Citations

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: Recent clinical trials of immune checkpoint inhibitors (ICI) in multiple myeloma (MM) demonstrated the need to prioritize patients most likely to benefit from this type of therapy (Richard, et al., Nat. Cancer, 2024). Immune checkpoints in MM function through receptor-ligand (RL) interactions between CD8+ T cells and malignant plasma cells. However, there is a gap in our understanding of the immune checkpoint landscape in newly diagnosed MM (NDMM). To explore this, we mapped known immune checkpoint RL pairs in subjects enrolled in the CoMMpass Study (NCT01454297), a prospective, longitudinal observational trial. Methods Bone marrow aspirates from study participants were collected and separated into CD138 positive and CD138 negative fractions for comprehensive molecular characterization of the tumor (using bulk RNA sequencing and whole genome sequencing) and tumor immune microenvironment (using 3' single cell RNA sequencing (scRNA-seq)). 191 patients had paired bulk tumor and single cell immune expression profiles. To evaluate the co-expression of receptor-ligand pairs, we developed two approaches that combine gene expression values across single cell and bulk RNA-seq. The first approach uses joint percentiles to identify patients with high expression (top 75%) of both receptor and ligand (referred to as high-high). The second approach uses a rank-based interaction score to create a single value for each patient within a distribution defined for each receptor-ligand pair; patients with extreme values have high expression of both receptor and ligand. The two methods identified similar sets of patients with high co-expression of receptor and ligand. We then compared progression free survival (PFS) across receptor-ligand co-expression groups (high-high vs. others) and tested for other clinical associations. From a pre-defined list of 17 receptor-ligand pairs (Liu, et al., Exp. Hematol. Oncol., 2023), we focused on the following receptors (from CD8+ T cells) and ligands (from tumor plasma cells): PD-1 with PD-L1; LAG-3 with MHC-II; TIGIT with CD115; and TIM-3 with phosphatidylserine. Results Overall, 91 patients (91/191, 47.6%) showed high-high co-expression for at least 1 out of 17 receptor-ligand pairs, and 100 patients were high-high for no receptor-ligand pairs. Among patients with at least one high-high pair, there was a median of 2.0 high-high pairs (range: 1-11). Hierarchical clustering of high-high status and rank-based interaction score correlations showed that for a given receptor, patients often showed high-high co-expression across multiple related ligands. For TIM-3 (receptor, CD8+ T cells) and phosphatidylserine (ligand, tumor plasma cells), we identified 16 patients (16/191, 8.4%) with high-high co-expression and significantly worse PFS (median survival 485 vs. 1503 days, log-rank p-value 0.043). For PD-1-PD-L1, we identified 7 patients with high-high co-expression; for LAG-3-MHC-II, 12 patients (6.3%); and for TIGIT-CD115, 13 patients (6.8%). Conclusion ICI therapy remains an emerging area of study in MM. Here, we developed methods to explore immune checkpoint receptor-ligand co-expression from paired immune microenvironment and tumor cell populations. Our approach demonstrates the value of data integration across gene expression modalities, especially when standard sample collection methodologies segregate tumor and immune populations. Co-expression analysis may be one factor in prioritizing patients for immune checkpoint inhibitor therapy.

Abstract Background: For LS-DLBCL, clinical trials (FLYER, LYSA/GOELAMS 02-03, LYSA LNH09-1B, S1001) have shown that 4 cycles of rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone (RCHOP4) without radiation (RT) leads to durable remissions in >90% of cases. However, only patients (pts) with non-bulky disease and/or international prognostic index (IPI) of 0 and complete metabolic response (CMR) on interim positron emission tomography (PET) scan, if performed, were eligible for RCHOP4 alone in these studies. Outcomes in trial-ineligible LS-DLBCL and the appropriate real-world candidates for RCHOP4 are still undefined. Methods: We conducted a multicenter retrospective study of adult pts with stage I/II DLBCL of any tumor bulk, IPI and with or without B-symptoms diagnosed after 2011 and treated with RCHOP4 +/- 2 cycles R from 21 U.S. centers. Pts with PMBCL, PTLD or receiving non-standard dose RCHOP for cycle (C) 1 or planned consolidative RT were excluded. The primary endpoint was PFS from C1 by Kaplan-Meier method, not counting indolent lymphoma relapse. Event free survival (EFS) was time to next therapy without progression (including unplanned RT for non-CR), progression or death. A competing risks analysis of non-relapse mortality (NRM) vs. DLBCL progression was performed. Results: The characteristics of the 428 pts were: median age 60 (18-88), 60% male, 11% Hispanic and 4% non-Hispanic Black, 62% stage I, 15% elevated LDH, 3% ECOG PS>1, 5% tumor bulk >7cm, 9% had B-symptoms and median Charlson Comorbidity Index (CCI) was 4 (2-12). IPI was 0, 1 and 2-3 in 42%, 46% and 12% and stage-modified IPI (smIPI) was 0, 1, 2 and 3-4 in 25%, 48%, 21% and 6% of pts. 66% had nodal (59% head/neck, 11% pelvic, 9% multiple above diaphragm, 7% abdominal) and 46% extranodal sites (37% head/neck, 20% gastric/intestinal, 9% spleen, 8% skin/soft tissue); 6% had transformed/concurrent FL/MZL or grade 3B FL, 33% (138/408) were non-GCB cell of origin (COO), 25% (90/357) double expressor (DEL) and 0.5% (2/379) double-hit. 13% had completely resected disease, 97% staging PET and 47% bone marrow biopsy. Median diagnosis to treatment interval was 30 days (IQR 20-43), 6% had dose reductions after C1, 77% had an interim PET (iPET) after C2 (33%) or C3 (67%), 15% received 2 additional cycles R and 4% CNS prophylaxis. CMR rates by iPET were 83% after C2 and 94% after C3, and 95% by end-of-treatment PET. iPET PMR was more likely if smIPI>2 or bulky disease. Median follow-up time was 2.7 years. There were 32 progression events: 14 occurred at the primary site and 17 at distant sites (1 unknown), and 12 occurred after 2 years. Another 11 pts received unplanned RT after RCHOP4 for non-CR. There were 24 deaths, 12 without prior progression. Cause of death was DLBCL in 7 and non-DLBCL in 17 cases (6 infection, 2 ILD, 2 heart failure, 2 second cancer, 1 seizure, 4 unknown). EFS, PFS and OS rates were 88%, 90% and 96% at 3 years. By univariable Cox regression, Black race, elevated LDH, smIPI>2, DEL, increasing CCI, multiple subdiaphragmatic nodal sites and iPET PMR were associated with worse PFS. Non-significant variables of note included COO, extranodal sites, complete resection, missing bone marrow biopsy, missing iPET and additional cycles R. By multivariable analysis (including age>60, stage, ECOG PS>1, elevated LDH, bulky disease, CCI, B-symptoms and DEL), ECOG PS>1 (HR 3.95 p=0.050), CCI (HR 1.29 p=0.003) and DEL (HR 2.02 p=0.069) were associated with worse PFS. Cumulative incidence of DLBCL progression and NRM were 8% and 2% at 3 years. Competing risk analysis by univariable models found that age>60, ECOG PS>1, smIPI>2, elevated LDH, CCI and bulky disease were associated with NRM, while DEL and B-symptoms were associated with DLBCL progression.Conclusion: Presented is the largest retrospective cohort of LS-DLBCL treated uniformly with RCHOP4 to date. Despite modest follow-up time and lack of an “intention-to-treat“ population, this study shows that abbreviated RCHOP4 leads to excellent outcomes in the real-world, albeit with continuous risk of late relapse. smIPI risk factors were associated with worse PFS, though this may in part be driven by risk of non-lymphoma death. As pts with advanced age, poor performance status or comorbidities may benefit from reduced treatment exposure, RCHOP4 should still be considered for these and other “trial-ineligible” pts, particularly if other high-risk features (iPET PMR, DEL or B-symptoms) are absent.

Abstract The CoMMpass study (NCT01454297) is a prospective, longitudinal observational trial involving 1,141 newly diagnosed, treatment-naïve multiple myeloma (NDMM) patients. Bone marrow aspirates from the study participants were collected, separated into CD138 negative and CD138 positive fractions 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 these study participants. CE provides four main views: Overall Summary for clinical feature distribution and Kaplan-Meier curves; Mutational Profile for visualizing and comparing somatic mutations; Tumor Profile for differential expression and gene set enrichment; and Immune Microenvironment for comparing cell type abundance and cell cycle dynamics between cohorts using scRNA-seq data. 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. We validated CE by reproducing findings from two prior CoMMpass-based studies. In the first study by Simhal et al, we stratified patients using transcript-level expression by WEE1 into tertiles and confirmed that high WEE1 expression is associated with poorer progression-free survival across multiple genomic subgroups. In the second study by Manojlovic et al, we replicated mutation frequencies between African American and Caucasian patients by creating race-based cohorts. We further demonstrate CE's utility by identifying and comparing two NDMM cohorts of patients at baseline who have not received autologous stem cell transplant: cohort 1 includes patients that received up-front triplet therapy (N=342) and cohort 2 includes those who did not receive a triplet up-front (N=235). While survival differences between these two cohorts were not statistically significant (p>0.05), CE revealed elevated epithelial-mesenchymal transition (EMT) pathway activity in cohort 1. Immune profiling showed lower abundance of CD8+ T cells (p < 0.05) and NK cells (p = 0.01), but a higher abundance of B cells (p < 0.05) in cohort 1. Genomic data showed fewer EIF2AK3 mutations and higher transcript-level expression of EIF2AK3 in cohort 1. Notably, patients in cohort 1 with lower transcript-level expression of EIF2AK3 had better survival outcomescompared to patients in cohort 2. CE democratizes access to the CoMMpass multi-omic resource, allowing researchers to interrogate clinical and molecular heterogeneity with ease. By enabling hypothesis generation and replication of published results, CE serves as a valuable tool for identifying meaningful patterns in gene expression, mutation profiles, and immune contexture. It also highlights potential prognostic biomarkers, such as EIF2AK3 expression, that may inform treatment decisions in NDMM, especially in the context of triplet-based regimens.

Importance Primary brain and central nervous system cancer (collectively referred to as CNS cancer) comprises 2% of all human cancers and poses significant health and economic challenges in the United States. Objective To analyze CNS cancer burden in the US, stratified by time, location (state and division), sex, age group, and Sociodemographic Index (SDI). Design, Setting, and Participants This cross-sectional study involved a repeated analysis of Global Burden of Disease Study (GBD) 2021 data in 2024. Using data from 183 sources, CNS cancer metrics in the US were estimated across states and years. US CNS cancer metrics across all sexes and age groups were included in the GBD. Exposure CNS cancer diagnosis. Main Outcomes and Measures Overall and age-standardized estimates of the incidence, prevalence, mortality, disability-adjusted life-years (DALYs), years of life lost, and years lived with disability per 100 000 population, including 95% uncertainty intervals (UIs), and time trends. Results In 2021, for all age groups and sexes across the US, there were 31 780 incident cases (95% UI, 29971.1 to 32843.9). Age-standardized incidence, DALYs, and mortality rates per 100 000 population were 6.91 (95% UI, 6.58 to 7.12), 134.38 (95% UI, 129.83 to 137.95), and 4.1 (95% UI, 3.87 to 4.22), respectively. Despite no significant change observed in the overall incidence between 1990 and 2021, DALY and mortality rates decreased by 15.77% (95% UI, −17.75% to −13.68%) and 8.41% (95% UI, −11.09% to −6.22%), respectively. Substantial geographic variability was noted. Mississippi, Alabama, Kentucky, and Kansas (West North Central and East South Central divisions) and West Virginia faced persistently high burdens over the past 30 years. Sex differences were evident; disease burden was consistently higher in males compared with females. Age-specific estimates showed a bimodal distribution: the youngest group (<5 years) showed a significant decrease in incidence rate (−34.42% to −11.56%), whereas older age groups (>70 years) experienced increasing trends. DALYs and mortality rates were negatively correlated with SDI (ρ = −0.6860 and ρ = −0.6391; P < .001). Conclusions and Relevance These findings provide valuable insights into the CNS cancer burden across the US by age, sex, location, and SDI, enabling better public health status assessments, health care policy restructuring, and resource redistribution for improved care.

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. The mean scores for the teams were calculated. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. The Dice score for the winning team was 0.65 ± 0.25. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space. The Dice scores and lesion detection rates of all algorithms diminished with decreasing tumor size, particularly for tumors smaller than 100 mm3. In conclusion, algorithms for BM segmentation require further refinement to balance high sensitivity in lesion detection with the minimization of false positives and negatives. The BraTS-METS 2023 challenge successfully curated well- annotated, diverse datasets and identified common errors, facilitating the translation of BM segmentation across varied environments and providing the tools for future development of personalized volumetric reports to patients undergoing BM treatment.

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.