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Ness, S.

Publications and source records attributed to Ness, S..

9 recordsLinked to original sources

Multi-Omic and Spatial Profiling Defines Outcome-Associated Tumor States in Head and Neck Adenoid Cystic Carcinoma

Abstract Head and neck adenoid cystic carcinoma (HNACC) shows highly variable clinical behavior that histopathological features only partly predict, and prognostic biomarkers for aggressive disease at diagnosis remain limited. Here, we show by integrating bulk, single-cell, and spatial transcriptomes from 25 HNACC tumors that poor survival is marked by profound loss of myoepithelial tumor cells and expansion of luminal tumor states. Both outcome groups share a myoepithelial-like origin, but aggressive tumors converge on an actively dividing, MYC/E2F-driven luminal state concentrated in discrete spatial niches. Aggressiveness therefore reflects where tumors end along a shared developmental path rather than a distinct lineage or altered immune infiltration. A four-gene classifier capturing this state predicted survival in an independent cohort, outperforming larger signatures and flagging aggressive subgroups in two others. These findings define a lineage proliferation axis linked to HNACC outcome, providing a basis for prospective risk stratification and proliferative-directed therapy.

cancer biology↗

Gene-Expression Programs in Salivary Gland Adenoid Cystic Carcinoma Analyzed Using Single-Cell and Spatial Transcriptomics

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 2{micro}m 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.

cancer biology↗

Identification of host lncRNAs that impact Venezuelan equine encephalitis virus replication

Venezuelan equine encephalitis virus (VEEV) causes encephalitis in humans and equids, and there are no vaccines or therapeutics available 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 during various viral infections; however, their role in regulating 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 about a 7-fold increase in VEEV TC-83 replication in primary mouse astrocytes. Knockdown of Snhg15 during VEEV TC-83 infection resulted in the suppression of ten genes including Irf1, Junb, Atf3, Relb, Pim1, Hbegf, Ccl5, Ankrd33b, and H2-K2, all of which were also increased during TC-83 infection when the expression of Snhg15 increased in primary mouse astrocytes. Most of these genes are involved in antiviral responses. KEGG pathway analysis confirmed the suppression of both pattern recognition receptor and inflammatory pathways after in Snhg15 knockdown. These data are the first to identify lncRNA responses in encephalitic alphavirus infection and demonstrate important roles for these overlooked RNAs on VEEV infection. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=186 SRC="FIGDIR/small/653438v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@15431eeorg.highwire.dtl.DTLVardef@9a22caorg.highwire.dtl.DTLVardef@1622310org.highwire.dtl.DTLVardef@1ebfd7b_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

The Association Between SLIT2 in Human Vitreous Humor and Plasma and Neurocognitive Test Scores

BackgroundSlit Guidance Ligand 2 (SLIT2) binds Roundabout (ROBO) guidance receptors to direct axon pathfinding and neuron migration during nervous system development. SLIT2 expression has previously been linked to dementia risk. ObjectiveTo study the association between SLIT2 expression in human vitreous humor and plasma samples and neurocognitive test scores in a cross-sectional cohort study utilizing a novel, highly-sensitive Meso Scale Discovery (MSD) assay for SLIT2 detection. MethodsSeventy-nine individuals with a mean age of 55.79 {+/-} 12.03 years underwent eye surgery with collection of vitreous humor, blood (plasma) collection, and neurocognitive assessment. Vitreous humor and plasma samples were analyzed by SLIT2 MSD electrochemiluminescence immunoassay. Associations between SLIT2 levels in vitreous humor and plasma were analyzed using GraphPad Prism. ResultsWe found up to a 7-fold higher level of SLIT2 in human vitreous humor compared to plasma. Lower vitreous SLIT2 levels were associated with a lower Montreal Cognitive Assessment (MoCA) score and Immediate Recall Verbatim (IRV) z-score, and higher plasma SLIT2 was associated with a lower MoCA score. In multivariate analysis using single and multiple predictor models, the same significant associations were found when adjusted for age, sex, race, diabetic status, diabetic retinopathy status, glaucoma status, and Apolipoprotein E (APOE) genotype. ConclusionsSLIT2 protein levels are significantly associated with MoCA score and IRV z-score in middle-aged individuals. The relationship remained significant when adjusted for demographics, co-morbidity, and APOE genotype, suggesting SLIT2 may be a sensitive biomarker for detection of mild cognitive impairment and early dementia, and warrants further studies.

neuroscience↗

The immune response to a fungus in pancreatic cancer samples

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 paired 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.

cancer biology↗

Comprehensive Analysis of Co-Mutations Identifies Cooperating Mechanisms of Tumorigenesis

Somatic mutations are one of the most important factors in tumorigenesis and are the focus of most cancer sequencing efforts. The co-occurrence of multiple mutations in one tumor has gained increasing attention as a means of identifying cooperating mutations or pathways that contribute to cancer.Using multi-omics, phenotypical, and clinical data from 29,559 cancer subjects and 1,747 cancer cell lines covering 78 distinct cancer types, we show that co-mutations are associated with prognosis, drug sensitivity, and disparities in sex, age, and race. Some co-mutation combinations displayed stronger effects than their corresponding single mutations. For example, co-mutation TP53:KRAS in pancreatic adenocarcinoma is significantly associated with disease specific survival (hazard ratio = 2.87, adjusted p-value = 0.0003) and its prognostic predictive power is greater than either TP53 or KRAS as individually mutated genes. Functional analyses revealed that co-mutations with higher prognostic values have higher potential impact and cause greater dysregulation of gene expression. Furthermore, many of the prognostically significant co-mutations caused gains or losses of binding sequences of RNA binding proteins or micro RNAs with known cancer associations. Thus, detailed analyses of co-mutations can identify mechanisms that cooperate in tumorigenesis.

cancer biology↗

Two-Step Mixed Model Approach to Analyzing Differential Alternative RNA Splicing

Changes in gene expression can correlate with poor disease outcomes in two ways: through changes in relative transcript levels or through alternative RNA splicing leading to changes in relative abundance of individual transcript isoforms. The objective of this research is to develop new statistical methods in detecting and analyzing both differentially expressed and spliced isoforms, which appropriately account for the dependence between isoforms and multiple testing corrections for the multi-dimensional structure of at both the gene- and isoform-level. We developed a linear mixed effects model-based approach for analyzing the complex alternative RNA splicing regulation patterns detected by whole-transcriptome RNA-sequencing technologies. This approach thoroughly characterizes and differentiates three types of genes related to alternative RNA splicing events with distinct differential expression/splicing patterns. We applied the concept of appropriately controlling for the gene-level overall false discovery rate (OFDR) in this multi-dimensional alternative RNA splicing analysis utilizing a two-step hierarchical hypothesis testing framework. In the initial screening test we identify genes that have differentially expressed or spliced isoforms; in the subsequent confirmatory testing stage we examine only the isoforms for genes that have passed the screening tests. Comparisons with other methods through application to a whole transcriptome RNA-Seq study of adenoid cystic carcinoma and extensive simulation studies have demonstrated the advantages and improved performances of our method. Our proposed method appropriately controls the gene-level OFDR, maintains statistical power, and is flexible to incorporate advanced experimental designs.

bioinformatics↗

Visible light optical coherence tomography angiography (vis-OCTA) and local microvascular retinal oximetry in human retina

We report herein the first visible light optical coherence tomography angiography (vis-OCTA) for human retinal imaging. Compared to the existing vis-OCT systems, we devised a spectrometer with a narrower bandwidth to increase the spectral power density for OCTA imaging, while retaining the major spectral contrast in the blood. We achieved a 100 kHz A-line rate, the fastest acquisition speed reported so far for human retinal vis-OCT. We rigorously optimized the imaging protocol such that a single acquisition takes <6 seconds with a field of view (FOV) of 3x7.8 mm2. The angiography enables accurate localization of microvasculature down to the capillary level and thus enables oximetry at vessels < 100 m in diameter. We demonstrated microvascular hemoglobin oxygen saturation (sO2) at the feeding and draining vessels at the perifoveal region. The longitudinal repeatability was assessed by <5% coefficient of variation (CV). The unique capabilities of our vis-OCTA system may allow studies on the role of microvascular oxygen in various retinal pathologies.

bioengineering↗

Early detection of retinal alteration by visible and near-infrared optical coherence tomography (vnOCT) in a dexamethasone-induced ocular hypertension mouse model

PurposeTo apply a novel visible and near-infrared optical coherence tomography (vnOCT) in the dexa-methasone-induced ocular hypertension mouse model, and test the capability of four optical markers, peri-papillary retinal nerve fiber layer (RNFL) thickness, total retinal blood flow, VN ratio and hemoglobin oxygen saturation (sO2), in detecting retinal ganglion cell (RGC) damage in association with ocular hyper-tension.\n\nMethodsTwelve mice (C57BL/6J) were separated into a control (n=6) and a dexamethasone group (n=6) receiving twice daily saline or dexamethasone eye drops, respectively, for 7 weeks. Intraocular pressure (IOP) measurements were taken at baseline and weekly. Optical measurements by vnOCT were longitudinally taken at baseline, 4 weeks and 7 weeks. Following week 7, ex vivo RGC counting was performed by immunostaining.\n\nResultsThe dexamethasone group showed a measurable rise in IOP by week 2. Despite the IOP differences between the dexamethasone and control groups, there was not a statistical difference in RNFL thickness or total blood flow over 7 weeks. The dexamethasone group did show an increase in retinal arteriovenous sO2 difference (A-V sO2) that was significant at week 4 and 7. The RNFL VN ratio showed a significant decrease at week 4 and 7 in dexamethasone group associated with a decreased RGC count.\n\nConclusionsRNFL VN ratio and A-V sO2 are capable of detecting early retinal alterations in the dexamethasone-induced ocular hypertension mouse model. Data analysis suggests VN ratio and A-V sO2 are corralated with RGC loss secondary to ocular hypertension, while being independent of IOP.

bioengineering↗