoxicity syndrome (ICANS) after chimeric antigen receptor T-cell therapy, but disease-specific baseline variation may influence biomarker interpretation. We compared pre-infusion CSF proteomic profiles from 28 patients with diffuse large B-cell lymphoma (DLBCL) and 9 with multiple myeloma (MM). Although principal component analysis showed substantial overlap, orthoPLS-DA identified significant disease-associated discrimination supported by permutation testing. Proteins contributing to this separation were enriched for plasma cell-related, extracellular, and metabolic signatures. ICANS occurred in 7 of 28 DLBCL patients but in none of the 9 MM patients. MM cases aligned with the ICANS-negative group in binary analysis while remaining distinct from both DLBCL subgroups in three-group analysis. These findings indicate that pre-infusion CSF proteomics captures disease-specific molecular structure that should be considered when developing and interpreting biomarkers of CAR-T-associated neurotoxicity.

Background/Objectives: Many myeloid malignancies are defined by recurrent structural variants (SVs) and copy-number alterations (CNAs) under the current World Health Organization (WHO) and International Consensus Classification (ICC) frameworks. Detecting these abnormalities typically requires several standard-of-care (SOC) assays, each with its own blind spots, and then laboratories and clinicians are left to piece the results together. Genome mapping has emerged as a mainstream technology with the potential to serve as a high-resolution alternative to several standard-of-care cytogenetic assays such as karyotyping (KT), fluorescence in situ hybridization (FISH) or chromosomal microarray (CMA). Our laboratory at Augusta University has published numerous publications on the analytical and clinical utility of optical genome mapping (OGM) as a first-line assay for hematological malignancies. Electronic genome mapping (EGM) pursues the same goal with an electronic rather than optical readout. The objective of this study was to demonstrate the performance and utility of EGM as a valuable tool to detect clinically relevant SVs and CNAs found by SOC testing. Cytogenomic characterization of hematologic malignancies commonly requires multiple complementary assays, including karyotyping, FISH, and chromosomal microarray, each with distinct analytical limitations. Electronic genome mapping (EGM) provides genome-wide interrogation of structural variants and copy-number alterations using electronic single-molecule detection. We evaluated the feasibility and analytical performance of EGM in previously characterized myeloid malignancies. Methods: EGM was performed on the Nabsys OhmX platform using five previously characterized bone marrow aspirates from cases with acute myeloid leukemia (AML) or chronic myeloid leukemia (CML). EGM calls were compared with findings from karyotyping (KT), fluorescence in situ hybridization (FISH), and OGM. Results: All five samples passed quality control, with contig N50 values ranging from 1.8 to 3.8 Mb and more than 90% of reference labels represented in the assembled contigs. EGM detected every SOC-reported abnormality including two t(9;22)(q34.12;q11.23)/BCR::ABL1 rearrangements, trisomy 4, trisomy 21, and monosomy 7. In the most complex case, EGM resolved a del(20q) reported by KT and FISH into an intrachromosomal fusion, fus(20;20)(q11.21;q13.12), showing not only what was lost but where the chromosome rejoined. Like OGM, EGM identified an approximately 1.8 Mb loss at 7q22.1 involving 45 of genes of which only CUX1 is associated with cancer. This 7q loss was not detected by KT or FISH. Interestingly, EGM also detected the KMT2A-PTD variant previously detected by OGM. Collectively, EGM demonstrated 100% concordance (6/6 SOC-reported abnormalities; 9/9 OGM calls). Conclusions: In this pilot study on five hematological malignancy specimens, EGM matched SOC and OGM across translocations, aneuploidies, insertions and deletions, including BCR::ABL1 rearrangements in both AML and CML, and added high-resolution breakpoint detail beyond karyotype resolution. These results support larger studies across more subtypes to establish EGM as a first-line genome-wide cytogenomic tool for hematological malignancies. Keywords: Genome mapping, Electronic genome mapping, hematological malignancies, structural variants, copy number variants

Background: The clinical course of acute leukemias and related hematologic neoplasms is defined by aggressive clonal proliferation, severe hematopoietic disruption, and recurrent molecular alterations. Although serial bone marrow biopsies, multiparameter flow cytometry, and next-generation sequencing remain standard surveillance modalities, procedural invasiveness, high costs, and operational turnaround times limit their frequency. Minimally invasive, scalable biomarkers integrating routine hematologic indices, targeted gene expression, circulating oncoprotein levels, and patient compliance metrics may provide an accessible framework for dynamic monitoring. Methods: In this longitudinal cohort study of 66 patients across 272 serial encounters (discrete follow-up intervals: days 0, 14, 41, 71, and 78), we assessed the prognostic value of peripheral complete blood counts (white blood cell count [WBC], hemoglobin [Hb]), molecular indicators (FLT3, NPM1, and DNMT3A transcript levels; targeted soluble FLT3 quantification), and medication adherence. The primary clinical endpoint was longitudinal progression to critical deterioration or disease-related mortality. Generalized linear mixed-effects models (GLMM) with patient-specific random intercepts were constructed to account for intra-subject repeated measures. Predictors were standardized per 1-SD increment. Model performance was assessed via the Akaike Information Criterion (AIC) and the Concordance index (C-index). Results: Leukocyte expansion correlated inversely with hemoglobin concentration (r=-0.877, p<0.001), reflecting bone marrow infiltration and secondary erythroid suppression. Multivariable mixed-effects modeling confirmed that elevated WBC count (adjusted odds ratio [aOR] = 1.52 per 1-SD increase; 95% CI: 1.24-1.86; p<0.001) and reduced medication adherence (aOR = 0.58; 95% CI: 0.44-0.76; p<0.001) independently predicted adverse clinical transition. Integrating targeted molecular markers (FLT3 expression and soluble protein levels) with routine hematologic indices and adherence demonstrated superior calibration and discrimination over single-domain models ({Delta}AIC[&ge;]116; Harrells C-index = 0.81). Conclusions: Readily accessible peripheral hematologic indices, targeted molecular quantification, and medication adherence provide complementary prognostic information regarding disease activity. Integrating these low-burden parameters into clinical workflows offers an efficient, scalable paradigm for early risk stratification in hematologic malignancies.

Multiple myeloma is bone-marrow-predominant, motivating marrow plasma cell-free DNA (cfDNA) as a tumor-proximal liquid biopsy. We tested whether marrow plasma cfDNA better represents the myeloma genome than peripheral blood cfDNA by profiling matched marrow plasma cells and both cfDNA compartments from 74 patients across 372 cfDNA sample time points. Tumor fractions correlated between compartments (r=0.84), but marrow plasma cfDNA was not a superior surrogate: peripheral-blood cfDNA matched or exceeded marrow-plasma cfDNA for marrow-defined CNA and mutation recovery (77.4% vs 72.0%; 69.2% vs 65.4%), with high specificity. Disease-associated features were detected in 69/74 peripheral-blood and 68/74 marrow-plasma profiles. BCR clonotypes were the highest-recovery feature, with BM-dominant clonotypes recovered in 31/34 callable profiles per compartment. At high tumor fraction, adverse-lesion sensitivity reached 100% in both cfDNA compartments. Marrow plasma cfDNA showed distinct, handling-sensitive fragmentomic architecture (LOOCV AUC=0.910), demonstrating performance depends on compartment, biomarker class, tumor fraction and processing context.

The emergence of bispecific antibodies (BsAbs) targeting T cells (CD3+) and tumor plasma B cells (BCMA+) has provided a new therapeutic option for patients with relapsed/refractory multiple myeloma cancer. However, responses to CD3xBCMA BsAb therapy remain heterogeneous, and treatment is associated with frequent immune-related adverse events. Although baseline immune characteristics have been associated with clinical outcomes, little is known about the early immune dynamics induced by this therapy. Here, we investigated whether longitudinal clinical monitoring and high-dimensional profiling of blood circulating T cells could identify early biomarkers of response or toxicity during treatment. Our results indicate that all treated patients exhibit an early depletion of circulating T cells associated with T-cell activation within the first two weeks. Integration of clinical and immunological parameters using Factorial Analysis of Mixed Data (FAMD) identified immune features associated with treatment outcome. Responders had lower plasma soluble BCMA concentrations, fewer bone lesions, higher circulating lymphocyte counts at baseline. During the first days of treatment, responders exhibited a more pronounced increase in plasma CXCL10 levels, associated with a greater decrease in T lymphocyte counts. Overall, our findings suggest that integrating clinical and immune parameters measured during the first days of treatment may enable early patient stratification and support the development of a predictive score to identify patients with multiple myeloma who are most likely to benefit from CD3xBCMA BsAb therapy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/743749v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1cb079org.highwire.dtl.DTLVardef@1860106org.highwire.dtl.DTLVardef@ad36d3org.highwire.dtl.DTLVardef@1ea5c1e_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIIntegrated clinical and blood T-cell immune profiling using FAMD enables patient stratification following CD3xBCMA BsAb therapy. C_LIO_LIT-cell immune activation occurs predominantly within the first two weeks of therapy. C_LIO_LIFirst-week clinical and immune parameters identify patients most likely to benefit from therapy. C_LIO_LIHigh CXCL10 levels, a profound early decline in circulating T cells, low sBCMA levels, and fewer bone lesions are candidate predictive markers of treatment response. C_LI

Immunotherapy has transformed treatment for many cancers. In the aggressive and genetically heterogeneous diffuse large B-cell lymphoma (DLBCL), CD19 CAR T-cell therapy is highly effective, whereas immune checkpoint blockade has shown limited benefit. Loss of MHC expression is a common mechanism to escape T-cell cytotoxicity, and loss of MHC class I (MHC-I) and II are frequent in DLBCL. We applied imaging mass cytometry to diagnostic biopsies from younger, high-risk DLBCL patients to map the tumor microenvironment (TME) spatial architecture in relation to tumor cell MHC expression, mutational status, transcriptomic and proteomic profiles. Neighborhood analyses identified four TME subtypes: immune-cell depleted and three immune-infiltrated types (mixed, CD4 T cell-rich, CD8 T-cell/macrophage-rich). Depleted cases had shorter overall survival (p = 0.033) and increased expression of proteins involved in DNA replication and proliferation markers compared to infiltrated cases. Tumor cell MHC-I expression was heterogeneous. Cases with low frequency of MHC-I-pos tumor cells were enriched for the depleted TME type. MHC-I-pos tumor cells were surrounded by CD4 and CD8 T cells and M1 macrophages, whereas MHC-I-neg tumor cells were closer to other MHC-I-neg tumor cells. These findings suggest that TME-based classification incorporating tumor cell MHC-I status may improve individualized immunotherapy selection.

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.

Venetoclax and azacitidine (ven-aza) is a standard of care therapy for newly diagnosed acute myeloid leukemia (AML) patients unfit to receive intensive therapy, and may also be appropriate for certain fit patients. Models predicting response to ven-aza currently focus predominantly on genetics. Here, we present two multimodal fusion models: a custom ResNet-34-based model and a pathology foundation model fine-tuned for bone marrow smear (BMS) images that combine clinical and genetic variables with whole slide images. Training on 193 newly diagnosed AML patients who received ven-aza, we obtained an area-under-the-receiver-operating-characteristic (AUROC) of 0.79 and 0.82 for the ResNet-based and fine-tuned foundation models in a heldout test set, and 0.76 and 0.73 in an external validation set, predicting best response to this therapy. Sensitivity analysis showed that fusing image data with clinical and genetic variables outperformed training on either modality alone. In univariable and multivariable analyses, image-based classification was an independent predictive marker, second only in effect size to IDH1/2 mutation status, outperforming other genetic alterations. Image-based explainability showed high model attention on myeloblasts, suggesting previously unrecognized cell-specific patterns associated with response. Our findings suggest BMS images complement genetic biomarkers to refine outcome prediction in ven-aza treatment and incentivize AI-supported outcome prediction, including bone marrow morphology.

Multiple myeloma (MM) exhibits profound molecular heterogeneity, yet current risk stratification relies on cytogenetics or single-omics signatures that often fail to capture cross-layer regulatory complexity. We re-analyzed a multi-omics dataset integrating copy-number, transcriptomic, proteomic, and phosphoproteomic data to dissect how common genomic driver alterations propagate through the molecular cascade. Supervised classification demonstrated that downstream layers, particularly the proteome and phosphoproteome, classify genomic events more accurately than primary genomic or transcriptomic data. Intriguingly, trans-acting features alone were sufficient for classification, indicating that while direct dosage effects manifest at the RNA level, downstream network responses dominate the proteomic state. Multi-omics factor analysis (MOFA2) identified a continuous latent axis predicting progression-free and overall survival independent of R-ISS. This factor captured a gain(1q)/del(13q) axis modulated by immune infiltration and NSD2 expression, integrating variance across all four modalities. To enable clinical translation, we derived sparse, single-modality proxies using elastic net regression. An RNA proxy faithfully recapitulated the multi-omic factor and validated independently in published microarray and RNAseq cohorts, demonstrating robust prognostic utility across treatment eras. These findings reveal that multi-omics integration uncovers hidden prognostic axes obscured by single-omics analyses, and that sparse proxies can bridge the gap between complex discovery and clinical implementation.

Lenalidomide (Revlimid), bortezomib (Velcade), and dexamethasone, are used alone or in combination (RVd therapy) as first-line therapies for hematologic malignancies including the plasma cell dyscrasia, Multiple Myeloma (MM). The effects of RVd treatment on tumor cells have been documented, but little is known about their impacts on "healthy" immune cells. New therapeutics, including chimeric antigen receptor T cell (CAR-T) and bispecific T-cell engagers (BiTEs) depend on robust T cell function but these are often harvested for cellular therapies after or in tandem with RVd therapy. Understanding the molecular effects of these drugs on healthy T cells is therefore of particular importance. Since the molecular effects of each drug includes regulation of key transcription factors, we used a tri-modal, single-cell assay (TEA-seq), simultaneously profiling mRNA transcripts, cell surface proteins, and chromatin accessibility in primary human peripheral blood T cells treated for 4, 24, or 72 hours in vitro. Synergies and conflicts potentially arising from combinatorial therapy were identified and validated by flow cytometry. Doublet and triplet drug combinations were used to assess effects on cell-surface marker expression and on T cell activation. Our results suggest that T cell function can be optimized by the administration of these drugs individually and that sequential administration may offer an opportunity to enhance T cell function by affecting localization and altering T cell states. This work provides those interested in immunology, oncology, and cell therapies an opportunity to explore molecular pathways that could be manipulated by these commonly used drugs to modify T cell function.

Large genomically annotated acute myeloid leukaemia (AML) datasets exist, but population-based contemporary cohorts remain scarce. Here we report clinicopathological, genomic, and outcome data from Danish AML patients. 2,512 AML patients were identified between 2015-2022, of whom 33.8% had available NGS data (NGS+). In patients [&le;]70 years, baseline characteristics and outcomes were comparable between NGS+ and NGS- groups. In patients >70 years, more NGS+ patients received intensive treatment, but survival was similar among intensively treated patients. The distribution of mutations varied significantly by age and sex, with older age and male sex exhibiting higher frequencies of adverse-risk gene mutations. In intensively treated NGS+ patients, ELN2017 stratified 5-year OS: 58.4% (favorable), 43.4% (intermediate), and 28.2% (adverse), with hazard ratios (HRs) of 0.63 (favorable) and 1.45 (adverse) relative to intermediate. ELN2022 yielded corresponding OS rates of 56.9%, 51.8%, and 29.7%, with HRs of 0.78 and 1.86. The two models had comparable predictive performance for OS in a time-dependent model. In conclusion, outcomes of intensively treated AML patients were comparable irrespective of NGS status, underscoring the representativeness of the REFORM-AML database for the Danish AML population. Age and male sex correlated with adverse-risk mutations, and both ELN2017 and ELN2022 robustly predicted survival.

IDH inhibitors promote differentiation and hematological improvement in myeloid malignancies by reversing epigenetic dysregulation. However, molecular predictors of response remain poorly defined. We retrospectively analyzed 79 patients with IDH mutated myeloid malignancies treated with either ivosidenib (IDH1; n=36) or enasidenib (IDH2; n=43). Hematologic benefit was assessed using a composite complete hematologic response (CHR), defined by neutrophil and platelet recovery, and transfusion independence. Targeted sequencing was performed at baseline and at best hematologic response. Associations between co mutations, hematologic response, and treatment duration were evaluated using multivariable models. Overall, 43% of patients achieved CHR, with similar rates between inhibitors. Ivosidenib treated patients achieving CHR demonstrated a significant reduction in IDH1 VAF (p=0.010), which was not observed in enasidenib-treated CHR patients. Within the CHR cohort, ivosidenib patients had a greater reduction in IDH VAF relative to enasidenib patients (mean VAF change -16.74% vs -0.05%, p=0.034). Ivosidenib responders demonstrated a trend toward more durable treatment duration compared with enasidenib responders (p = 0.0908). RUNX1 and BCOR mutations were significantly enriched among patients with incomplete hematologic response and were independently associated with shorter treatment duration after adjustment for clinical factors (RUNX1: HR 2.53, p=0.0024; BCOR: HR 2.31, p=0.0058). IDH1 inhibition was associated with clonal contraction and durable hematologic benefit, a pattern not observed with IDH2 inhibition. Co mutations in RUNX1 and BCOR identified patients unlikely to achieve sustained hematologic improvement, suggesting a secondary block to differentiation. These findings support the integration of mutational and molecular profiling to refine patient selection and guide combinatorial strategies in IDH mutated myeloid malignancies.

Background: African populations remain underrepresented in global genomic reference databases, complicating germline variant interpretation in clinical and research settings. This concern is particularly relevant in Malawi, where population-matched allele-frequency resources are limited. We assessed germline variants in Malawian patients with diffuse large B-cell lymphoma (DLBCL) that were absent from commonly used global reference databases. Methods: Whole-exome sequencing data from 55 histologically confirmed DLBCL cases recruited at Kamuzu Central Hospital, Lilongwe, were analyzed. Germline variants were called using GATK HaplotypeCaller and annotated with Ensembl VEP v110. Cohort allele frequencies were compared with gnomAD v3.1.2, ExAC v1.0, and the 1000 Genomes Project Phase 3 using African (AFR) and European (EUR) reference subsets. Variants absent from all three databases were designated database-absent variants (DAVs); this designation indicates absence from the queried reference panels and does not establish population restriction. Functional consequence, genomic distribution, and enrichment in immune-related loci were evaluated. Results: We identified 127,456 PASS-filtered germline variants across 55 samples. Of these, 332 variants (0.26%) were absent from gnomAD, ExAC, and 1000 Genomes and were distributed across 289 genes (median, one variant per gene; range, 1-8). Predicted loss-of- function variants comprised 16.9% of DAVs compared with 7.8% of the full call set (odds ratio, 2.41; 95% confidence interval, 1.79-3.24; p < 0.001). Seventy-eight DAVs (23.5%) occurred in HLA class I loci (HLA-A, HLA-B, and HLA-C; Fisher's exact test, p < 0.001). Allele-frequency distributions differed from both AFR and EUR reference populations, with greater divergence from EUR (Kolmogorov-Smirnov D = 0.31) than AFR (D = 0.13). The cohort also showed an increased proportion of low-frequency variants relative to both references. Conclusions: Database-absent germline variants were observed in this Malawian DLBCL cohort, including variants with predicted loss-of-function consequences and variants in HLA class I loci. These findings highlight gaps in the representation of Malawian and Southern African genomes in commonly used reference resources and the resulting potential for uncertainty in variant interpretation. Because this case-only cohort lacked matched population controls and sequencing depth was limited, DAVs should not be interpreted as definitively Malawian-specific or pathogenic. Larger, well-covered studies including matched Malawian and Southern African controls are needed to establish population frequencies and improve equitable genomic interpretation.

Diffuse B-cell lymphomas are the most prevalent canine hematologic malignancies, and their clinical presentation resembles that of human B-cell non-Hodgkin lymphomas (NHLs). However, a lack of a clear subtyping framework perpetuates imprecise treatment approaches that fail to address mechanisms of therapy resistance. Here, we employed deep phenotyping via serial sampling and longitudinal transcriptomics to evaluate intratumoral composition and therapy response in a 6-year-old neutered male goldendoodle with stage 5A marginal zone lymphoma (MZL). Following sequential treatment consisting of a single IV dose of oncolytic vesicular stomatitis virotherapy (VSV) and standard CHOP chemotherapy 30 days later, we performed scRNAseq on seven serial lymph node biopsies and spatial sequencing on a resection taken 10 days post-VSV treatment. B cells (>90%) comprised three transcriptionally distinct and temporally stable subpopulations, with specific copy number profiles and robust spatial organization despite disrupted lymph node architecture. Analysis across subpopulations revealed downregulation of the quiescence program including KLF2, suggesting similarity to KLF2-deficient human MZL. While VSV successfully reached target B cells, downstream transcriptional responses were predominantly localized to the T-cell compartment. T cells ([&le;]6%) showed increased proliferation and upregulation of cytotoxicity markers post-VSV administration, enriching for leukocyte-mediated cytotoxicity pathways consistent with an anti-viral immune response. Ultimately, these results provide an in vivo proof-of-concept for the treatment paradigm in canine lymphoma, while emphasizing the need for improved subtyping frameworks and multidimensional treatment strategies targeting intratumoral heterogeneity.

Although B-cell acute lymphoblastic leukemia (B-ALL) is highly responsive to antigen-directed immunotherapies, treatment resistance remains a major barrier to achieving durable responses in patients. We recently developed a novel VpreB1 (CD179a)-directed antibody-drug conjugate with calicheamicin (VpreB1-ADC) that exploits the restricted expression of VpreB1 within the surrogate light chain in early B cells, including B-ALL. In the present work, we investigated mechanisms of resistance to the VpreB1-ADC. Mechanisms of resistance were evaluated using a TCF3::HLF B-ALL model, assessing target engagement parameters including VpreB1 surface expression and antibody internalization. The role of the multidrug resistance transporter ABCB1 (P-glycoprotein) was evaluated via pharmacologic inhibition, using tariquidar and zosuquidar, and enforced overexpression across multiple B-ALL cell lines. Sensitivity to alternative non-ABCB1 substrate payloads exatecan and PNU-159682 was also assessed. Resistant TCF3::HLF cells retained VpreB1 expression and efficient antibody internalization. Instead, resistance was driven by elevated ABCB1 expression and activity. ABCB1 inhibition with tariquidar or zosuquidar restored VpreB1-ADC sensitivity. Conversely, enforced ABCB1 overexpression conferred ADC resistance, which was reversed by ABCB1 inhibition. Cells with high ABCB1 activity remained fully sensitive to alternative payloads, including exatecan and PNU-159682, which are not ABCB1 substrates. ABCB1-mediated drug efflux drives intrinsic resistance to calicheamicin-conjugated ADCs in B-ALL. Combining ADCs with ABCB1 inhibitors or selecting payloads non-susceptible to ABCB1 efflux offer viable strategies to overcome resistance and optimize future ADC therapies.

Acute myeloid leukemia (AML) is an aggressive hematologic malignancy associated with a poor prognosis and an unmet need for more effective treatment options, particularly after relapse. One potential approach to address this need, which has been used successfully in solid tumors, is adoptive transfer of T cells engineered to express specific T cell receptors (TCRs). Particularly attractive are TCRs that can target epitopes derived from oncogenes on which cancer cells depend while sparing normal cells that do not harbor the mutation. One promising oncogenic target in AML is mutated nucleophosmin 1 (mtNPM1), present in up to 30% of AML cases. Most NPM1 mutations result in a common frameshifted sequence that generates peptides presented by several class I human leukocyte antigens (HLAs), such as HLA-A*11:01. In this study, we vaccinated HLA-A*11:01-transgenic mice with the mtNPM1 peptide AVEEVSLRK and isolated six functional TCRs from mtNPM1-reactive lymphocytes. When engineered into human T cells, two of these TCRs consistently mediated robust and specific lysis of an AML cell line and primary AML cells co-expressing HLA-A*11:01 and mtNPM1. Neither TCR recognized related human peptides, HLA-A*11:01-expressing normal peripheral blood mononuclear cells or stem/progenitor cells, or cells expressing diverse allogeneic HLAs, suggesting a low risk of cross-reactivity and alloreactivity. In an AML xenograft model, both TCRs controlled AML in hematopoietic organs, although extramedullary tumors emerged during treatment, potentially reflecting the aggressive behavior of the model that may not be representative of AML in patients. Together, these data suggest that the two TCRs represent strong candidates for further preclinical development in adoptive T cell therapy for NPM1-mutated, HLA-A*11:01-positive AML. These results also support the use of HLA-transgenic mice as a platform for generating TCRs targeting oncogene-derived epitopes in hematologic malignancies.