Analysis Of Sequence Data Research Articles

OSCC-derived EVs educate fibroblasts and remodel collagen landscape

Cancer-associated myofibroblasts (mCAFs) represent a significant component of the tumor microenvironment due to their contributions to extracellular matrix (ECM) remodeling. The pro-tumor mechanisms of extracellular vesicles (EVs) by regulating mCAFs and related collagens remain poorly understood in oral squamous cell carcinoma (OSCC). In this study, through analysis of single-cell sequencing data and immunofluorescence staining, we confirmed the increased presence of mCAFs and enrichment of specific collagen types in OSCC tissues. Furthermore, we demonstrated that OSCC-derived EVs promote the transformation of fibroblasts into mCAFs, leading to tumor invasion. Proteomic analysis identified the presence of TGF-β1 in EVs and revealed its role in inducing mCAFs via the TGF-β1/Smad3 signaling pathway. Experiments in vivo confirmed that EVs, particularly those carrying TGF-β1, trigger COL18high COL5high matrix deposition, thereby forming the pro-tumor ECM in OSCC. In summary, our investigation unveils the significant involvement of OSCC-derived EVs in orchestrating the differentiation of fibroblasts into mCAFs and modulating specific collagen types within the ECM. Therefore, this study provides a theoretical basis for targeting the EV-mediated TGF-β1 signaling pathway as a potential therapeutic strategy for OSCC.

Journey to the West: migration patterns of the riparian montane genus Myricaria

Myricaria Desv. (Tamaricaceae) is a genus of riparian plants found in montane regions throughout Eurasia. We present molecular phylogenies covering the entire Eurasian range of the genus using the chloroplast interspacer region psbA-trnH, the chloroplast region trnL-trnF, and the nuclear ribosomal Internal Transcribed Spacer (ITS). Biogeographical analyses of the DNA sequencing data based on Takhtajan's Floristic Provinces using a Bayesian Binary Markov Chain Monte Carlo reconstruction show that the origin of Myricaria is the Tibetan Floristic Province, specifically in the Qinghai-Tibetan Plateau. A molecular clock analysis was also performed. We estimate that the crown age of Myricaria is around 22.8 Ma and that the common ancestor of all European Myricaria occurred around 8.8 Ma ago. By covering the entire native range of the genus, our analyses confirm previous hypotheses on the origin and migration patterns of Myricaria, namely a central Asian centre of origin, followed by a westward migration to Europe via the central Asian mountain ranges, the Caucasus, and Eastern Europe. The divergence times and migration routes of Myricaria are remarkably similar to that of the genus Hippophae L.

Ubiquitin-Activating Enzyme E1 (UBA1) as a Prognostic Biomarker and Therapeutic Target in Breast Cancer: Insights into Immune Infiltration and Functional Implications

Ubiquitin-Activating Enzyme E1 (UBA1), an E1 enzyme involved in the activation of ubiquitin enzymes, has been involved in the onset and progression of different cancers in humans. Nevertheless, the precise contribution of UBA1 in breast cancer (BC) is still poorly characterized. In this study, a thorough investigation was carried out to elucidate the significance of UBA1 and validate its functionality in BC. Through the analysis of mRNA sequencing data of BC patients, the mRNA expression of UBA1 was observed to be notably enhanced in cancer tissues relative to controls, and high UBA1 expression was linked to worse overall survival (OS), disease-specific survival (DSS), and progress-free survival (PFS). Moreover, UBA1 exhibited potential as an independent prognostic and diagnostic biomarker for individuals with BC. Additionally, functional enrichment analysis revealed the involvement of UBA1 in inflammation-linked pathways, like the TNF-α signaling pathway, the IL-6 signaling pathway, and various immune-related biological processes. Notably, single-sample gene set enrichment analysis (ssGSEA) aided in the identification of a negative link between UBA1 expression and the levels of infiltrating mast cells, Th1 cells, iDC cells, B cells, DC cells, Tem cells, Cytotoxic cells, T cells, CD8T cells, and pDC cells. Finally, this study demonstrated that silencing UBA1 significantly impeded the growth and development of BC cell lines. These findings highlight UBA1 as a potential prognostic biomarker linked to immune infiltration in BC, thereby depicting its potential as a new therapeutic target for individuals with BC.

Molecular diagnoses and candidate gene identification in the congenital heart disease cohorts of the 100,000 genomes project.

Congenital heart disease (CHD) describes a structural cardiac defect present from birth. A cohort of participants recruited to the 100,000 Genomes Project (100 kGP) with syndromic CHD (286 probands) and familial CHD (262 probands) were identified. "Tiering" following genome sequencing data analysis prioritised variants in gene panels linked to participant phenotype. To improve diagnostic rates in the CHD cohorts, we implemented an agnostic de novo Gene Discovery Pipeline (GDP). We assessed de novo variants (DNV) for unsolved CHD participants following filtering to select variants of interest in OMIM-morbid genes, as well as novel candidate genes. The 100kGP CHD cohorts had low rates of pathogenic diagnoses reported (combined CHD "solved" 5.11% (n = 28/548)). Our GDP provided diagnostic uplift of nearly one third (1.28% uplift; 5.11% vs. 6.39%), with a new or potential diagnosis for 9 additional participants with CHD. When a filtered DNV occurred within a non-morbid gene, our GDP prioritised biologically-plausible candidate CHD genes (n = 79). Candidate variants occurred in both genes linked to cardiac development (e.g. AKAP13 and BCAR1) and those currently without a known role (e.g. TFAP2C and SETDB1). Sanger sequencing of a cohort of patients with CHD did not identify a second de novo variant in the candidate dataset. However, literature review identified rare variants in HMCN1, previously reported as causative for pulmonary atresia, confirming the approach utility. As well as diagnostic uplift for unsolved participants of the 100 kGP, our GDP created a dataset of candidate CHD genes, which forms an important resource for further evaluation.

Generation and characterization of two induced pluripotent stem cell lines (ICGi052-A and ICGi052-B) from a patient with frontotemporal dementia with parkinsonism-17 associated with the pathological variant c.2013T>G in the MAPT gene

Frontotemporal dementia with parkinsonism-17 is a neurodegenerative disease characterised by pathological aggregation of the tau protein with the formation of neurofibrillary tangles and subsequent neuronal death. The inherited form of frontotemporal dementia can be caused by mutations in several genes, including the MAPT gene on chromosome 17, which encodes the tau protein. As there are currently no medically approved treatments for frontotemporal dementia, there is an urgent need for research using in vitro cell models to understand the molecular genetic mechanisms that lead to the development of the disease, to identify targets for therapeutic intervention and to test potential drugs to prevent neuronal death. Analysis of exome sequencing data from a 46-year-old patient with a clinical diagnosis of Parkinson’s disease revealed the presence of the pathological variant c.2013T>G (rs63750756) in the MAPT gene, which is associated with frontotemporal dementia with parkinsonism-17. By reprogramming the patient’s peripheral blood mononuclear cells, we obtained induced pluripotent stem cells (iPSCs). Two iPSC lines were characterised in detail. Reprogramming was performed by transfection with non-integrating episomal vectors expressing the OCT4, SOX2, KLF4, LIN28, L-MYC and mp53DD proteins. The iPSC lines ICGi052-A and ICGi052-B proliferate stably, form colonies with a morphology characteristic of human pluripotent cells, have a normal diploid karyotype (46,XX), express endogenous alkaline phosphatase and pluripotency markers (OCT4, NANOG, SSEA-4 and TRA-1-60) and are able to differentiate into derivatives of three germ layers: ento-, ecto- and mesoderm. The iPSC lines obtained and characterised in detail in this work represent a unique tool for studying the molecular genetic mechanisms of the pathogenesis of frontotemporal dementia with parkinsonism-17, as well as for testing potential drugs in vitro.

Genomic profiling and expanded use of targeted anticancer drugs in solid cancers with exhausted evidence-based treatment options (PRECODE): study protocol of a prospective, non-randomized, cohort study

BackgroundGenomic profiling of advanced solid cancer in patients with no further evidence based standard treatment options is a novel approach to identify potential experimental treatment options based on specific genomic alterations. Due to the expected short survival of these patients timely assessment of potential druggable targets is critical to minimize the risk of deterioration during the analysis.The primary objective of this prospective study is to evaluate the turnaround time for genomic profiling and the clinical investigational procedures. The secondary objectives are to investigate how often genomic alterations in tumor tissue gives rise to a matched treatment offer and evaluate the clinical outcome.MethodsThe PRECODE study is a prospective, non-randomized, single-center cohort study conducted at Departments of Oncology and Pathology, Odense University Hospital, Denmark. Enrollment between March 1, 2019 and December 31, 2024. Eligibility criteria are age ≥ 18 years, written informed consent, advanced solid tumors, exhausted treatment options, ECOG performance status 0–2, adequate organ function and life expectancy ≥ 3 months. A core needle biopsy is analyzed by next generation sequencing using a pan-cancer comprehensive panel. Results are discussed weekly at institutional/local and national multidisciplinary tumor boards.DiscussionStrategies and methods for genomic profiling of advanced solid cancers differ. Rapid analysis and interpretation of sequencing data are key to avoiding delays in initiation potential experimental treatments, as these late-stage patients may quickly deteriorate.Although a highly optimized setup with fast-track clinical evaluation and genomic profiling has been established a subset will not be offered a targeted treatment due to deterioration. Local and national multidisciplinary teams have been established to optimize individualized treatment decisions. After genomic profiling a subset of patients will take part in clinical trials, which will constrain the reporting of overall survival or progression free survival.Trial registrationDanish Ethics Committee, Projekt-ID: S-2018014, date of approval: 27- FEB- 2019) Danish Data Protection Agency (Journal no: 18/58329, date of approval: 23-NOV-2018).ClinicalTrials.gov Identifier: NCT05385081 (retrospectively registered).

Genome-Wide Identification of AGO, DCL, and RDR Genes and Their Expression Analysis in Response to Drought Stress in Peach

Small RNAs (sRNAs) control a wide range of development and physiological pathways in plants. To address the response of sRNA biogenesis to drought stress, we identified sRNA biogenesis genes, including 11 encoding argonautes (AGO), 8 encoding Dicer-like proteins (DCL), and 9 encoding RNA-dependent RNA polymerases (RDR) in the peach genome. Notably, the largest numbers of sRNA biogenesis genes are located to chromosome 1. The PAZ, PIWI, and MID domains were identified in PpAGOs, while the ribonuclease IIIa and IIIb domains were characterized in PpDCLs. The RDRP domain was recognized in PpRDRs. Orthologous similarity and collinearity analyses between Arabidopsis and peach revealed 5, 1, and 2 collinear blocks in AGOs, DCLs, and RDRs, respectively. Moreover, 41, 40, and 42 cis-acting elements were located in the promoters of PpAGOs, PpDCLs, and PpRDRs, respectively, with the majority related to drought stress response. Analysis of RNA sequencing (RNA-seq) data revealed that sRNA biogenesis genes were involved in drought stress response in different tissues. Furthermore, the expression of candidate genes was verified in two peach cultivars, Beijing 2-7 (BJ2-7) and Sinai (SN), which are tested as drought-tolerant and sensitive cultivars, respectively, based on the physiological and biochemical analyses, which revealed that the Chinese peach cultivar ‘BJ2-7’ exhibits greater drought resistance compared to the Egyptian peach cultivar ‘SN’. Interestingly, the expression of PpAGO2b, PpDCL2b, PpDCL4, and PpRDR4 genes was induced in ‘BJ2-7’ but inhibited in ‘SN’ under drought stress. Overall, this study provides insight into the roles of sRNA biogenesis genes in response to drought stress in peach.

Identification of Spatial Specific Lipid Metabolic Signatures in Long-Standing Diabetic Kidney Disease.

Background: Diabetic kidney disease (DKD) is a major complication of diabetes leading to kidney failure. Methods: This study investigates lipid metabolism profiles of long-standing DKD (LDKD, diabetes duration > 10 years) by integrative analysis of available single-cell RNA sequencing and spatial multi-omics data (focusing on spatial continuity samples) from the Kidney Precision Medicine Project. Results: Two injured cell types, an injured thick ascending limb (iTAL) and an injured proximal tubule (iPT), were identified and significantly elevated in LDKD samples. Both iTAL and iPT exhibit increased lipid metabolic and biosynthetic activities and decreased lipid and fatty acid oxidative processes compared to TAL/PT cells. Notably, compared to PT, iPT shows significant upregulation of specific injury and fibrosis-related genes, including FSHR and BMP7. Meanwhile, comparing iTAL to TAL, inflammatory-related genes such as ANXA3 and IGFBP2 are significantly upregulated. Furthermore, spatial metabolomics analysis reveals regionally distributed clusters in the kidney and notably differentially expressed lipid metabolites, such as triglycerides, glycerophospholipids, and sphingolipids, particularly pronounced in the inner medullary regions. Conclusions: These findings provide an integrative description of the lipid metabolism landscape in LDKD, highlighting injury-associated cellular processes and potential molecular mechanisms.

Genetic Insights into Therapeutic Targets for Neuromyelitis Optica Spectrum Disorders: A Mendelian Randomization Study.

Neuromyelitis optica spectrum disorder (NMOSD) is a severe central nervous system disease primarily characterized by optic neuritis and myelitis, which can result in vision loss and limb paralysis. Current treatment options are limited in their ability to prevent relapses and mitigate disease progression, underscoring the urgent need for new drug targets to develop more effective therapies. The objective of this study is to identify potential drug targets associated with a reduced risk of NMOSD attacks or relapses through Mendelian randomization (MR) analysis, thereby addressing the limitations of existing treatment methods and providing better clinical options for patients. To identify therapeutic targets for NMOSD, a MR analysis was conducted. The cis-expression quantitative trait loci (cis-eQTL, exposure) data were sourced from the eQTLGen consortium, which included a sample size of 31,684. NMOSD (outcome) summary data were obtained from two of the largest independent cohorts: one cohort consisted of 86 NMOSD cases and 460 controls derived from whole-genome sequencing data, while the other cohort included 129 NMOSD patients and 784 controls. We performed a two-sample MR analysis to evaluate the association between single nucleotide polymorphisms (SNPs) and copy number variations with NMOSD. The MR analysis utilized the inverse variance weighted (IVW) method, supplemented by MR-Egger, weighted median, simple mode, and weighted mode methods. Sensitivity analyses were conducted to assess the presence of horizontal pleiotropy and heterogeneity. Colocalization analysis was employed to test whether NMOSD risk and gene expression are driven by common SNPs. Additionally, a phenome-wide association study (PheWAS) was performed to detect disease outcomes associated with NEU1. Supplementary analyses included single-nucleus RNA sequencing (snRNA-seq) data analysis, protein-protein interaction (PPI) networks, and drug feasibility assessments to prioritize potential therapeutic targets. Two drug targets, COL4A1 and NEU1, demonstrated significant MR results in two independent datasets. Notably, NEU1 showed substantial evidence of colocalization with NMOSD. Additionally, apart from the association between NEU1 and NMOSD, no other associations were observed between gene-proxied NEU1 inhibition and the increased risk of other NMOSD-related diseases. This study supports the potential of targeting NEU1 for drug inhibition to reduce the risk of NMOSD. Further preclinical research and drug development are warranted to validate the efficacy and safety of NEU1 as a therapeutic target and to explore its potential in NMOSD treatment.

MUC1-associated autosomal dominant tubulointerstitial kidney disease: prevalence in kidney failure of undetermined aetiology and clinical insights from Danish families

Abstract Background Frameshift variants in the variable number tandem repeat region of MUC1 cause autosomal dominant tubulointerstitial kidney disease (ADTKD-MUC1) but are challenging to detect. We investigated the prevalence in patients with kidney failure of undetermined aetiology and compared Danish families with ADTKD-MUC1. Methods We recruited patients with suspected kidney failure of undetermined aetiology at ≤ 50 years and excluded those with a clear-cut clinical or histopathological kidney diagnoses or established genetic kidney diseases identified thorough medical record review. MUC1 genotyping was performed by SNaPshot analysis, detecting the most common pathogenic cytosine duplication, followed by bioinformatics pipeline VNtyper analysis of short-read sequencing data.. Results Of 172 recruited patients, 123 underwent SNaPshot analyses, which were abnormal in 5/123 patients (4%). Next, VNtyper genotyping was performed in all patients, including the five with abnormal SNaPshot analysis. VNtyper re-identified the common cytosine duplication in all five patients and revealed novel frameshift variants in two additional patients, while the analyses were normal in the remaining 116 patients. All patients carrying frameshift variants in MUC1 full-filled ADTKD criteria and had a family history of kidney failure . A considerable inter- and intra-familial variability of chronic kidney disease stage relative to age was observed in families with ADTKD-MUC1. Conclusions ADTKD-MUC1 was identified in 7/123 patients (6%) in a selected cohort of kidney failure of undetermined aetiology ≤ 50 years, and VNtyper effectively identified all pathogenic MUC1 variants.

Integrated analysis of single-cell RNA sequencing and bulk transcriptome data identifies a pyroptosis-associated diagnostic model for Parkinson’s disease

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by an insidious onset. Despite the emphasis on motor symptom-based diagnosis, there remains an unmet clinical need for effective diagnostic approaches during the prodromal phase of PD. Recent advances in single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic analyses of PD patients open avenues for identifying potential diagnostic biomarkers. A comprehensive cell trajectory analysis was conducted using scRNA-seq datasets to identify gene expressions associated with the cellular transition from healthy to PD-associated states. Integration of scRNA-seq datasets with weighted gene co-expression network analysis (WGCNA) allowed extraction of pyroptosis-associated differentially expressed genes (PDEGs). Using LASSO logistic regression, support vector machine recursive feature elimination (SVM-RFE) and random forest methods, we developed a diagnostic model centred on PDEGs. In addition, immunoinfiltration, inflammatory signalling pathways and intercellular communication were detected by scRNA-seq analyses. In PD patients, the number of cells including metencephalic-like cells, excitatory neurons, inhibitory neurons and MHB-like cells was significantly reduced, whereas the proportion of astrocytes and microglia, immunoinfiltration and inflammatory signalling pathways were upregulated compared to healthy individuals. Using scRNA-seq and WGCNA analyses, two pyroptosis-related diagnostic genes, POLR2K and TIMM8B, were identified and a diagnostic model based on them was constructed, which showed promising performance upon validation. This study established a pyroptosis-related diagnostic model for PD through the analyses of scRNA-seq combined with bulk transcriptome data, which improved the understanding of the role of PDEGs in PD and provided new insights into the diagnostic strategies for this neurodegenerative disease.

Isolation and identification of patient-derived liver cancer stem cells and development of personalized treatment strategies

BackgroundLiver cancer stem cells (LCSCs) are thought to drive the metastasis and recurrence, however, the heterogeneity of molecular markers of LCSCs has hindered the development of effective methods to isolate them.MethodsThis study introduced an effective approach to isolate and culture LCSCs from human primary liver cancer (HPLC), leveraging mouse embryonic fibroblasts (MEFs) as feeder cells in conjunction with using defined medium. Isolated LCSCs were further characterized by multiple approaches. Transcriptome sequencing data analysis was conducted to identify highly expressed genes in LCSCs and classify different subtypes of liver cancers.ResultsTotal sixteen cell strains were directly isolated from 24 tissues of three types of HPLC without sorting, seven of which could be maintained long-term culture as colony growth on MEFs, which is unique characteristics of stem cells. Even 10 of cloned cells formed the tumors in immunodeficient mice, indicating that those cloned cells were tumorgenic. The histologies and gene expression pattern of human xenografts were very similar to those of HPLC where these cloned cells were isolated. Moreover, putative markers of LCSCs were further verified to all express in cloned cells, confirming that these cells were LCSCs. These cloned LCSCs could be cryopreserved, and still maintained the feature of colony growth on MEFs after the recovery. Compared to suspension culture as conventional approach to culture LCSCs, our approach much better maintained stemness of LCSCs for a long time. To date, these cloned cells could be cultured on MEFs over 12 passages. Moreover, bioinformatics analysis of sequencing data revealed the gene expression profiles in LCSCs, and liver cancers were classified into two subtypes C1 and C2 based on genes associated with the prognosis of LCSCs. Patients of the C2 subtype, which is closely related to the extracellular matrix, were found to be sensitive to treatments such as Cisplatin, Axitinib, JAK1 inhibitors, WNT-c59, Sorafenib, and RO-3306.ConclusionIn summary, this effective approach offers new insights into the molecular landscape of human liver cancers, and the identification of the C2 subtype and its unique response to the treatment pave the way for the creation of more effective, personalized therapeutic strategies.

Application and development of wastewater epidemiology in public health current status and future trends

Abstract. Wastewater epidemiology has emerged as a powerful tool for public health surveillance, enabling the monitoring of infectious diseases at the community level. This paper provides an overview of wastewater epidemiology, including its methodology, applications, current status, and future trends. The challenges and ethical considerations associated with its implementation are also discussed. The methodology section explores the various techniques used in wastewater epidemiology, such as analyzing viral RNA and biomarkers in wastewater samples. These methods offer valuable insights into disease prevalence, transmission patterns, and trends in a population. The applications section highlights the wide range of public health applications for wastewater epidemiology. It discusses how this approach can contribute to disease surveillance, early detection of outbreaks, and monitoring the effectiveness of interventions. The current status section examines the progress made in wastewater epidemiology. It discusses the standardization of methodologies and the need for research collaboration to ensure reliable and comparable results. The future trends and developments section explores potential advancements in wastewater epidemiology. It discusses emerging technologies, such as next-generation sequencing and advanced data analysis techniques, that could enhance the capabilities of this approach. The challenges and ethical considerations section addresses the hurdles in implementing wastewater epidemiology. It emphasizes the importance of standardization, logistical considerations, privacy protection, transparent reporting, and equitable distribution of benefits. In conclusion, wastewater epidemiology holds great promise for public health surveillance. However, addressing the challenges and ethical considerations is crucial for its responsible and effective implementation. By proactively overcoming these obstacles and upholding ethical principles, wastewater epidemiology can continue to evolve as a valuable tool for improving public health outcomes.

Abstract B017: Discovery of cancer-specific small RNAs using a new unbiased analysis of cohort sequence data

Abstract It is well-established that small RNAs such as microRNAs can have important roles as oncogenes or tumor suppressors. The majority of studies of small RNAs in cancer have focused on examining the often subtle deregulation of specific, well-characterized molecules, aiming to understand their role in tumorigenesis. However, these efforts have predominantly concentrated on known, well-annotated RNA sequences, potentially overlooking novel, cancer-specific molecules. In this study, we sought to apply a new computational approach to uncover small RNA molecules that are uniquely associated with cancer and are completely absent from all non- cancerous tissues. To achieve this, we developed an unbiased approach that can detect cancer- specific sequences even if they are lowly abundant, do not overlap with existing genome annotations and even if they do not map to the human reference genome. We applied our framework to hundreds of small RNA-seq samples across a diverse range of cancer types from two large-scale public resources: The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Through this comprehensive analysis, we identified a series of small RNA molecules that are exclusively present in tumor samples and completely absent in adjacent normal tissues across multiple cancer types. Furthermore, these molecules were not detected in a large cohort comprising over 2,500 non-cancerous public samples, underscoring their specificity to cancerous conditions. Some of these molecules are also associated with different patient metadata. For example, one of these candidates exhibited significant correlation with poor patient survival in both Lung Adenocarcinoma and Endometrial Carcinoma within both the TCGA and CPTAC datasets. The discovery of such cancer-specific small RNAs holds immense potential for clinical applications. These molecules could serve as highly specific diagnostic and prognostic biomarkers, aiding in the early detection and stratification of cancers. Moreover, their unique presence in cancer cells, positions them as promising targets for the development of novel therapeutic interventions. In summary, our findings highlight the importance of exploring the full spectrum of small RNAs in cancer research. By moving beyond the constraints of known annotations, we have uncovered previously unknown molecules that could improve cancer diagnostics, prognostics, and treatment. Citation Format: Panagiotis Kalogeropoulos, Maria Alejandra Ulloa, Marc Friedländer. Discovery of cancer-specific small RNAs using a new unbiased analysis of cohort sequence data [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: RNAs as Drivers, Targets, and Therapeutics in Cancer; 2024 Nov 14-17; Bellevue, Washington. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(11_Suppl):Abstract nr B017.

Visualization Methods for DNA Sequences: A Review and Prospects.

The efficient analysis and interpretation of biological sequence data remain major challenges in bioinformatics. Graphical representation, as an emerging and effective visualization technique, offers a more intuitive method for analyzing DNA sequences. However, many visualization approaches are dispersed across research databases, requiring urgent organization, integration, and analysis. Additionally, no single visualization method excels in all aspects. To advance these methods, knowledge graphs and advanced machine learning techniques have become key areas of exploration. This paper reviews the current 2D and 3D DNA sequence visualization methods and proposes a new research direction focused on constructing knowledge graphs for biological sequence visualization, explaining the relevant theories, techniques, and models involved. Additionally, we summarize machine learning techniques applicable to sequence visualization, such as graph embedding methods and the use of convolutional neural networks (CNNs) for processing graphical representations. These machine learning techniques and knowledge graphs aim to provide valuable insights into computational biology, bioinformatics, genomic computing, and evolutionary analysis. The study serves as an important reference for improving intelligent search systems, enriching knowledge bases, and enhancing query systems related to biological sequence visualization, offering a comprehensive framework for future research.

Abstract 4145829: Fatty Acid Binding Protein 4 as Potential Indicator for Gestational Diabetes Mellitus-Induced Fetal Endothelial Dysfunction

Introduction/Background: Gestational diabetes mellitus (GDM) is the most common complication during pregnancy. GDM is leading to an elevated risk for the development of cardiovascular diseases both in the mother and the child in later life. Previous studies have identified fatty acid-binding protein 4 (FABP4) as a prime candidate involved in the pathophysiology of GDM. Indeed, women with GDM exhibit elevated blood levels of FABP4, suggesting its potential role as a biomarker for endothelial dysfunction and cardiovascular risk assessment in GDM. Research Question/Hypothesis: Does FABP4 affect the function of human endothelial cells from patients with GDM? Goals/Aim: Our aim is a better understanding of the role of FABP4 in fetal endothelial dysfunction of patients with GDM and the development of potential therapeutic strategies. Methods/Approach: Primary human umbilical vein endothelial cells (HUVECs) were isolated from umbilical cords obtained from normoglycemic and GDM pregnancies. Total mRNA from HUVECs was used for bulk RNA sequencing to compare gene expression pattern. HUVECs were subjected to functional analyses assessing proliferation, migration, NO and insulin signaling. Finally, human endothelial cells were exposed to high laminar flow (30 dyn/cm 2 ) or simvastatin (10 nM) treatment to investigate their impact on FABP4 expression and endothelial function. Results/Data: Bulk RNA sequencing data analysis revealed FABP4 as a gene overexpressed in GDM HUVECs compared to normoglycemic controls. Gene set enrichment analysis showed in addition an enrichment of genes involved in angiogenesis and Notch signaling pathways in human endothelial cells from GDM patients. GDM HUVECs had a significantly higher wound healing capacity compared to normoglycemic controls. The PI3K/AKT/mTOR pathway was enriched in GDM HUVECs. GDM HUVECs displayed impaired activation of AKT and eNOS (expression and phosphorylation) after stimulation with insulin, suggesting a possible insulin resistance. Finally, subjecting HUVECs to high laminar shear stress or simvastatin treatment caused a reduction of FABP4 mRNA expression and an increase of eNOS expression, indicating potential therapeutic strategies to improve endothelial function. Conclusions: We provided evidence that FABP4 could be involved in fetal GDM-induced endothelial dysfunction. High laminar shear stress and medications activating eNOS signaling could protect the endothelium against the negative impact of FABP4 in GDM.

SURG-25. PREOPERATIVE EMBOLIZATION IMPROVES LOCAL CONTROL AND REPROGRAMS GENE EXPRESSION IN ATYPICAL WHO GRADE 2 MENINGIOMAS

Abstract Preoperative embolization is hypothesized to reduce blood loss and surgical time for meningioma resection, but the impact of embolization on long-term clinical outcomes and molecular profiling of meningiomas is incompletely understood. To address this, we evaluated the impact of embolization on outcomes and molecular features of WHO grade 2 meningiomas. A series of patients with grade 2 meningiomas who underwent resection at our institution from 1997 to 2021 were identified and reviewed. Available DNA methylation profiling and bulk RNA sequencing data were analyzed (n=200). Univariate and multivariate analyses, Cox proportional hazards modeling, and propensity matching (sex, age at surgery, previous surgery, extent of resection, postoperative radiation) were used. A total of 357 patients with WHO grade 2 meningiomas were included, 129 (36.1%) of which underwent preoperative embolization. Mean age at diagnosis was 53.5 years and 61.4% of patients were female. There was no significant difference in time to recurrence with or without embolization for cases with gross total resection (229/357), but embolization was independently associated with improved local control for cases with subtotal resection even after accounting for postoperative radiotherapy (HR 0.49, 95% CI 0.32-2.20 p=0.028). The average time to recurrence of atypical WHO grade 2 meningioma was 3.3 years after subtotal resection and 6.7 years after embolization and subtotal resection (p<0.001, propensity matched). The distribution of Merlin-intact vs Immune-enriched vs Hypermitotic meningioma DNA methylation groups was equivalent with versus without embolization, but differential gene expression analysis of RNA sequencing data revealed enrichment of hypoxia related pathways after embolization that were unique to each DNA methylation group. In summary, these data show that preoperative embolization improves local control and reprograms gene expression in atypical WHO grade 2 meningiomas. Additional investigation into the impact of embolization on clinical outcomes and gene expression for meningiomas, especially for higher-grade tumors, is warranted.

IMMU-07. THE IMMUNE LANDSCAPE OF PEDIATRIC BRAIN TUMORS: A TRANSCRIPTOMIC ANALYSIS

Abstract Despite standard-of-care therapy, pediatric brain tumors are now the leading cause of cancer-related death in children, highlighting an urgent need for the development of new treatments. Immunotherapy is actively being evaluated as a therapeutic approach to pediatric brain tumors, however, more research is needed to reveal additional antigenic targets that exist in these malignancies. In this study, our team performed a transcriptomic analysis of pediatric brain tumor RNA sequencing data within the Children’s Brain Tumor Network (CBTN) to identify intra and extracellular antigens that are highly expressed across major tumor types. Interestingly, our team observed that most tumors had high gene expression of a group of antigens that were unique to that specific tumor type. Specifically, our analysis revealed that diffuse midline gliomas (DMGs) highly expressed the extracellular antigens CA9, CTCFL, and ST8SIA1, whereas atypical rhabdoid tumors (ATRTs) highly expressed MUC1 and TEK. Other tumors that displayed high gene expression for a variety of antigenic targets included H3-wildtype high-grade gliomas (HGGs), and ependymomas (EPNs). Strikingly, we observed minimal difference in antigen expression in primary tumors when compared to patient-matched recurrences. Beyond antigen expression, we evaluated the expression of antigen processing machinery (APM) which includes major histocompatibility complexes (MHCs). Our findings revealed that DMGs had the lowest level of APM expression, however, these tumors uniquely expressed high levels of the immune checkpoints ADORA2A, CD276, and KLRC1. Contrarily, ATRTs showed a high expression of immune checkpoints CD274 (PD-L1), PVR, and CD80. Other tumors included in our analysis had unique expression patterns of antigen, as well as APM and immune checkpoints. Our findings illustrate that pediatric brain tumors have distinct expression patterns of antigens, APM, and immune checkpoints that are specific to tumor type, emphasizing diverse, rather than general, immunotherapeutic approaches must be considered for childhood brain tumors.

BIOM-30. NOVEL HISTOLOGIC AND MOLECULAR BIOMARKERS FOR OLIGODENDROGLIOMA

Abstract Oligodendrogliomas are progressive, infiltrative gliomas. While new molecular criteria were introduced in 2016 for diagnosing oligodendroglioma, the grading criteria remains largely unchanged. We evaluated histologic and molecular features for new biomarkers of aggressive behavior, using a cohort of 184 specimens diagnosed as low grade oligodendroglioma within the Duke Brain Tumor Center Biorepository. To identify tumors meeting current molecular criteria for oligodendroglioma, IDH1/2 status was confirmed by whole exome sequencing and 1p/19q codeletion confirmed using inferred copy number variation. First, we assessed for a histologic feature called hypercellular nodules (HCN), which are foci of increased cellularity in regions of otherwise lower cellularity tumor. In patients with newly diagnosed grade 2 oligodendroglioma, 16% (15/92) had HCN. While the median overall survival (OS) was 24.1 years without HCN, the median OS with HCN was only 13.6 years (p<0.02, Mantel-Cox test). We then assessed for homozygous deletion of CDKN2A. Cases with potential CDKN2A homozygous deletion by inferred copy number variation were validated by fluorescence in situ hybridization. In patients with newly diagnosed grade 2 oligodendroglioma, 2% had homozygous CDKN2A deletion (2/107). While the median OS with intact or hemizygous CDKN2A loss was 21 years, it decreased to 3.8 years with homozygous CDKN2A deletion (p<0.0001, Mantel-Cox test), although interpretation is limited given the rarity of homozygous CDKN2A loss at initial diagnosis. For recurrent grade 2 oligodendroglioma, 6% had homozygous deletion (5/77). While the median OS with intact or hemizygous CDKN2A loss in recurrent oligodendroglioma was 25.4 years, it decreased to 6.7 years with homozygous CDKN2A deletion (p< 0.04, Mantel-Cox test). These studies provide support for using HCN and CDKN2A homozygous deletion as grading criteria for oligodendroglioma. Further studies are ongoing, including covariate analysis, expanded cohorts, and ongoing analysis of whole exome sequencing data to identify additional genetic alterations correlated with overall survival.

Interpretable machine learning uncovers epithelial transcriptional rewiring and a role for Gelsolin in COPD.

Transcriptomic analyses have advanced the understanding of complex disease pathophysiology including chronic obstructive pulmonary disease (COPD). However, identifying relevant biologic causative factors has been limited by the integration of high dimensionality data. COPD is characterized by lung destruction and inflammation, with smoke exposure being a major risk factor. To define previously unknown biological mechanisms in COPD, we utilized unsupervised and supervised interpretable machine learning analyses of single-cell RNA-Seq data from the mouse smoke-exposure model to identify significant latent factors (context-specific coexpression modules) impacting pathophysiology. The machine learning transcriptomic signatures coupled to protein networks uncovered a reduction in network complexity and new biological alterations in actin-associated gelsolin (GSN), which was transcriptionally linked to disease state. GSN was altered in airway epithelial cells in the mouse model and in human COPD. GSN was increased in plasma from patients with COPD, and smoke exposure resulted in enhanced GSN release from airway cells from patients with COPD. This method provides insights into rewiring of transcriptional networks that are associated with COPD pathogenesis and provides a translational analytical platform for other diseases.