Asmann, Yan W.

Glioblastoma (GBM) is the most prevalent and aggressive malignant primary brain tumor. GBM proximal to the lateral ventricles (LVs) is more aggressive, potentially because of subventricular zone contact. Despite this, cross-talk between GBM and neural stem/progenitor cells (NSC/NPCs) is not well understood. Using cell-specific proteomics, we show that LV-proximal GBM prevents neuronal maturation of NSCs through induction of senescence. In addition, GBM brain tumor–initiating cells (BTICs) increase expression of cathepsin B (CTSB) upon interaction with NPCs. Lentiviral knockdown and recombinant protein experiments reveal that both cell-intrinsic and soluble CTSB promote malignancy-associated phenotypes in BTICs. Soluble CTSB stalls neuronal maturation in NPCs while promoting senescence, providing a link between LV-tumor proximity and neurogenesis disruption. Last, we show LV-proximal CTSB up-regulation in patients, showing the relevance of this cross-talk in human GBM biology. These results demonstrate the value of proteomic analysis in tumor microenvironment research and provide direction for new therapeutic strategies in GBM.

TPS2700 Background: Though immunotherapy with anti-PD-1 immune checkpoint inhibitors (ICIs) has led to improvements in clinical outcomes in patients with cancer, when used as monotherapy in the advanced setting, only 18-25% of patients respond to ICI. Notably, ICI frequently lacks anti-tumor activity in immune-cold cancers where T cell priming is missing. Recent breakthroughs in identifying personal neoantigens via a comprehensive analysis of cancer sequencing data have brought increased attention to neoantigen cancer vaccines. Personalized cancer vaccines targeting neoantigens have shown early promise. While neoantigens have recently been investigated in some cancer types, the current neoantigen prediction algorithms have often focused on the MHC class-I subtype, single nucleotide mutations (SNM), small insertions and deletions (INDEL). We recently developed an informatics workflow, REAL-neo, for the identification, quality control (QC), and prioritization of both class-I and class-II human leukocyte antigen (HLA) bound neoantigens that arise from somatic SNM, INDEL, aberrant RNA splicing, and gene fusions, generating much more potent neoantigen candidates. Furthermore, we demonstrated robust T-cell response and prolonged survival by combining ICI and cancer vaccines in preclinical models. This single-arm phase I clinical trial is in progress to assess the safety, feasibility, and immunogenicity of personalized neoantigen vaccines in combination with pembrolizumab in patients with advanced solid cancers. Methods: The vaccine consists of up to 20 peptides (15-30 mer) comprising patient-specific neoantigens identified from tumor DNA and mRNA sequencing data using REAL-neo and delivered with GM-CSF as an adjuvant. The first cohort of three patients will be treated at dose level 1 consisting of 4 or 5 peptides at 300 mcg/peptide and GM-CSF 125 mcg per injection site in each of four limbs. After Cohort 1 is deemed safe, the study will expand to cohort 2, when patients will be enrolled at the same dose level for vaccine plus Pembrolizumab 200 mg i.v. Neoantigen vaccine will be given via subcutaneous injection on days 1, 4, 8, 15, and 21 (cohorts 1 and 2) and weeks 5 and 8 (booster dose for cohort 2 only). Cohort 1 has been completed without dose-limiting toxicity (DLT). Enrollment in Cohort 2 began in January 2024. AEs are assessed according to CTCAE v5. and safety findings are reviewed by data safety medical board (DSMB). Key eligibility criteria include 1) histologically confirmed locally advanced or metastatic solid malignancies and 2) cancer progression after at least one line of the standard-of-care (SOC) systemic treatment. For cohort 2, patients must be eligible to receive pembrolizumab per SOC or the treating physician’s judgment. Clinical trial information: NCT05269381 .

Background Cancer neoantigens arise from protein-altering somatic mutations in tumor and rank among the most promising next-generation immuno-oncology agents when used in combination with immune checkpoint inhibitors. We previously developed a computational framework, REAL-neo, for identification, quality control, and prioritization of both class-I and class-II human leucocyte antigen (HLA)-presented neoantigens resulting from somatic single-nucleotide mutations, small insertions and deletions, and gene fusions. In this study, we developed a new module, SPLICE-neo, to identify neoantigens from aberrant RNA transcripts from two distinct sources: (1) DNA mutations within splice sites and (2) de novo RNA aberrant splicings. Methods First, SPLICE-neo was used to profile all DNA splice-site mutations in 11,892 tumors from The Cancer Genome Atlas (TCGA) and identified 11 profiles of splicing donor or acceptor site gains or losses. Transcript isoforms resulting from the top seven most frequent profiles were computed using novel logic models. Second, SPLICE-neo identified de novo RNA splicing events using RNA sequencing reads mapped to novel exon junctions from either single, double, or multiple exon-skipping events. The aberrant transcripts from both sources were then ranked based on isoform expression levels and z-scores assuming that individual aberrant splicing events are rare. Finally, top-ranked novel isoforms were translated into protein, and the resulting neoepitopes were evaluated for neoantigen potential using REAL-neo. The top splicing neoantigen candidates binding to HLA-A*02:01 were validated using in vitro T2 binding assays. Results We identified abundant splicing neoantigens in four representative TCGA cancers: BRCA, LUAD, LUSC, and LIHC. In addition to their substantial contribution to neoantigen load, several splicing neoantigens were potent tumor antigens with stronger bindings to HLA compared with the positive control of antigens from influenza virus. Conclusions SPLICE-neo is the first tool to comprehensively identify and prioritize splicing neoantigens from both DNA splice-site mutations and de novo RNA aberrant splicings. There are two major advances of SPLICE-neo. First, we developed novel logic models that assemble and prioritize full-length aberrant transcripts from DNA splice-site mutations. Second, SPLICE-neo can identify exon-skipping events involving more than two exons, which account for a quarter to one-third of all skipping events.

The immune system substantially influences age-related cognitive decline and Alzheimer’s disease (AD) progression, affected by genetic and environmental factors. In a Mayo Clinic Study of Aging cohort, we examined how risk factors like APOE genotype, age, and sex affect inflammatory molecules and AD biomarkers in cerebrospinal fluid (CSF). Among cognitively unimpaired individuals over 65 ( N = 298), we measured 365 CSF inflammatory molecules, finding age, sex, and diabetes status predominantly influencing their levels. We observed age-related correlations with AD biomarkers such as total tau, phosphorylated tau-181, neurofilament light chain (NfL), and YKL40. APOE4 was associated with lower Aβ42 and higher SNAP25 in CSF. We explored baseline variables predicting cognitive decline risk, finding age, CSF Aβ42, NfL, and REG4 to be independently correlated. Subjects with older age, lower Aβ42, higher NfL, and higher REG4 at baseline had increased cognitive impairment risk during follow-up. This suggests that assessing CSF inflammatory molecules and AD biomarkers could predict cognitive impairment risk in the elderly.