Wickland, Daniel P.

Antisense oligonucleotides (ASOs) represent a promising therapeutic modality for RNA-based disease mechanisms, but identifying high-efficacy candidates from large sequence spaces remains a major bottleneck in drug development. Here, we present ASOFormer, a novel Transformer-based neural network that predicts the inhibition efficiency of RNase H-mediated ASOs from sequence, predicted secondary structure, and chemical modification features. ASOFormer was trained on a knockdown efficacy dataset spanning over 170,000 ASO-target pairs compiled largely from published patents. Ablation analysis confirmed that the addition of chemical modification features to the primary sequence drove the largest performance gains, with predicted secondary structure providing complementary benefit when combined with modification information. Further analysis highlighted the importance of the wings of gapmer ASOs and other features. As independent validation, ASOFormer was applied to ASOs targeting seven genes that were not in the training dataset gene list. For four out of the seven genes, the ground truth ASO inhibition efficiency was obtained from a public dataset, whereas the others were measured in-house via qPCR. Compared to two published state-of-the-art methods, ASOFormer achieved the best overall accuracy and prioritized the strongest inhibitors. Crucially, only ASOFormer consistently exceeded random expectation for top-candidate recovery across all seven test genes.

Abstract Background Glioblastoma (GBM) remains a devastating cancer with limited treatment options, largely due to its heterogeneity. While supramaximal resection has recently provided survival benefits, therapeutic profiling of different tumor compartments, particularly its infiltrative edge remains largely unexplored. Methods Here, we leveraged magnetic resonance imaging (MRI)-guided multi-sampling, collecting 2 cores and 2 margins per case, to query GBM heterogeneity. Whole-exome and RNA-seq with drug testing in two patient-derived 3D models were used to reveal similarities and differences in genomic and transcriptomic makeups, cellular compositions, and drug responses across cores and margins. Bioinformatics interrogations further identified response biomarkers. Results Mutation analysis showed that oncogenes exhibited a higher degree of spatial heterogeneity than tumor suppressor genes, regardless of MRI status. While the mesenchymal transcriptional subtype with extracellular matrix remodeling, stress response, and immune programs were preferentially enriched in enhancing cores, proneural tumors with neurological processes favored non-enhancing margins. Using a 15-drug GBM-targeted panel, ERK (ulixertinib) and PI3K pathway (paxalisib, CC-115) inhibitors showed preferential efficacy in enhancing cores and non-enhancing margins, respectively. The anti-apoptosis, pan-Bcl2 agent navitoclax and the epigenetic drug trotabresib represented the most effective, tumor-wide monotherapies. Importantly, drug combinations generally outperformed single agents across all regions. Conclusions This work demonstrates the regional heterogeneity of therapeutic vulnerabilities in GBM ex vivo, showing various drugs with tumor-wide or MRI-enhancement informed activity. These findings offer preclinical bases of numerous monotherapies and drug combinations for future clinical trial design.

Tumor-associated antigens (TAAs) are non-mutated antigenic peptides expressed in cancer tissue at abnormally high levels but in normal tissue either at negligible levels, during only particular developmental stages, or in a tissue-restricted manner. The shared nature of TAAs across patients makes them attractive targets for off-the-shelf immunotherapies. However, no studies have comprehensively surveyed the TAA potential of all possible wild-type peptides originating from cancer-associated genes. In this study of 16 cancer tissue types and 39 normal tissue types, we analyzed the expression profiles of protein-coding genes to identify those with aberrantly high RNA levels across multiple solid tumor types and low RNA levels across all normal tissue types examined. We then developed a score to quantify tumor specificity of gene expression. Compared to previously reported TAA genes, those we identified exhibited substantially greater tumor specificity. Seven of these genes demonstrated consistently elevated expression in at least five tumor types and minimal expression across all non-immune-privileged normal tissues. To assess Human Leukocyte Antigen (HLA) class I presentation potential of the multi-cancer-associated genes, we computationally predicted the binding affinities between the most common class I HLA alleles and all possible wild-type TAA epitopes of 8–11 amino acids arising from those genes. We then applied rigorous filtering criteria to prioritize the most promising multi-cancer TAA peptide candidates and evaluated their HLA binding and cell-surface presentation using T2 and immunopeptidome analysis. Our results highlight new potential targets for multi-cancer immunotherapies.

Abstract The purpose of this study was to identify glioblastoma (GBM) proteins that contribute to the hijacking of the tumor microenvironment through extracellular vesicles (EVs). GBM is the most aggressive primary brain tumor in adults. It presents significant challenges due to its universal recurrence and limited survival rates, exacerbated when its located proximal to the lateral ventricles (LV). The cellular subpopulation of brain tumor-initiating cells (BTICs) plays a pivotal role in tumor initiation and invasiveness, interacting with the microenvironment, particularly the cellular components in the subventricular zone (SVZ) in the LV. We employed an integrated multi-omic strategy combining cell-specific proteomics of EV cargo and whole-cell transcriptomics of EV-treated neural progenitor cells (NPCs) to define mechanisms by which BTICs remodel the tumor microenvironment. Using the TurboID cell-specific protein labeling system, we identified a previously unrecognized repertoire of BTIC-derived proteins selectively packaged into EVs. Among these, DPYSL2 (CRMP2) emerged as a prominent EV cargo as it is implicated in cancer cell migration and invasion. Functionally, exposure of human NPCs to BTIC-derived EVs significantly increased NPC proliferation and migratory capacity in vitro, findings that were recapitulated in vivo following intracranial and intranasal delivery of GBM-derived EVs. To define the molecular basis of these phenotypic changes, we performed RNA sequencing of NPCs following EV treatment. Bioinformatic integration, including ontogenic and pathway enrichment analyses, revealed robust activation of oncogenic signaling pathways, notably JAK/STAT, mTOR, and WNT, accompanied by upregulation of downstream effector genes. Importantly, integrative proteomic-transcriptomic analyses identified DPYSL2 as a mechanistic link between EV cargo and NPC transcriptional reprogramming. Prior studies demonstrate that DPYSL2 can interact with JAK kinases, promoting STAT3 activation and transcription of genes such as Vimentin (VIM) and CALCA, consistent with the transcriptomic changes observed in EV-treated NPCs. Overall, we have identified DPYSL2 as a novel regulator of tumor microenvironment hijacking mediated by extracellular vesicles. This multi-omic approach is the first use of cell-specific proteomics to study extracellular vesicles and the first time pairing this method to identify upstream regulators of transcriptomic changes in neural progenitor cells. Collectively, these findings establish a direct molecular connection between BTIC-derived EV proteins and functional reprogramming of neural progenitor cells, providing mechanistic insight into how glioblastoma exploits developmental programs to promote tumor progression. Citation Format: Marissa Russo, Emily Norton, Weiwei Wang, Shreyartha Mukherjee, Daniel Wickland, TuKiet Lam, Hugo Guerrero-Cazares. DPYSL2 mediates extracellular vesicle-driven reprogramming of the glioblastoma tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(8_Suppl):Abstract nr LB228.

Abstract Background The incidence of early onset breast cancers (BCs) has increased, paralleling rising trends in delayed childbearing. We hypothesize that a distinct postpartum BC (PPBC) subtype, identifiable by time since last birth (TSLB) and biomarker expression, contributes to this trend. Methods We applied GeoMx Digital Spatial Profiling (DSP) to measure associations between TSLB and 71 proteins in 640 BCs from women aged ≤40 years included in the Young Women’s Breast Cancer Study. We analyzed data using univariable linear regression and multivariable sliced inverse regression to account for higher order interactions among biomarkers. Results In keratin-rich segments, progesterone receptor (PR) (P = 1.00 × 10−4) and PTEN (P = 1.00 × 10−3) were associated with longer TSLB; multivariable analyses revealed positive associations for GZMB (P = 4.00 × 10−4), SMA (P = 1.00 × 10−4), and NF-1 (P = 1.00 × 10−3). In keratin-poor segments, univariable significant positive associations were found for PR (P = 2.00 × 10−4) and PTEN (P = 1.00 × 10−3), whereas CD20 (P = 3.00 × 10−4) and CTLA4 (P = 4.00 × 10−5) were negatively associated; multivariable significant associations were found for fibronectin (P = 3.00 × 10−5) and pan-Akt (P = 1.00 × 10−3). Associations persisted after adjustment for multiple comparisons and BC molecular subtypes. Associations including for PR, PTEN, and CD20 were strongest among women with the shortest TSLB. OPAL multiplex immunofluorescence assays for PR, PTEN, CD20, SMA, and CTLA4 replicated several DSP findings, particularly when stratified by subtype and with compartment matching. In TCGA, RNA species linked to proteins associated with TSLB correlated strongly with a T-cell exhaustion signature previously linked to poor prognosis among premenopausal women. Conclusion These data support PPBC as a biologically coherent phenotype defined by TSLB and biomarker profile, with potential implications for prevention and therapy.

Abstract Glioblastoma (GBM), the most aggressive primary brain tumor in adults, presents significant challenges due to its universal recurrence and limited survival rates, exacerbated when proximal to the lateral ventricles (LV). The subpopulation of brain tumor-initiating cells (BTICs) plays a pivotal role in tumor initiation and invasiveness, interacting with the microenvironment, particularly the cellular components in the subventricular zone (SVZ), like Neural Progenitor Cells (NPCs). Mechanisms of intercellular communication present in the SVZ include paracrine, autocrine, direct cell contact, and more recently extracellular vesicles (EVs). EVs are membrane-bound particles released by cells that are central to intercellular communication. They carry bioactive proteins, RNA, and other molecules that influence recipient cell behavior. This study investigates the role of EVs in GBM’s communication with non-cancer cells. Our findings indicate that BTIC-derived EVs promote migration and proliferation (*p < 0.02, ****p <0.001) in NPCs in vitro, highlighting the EVs’ role in altering the microenvironment. Additionally, we leverage a multi-omic approach to profile the small RNA and protein cargo of BTIC-EVs while also evaluating changes in the transcriptome of NPCs after BTIC-EV treatment. To identify the protein cargo contained in GBM-derived EVs, we utilized the innovative proximity-labeling system TurboID. We successfully induced TurboID expression in primary-cultured human BTICs from GBM patients, enabling the unbiased biotinylation of proteins in EVs. This method marks the first implementation of TurboID for unbiased global labeling of EV protein cargo in primary GBM cells. We identified unique miRNAs to be regulators of NPC’s transcriptome, and ontogenic analysis revealed upregulation of pathways involved in maintaining stem-like state, and upregulating PI3k-AKT, mTOR, and WNT signaling. This approach facilitates the investigation of EV-mediated communication and potential therapeutic targets, contributing to the understanding of GBM’s complex interactions with the brain’s microenvironment and the identification of biomarkers for improved diagnosis and treatment response.

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.

Importance Factors associated with clinical heterogeneity in Alzheimer disease (AD) lay along a continuum hypothesized to associate with tangle distribution and are relevant for understanding glial activation considerations in therapeutic advancement. Objectives To examine clinicopathologic and neuroimaging characteristics of disease heterogeneity in AD along a quantitative continuum using the corticolimbic index (CLix) to account for individuality of spatially distributed tangles found at autopsy. Design, Setting, and Participants This cross-sectional study was a retrospective medical record review performed on the Florida Autopsied Multiethnic (FLAME) cohort accessioned from 1991 to 2020. Data were analyzed from December 2022 to December 2023. Structural magnetic resonance imaging (MRI) and tau positron emission tomography (PET) were evaluated in an independent neuroimaging group. The FLAME cohort includes 2809 autopsied individuals; included in this study were neuropathologically diagnosed AD cases (FLAME-AD). A digital pathology subgroup of FLAME-AD cases was derived for glial activation analyses. Main Outcomes and Measures Clinicopathologic factors of heterogeneity that inform patient history and neuropathologic evaluation of AD; CLix score (lower, relative cortical predominance/hippocampal sparing vs higher, relative cortical sparing/limbic predominant cases); neuroimaging measures (ie, structural MRI and tau-PET). Results Of the 2809 autopsied individuals in the FLAME cohort, 1361 neuropathologically diagnosed AD cases were evaluated. A digital pathology subgroup included 60 FLAME-AD cases. The independent neuroimaging group included 93 cases. Among the 1361 FLAME-AD cases, 633 were male (47%; median [range] age at death, 81 [54-96] years) and 728 were female (53%; median [range] age at death, 81 [53-102] years). A younger symptomatic onset (Spearman ρ = 0.39, P < .001) and faster decline on the Mini-Mental State Examination (Spearman ρ = 0.27; P < .001) correlated with a lower CLix score in FLAME-AD series. Cases with a nonamnestic syndrome had lower CLix scores (median [IQR], 13 [9-18]) vs not (median [IQR], 21 [15-27]; P < .001). Hippocampal MRI volume (Spearman ρ = −0.45; P < .001) and flortaucipir tau-PET uptake in posterior cingulate and precuneus cortex (Spearman ρ = −0.74; P < .001) inversely correlated with CLix score. Although AD cases with a CLix score less than 10 had higher cortical tangle count, we found lower percentage of CD68-activated microglia/macrophage burden (median [IQR], 0.46% [0.32%-0.75%]) compared with cases with a CLix score of 10 to 30 (median [IQR], 0.75% [0.51%-0.98%]) and on par with a CLix score of 30 or greater (median [IQR], 0.40% [0.32%-0.57%]; P = .02). Conclusions and Relevance Findings show that AD heterogeneity exists along a continuum of corticolimbic tangle distribution. Reduced CD68 burden may signify an underappreciated association between tau accumulation and microglia/macrophages activation that should be considered in personalized therapy for immune dysregulation.

Abstract Metastatic castration-resistant prostate cancer (mCRPC) is an aggressive malignancy with poor outcomes. To investigate novel therapeutic strategies, we characterized three new metastatic prostate cancer patient derived-tumor xenograft (PDTX) models and developed 3D spheroids from each to investigate molecular targeted therapy combinations including CDK4/6 inhibitors (CDK4/6i) with AKT inhibitors (ATKi). Metastatic prostate cancer tissue was collected and three PDTX models were established and characterized using whole-exome sequencing. PDTX 3D spheroids were developed from these three PDTXs to show resistance patterns and test novel molecular-targeted therapies. CDK4/6i's were combined with AKTi's to assess synergistic antitumor response to prove our hypothesis that blockade of AKT overcomes drug resistance to CDK4/6i. This combination was evaluated in PDTX three-dimensional (3D) spheroids and in vivo experiments with responses measured by tumor volumes, PSA, and Ga-68 PSMA-11 PET-CT imaging. We demonstrated CDK4/6i's with AKTi's possess synergistic antitumor activity in three mCRPC PDTX models. These models have multiple unique pathogenic and deleterious genomic alterations with resistance to single-agent CDK4/6i's. Despite this, combination therapy with AKTi's was able to overcome resistance mechanisms. The IHC and Western blot analysis confirmed on target effects, whereas tumor volume, serum PSA ELISA, and radionuclide imaging demonstrated response to therapy with statistically significant SUV differences seen with Ga-68 PSMA-11 PET-CT. These preclinical data demonstrating antitumor synergy by overcoming single-agent CDK 4/6i as well as AKTi drug resistance provide the rational for a clinical trial combining a CDK4/6i with an AKTi in patients with mCRPC whose tumor expresses wild-type retinoblastoma 1.

AbstractBackgroundPSEN1 mutations are the most common genetic cause for autosomal dominant forms of Alzheimer’s disease patients with an age at onset below 65 years (ADAD). Even though all PSEN1 mutations lead to an increased Aβ processing and production, there is a large variability in phenotypic presentation even in individuals with the same mutation. Splicing isoforms in AD genes are reported to be associated with the disease, however little is known about correlation between splicing pattern and phenotypic presentation (e.g. variable age onset). We hypothesized that cellular and transcriptomic alterations differ amongst patients with different phenotypic presentation. In a group of 8 ADAD with the same PSEN1 p.G206A mutation, we investigate the association between brain cell type proportion, gene expression, and splicing isoforms with age at onset, Aβ plaque type and severity of AD neuropathologic change.MethodsEight Hispanic ADAD cases with PSEN1 p.G206A mutation were identified in the Mayo Clinic brain bank housed in Jacksonville, FL. Standard (immuno)histochemical stains, including H&E and thioflavin S, were performed to evaluate AD neuropathologic change. We focused on distinct Aβ plaque types in an association cortex (inferior parietal gyrus) and primary cortex (motor). We carried‐out single‐nuclei short and long read RNA sequencing on both brain regions. We will stratify our transcriptomic analyses based on neuropathology and phenotypic presentation.ResultsWe observed large variability in age at onset (median = 53 years; range: 42‐59 years). Furthermore, disease duration was reportedly variable (median = 10 years; range: 8‐17). All cases had a Braak tangle stage VI and Thal amyloid phase 5. Only 3 patients carried at least one APOE*ε4 risk allele, suggesting that its effect was minimal on ages at onset and death. Different plaque types were observed for short versus long survivors. In short survivors, plaques were predominantly fibrillar with an eosinophilic radial component, whereas in longer survivors predominantly cored plaques were observed.ConclusionLarge phenotypic variability within patients with the same mutation is observed suggesting the involvement of yet to be discovered genetic modifiers. Understanding cellular transcriptomic events in ADAD is essential to future development of therapeutic approaches and development of biomarkers.