Citations

Abstract Genome sequencing of the heterogeneous primary mitochondrial disorders (PMD) frequently reveals variants of uncertain significance that require functional tests for diagnosis, and does not identify variants in all patients. We analyzed mitochondrial enzyme assays, blue native polyacrylamide gel electrophoresis (BN-PAGE) with in-gel activity staining, complex I assembly blot, and select protein abundances in fibroblasts of a case series of 204 PMD patients divided into functional classes, in comparison to 51 controls and 53 differential diagnostic conditions. Overall, sensitivity and specificity for respiratory chain enzyme assays were 46% and 93% respectively, for BN-PAGE 40% and 98%, for complex I assembly assay 49% and 99%. The overall sensitivity of all tests was 76%, specificity 93%, with positive predictive value 96% and negative predictive value 67%. Categories with high sensitivity were isolated complex deficiencies, nuclear DNA-encoded mitochondrial protein synthesis defects, co-factor defects, and mitochondrial amino-acyl-tRNA synthetase conditions when aided by protein abundance. Mitochondrial DNA mutations and maintenance disorders showed poor sensitivities. Secondary dysfunctions were rare. A complete battery of functional tests showed strong diagnostic clinical utility in fibroblasts. One sentence summary A combination of four mitochondrial functional tests to identify or confirm suspected primary mitochondrial disease in fibroblasts had good sensitivity and excellent specificity, well beyond what was perceived using enzyme assays only.

Abstract Background: The Multiple Myeloma Research Foundation (MMRF) and its partners launched the MyDRUG platform clinical trial (NCT03732703) to evaluate the safety and efficacy of genomically-guided treatments for functional high-risk relapsed/refractory myeloma patients (fHRMM). fHRMM patients with no discernible activating mutations and who had received 1-3 prior therapies (exposed to at least one proteasome inhibitor and an IMiD) were given a combination of daratumumab (D), ixazomib (I), pomalidomide (P) and dexamethasone (d) (D-IPd) quadruplet therapy. The goal of this study is to evaluate the immunomodulatory effects of daratumumab-(anti-CD38)-based therapy on fHRMM patients enrolled in the MMRF-sponsored MyDRUG umbrella clinical trial over the duration of therapy and to correlate immune changes with patient response immediately following the first two cycles of therapy. Methods Bone marrow (BM) aspirates were collected at baseline (BL) prior to therapy, at the end of 2 cycles (EOC2), 4 cycles (EOC4) of the quadruplet therapy and at the end of treatment (EOT) or progressive disease (PD). CD138-negative bone marrow mononuclear cells were isolated for profiling the immune microenvironment using scRNAseq, scTCRseq and CyTOF. Results Single-cell RNA and TCR profiles were generated from ~90,000 cells across 41 samples from 16 subjects. scRNAseq identified CD3+ T cells, NK cells, classical and non-classical monocytes and B cells. CD8+ T cells were further resolved into their subsets including precursor (TPEX) and terminally exhausted T cells (TEX) within the bone marrow microenvironment. Within the CD8+ T cell compartment, an expansion of the effector memory (TEM) cell population was observed following 2-cycles of therapy (EOC2). However, this TEM expansion was not sustained at timepoint EOC4. Towards the end of therapy, enrichment of precursors to putative exhausted and terminal dysfunctional effector memory cells (TEMRA) was observed. Subjects with partial (PR), very good partial (VGPR) and complete (CR) best overall responses showed an initial increase in TEM cells followed by a slow expansion of TEX and TEMRAcells over time. One patient with progressive disease (PD) maintained the highest LAG3 expression across the cohort among CD8 T cell subsets (TEMRA, EM) and CD4 Tregs at baseline while observing a significant upregulation of PDCD1 in CD4 Tregs and CD8 Naive cells by EOC2. Cell-cell communication network analysis identified secreted ligands between responders (CR/VGPR) and partial responders (PR) at EOC2. Samples with PR exhibited upregulation of signaling of TNF from the CD8 Naïve compartment (p=0.048, Wilcoxon), IFNG from the CD8 EM (p=0.073, Wilcoxon) and TEMRA (p=0.048, Wilcoxon) populations along with IFNG (p=0.073, Wilcoxon) from NK cells. CD14+ and CD14+16+ Monocytes on the other hand showed enrichment of LGALS9 (p=0.03 (CD14+), p=0.048 (CD14+CD16), Wilcoxon) in the PR group at EOC2 relative to responders. Finally, longitudinal tracking of T cell clonality showed preferential progressive expansion of TEMRA cells after the therapy. We mapped hyperexpanded (more than 16 copies) clonotypes, presumed to be tumor-reactive, to various CD8+ T cell subsets. These hyperexpanded clonotypes are mapped to the TEMRA, TEX and TEM CD8+ T cells. Analysis of TCR repertoires clonality and diversity also demonstrated a reduced richness and increased clonality of CD8+ TCRs in responders. Summary/Conclusion These preliminary analyses of D-IPd quadruplet therapy of RRMM indicate that paired single cell RNA and TCR sequencing of BM T cells suggests a selective expansion of clonotypic CD8+ T cells. When considering patient response, the only PD patient profiled in this study maintained an exhaustive signature (LAG3, PDCD1) in multiple T cell compartments at BL. The differential expression of the receptor ligand pairs after treatment between different clinical response groups suggests an altered TME response that may inform future therapeutic stratification. These results support further explorations of rational combinations of targeted and immune therapies for greater efficacy in this disease.

Abstract Background: The goal of this study is to evaluate the immunomodulatory effects of daratumumab-(anti-CD38)-based therapy on fHRMM patients enrolled in the MMRF sponsored MyDRUG umbrella clinical trial (NCT03732703) over the duration of therapy and to correlate immune changes with patient response. Methods: fHRMM who had received 1-3 prior therapies (exposed to at least one proteasome inhibitor and an IMiD) were given a combination of daratumumab (D), ixazomib (I), pomalidomide (P) and dexamethasone (d) (D-IPd) quadruplet therapy. Bone marrow (BM) aspirates were then collected from patients prior to therapy (BL), after 2 cycles (EOC2), after 4 cycles (EOC4) of the quadruplet therapy and at the end of treatment or disease progression (EOT). Immune and tumor fractions were enriched by CD138 selection. Here, CD138- bone marrow mononuclear cells were isolated and transcriptionally profiled by scRNAseq and scTCRseq. Results: Single-cell RNA and TCR profiles were generated from ∼90,000 cells across 41 samples from 16 subjects. scRNAseq identified CD3+ T cells, NK cells, classical and non-classical monocytes and B cells. CD8+ T cells were further resolved into their subsets including precursor (TPEX) and terminally exhausted T cells (TEX) within the bone marrow microenvironment. Within the CD8+ T cell compartment, an expansion of the effector memory (TEM) cell population was observed following 2-cycles of therapy (EOC2). However, this TEM expansion was not sustained at timepoint EOC4. Towards the end of therapy, enrichment of precursors to exhausted and terminal dysfunctional effector memory cells (TEMRA) was observed. Subjects with partial (PR), very good partial (VGPR) and complete (CR) best overall responses showed an initial increase in TEM cells followed by a slow expansion of TEX and TEMRA cells over time. Longitudinal tracking of T cell clonality showed preferential progressive expansion of TEMRA cells after the therapy. We mapped hyperexpanded (more than 16 copies) clonotypes, presumed to be tumor-reactive, to various CD8+ T cell subsets. These hyperexpanded clonotypes mapped to the TEMRA, TEX and TEM CD8+ T cells. Analysis of TCR repertoires clonality and diversity also demonstrated a reduced richness and increased clonality of CD8+ TCRs in responders. Conclusions: Paired single cell RNA and TCR sequencing of BM T cells from RRMM patients receiving D-IPd quadruplet therapy revealed a selective expansion of clonotypic CD8+ T cells with a clonal replacement of BM exhausted clonotypes by dysfunctional circulating CD8+ T cells in responders over time. Citation Format: Chaitanya R. Acharya, Darwin D'souza, Reyka Jayasinghe, Mark Hamilton, Zhihong Zhihong, Seunghee Kim-Schulze, Hearn J. Cho, Shaji Kumar, George Mulligan. The immunomodulatory effects of daratumumab-based therapy on functional high-risk relapse/refractory multiple myeloma (fHRMM) patients enrolled in the MyDRUG trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5258.

Introduction: In recent years, multiple myeloma (MM) research has increasingly focused on unraveling the complex interactions between malignant plasma cells and their surrounding bone marrow microenvironment (BMME). To further elucidate these interactions, we developed a comprehensive single-cell atlas of the MM BMME, integrating both coding and noncoding (ncRNA) transcriptional profiles. By correlating these profiles with specific cytogenetic abnormalities in myeloma cells, we aim to uncover how ncRNAs regulate the phenotypic and functional states of myeloma cells and, consequently, shape the cellular landscape of the BMME. A detailed understanding of how the noncoding transcriptome affects the cellular components and immune landscape of the BMME is essential for advancing our knowledge of MM pathogenesis and identifying novel biomarkers and therapeutic targets. Methods: Our atlas was constructed using single-cell RNA sequencing data from 481 samples of CD138neg cells sorted from bone marrow aspirates of MM patients enrolled in the MMRF CoMMpass study. This dataset includes accompanying whole-genome sequencing and survival data, enabling correlative analysis between transcriptional profiles, cytogenetic abnormalities, and patient outcomes. To generate a combined coding and non-coding transcriptome, we developed an expanded human reference genome by systematically merging mRNA and ncRNA transcripts from the LncBook2.0 and GENECODEv42 reference genomes. The sequencing data was aligned to this expanded genome, followed by quality control processing, batch correction, clustering, and supervised analysis. Results: The resulting coding and non-coding atlas comprises over 1.9 million cells, spanning immune, plasma, and stromal compartments. Remarkably, ncRNAs constituted 46% of the associated genes, including 22,102 long ncRNAs (lncRNAs) and 3,112 small ncRNAs. Subclustering analysis of the major immune compartments (B lymphoid, myeloid, and NK and T lymphoid) yielded 70 subclusters, with ncRNAs representing 24-38% of the top 100 differentially expressed genes within each compartment. This underscores the significant role of ncRNAs in distinguishing immune subpopulations. Moreover, examining the association between specific cytogenetic abnormalities and the immune composition of the BMME, 30 subclusters were found to be differentially abundant (P < 0.05) between cytogenetic abnormalities, supporting our hypothesis that myeloma cell genotypes significantly shape the immune microenvironment. For instance, patients with CCND1 amplification displayed an increase CD4+ central memory T cells with a decrease in CD8+ cytotoxic T cells. Similarly, patients with 1q21 gain exhibited an increase in TGFβ-stimulated monocytes, while a decrease in cytotoxic CD8+ T and CD56dim NK cells was observed in patients with 17p13 deletion. Next, examining which ncRNAs are associated with specific cytogenetic abnormalities, we identified 14 ncRNAs significantly differentially expressed across cytogenetic abnormalities. Increased expression of six of these ncRNAs were associated with poor overall survival both independently and in combination (P < 0.05, HR = 3.7). Notably, three of these ncRNAs have documented roles in cancer progression but have not been previously studied in the context of MM. Subsequently stratifying patients based on their enrichment of these outcome-associated ncRNAs revealed even stronger associations with immune composition, including an increase in CD4+ regulatory T cells (P < 0.05). This further supports our hypothesis that myeloma cell genotypes shape the BMME. Lastly, by constructing a gene regulatory network to predict the interactions between coding and noncoding RNAs, we illustrate the regulatory networks of ncRNAs modulating the phenotypes of myeloma and immune cell subpopulations. Conclusion: In summary, we present the first high-resolution transcriptomic atlas of the MM BMME, integrating both coding and noncoding RNAs. This study reveals distinct immune subpopulations associated with specific myeloma cell genotypes and highlights the central role of ncRNAs in modulating the phenotypic and functional states of both malignant and non-malignant cells in the MM BMME. Our findings emphasize the potential of ncRNAs as therapeutic targets and prognostic markers for MM, offering new avenues for research and clinical intervention.

Introduction As part of the Multiple Myeloma Research Foundation (MMRF) MyDRUG umbrella clinical trial, we compared immune cell transcriptomic and proteomic signatures of multiple myeloma bone marrow samples from patients assessed by single-cell RNA sequencing (scRNA-seq) and mass cytometry (CyTOF). The goal of our study is to evaluate the effects of cobimetinib on the immune repertoire over the treatment course at single-cell resolution. Methods Bone marrow samples were collected from patients prior to therapy with cobimetinib (baseline/BL), after 2 cycles of cobimetinib therapy (EOC2), after 2 cycles of combination cobimetinib with IPd (EOC4) and at the end of treatment or at disease progression (EOT). All samples were processed into CD138+ myeloma cell and CD138- “immune cell” fractions for single-cell analysis. In this study, the CD138- “immune cell” fractions were transcriptionally profiled by single-cell RNA-sequencing (scRNA) at up to four time points. Results Transcriptome profiles of approximately 50,000 cells were analyzed across 22 samples from 9 patients with tumor MAPK Pathway mutations including: BRAF (p.K483Q, p.V600E, n=2); KRAS (p.Q61H, p.G12V, p.G12R, n=3); NRAS (p.Q61H, p.Q61R, p.Q61K, n=4). A subset of paired samples were subject to CyTOF with two immune related panels to supplement the single-cell transcriptomic findings. Focusing on one immune panel, 4 samples were profiled at baseline and end of cycle 2 while two samples were profiled only at baseline capturing over 600,000 cells spanning both timepoints. Our immune focused CyTOF panel contained 41 markers including T and NK cell markers (CD4,CD8A,CD3, GZMB, CD56), Myeloid lineage markers (CD14), B/Plasma markers (CD19, CD20, SLAMF7, CD38) among others. The largest populations captured by CyTOF included 260,000 neutrophils, 139,000 monocytes, 130,000 CD4/CD8 T cells, 43,000 NK cells, 40,000 dendritic cells and 22,000 B/plasmablasts/myeloma cells. Exhaustion markers, including LAG3 and TIGIT, are increased in CD8 and CD4 T cells after MEK inhibition, while PD1 is downregulated. PD-L1 is upregulated in both T cell compartments (CD4/CD8), monocytes and in residual myeloma cells profiled by both CyTOF and scRNA-seq. Both the IFNG and STAT1 pathways are concurrently upregulated post MEK inhibition in transcriptionally distinct CD8 T cell subsets profiled by scRNA-seq, suggesting a mechanism influencing PD-L1 expression. Conclusions These data indicate IFNG pathway activation by CD8+ T cells post MEK inhibition promotes PD-L1 expression on residual myeloma cells, suggesting the PD-L1 and IFNG signaling axes is activated in relapsed refractory myeloma patients after MEKi treatment. Here we present immunophenotypic and transcriptional profiling of longitudinal samples pre/post-MEK inhibition with multiple myeloma patients which can inform precision guided treatment options.

Introduction Newly-diagnosed multiple myeloma (MM) patients often share tumor genetic abnormalities associated with a high risk of progression and poor survival. We hypothesized that single-cell transcriptomic characterization of the tumor immune microenvironment (TIME) may be combined with tumor-based risk stratification to uncover novel disease biology mechanisms associated with clinical outcomes and improve risk stratification. Methods We performed single-cell RNA sequencing of 361 CD138 negative sorted bone marrow mononuclear cells (BMMCs) samples from 263 MM patients enrolled at time of diagnosis in the Multiple Myeloma Research Foundation CoMMpass study (NCT01454297). Specimens were analyzed at baseline (n=263) across a network of five collaborating academic research centers following assay harmonization. Genetic factors that determine risk were defined as one or more of the following gain- or loss-of-function events derived from baseline genomic sequencing data: del17p14, translocations of the Ig locus with the MAF/A/B or WHSC1/MMSET/NSD2 loci, and gain of chromosome 1q21. Statistical modeling strategies were used to assess single-cell populations or RNA signatures associations with known risk factors or disease progression (FDR<0.05). Results The study generated high-quality single-cell profiles of 731,643 cells from 123 high-risk and 107 standard-risk MM patients based on genetics. Based on distinct transcriptome profiles, BMMCs formed 106 clusters corresponding to 5 major compartments: NK and T cells, B cells, erythrocytes, myeloid cells, and plasma cells. Our preliminary differential abundance analysis comparing high- vs standard-risk patients at baseline uncovered significant differences in the TIME associated with genetic risk. The high-risk group was identified as enriched in effector CD8+, and CD4+ T cells. In contrast, the high-risk group exhibited depletion of naive CD8+ and interferon-associated CD4+ and CD8+ T as compared to the standard-risk group. Within subclusters in the T and NK cells compartment, a higher cytotoxicity signature was observed in high-risk patients, characterized by the expression of granzymes and perforin. Finally, our preliminary survival and progression analysis associated a higher frequency of IDO1-expressing macrophages in worst progression patients, while better outcomes were associated with CD8+ T and B cells expressing androgen response and IL6/STAT3/EMT programs, respectively. Conclusions Current approaches for risk stratification are based on bulk measurements of tumor's genetic or epigenetics features, which do not capture the diversity and dynamics of the TIME. Through single-cell transcriptomics, we were able to capture, in high granularity, the TIME and correlate specific immune cell populations and phenotypes with relapse risk and poor prognostic outcomes. These results suggest that immune subpopulations may be an essential novel aspect for improving current risk stratification models.

OBJECTIVE The management of excess CSF in patients with hydrocephalus typically requires using a shunt to divert CSF. Unfortunately, there is a high rate of shunt failure despite improvements in device components and insertion techniques. Reoperation is frequently necessary, which contributes to patient harm and increased healthcare costs. While factors affecting shunt failure are well defined in the pediatric population, information regarding adults is lacking. The authors undertook a systematic review and meta-analysis to determine how shunt failure in the adult population is reported and investigated the etiologies of shunt failure. METHODS This review is reported according to PRIMSA and utilized the MEDLINE, Embase, and Google Scholar databases. Abstracts were screened by two independent reviewers, and data were extracted in duplicate by two independent reviewers. Statistical analyses were performed using SPSS and Stata. RESULTS The pooled rates of shunt failure were 10% (95% CI 5%–15%) in studies with a mean follow-up time of less than 1 year, 12% (95% CI 8%–14%) with a follow-up time between 1 and 2 years, and 32% in studies with a follow-up time of 2 years or greater (95% CI 19%–43%). The pooled rate of failure was 17% across all studies. The most common cause of shunt failure was obstruction at 3.0% (95% CI 2%–4%), accounting for 23.2% of shunt failures. Infection was the second most common at 2.8% (95% CI 2%–3%), accounting for 22.5% of shunt failures. The most common location of shunt failure was the distal catheter, with a failure rate of 4.0% (95% CI 3%–5%), accounting for 33.4% of shunt failures. The definition of shunt failure was heterogeneous and varied depending on institutional practices. The combination of symptoms with either CT or MRI was the most frequently reported method for assessing shunt failure. CONCLUSIONS Important variation regarding how to define, investigate, and report shunt failure was identified. The overall shunt failure rate in adults is at least 32% after 2 years, which, while lower than that typically reported in the pediatric population, is significant. The most common causes of shunt failure in adults are infection and obstruction. The most common site of failure occurred at the distal catheter, highlighting the need to develop strategies to both report and mitigate distal shunt failure in adult shunt patients.