Citations

Abstract Background Relapsed medulloblastoma remains a significant therapeutic challenge as it is near universally fatal. The tumor microenvironment of medulloblastoma plays a critical role in tumor progression, influencing tumor growth, immune evasion, and therapeutic resistance. We hypothesized that defining tumor-immune interactions in diagnostic and relapsed medulloblastoma may uncover mechanisms of immune evasion and identify novel therapeutic targets. Methods We analyzed paired primary and recurrent RNA-sequencing data from 140 medulloblastoma patients to profile immune cell composition and validate spatial relationships within the TME. To identify key tumor-immune interactions, we developed a novel algorithm to detect receptor-ligand pairs using single-cell RNA-sequencing data. These interactions were validated across RNA and proteomic datasets. Their functional significance was empirically demonstrated in newly developed immunocompetent models of recurrent medulloblastoma that closely recapitulate the human disease. Results We observed a shift toward a heightened immunosuppressive TME at relapse. Using our algorithm, we identified biologically significant receptor-ligand interactions, most notably MIF-CD74, constitutively expressed at RNA and protein levels across medulloblastoma subgroups, at diagnosis and relapse. Disrupting MIF-CD74 interactions led to significant alterations in the tumor microenvironment, highlighting its functional significance. Conclusions Our multifaceted approach identified key tumor-immune interactions in medulloblastoma. Among these, MIF-CD74 was validated as a targetable interaction, demonstrating the utility of our integrative approach for identifying novel therapeutic targets across multiple tumor types.

OBJECTIVE Core outcome sets (COSs) are needed to promote data consistency across studies as well as data synthesis and comparability. The aim of the current study was to use a modified Delphi process to develop a COS for lateral femoral cutaneous neuropathy (LFCN), hereafter COS-LFCN. METHODS A 5-stage approach was used to develop the COS-LFCN: 1) consortium development, 2) literature review to identify potential outcome measures, 3) Delphi survey to develop consensus on outcomes for inclusion, 4) Delphi survey to develop definitions, and 5) consensus meeting to finalize the COS and definitions. This study followed the Core Outcome Set - STAndards for Development, (COS-STAD) recommendations. RESULTS The Core Outcomes in Nerve Surgery (COINS) Consortium comprised 25 participants, all neurological surgeons, representing 14 countries. The final COS-LFCN consisted of 41 factors and outcomes covering domains of demographics, diagnostics, patient-reported outcomes, motor/sensory outcomes, and complications. Appropriate instruments, methods of testing, and definitions were set. The consensus minimum duration of follow-up was 12 months, with the consensus optimal time points for assessment being preoperatively and 3, 6, and 12 months postoperatively. CONCLUSIONS The COINS Consortium developed a consensus COS for LFCN and provided definitions, methods of implementation, and time points for assessment. The COS-LFCN should serve as the minimum data to be collected in all future neurosurgical studies on LFCN. Incorporation of this COS will help improve consistency in reporting, data synthesis and comparability, and minimize outcome reporting bias.

With most states lacking comprehensive legislation addressing overdose preparedness in schools, there is an urgent necessity for prompt and effective solutions that accommodate existing resource constraints. Arizona, the primary entry point for over 55% of US fentanyl trafficking, responded to this critical public health challenge by initiating the nation’s first unfunded grassroots collaboration between community and government sectors to enhance statewide school overdose prevention and preparedness. The School Training, Overdose Preparedness and Intelligence Task force (STOP-IT) included more than 60 volunteers from the health care, legal, education, local government and behavioral health fields and worked collaboratively with the Arizona Department of Education to develop a response. Within 6 months of inception, STOP-IT conducted a comprehensive school survey to identify barriers to naloxone accessibility, created evidence-based school policies, established a sustainable and complimentary naloxone supply chain for schools with an ordering platform, and implemented a statewide naloxone distribution plan. The amassed resources were organized into a Fentanyl and Overdose Response Toolkit, widely disseminated to more than 2000 public, private, and charter schools. Moreover, STOP-IT launched both a local and national public information campaign to effectively raise awareness about the opioid crisis in schools. Using various media channels such as webinars, podcasts, media broadcasts, newsletters, and peer-reviewed publications, the campaign successfully amplified its message and enhanced community engagement. The STOP-IT initiative emerged as an innovative collaboration between government and community leaders, united in their mission to combat the growing opioid crisis in schools.

Autoantibodies contribute to many autoimmune diseases, yet there is no approved therapy to neutralize them selectively. A popular mouse model, experimental autoimmune encephalomyelitis (EAE), could serve to develop such a therapy, provided we can better understand the nature and importance of the autoantibodies involved. Here, we report the finding of autoantibody-secreting extrafollicular plasmablasts in EAE induced with specific myelin oligodendrocyte glycoprotein (MOG) antigens. Single-cell RNA sequencing reveals that these cells produce nonaffinity-matured IgG antibodies. These include pathogenic antibodies competing for shared binding space on MOG’s extracellular domain. Interestingly, the synthetic anti-MOG antibody 8-18C5 can prevent the binding of pathogenic antibodies from either EAE mice or people with MOG antibody disease. Moreover, an 8-18C5 variant carrying the NNAS mutation, which inactivates its effector functions, can reduce EAE severity and promote functional recovery. In brief, this study provides not only a comprehensive characterization of the humoral response in EAE models but also a proof of concept for a therapy to antagonize pathogenic anti-MOG antibodies.

ABSTRACT Chimeric antigen receptor T-cell (CART) and T-cell engager (TCE) therapies targeting B-cell maturation antigen (BCMA) are transforming the treatment landscape for relapsed multiple myeloma (MM). However, despite impressive initial response rates, most patients eventually relapse. To investigate this unmet medical need, we applied whole-genome sequencing (WGS) to MM cells from cohorts of 102 relapsed patients treated with anti-BCMA CART and TCE therapies. Several genomic alterations were associated with clinical outcomes, particularly primary refractoriness, including high genomic complexity and mutations in genes regulating plasma cell identity, which predicted resistance to therapy. Single-cell RNA sequencing further revealed that MM cells from refractory patients exhibited high proliferation signatures and reduced expression of TNFRSF17 (encoding BCMA), while were less enriched for plasma cell–associated transcriptional programs, a phenomenon we term “plasma cell identity escape.” This profile was strongly associated with immune dysregulation of CD8 T cells including increased activation and exhaustion. This evolution of MM toward a more proliferative and lineage-divergent state, refractory to the anti-BCMA T-cell redirecting therapies, was functionally validated in preclinical MM mouse models. Collectively, our results comprehensively define the cellular and molecular mechanisms underlying primary resistance to anti-BCMA therapies.

PURPOSE Venetoclax, an oral BCL-2 inhibitor, has efficacy in t(11;14)-positive relapsed/refractory multiple myeloma (RRMM), which is enhanced by dexamethasone, which promotes BCL-2 dependency. METHODS The randomized, open-label, phase III CANOVA study (ClinicalTrials.gov identifier: NCT03539744 ) enrolled adults with t(11;14)-positive RRMM who had received ≥2 previous lines of therapy. Patients were randomly assigned (1:1) to venetoclax-dexamethasone or pomalidomide-dexamethasone until progression or intolerable toxicity. The primary end point was independent review committee assessed–progression-free survival (PFS) in the intention-to-treat population analyzed by stratified log-rank test (two-sided type I error rate, α = .05), with hazard ratio (HR) and 95% CI estimated by stratified Cox proportional hazard model. Secondary end points included response rates, overall survival (OS), minimal residual disease (MRD) negativity rate (<10 –5 ), and safety. RESULTS Overall, 263 patients were randomly assigned (venetoclax-dexamethasone, n = 133; pomalidomide-dexamethasone, n = 130). Median PFS was 9.9 months (95% CI, 6.9 to 12.6) with venetoclax-dexamethasone versus 5.8 months (95% CI, 3.8 to 9.2) with pomalidomide-dexamethasone (HR, 0.823 [95% CI, 0.596 to 1.136]; P = .24). Overall response and very good partial response or better rates were 62% and 39%, respectively, with venetoclax-dexamethasone versus 35% and 14% with pomalidomide-dexamethasone. MRD negativity rate was 8% with venetoclax-dexamethasone and 0% with pomalidomide-dexamethasone. Median OS was 32.4 months (95% CI, 26.4 to 40.7) with venetoclax-dexamethasone and 26.9 months (95% CI, 20.4 to 38.9) with pomalidomide-dexamethasone (HR, 0.856 [95% CI, 0.612 to 1.197]). Grade ≥3 treatment-emergent adverse event rates were 67% with venetoclax-dexamethasone versus 83% with pomalidomide-dexamethasone. There were 16 (12%) treatment-emergent deaths with venetoclax-dexamethasone versus 8 (6%) with pomalidomide-dexamethasone. CONCLUSION The primary end point of PFS was not met. PFS and OS were numerically longer with venetoclax-dexamethasone versus pomalidomide-dexamethasone in t(11;14)-positive RRMM. Consistent with previous studies, infections were associated with venetoclax-dexamethasone; no new safety signals were observed.

Abstract Two recent studies suggested that the APOE ε4 haplotype was associated with increased α-synuclein pathology in cell and mouse models. Genetic variants in the SNCA region have strong association with Parkinson’s disease (PD), dementia with Lewy bodies (DLB) and idiopathic REM sleep behaviour disorder (iRBD), while APOE is a genetic risk determinant for only DLB. To determine if genetic-level interactions between SNCA and APOE exists that can explain the protein-level association, we investigated the genotypic interaction of APOE and SNCA in cohorts of PD, DLB and iRBD. We analysed genome-wide association study (GWAS) data from 5229 PD patients and 5480 controls, 2610 DLB patients and 1920 controls, and 1055 iRBD patients and 3667 controls. We used logistic regression interaction models across all three cohorts independently between the (i) top GWAS signals of SNCA single nucleotide polymorphisms (SNPs) and APOE haplotypes and (ii) SNP×SNP and three-way SNP interaction across the entire coding region plus 200 kb flanking each gene. No significant interactions were found to be associated with any of the synucleinopathies after correction for multiple testing. Our results do not support a role for genetic interactions between APOE and SNCA across PD, DLB and iRBD. Since the tested genetic variants affect the expression and function of these proteins, it is likely that any interactions between them do not affect the risk of PD, DLB and iRBD.

Background: Age is the strongest factor determining disease expression in multiple sclerosis (MS). We previously demonstrated biological age acceleration in pediatric-onset MS (POMS) compared to controls with both epigenetic clocks (DNAm) and telomere length (TL). It is unknown whether these markers report overlapping or distinct aging-related processes. Objectives: To determine the correlation between DNAm and TL aging markers. Methods: We conducted a cross-sectional case–control study within the US Network of Pediatric MS Centers. We calculated age acceleration residuals for the Horvath, Hannum, PhenoAge, and GrimAge epigenetic clocks and measured TL from whole blood samples to estimate telomere to somatic DNA ratios (T/S ratio). We employed multivariable analysis of covariance to assess the correlation between DNAm estimates and TL. Results: We analyzed biological ages in 270 participants (125 POMS, mean 15.7 years; 145 controls, mean 15.3 years). There were moderate correlations among the different DNAm clocks, but no correlations between DNAm clocks and TL in pooled analyses. In a stratified analysis, only the control group showed a modest correlation between TL and PhenoAge clock ( r = 0.2, p = 0.06). Conclusions: DNAm did not correlate with TL in this sample of POMS and controls, suggesting that these biomarkers may capture complementary and non-overlapping elements of aging-related biology.