Abstract Adenoid Cystic Carcinoma (ACC) of the head and neck is a rare malignancy with a paradoxical clinical course, slow-growing yet highly invasive, with limited therapeutic options and no validated molecular prognostic biomarkers. To address this unmet need, we implemented a comprehensive multi-omics strategy integrating bulk RNA sequencing (n=20), single-cell RNA sequencing (n=24), and high-resolution spatial transcriptomics (4 Visium HD samples) from ACC tumors spanning eight distinct anatomical subsites. Clinical metadata enabled stratification into “poor” (<2-year survival) and “good” (>5-year survival) prognosis groups. In the absence of definitive cause-of-death data, we developed a machine learning-based classifier to define transcriptomic prognosis subgroups, revealing biologically coherent clusters aligned with clinical outcomes.Our biomarker discovery pipeline encompassed three key phases: 1. Cross-Modality Differential Expression and Pathway Profiling: We identified conserved gene expression signatures and dysregulated pathways distinguishing poor from good prognosis tumors across bulk, single-cell, and spatial modalities. High-risk tumors exhibited consistent enrichment of oncogenic signaling (e.g., MYC, NOTCH), immune suppression, and stromal activation programs across shared cell types and anatomical regions. 2. Spatially Resolved Cellular Ecosystem Mapping: Integration of single-cell and spatial transcriptomics enabled precise localization of malignant cell states and immune niches associated with poor prognosis. Spatial analyses revealed intratumoral “hotspots” characterized by elevated oncogenic activity, immune exclusion, and stromal remodeling. Ligand-receptor interaction networks, validated by spatial proximity, uncovered key signaling axes (e.g., CXCL12-CXCR4, TGFB1-TGFBR2) driving tumor progression. 3. Development of a Prognostic Biomarker Panel: We constructed a machine learning-derived multi-gene signature reproducible across all modalities. This panel demonstrated superior risk-stratification performance compared with existing ACC gene sets, with prognostic accuracy independent of clinical features. Importantly, the biomarker panel is amenable to clinical translation via bulk RNA profiling, offering immediate utility for patient stratification and therapeutic decision-making. In summary, our integrative multi-omics approach reveals robust molecular programs and spatially defined cellular ecosystems underlying poor prognosis in ACC. The resulting biomarker panel offers a powerful tool for precision prognostication and lays the foundation for targeted therapeutic development in this challenging malignancy. Citation Format: Gopikrishnan Bijukumar, Kathryn J. Brayer, David Lee, Scott A. Ness, Jeremy S. Edwards, Viswanathan Palanisamy. Multi-omics integration of bulk, single-cell, and spatial transcriptomics identifies robust prognostic biomarkers in head and neck salivary adenoid cystic carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1217.

Venezuelan equine encephalitis virus (VEEV) causes encephalitis in humans and equids, and there are no vaccines or therapeutics for humans. In recent years, non-coding RNAs have emerged as critical regulatory factors affecting different cellular pathways. Specifically, long non-coding RNAs (lncRNAs) have been identified as regulators of antiviral pathways; however, their role in VEEV infection has not been assessed. Here, we show differential expression of several lncRNAs in primary mouse target cells infected with a vaccine strain of VEEV (TC-83) but not a pathogenic strain (TrD). Among the differentially expressed genes (DEGs), suppressing lncRNA small nucleolar RNA host gene 15 (Snhg15) resulted in a 7-fold increase in TC-83 replication in primary mouse astrocytes. Knockdown of Snhg15 during TC-83 infection resulted in the suppression of ten genes, all of which were also increased during TC-83 infection along with Snhg15. Most of these genes are involved in antiviral responses. KEGG pathway analysis confirmed the suppression of both pattern recognition receptor and inflammatory pathways after Snhg15 knockdown. However, Snhg15 suppression did not significantly alter NF-kB signaling in TC-83-infected cells. These data are the first to identify lncRNA responses in encephalitic alphavirus infection and demonstrate important roles for these overlooked RNAs in VEEV infection.IMPORTANCEAlthough many studies have reported differential expression of lncRNAs during viral infections, the lncRNA response to VEEV infection and its functional roles have not been previously characterized. In this study, we provide the first comprehensive analysis of host lncRNA expression in primary cells that are targeted during VEEV infection. We demonstrate that the expression of specific host lncRNAs is altered during VEEV infection and that modulation of these lncRNAs changes the expression of host antiviral and inflammatory pathways and impacts viral replication. These findings advance our understanding of VEEV-host interaction and shed light on previously unappreciated regulatory layers of infection. Given the absence of approved vaccines or antiviral therapies for VEEV, our work identifies novel host factors that may serve as potential targets for the development of anti-VEEV therapeutics upon further investigation.

Adenoid cystic carcinoma of the salivary gland (SGACC) is a highly aggressive malignancy characterized by poor patient survival outcomes. While several studies have analyzed the transcriptome of the salivary gland at the bulk and single-cell level, no spatial transcriptomic analyses of this tissue have been published. Most of the existing publications on SGACC have predominantly relied on bulk and single cell RNA sequencing approaches, which do not resolve the spatially localized transcriptional heterogeneity nor have the resolution for defining molecular markers within tumor subpopulations. SGACC is clinically notable for the presence of multiple tumor clones, distinct spatial phenotypes, and its indolent yet invasive nature coupled with a high propensity for distant metastasis. These features may reflect co-expression of tumor-associated markers across diverse cellular niches, and a resultant biological complexity which causes standard treatment such as surgical resection, radiation therapy, and chemotherapy to be largely ineffective in significantly improving long-term survival, and highlights the need for more precise, targeted therapeutic strategies. Herein, we analyzed single cell (n = 4) and high-resolution spatial transcriptomics samples (n = 5) to characterize cancer cell populations in MYB- and non-MYB-expressing cell states, delineated gene expression signatures, and identified critical molecular interactions specific to SGACC. We used Visum HD to obtain spatial transcriptomics data at 2μm squared high resolution. This allowed a multi-omics approach comprising single cell and spatial transcriptomic methods to enable the discovery of novel transcriptional signatures and microenvironmental features not captured by conventional methods. Spatial mapping revealed marked cellular heterogeneity and demonstrated how tissue environments influence cellular transcriptomics. To tumor heterogeneity, we focused on tumorigenic cell populations, profiled plasma and T cell enrichment within the tumor microenvironment and identified key pathways and transcriptional drivers including the MYB-NFIB fusion underlying the tumor cluster formation. Our findings indicate an upregulation of genes involved in extracellular matrix remodeling, autophagy, and reactive stromal cell populations. We further found evidence of partial epithelial-mesenchymal transition (P-EMT) programming within MYB-expressing tumor clusters. Pathway analysis revealed that mutations in the spatial query sample prominently affect the PI3K-AKT and IL-17 signaling pathways, together with a downregulation of canonical Wnt signaling in some regions of the tissue architecture adjacent to immune cells. Collectively, these results underscore the complex regulatory landscape of SGACC and offer insights into its cellular dynamics and possible therapeutic vulnerabilities.

ABSTRACTGlioblastomas (GBMs) are highly aggressive, infiltrative, and heterogeneous brain tumors driven by complex driver mutations and glioma stem cells (GSCs). The neurodevelopmental transcription factors ASCL1 and OLIG2 are co-expressed in GBMs, but their role in regulating the heterogeneity and hierarchy of GBM tumor cells is unclear. Here, we show that oncogenic driver mutations lead to dysregulation of ASCL1 and OLIG2, which function redundantly to initiate brain tumor formation in a mouse model of GBM. Subsequently, the dynamic levels and reciprocal binding of ASCL1 and OLIG2 to each other and to downstream target genes then determine the cell types and degree of migration of tumor cells. Single-cell RNA sequencing (scRNA-seq) reveals that a high level of ASCL1 is key in defining GSCs by upregulating a collection of ribosomal protein, mitochondrial, neural stem cell (NSC), and cancer metastasis genes – all essential for sustaining the high proliferation, migration, and therapeutic resistance of GSCs.

Abstract Glioblastomas (GBMs) are highly aggressive, infiltrative, and heterogeneous brain tumors driven by complex genetic alterations. The neurodevelopmental transcription factors ASCL1 and OLIG2 are highly co-expressed in GBMs. However, their combinatorial roles in regulating the hierarchy and heterogeneity of GBM cells are unknown. Here, we show that induction of somatic mutations in neural progenitor cells lead to the dysregulation of ASCL1 and OLIG2, which then function redundantly and are required for brain tumor formation in a mouse model of GBM. Subsequently, the binding of ASCL1 and OLIG2 to each other’s loci and to downstream target genes then determine the cell types and degree of migration of tumor cells. Notably, single-cell RNA sequencing (scRNA-seq) reveals that a high level of ASCL1 is key in promoting neural stem cell (NSC)/astrocyte-like tumor cell types, which are highly proliferative, migratory, and are marked by upregulation of ribosomal protein, oxidative phosphorylation, cancer metastasis, and therapeutic resistance genes.

Glioblastomas (GBMs) are highly aggressive, infiltrative, and heterogeneous brain tumors driven by complex genetic alterations. The basic-helix-loop-helix (bHLH) transcription factors ASCL1 and OLIG2 are dynamically co-expressed in GBMs; however, their combinatorial roles in regulating the plasticity and heterogeneity of GBM cells are unclear. Here, we show that induction of somatic mutations in subventricular zone (SVZ) progenitor cells leads to the dysregulation of ASCL1 and OLIG2, which then function redundantly and are required for brain tumor formation in a mouse model of GBM. Subsequently, the binding of ASCL1 and OLIG2 to each other's loci and to downstream target genes then determines the cell types and degree of migration of tumor cells. Single-cell RNA sequencing (scRNA-seq) reveals that a high level of ASCL1 is key in specifying highly migratory neural stem cell (NSC)/astrocyte-like tumor cell types, which are marked by upregulation of ribosomal protein, oxidative phosphorylation, cancer metastasis, and therapeutic resistance genes. ASCL1 and OLIG2 are two basic-helix-loop-helix transcription factors that are highly co-expressed in glioblastoma (GBM). Here the authors find these two transcription factors function redundantly and are required for brain tumor initiation in a mouse model of GBM, while they possess inverse roles in determining tumor cell types and cell migration ability.

Abstract Glioblastomas (GBM) make up ~50% of primary brain tumors and prognosis has not improved over the last 30 years. Despite high inter- and intratumoral heterogeneity, basic-helix-loop-helix (bHLH) transcription factors, ASCL1 and OLIG2, are present in the majority of tumors. Previously, we showed in patient-derived GBM xenograft (PDX-GBM) that ASCL1 binds to promoter and enhancer regions of cell cycle genes, as well as neurodevelopmental transcription factors including OLIG2. Similarly, we showed that OLIG2 binding overlaps with the majority (~90%) of ASCL1 binding sites, including at promoter and/or enhancer regions of ASCL1 and OLIG1/2 loci, illustrating their potential redundant and/or feed-forward function in GBM. It has been proposed that ASCL1 and OLIG2 contribute to the neural stem cell-like properties of tumor cells, which may promote tumor growth and progression but also the treatment resistivity and high recurrence rate of GBMs in patients. Using an immune competent glioma mouse model, we are able to efficiently induce tumors from glial progenitors surrounding the lateral ventricle while altering the levels of ASCL1 and OLIG2 to assess their combinatory roles in GBM progression. Remarkably, we found that loss of both Ascl1 and Olig2 prevents tumor formation in 80% of mice, whereas the loss of only Ascl1 resulted in reduced cellular migration from the tumor bulk while the loss of Olig2 promotes a highly migratory phenotype. Conversely, elevating the levels of Ascl1increased both tumor cell proliferation and migration similar to the loss of OLIG2. Using single cell RNA-sequencing, we found that tumor cells which express high levels of Ascl1 exhibit neural stem cell/astrocytic gene signatures, which supports ASCL1’s role as a marker of glioma-stem-cells. Collectively, these findings illustrate the role of ASCL1 and OLIG2 in regulating GBM initiation, proliferation, and migration where ASCL1 may directly be responsible for the highly invasive and proliferative phenotype of GBMs.

all genes identified in smooth muscle between large and small mesenteric arteries of rat

Ozone (O3) is a criteria air pollutant with the most frequent incidence of exceeding air quality standards. Inhalation of O3 is known to cause lung inflammation and consequent systemic health effects, including endothelial dysfunction. Epidemiologic data have shown that gestational exposure to air pollutants correlates with complications of pregnancy, including low birth weight, intrauterine growth deficiency, preeclampsia, and premature birth. Mechanisms underlying how air pollution may facilitate or exacerbate gestational complications remain poorly defined. The current study sought to uncover how gestational O3 exposure impacted maternal cardiovascular function, as well as the development of the placenta. Pregnant mice were exposed to 1PPM O3 or a sham filtered air (FA) exposure for 4 h on gestational day (GD) 10.5, and evaluated for cardiac function via echocardiography on GD18.5. Echocardiography revealed a significant reduction in maternal stroke volume and ejection fraction in maternally exposed dams. To examine the impact of maternal O3 exposure on the maternal-fetal interface, placentae were analyzed by single-cell RNA sequencing analysis. Mid-gestational O3 exposure led to significant differential expression of 4021 transcripts compared with controls, and pericytes displayed the greatest transcriptional modulation. Pathway analysis identified extracellular matrix organization to be significantly altered after the exposure, with the greatest modifications in trophoblasts, pericytes, and endothelial cells. This study provides insights into potential molecular processes during pregnancy that may be altered due to the inhalation of environmental toxicants.

Pancreatic ductal adenocarcinoma (PDAC) is a poor prognosis cancer with an aggressive growth profile that is often diagnosed at late stage and that has few curative or therapeutic options. PDAC growth has been linked to alterations in the pancreas microbiome, which could include the presence of the fungus Malassezia. We used RNA-sequencing to compare 14 matched tumor and normal (tumor adjacent) pancreatic cancer samples and found Malassezia RNA in both the PDAC and normal tissues. Although the presence of Malassezia was not correlated with tumor growth, a set of immune- and inflammatory-related genes were up-regulated in the PDAC compared to the normal samples, suggesting that they are involved in tumor progression. Gene set enrichment analysis suggests that activation of the complement cascade pathway and inflammation could be involved in pro PDAC growth.

The endothelium contains morphologically similar cells throughout the vasculature, but individual cells along the length of a single vascular tree or in different regional circulations function dissimilarly. When observations made in large arteries are extrapolated to explain the function of endothelial cells (ECs) in the resistance vasculature, only a fraction of these observations are consistent between artery sizes. To what extent endothelial (EC) and vascular smooth muscle cells (VSMCs) from different arteriolar segments of the same tissue differ phenotypically at the single-cell level remains unknown. Therefore, single-cell RNA-seq (10x Genomics) was performed using a 10X Genomics Chromium system. Cells were enzymatically digested from large (>300 µm) and small (<150 µm) mesenteric arteries from nine adult male Sprague-Dawley rats, pooled to create six samples (3 rats/sample, 3 samples/group). After normalized integration, the dataset was scaled before unsupervised cell clustering and cluster visualization using UMAP plots. Differential gene expression analysis allowed us to infer the biological identity of different clusters. Our analysis revealed 630 and 641 differentially expressed genes (DEGs) between conduit and resistance arteries for ECs and VSMCs, respectively. Gene ontology analysis (GO-Biological Processes, GOBP) of scRNA-seq data discovered 562 and 270 pathways for ECs and VSMCs, respectively, that differed between large and small arteries. We identified eight and seven unique ECs and VSMCs subpopulations, respectively, with DEGs and pathways identified for each cluster. These results and this dataset allow the discovery and support of novel hypotheses needed to identify mechanisms that determine the phenotypic heterogeneity between conduit and resistance arteries.

The importance of the immune microenvironment in ovarian cancer progression, metastasis, and response to therapies has become increasingly clear, especially with the new emphasis on immunotherapies. To leverage the power of patient-derived xenograft (PDX) models within a humanized immune microenvironment, three ovarian cancer PDXs were grown in humanized NBSGW (huNBSGW) mice engrafted with human CD34+ cord blood–derived hematopoietic stem cells. Analysis of cytokine levels in the ascites fluid and identification of infiltrating immune cells in the tumors demonstrated that these humanized PDX (huPDX) established an immune tumor microenvironment similar to what has been reported for patients with ovarian cancer. The lack of human myeloid cell differentiation has been a major setback for humanized mouse models, but our analysis shows that PDX engraftment increases the human myeloid population in the peripheral blood. Analysis of cytokines within the ascites fluid of huPDX revealed high levels of human M-CSF, a key myeloid differentiation factor as well as other elevated cytokines that have previously been identified in ovarian cancer patient ascites fluid including those involved in immune cell differentiation and recruitment. Human tumor-associated macrophages and tumor-infiltrating lymphocytes were detected within the tumors of humanized mice, demonstrating immune cell recruitment to tumors. Comparison of the three huPDX revealed certain differences in cytokine signatures and in the extent of immune cell recruitment. Our studies show that huNBSGW PDX models reconstitute important aspects of the ovarian cancer immune tumor microenvironment, which may recommend these models for preclinical therapeutic trials. Significance: huPDX models are ideal preclinical models for testing novel therapies. They reflect the genetic heterogeneity of the patient population, enhance human myeloid differentiation, and recruit immune cells to the tumor microenvironment.

Supplementary Figure S1. Verification of MYBL1 Translocation in Genomic DNA. Supplementary Figure S2. Expression of Recombinant c-Myb and A-Myb Fusion Proteins. Supplementary Figure S3. Gene Expression Analysis. Supplementary Figure S4. Gene Set Enrichment Analysis. Supplementary Figure S5. Heatmap of Genes Correlated to Combined MYB and MYBL1 Levels. Supplementary Table S7. Gene Ontology Analysis. Supplementary Table S8. GO analysis of genes whose expression is either positively (Top) or negatively (Bottom) correlated with combined MYB and MYBL1 expression.

Differentially Expressed Genes, Group 1 vs Normal.

Adenoid cystic carcinoma (ACC) is an aggressive malignancy that most often arises in salivary or lacrimal glands but can also occur in other tissues. We used optimized RNA-sequencing to analyze the transcriptomes of 113 ACC tumor samples from salivary gland, lacrimal gland, breast or skin. ACC tumors from different organs displayed remarkedly similar transcription profiles, and most harbored translocations in the MYB or MYBL1 genes, which encode oncogenic transcription factors that may induce dramatic genetic and epigenetic changes leading to a dominant 'ACC phenotype'. Further analysis of the 56 salivary gland ACC tumors led to the identification of three distinct groups of patients, based on gene expression profiles, including one group with worse survival. We tested whether this new cohort could be used to validate a biomarker developed previously with a different set of 68 ACC tumor samples. Indeed, a 49-gene classifier developed with the earlier cohort correctly identified 98% of the poor survival patients from the new set, and a 14-gene classifier was almost as accurate. These validated biomarkers form a platform to identify and stratify high-risk ACC patients into clinical trials of targeted therapies for sustained clinical response.

Fatal metastasis occurs when circulating tumor cells (CTCs) disperse through the blood to initiate a new tumor at specific sites distant from the primary tumor. CTCs have been classically defined as nucleated cells positive for epithelial cell adhesion molecule and select cytokeratins (EpCAM/CK/DAPI), while negative for the common lymphocyte marker CD45. The enumeration of CTCs allows an estimation of the overall metastatic burden in breast cancer patients, but challenges regarding CTC heterogeneity and metastatic propensities persist, and their decryption could improve therapies. CTCs from metastatic breast cancer (mBC) patients were captured using the RareCyteTM Cytefinder II platform. The Lin- and Lin+ (CD45+) cell populations isolated from the blood of three of these mBC patients were analyzed by single-cell transcriptomic methods, which identified a variety of immune cell populations and a cluster of cells with a distinct gene expression signature, which includes both cells expressing EpCAM/CK ("classic" CTCs) and cells possessing an array of genes not previously associated with CTCs. This study put forward notions that the identification of these genes and their interactions will promote novel areas of analysis by dissecting properties underlying CTC survival, proliferation, and interaction with circulatory immune cells. It improves upon capabilities to measure and interfere with CTCs for impactful therapeutic interventions.

BackgroundRho-family GTPases, including Ras-related C3 botulinum toxin substrate 1 (Rac1) and cell division control protein 42 (Cdc42), are important modulators of cancer-relevant cell functions and are viewed as promising therapeutic targets. Based on high-throughput screening and cheminformatics we identified the R-enantiomer of an FDA-approved drug (ketorolac) as an inhibitor of Rac1 and Cdc42. The corresponding S-enantiomer is a non-steroidal anti-inflammatory drug (NSAID) with selective activity against cyclooxygenases. We reported previously that R-ketorolac, but not the S-enantiomer, inhibited Rac1 and Cdc42-dependent downstream signaling, growth factor stimulated actin cytoskeleton rearrangements, cell adhesion, migration and invasion in ovarian cancer cell lines and patient-derived tumor cells.MethodsIn this study we treated mice with R-ketorolac and measured engraftment of tumor cells to the omentum, tumor burden, and target GTPase activity. In order to gain insights into the actions of R-ketorolac, we also performed global RNA-sequencing (RNA-seq) analysis on tumor samples.ResultsTreatment of mice with R-ketorolac decreased omental engraftment of ovarian tumor cells at 18h post tumor cell injection and tumor burden after 2weeks of tumor growth. R-ketorolac treatment inhibited tumor Rac1 and Cdc42 activity with little impact on mRNA or protein expression of these GTPase targets. RNA-seq analysis revealed that R-ketorolac decreased expression of genes in the HIF-1 signaling pathway. R-ketorolac treatment also reduced expression of additional genes associated with poor prognosis in ovarian cancer.ConclusionThese findings suggest that R-ketorolac may represent a novel therapeutic approach for ovarian cancer based on its pharmacologic activity as a Rac1 and Cdc42 inhibitor. R-ketorolac modulates relevant pathways and genes associated with disease progression and worse outcome.

Abstract Rac1 is a high-value therapeutic target for cancer based on its tumor-promoting activities, yet clinical applications targeting Rac1 are in their infancy. High expression and hyperactivation of Rac1 in ovarian cancer, along with our identification of R-ketorolac as a novel Rac1 and Cdc42 selective inhibitor with translational potential, prompt us to test the hypothesis that targeting Rac1 has therapeutic utility for ovarian cancer. Ascites tumor cell samples from ovarian cancer patients in a prospective study receiving racemic ketorolac for clinically indicated use in pain relief were previously reported to show time-dependent reduction of Rac1 and Cdc42 activities post-treatment. New RNA seq data of these patient samples reveals significant downregulation of genes involved in endocytosis, regulation of actin cytoskeleton, ER protein processing, TNF and NOD signaling. Conversely, the identified downregulated genes were overexpressed and associated with worse survival in ovarian cancer patients analyzed through The Cancer Genome Atlas (TCGA). Among the downregulated genes in the NOD pathway are chemokines and proinflammatory cytokines. Follow-up cytokine panels from patients confirm that racemic ketorolac treatment reduces the levels of immunosuppressive cytokines IL-6, IL-10, and RANTES in ascites fluids. Together, these data indicate there may be a benefit to the anti-inflammatory activity of the S- enantiomer, as well as the GTPase inhibitory activity of the R-enantiomer of ketorolac for ovarian cancer treatment. Citation Format: Melanie Rivera, Martha M. Grimes, Dayna Dominguez, S. Ray Kenney, Yuna Guo, Elsa Romero, Kathryn J. Brayer, Yan Guo, Scott A. Ness, Sarah F. Adams, Carolyn Muller, Laurie G. Hudson, Angela Wandinger-Ness. Rac1 as a therapeutic target in ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr B70.