Data Science Commons^™

Bacteria Synergized With Pd-1 Blockade Enhance Positive Feedback Loop Of Cancer Cells-M1 Macrophages-T Cells In Glioma, Qi Chen, Yuyi Zheng, Xiaojie Chen, Yuan Xing, Jiajie Zhang, Xinyi Yan, Qi Zhang, Di Wu, Zhong Chen

Faculty, Staff and Student Publications

Cancer immunotherapy is an attractive strategy because it stimulates immune cells to target malignant cells by regulating the intrinsic activity of the immune system. However, due to lacking many immunologic markers, it remains difficult to treat glioma, a representative "cold" tumor. Herein, to wake the "hot" tumor immunity of glioma, Porphyromonas gingivalis (Pg) is customized with a coating to create an immunogenic tumor microenvironment and further prove the effect in combination with the immune checkpoint agent anti-PD-1, exhibiting elevated therapeutic efficacy. This is accomplished not by enhancing the delivery of PD-1 blockade to enhance the effect of immunotherapy, but by …

Comprehensive Analysis Of Bulk And Single-Cell Transcriptomic Data Reveals A Novel Signature Associated With Endoplasmic Reticulum Stress, Lipid Metabolism, And Liver Metastasis In Pancreatic Cancer, Xiaohong Liu, Bo Ren, Yuan Fang, Jie Ren, Xing Wang, Minzhi Gu, Feihan Zhou, Ruiling Xiao, Xiyuan Luo, Lei You, Yupei Zhao

Faculty, Staff and Student Publications

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with high probability of recurrence and distant metastasis. Liver metastasis is the predominant metastatic mode developed in most pancreatic cancer cases, which seriously affects the overall survival rate of patients. Abnormally activated endoplasmic reticulum stress and lipid metabolism reprogramming are closely related to tumor growth and metastasis. This study aims to construct a prognostic model based on endoplasmic reticulum stress and lipid metabolism for pancreatic cancer, and further explore its correlation with tumor immunity and the possibility of immunotherapy.

METHODS: Transcriptomic and clinical data are acquired from TCGA, ICGC, and GEO …

Advanced Nano-Drug Delivery Systems In The Treatment Of Ischemic Stroke, Jiajie Zhang, Zhong Chen, Qi Chen

Faculty, Staff and Student Publications

In recent years, the frequency of strokes has been on the rise year by year and has become the second leading cause of death around the world, which is characterized by a high mortality rate, high recurrence rate, and high disability rate. Ischemic strokes account for a large percentage of strokes. A reperfusion injury in ischemic strokes is a complex cascade of oxidative stress, neuroinflammation, immune infiltration, and mitochondrial damage. Conventional treatments are ineffective, and the presence of the blood-brain barrier (BBB) leads to inefficient drug delivery utilization, so researchers are turning their attention to nano-drug delivery systems. Functionalized nano-drug …

Ml241 Antagonizes Erk 1/2 Activation And Inhibits Rotavirus Proliferation, Jinlan Wang, Xiaoqing Hu, Jinyuan Wu, Xiaochen Lin, Rong Chen, Chenxing Lu, Xiaopeng Song, Qingmei Leng, Yan Li, Xiangjing Kuang, Jinmei Li, Lida Yao, Xianqiong Tang, Jun Ye, Guangming Zhang, Maosheng Sun, Yan Zhou, Hongjun Li

Faculty, Staff and Student Publications

Rotavirus (RV) is the main pathogen that causes severe diarrhea in infants and children under 5 years of age. No specific antiviral therapies or licensed anti-rotavirus drugs are available. It is crucial to develop effective and low-toxicity anti-rotavirus small-molecule drugs that act on novel host targets. In this study, a new anti-rotavirus compound was selected by ELISA, and cell activity was detected from 453 small-molecule compounds. The anti-RV effects and underlying mechanisms of the screened compounds were explored. In vitro experimental results showed that the small-molecule compound ML241 has a good effect on inhibiting rotavirus proliferation and has low cytotoxicity …

Tissue-Specific Atlas Of Trans-Models For Gene Regulation Elucidates Complex Regulation Patterns, Robert Dagostino, Assaf Gottlieb

Faculty, Staff and Student Publications

BACKGROUND: Deciphering gene regulation is essential for understanding the underlying mechanisms of healthy and disease states. While the regulatory networks formed by transcription factors (TFs) and their target genes has been mostly studied with relation to cis effects such as in TF binding sites, we focused on trans effects of TFs on the expression of their transcribed genes and their potential mechanisms.

RESULTS: We provide a comprehensive tissue-specific atlas, spanning 49 tissues of TF variations affecting gene expression through computational models considering two potential mechanisms, including combinatorial regulation by the expression of the TFs, and by genetic variants within the …

Non-Traumatic Osteonecrosis Of The Femoral Head Induced By Steroid And Alcohol Exposure Is Associated With Intestinal Flora Alterations And Metabolomic Profiles, Qing-Yuan Zheng, Ye Tao, Lei Geng, Peng Ren, Ming Ni, Guo-Qiang Zhang

Faculty, Staff and Student Publications

OBJECTIVE: Osteonecrosis of the femoral head (ONFH) is a severe disease that primarily affects the middle-aged population, imposing a significant economic and social burden. Recent research has linked the progression of non-traumatic osteonecrosis of the femoral head (NONFH) to the composition of the gut microbiota. Steroids and alcohol are considered major contributing factors. However, the relationship between NONFH caused by two etiologies and the microbiota remains unclear. In this study, we examined the gut microbiota and fecal metabolic phenotypes of two groups of patients, and analyzed potential differences in the pathogenic mechanisms from both the microbial and metabolic perspectives.

METHODS: …

Leveraging Explainable Artificial Intelligence To Optimize Clinical Decision Support, Siru Liu, Allison B Mccoy, Josh F Peterson, Thomas A Lasko, Dean F Sittig, Scott D Nelson, Jennifer Andrews, Lorraine Patterson, Cheryl M Cobb, David Mulherin, Colleen T Morton, Adam Wright

Faculty, Staff and Student Publications

OBJECTIVE: To develop and evaluate a data-driven process to generate suggestions for improving alert criteria using explainable artificial intelligence (XAI) approaches.

METHODS: We extracted data on alerts generated from January 1, 2019 to December 31, 2020, at Vanderbilt University Medical Center. We developed machine learning models to predict user responses to alerts. We applied XAI techniques to generate global explanations and local explanations. We evaluated the generated suggestions by comparing with alert's historical change logs and stakeholder interviews. Suggestions that either matched (or partially matched) changes already made to the alert or were considered clinically correct were classified as helpful. …

Identification Of Novel F2-Isoprostane Metabolites By Specific Udp-Glucuronosyltransferases, Ginger L Milne, Marina S Nogueira, Benlian Gao, Stephanie C Sanchez, Warda Amin, Sarah Thomas, Camille Oger, Jean-Marie Galano, Harvey J Murff, Gong Yang, Thierry Durand

Faculty, Staff and Student Publications

UDP-glucuronosyltransferases (UGTs) catalyze the conjugation of glucuronic acid with endogenous and exogenous lipophilic small molecules to facilitate their inactivation and excretion from the body. This represents approximately 35 % of all phase II metabolic transformations. Fatty acids and their oxidized eicosanoid derivatives can be metabolized by UGTs. F2-isoprostanes (F2-IsoPs) are eicosanoids formed from the free radical oxidation of arachidonic acid. These molecules are potent vasoconstrictors and are widely used as biomarkers of endogenous oxidative damage. An increasing body of evidence demonstrates the efficacy of measuring the β-oxidation metabolites of F2-IsoPs rather than the unmetabolized F2-IsoPs to quantify oxidative damage in …

Social And Behavior Factors Of Alzheimer's Disease And Related Dementias: A National Study In The Us, David Ciciora, Elizabeth Vásquez, Edward Valachovic, Lifang Hou, Yinan Zheng, Hua Xu, Xiaoqian Jiang, Kun Huang, Kelley Pettee Gabriel, Hong-Wen Deng, Mary P Gallant, Kai Zhang

Faculty, Staff and Student Publications

Introduction: Considerable research has linked many risk factors to Alzheimer's Disease and Related Dementias (ADRD). Without a clear etiology of ADRD, it is advantageous to rank the known risk factors by their importance and determine if disparities exist. Statistical-based ranking can provide insight into which risk factors should be further evaluated.

Methods: This observational, population-based study assessed 50 county-level measures and estimates related to ADRD in 3,155 counties in the U.S. using data from 2010 to 2021. Statistical analysis was performed in 2022-2023. The machine learning method, eXtreme Gradient Boosting, was utilized to rank the importance of these variables by …

An Exposome Atlas Of Serum Reveals The Risk Of Chronic Diseases In The Chinese Population, Lei You, Jing Kou, Mengdie Wang, Guoqin Ji, Xiang Li, Chang Su, Fujian Zheng, Mingye Zhang, Yuting Wang, Tiantian Chen, Ting Li, Lina Zhou, Xianzhe Shi, Chunxia Zhao, Xinyu Liu, Surong Mei, Guowang Xu

Faculty, Staff and Student Publications

Although adverse environmental exposures are considered a major cause of chronic diseases, current studies provide limited information on real-world chemical exposures and related risks. For this study, we collected serum samples from 5696 healthy people and patients, including those with 12 chronic diseases, in China and completed serum biomonitoring including 267 chemicals via gas and liquid chromatography-tandem mass spectrometry. Seventy-four highly frequently detected exposures were used for exposure characterization and risk analysis. The results show that region is the most critical factor influencing human exposure levels, followed by age. Organochlorine pesticides and perfluoroalkyl substances are associated with multiple chronic diseases, …

The Acceptance And Use Of Digital Technologies For Self-Reporting Medication Safety Events After Care Transitions To Home In Patients With Cancer: Survey Study, Yun Jiang, Misun Hwang, Youmin Cho, Christopher R Friese, Sarah T Hawley, Milisa Manojlovich, John C Krauss, Yang Gong

Faculty, Staff and Student Publications

BACKGROUND: Actively engaging patients with cancer and their families in monitoring and reporting medication safety events during care transitions is indispensable for achieving optimal patient safety outcomes. However, existing patient self-reporting systems often cannot address patients' various experiences and concerns regarding medication safety over time. In addition, these systems are usually not designed for patients' just-in-time reporting. There is a significant knowledge gap in understanding the nature, scope, and causes of medication safety events after patients' transition back home because of a lack of patient engagement in self-monitoring and reporting of safety events. The challenges for patients with cancer in …

Deep Learning Model For Personalized Prediction Of Positive Mrsa Culture Using Time-Series Electronic Health Records, Masayuki Nigo, Laila Rasmy, Bingyu Mao, Bijun Sai Kannadath, Ziqian Xie, Degui Zhi

Faculty, Staff and Student Publications

Methicillin-resistant Staphylococcus aureus (MRSA) poses significant morbidity and mortality in hospitals. Rapid, accurate risk stratification of MRSA is crucial for optimizing antibiotic therapy. Our study introduced a deep learning model, PyTorch_EHR, which leverages electronic health record (EHR) time-series data, including wide-variety patient specific data, to predict MRSA culture positivity within two weeks. 8,164 MRSA and 22,393 non-MRSA patient events from Memorial Hermann Hospital System, Houston, Texas are used for model development. PyTorch_EHR outperforms logistic regression (LR) and light gradient boost machine (LGBM) models in accuracy (AUROC

Spec: A Soft Prompt-Based Calibration On Performance Variability Of Large Language Model In Clinical Notes Summarization, Yu-Neng Chuang, Ruixiang Tang, Xiaoqian Jiang, Xia Hu

Faculty, Staff and Student Publications

Electronic health records (EHRs) store an extensive array of patient information, encompassing medical histories, diagnoses, treatments, and test outcomes. These records are crucial for enabling healthcare providers to make well-informed decisions regarding patient care. Summarizing clinical notes further assists healthcare professionals in pinpointing potential health risks and making better-informed decisions. This process contributes to reducing errors and enhancing patient outcomes by ensuring providers have access to the most pertinent and current patient data. Recent research has shown that incorporating instruction prompts with large language models (LLMs) substantially boosts the efficacy of summarization tasks. However, we show that this approach also …

The Pathogenicity Of Vancomycin-Resistant Enterococcus Faecalis To Colon Cancer Cells, Li Zhang, Mingxia Deng, Jing Liu, Jiajie Zhang, Fangyu Wang, Wei Yu

Faculty, Staff and Student Publications

BACKGROUND: The aim of this study was to investigate the pathogenicity of vancomycin-resistant Enterococcus faecalis (VREs) to human colon cells in vitro.

METHODS: Three E. faecalis isolates (2 VREs and E. faecalis ATCC 29212) were cocultured with NCM460, HT-29 and HCT116 cells. Changes in cell morphology and bacterial adhesion were assessed at different time points. Interleukin-8 (IL-8) and vascular endothelial growth factor A (VEGFA) expression were measured via RT-qPCR and enzyme-linked immunosorbent assay (ELISA), respectively. Cell migration and human umbilical vein endothelial cells (HUVECs) tube formation assays were used for angiogenesis studies. The activity of PI3K/AKT/mTOR signaling pathway was measured …

Generalizable Pipeline For Constructing Hiv Risk Prediction Models Across Electronic Health Record Systems, Sarah B May, Thomas P Giordano, Assaf Gottlieb

Faculty, Staff and Student Publications

OBJECTIVE: The HIV epidemic remains a significant public health issue in the United States. HIV risk prediction models could be beneficial for reducing HIV transmission by helping clinicians identify patients at high risk for infection and refer them for testing. This would facilitate initiation on treatment for those unaware of their status and pre-exposure prophylaxis for those uninfected but at high risk. Existing HIV risk prediction algorithms rely on manual construction of features and are limited in their application across diverse electronic health record systems. Furthermore, the accuracy of these models in predicting HIV in females has thus far been …

The Il6/Jak/Stat3 Signaling Axis Is A Therapeutic Vulnerability In Smarcb1-Deficient Bladder Cancer, Chandra Sekhar Amara, Karthik Reddy Kami Reddy, Yang Yuntao, Yuen San Chan, Danthasinghe Waduge Badrajee Piyarathna, Lacey Elizabeth Dobrolecki, David J H Shih, Zhongcheng Shi, Jun Xu, Shixia Huang, Matthew J Ellis, Andrea B Apolo, Leomar Y Ballester, Jianjun Gao, Donna E Hansel, Yair Lotan, H Courtney Hodges, Seth P Lerner, Chad J Creighton, Arun Sreekumar, W Jim Zheng, Pavlos Msaouel, Shyam M Kavuri, Nagireddy Putluri

Faculty, Staff and Student Publications

SMARCB1 loss has long been observed in many solid tumors. However, there is a need to elucidate targetable pathways driving growth and metastasis in SMARCB1-deficient tumors. Here, we demonstrate that SMARCB1 deficiency, defined as genomic SMARCB1 copy number loss associated with reduced mRNA, drives disease progression in patients with bladder cancer by engaging STAT3. SMARCB1 loss increases the chromatin accessibility of the STAT3 locus in vitro. Orthotopically implanted SMARCB1 knockout (KO) cell lines exhibit increased tumor growth and metastasis. SMARCB1-deficient tumors show an increased IL6/JAK/STAT3 signaling axis in in vivo models and patients. Furthermore, a pSTAT3 selective inhibitor, TTI-101, reduces …

Patient And Dentist Perspectives On Collecting Patient Reported Outcomes After Painful Dental Procedures In The National Dental Pbrn, Elsbeth Kalenderian, Sayali Tungare, Urvi Mehta, Sharmeen Hamid, Rahma Mungia, Alfa-Ibrahim Yansane, David Holmes, Kim Funkhouser, Ana M Ibarra-Noriega, Janelle Urata, D Brad Rindal, Heiko Spallek, Joel White, Muhammad F Walji

Faculty, Staff and Student Publications

BACKGROUND: Dental Patient Reported Outcomes (PROs) relate to a dental patient's subjective experience of their oral health. How practitioners and patients value PROs influences their successful use in practice.

METHODS: Semi-structured interviews were conducted with 22 practitioners and 32 patients who provided feedback on using a mobile health (mHealth) platform to collect the pain experience after dental procedures. A themes analysis was conducted to identify implementation barriers and facilitators.

RESULTS: Five themes were uncovered: (1) Sense of Better Care. (2) Tailored Follow-up based on the dental procedure and patient's pain experience. (3) Effective Messaging and Alerts. (4) Usable Digital Platform. …

The Hsp90-Myc-Cdk9 Network Drives Therapeutic Resistance In Mantle Cell Lymphoma, Fangfang Yan, Vivian Jiang, Alexa Jordan, Yuxuan Che, Yang Liu, Qingsong Cai, Yu Xue, Yijing Li, Joseph Mcintosh, Zhihong Chen, Jovanny Vargas, Lei Nie, Yixin Yao, Heng-Huan Lee, Wei Wang, Johnnelson R Bigcal, Maria Badillo, Jitendra Meena, Christopher Flowers, Jia Zhou, Zhongming Zhao, Lukas M Simon, Michael Wang

Faculty, Staff and Student Publications

Brexucabtagene autoleucel CAR-T therapy is highly efficacious in overcoming resistance to Bruton's tyrosine kinase inhibitors (BTKi) in mantle cell lymphoma. However, many patients relapse post CAR-T therapy with dismal outcomes. To dissect the underlying mechanisms of sequential resistance to BTKi and CAR-T therapy, we performed single-cell RNA sequencing analysis for 66 samples from 25 patients treated with BTKi and/or CAR-T therapy and conducted in-depth bioinformatics™ analysis. Our analysis revealed that MYC activity progressively increased with sequential resistance. HSP90AB1 (Heat shock protein 90 alpha family class B member 1), a MYC target, was identified as early driver of CAR-T resistance. CDK9 …

Dynamic Prognosis Prediction For Patients On Dapt After Drug-Eluting Stent Implantation: Model Development And Validation, Fang Li, Laila Rasmy, Yang Xiang, Jingna Feng, Ahmed Abdelhameed, Xinyue Hu, Zenan Sun, David Aguilar, Abhijeet Dhoble, Jingcheng Du, Qing Wang, Shuteng Niu, Yifang Dang, Xinyuan Zhang, Ziqian Xie, Yi Nian, Jianping He, Yujia Zhou, Jianfu Li, Mattia Prosperi, Jiang Bian, Degui Zhi, Cui Tao

Faculty, Staff and Student Publications

BACKGROUND: The rapid evolution of artificial intelligence (AI) in conjunction with recent updates in dual antiplatelet therapy (DAPT) management guidelines emphasizes the necessity for innovative models to predict ischemic or bleeding events after drug-eluting stent implantation. Leveraging AI for dynamic prediction has the potential to revolutionize risk stratification and provide personalized decision support for DAPT management.

METHODS AND RESULTS: We developed and validated a new AI-based pipeline using retrospective data of drug-eluting stent-treated patients, sourced from the Cerner Health Facts data set (n=98 236) and Optum's de-identified Clinformatics Data Mart Database (n=9978). The 36 months following drug-eluting stent implantation were …

Real-World Trends, Rural-Urban Differences, And Socioeconomic Disparities In Utilization Of Narrow Versus Broad Next-Generation Sequencing Panels, Yiqing Zhao, Anastasios Dimou, Zachary C Fogarty, Jun Jiang, Hongfang Liu, William B Wong, Chen Wang

Faculty, Staff and Student Publications

UNLABELLED: Advances in genetic technology have led to the increasing use of genomic panels in precision oncology practice, with panels ranging from a couple to hundreds of genes. However, the clinical utilization and utility of oncology genomic panels, especially among vulnerable populations, is unclear. We examined the association of panel size with socioeconomic status and clinical trial matching. We retrospectively identified 9,886 eligible adult subjects in the Mayo Clinic Health System who underwent genomic testing between January 1, 2016 and June 30, 2020. Patient data were retrieved from structured and unstructured data sources of institutional collections, including cancer registries, clinical …

Identification Of New Egfr Inhibitors By Structure-Based Virtual Screening And Biological Evaluation, Shuyi Wang, Xiaotian Xu, Chuxin Pan, Qian Guo, Qinlan Li, Shanhe Wan, Zhonghuang Li, Jiajie Zhang, Xiaoyun Wu

Faculty, Staff and Student Publications

Epidermal growth factor receptor (EGFR) inhibitors have been used in clinical for the treatment of non-small-cell lung cancer for years. However, the emergence of drug resistance continues to be a major problem. To identify potential inhibitors, molecular docking-based virtual screening was conducted on ChemDiv and Enamine commercial databases using the Glide program. After multi-step VS and visual inspection, a total of 23 compounds with novel and varied structures were selected, and the predicted ADMET properties were within the satisfactory range. Further molecular dynamics simulations revealed that the reprehensive compound ZINC49691377 formed a stable complex with the allosteric pocket of EGFR …

Safety, Immunogenicity, And Mechanism Of A Rotavirus Mrna-Lnp Vaccine In Mice, Chenxing Lu, Yan Li, Rong Chen, Xiaoqing Hu, Qingmei Leng, Xiaopeng Song, Xiaochen Lin, Jun Ye, Jinlan Wang, Jinmei Li, Lida Yao, Xianqiong Tang, Xiangjun Kuang, Guangming Zhang, Maosheng Sun, Yan Zhou, Hongjun Li

Faculty, Staff and Student Publications

Rotaviruses (RVs) are a major cause of diarrhea in young children worldwide. The currently available and licensed vaccines contain live attenuated RVs. Optimization of live attenuated RV vaccines or developing non-replicating RV (e.g., mRNA) vaccines is crucial for reducing the morbidity and mortality from RV infections. Herein, a nucleoside-modified mRNA vaccine encapsulated in lipid nanoparticles (LNP) and encoding the VP7 protein from the G1 type of RV was developed. The 5' untranslated region of an isolated human RV was utilized for the mRNA vaccine. After undergoing quality inspection, the VP7-mRNA vaccine was injected by subcutaneous or intramuscular routes into mice. …

Dementia Prediction In Older Adults Using Sex-Specific Health Trajectory Clustering, Omar A Ibrahim, Muskan Garg, Sunyang Fu, Maria Vassilaki, Ronald C Petersen, Jennifer St Sauver, Sunghwan Sohn

Faculty, Staff and Student Publications

With increasing number of people living with dementia, the problem of late diagnosis significantly impacts a person's quality of life while early signs of dementia may provide useful insights to facilitate better treatment plans. With time, this progressive neurodegenerative syndrome could progress from mild cognitive impairment to dementia. A pattern of health conditions can be characterized in unsupervised manner to help predict this progress. As a significant extension to our previous work with streaming clustering model, we consider additional information for predicting dementia onset. With empirical observations, we discover the importance of examining sex and age to predict dementia onset. …

Prevention And Potential Treatment Strategies For Respiratory Syncytial Virus, Bo-Wen Sun, Peng-Peng Zhang, Zong-Hao Wang, Xia Yao, Meng-Lan He, Rui-Ting Bai, Hao Che, Jing Lin, Tian Xie, Zi Hui, Xiang-Yang Ye, Li-Wei Wang

Faculty, Staff and Student Publications

Respiratory syncytial virus (RSV) is a significant viral pathogen that causes respiratory infections in infants, the elderly, and immunocompromised individuals. RSV-related illnesses impose a substantial economic burden worldwide annually. The molecular structure, function, and in vivo interaction mechanisms of RSV have received more comprehensive attention in recent times, and significant progress has been made in developing inhibitors targeting various stages of the RSV replication cycle. These include fusion inhibitors, RSV polymerase inhibitors, and nucleoprotein inhibitors, as well as FDA-approved RSV prophylactic drugs palivizumab and nirsevimab. The research community is hopeful that these developments might provide easier access to knowledge and …

Fusionnw, A Potential Clinical Impact Assessment Of Kinases In Pan-Cancer Fusion Gene Network, Chengyuan Yang, Himansu Kumar, Pora Kim

Faculty, Staff and Student Publications

Kinase fusion genes are the most active fusion gene group in human cancer fusion genes. To help choose the clinically significant kinase so that the cancer patients that have fusion genes can be better diagnosed, we need a metric to infer the assessment of kinases in pan-cancer fusion genes rather than relying on the sample frequency expressed fusion genes. Most of all, multiple studies assessed human kinases as the drug targets using multiple types of genomic and clinical information, but none used the kinase fusion genes in their study. The assessment studies of kinase without kinase fusion gene events can …

Revealing Chronic Disease Progression Patterns Using Gaussian Process For Stage Inference, Yanfei Wang, Weiling Zhao, Angela Ross, Lei You, Hongyu Wang, Xiaobo Zhou

Faculty, Staff and Student Publications

OBJECTIVE: The early stages of chronic disease typically progress slowly, so symptoms are usually only noticed until the disease is advanced. Slow progression and heterogeneous manifestations make it challenging to model the transition from normal to disease status. As patient conditions are only observed at discrete timestamps with varying intervals, an incomplete understanding of disease progression and heterogeneity affects clinical practice and drug development.

MATERIALS AND METHODS: We developed the Gaussian Process for Stage Inference (GPSI) approach to uncover chronic disease progression patterns and assess the dynamic contribution of clinical features. We tested the ability of the GPSI to reliably …

Expanded T Lymphocytes In The Cerebrospinal Fluid Of Multiple Sclerosis Patients Are Specific For Epstein-Barr-Virus-Infected B Cells, Assaf Gottlieb, H Phuong T Pham, Jerome G Saltarrelli, J William Lindsey

Faculty, Staff and Student Publications

Epstein-Barr virus (EBV) infection has long been associated with multiple sclerosis (MS), but the role of EBV in the pathogenesis of MS is not clear. Our hypothesis is that a major fraction of the expanded clones of T lymphocytes in the cerebrospinal fluid (CSF) are specific for autologous EBV-infected B cells. We obtained blood and CSF samples from eight relapsing-remitting patients in the process of diagnosis. We stimulated cells from the blood with autologous EBV-infected lymphoblastoid cell lines (LCL), EBV, varicella zoster virus, influenza, and candida and sorted the responding cells with flow cytometry after 6 d. We sequenced the …

Stemdriver: A Knowledgebase Of Gene Functions For Hematopoietic Stem Cell Fate Determination, Yangyang Luo, Jingjing Guo, Jianguo Wen, Weiling Zhao, Kexin Huang, Yang Liu, Grant Wang, Ruihan Luo, Ting Niu, Yuzhou Feng, Haixia Xu, Pora Kim, Xiaobo Zhou

Faculty, Staff and Student Publications

StemDriver is a comprehensive knowledgebase dedicated to the functional annotation of genes participating in the determination of hematopoietic stem cell fate, available at http://biomedbdc.wchscu.cn/StemDriver/. By utilizing single-cell RNA sequencing data, StemDriver has successfully assembled a comprehensive lineage map of hematopoiesis, capturing the entire continuum from the initial formation of hematopoietic stem cells to the fully developed mature cells. Extensive exploration and characterization were conducted on gene expression features corresponding to each lineage commitment. At the current version, StemDriver integrates data from 42 studies, encompassing a diverse range of 14 tissue types spanning from the embryonic phase to adulthood. In order …

Ageannomo: A Knowledgebase Of Multi-Omics Annotation For Animal Aging, Kexin Huang, Xi Liu, Zhaocan Zhang, Tiangang Wang, Haixia Xu, Qingxuan Li, Yuhao Jia, Liyu Huang, Pora Kim, Xiaobo Zhou

Faculty, Staff and Student Publications

Aging entails gradual functional decline influenced by interconnected factors. Multiple hallmarks proposed as common and conserved underlying denominators of aging on the molecular, cellular and systemic levels across multiple species. Thus, understanding the function of aging hallmarks and their relationships across species can facilitate the translation of anti-aging drug development from model organisms to humans. Here, we built AgeAnnoMO (https://relab.xidian.edu.cn/AgeAnnoMO/#/), a knowledgebase of multi-omics annotation for animal aging. AgeAnnoMO encompasses an extensive collection of 136 datasets from eight modalities, encompassing 8596 samples from 50 representative species, making it a comprehensive resource for aging and longevity research. AgeAnnoMO characterizes …

Fusionneoantigen: : A Resource Of Fusion Gene-Specific Neoantigens, Himansu Kumar, Ruihan Luo, Jianguo Wen, Chengyuan Yang, Xiaobo Zhou, Pora Kim

Faculty, Staff and Student Publications

Among the diverse sources of neoantigens (i.e. single-nucleotide variants (SNVs), insertions or deletions (Indels) and fusion genes), fusion gene-derived neoantigens are generally more immunogenic, have multiple targets per mutation and are more widely distributed across various cancer types. Therefore, fusion gene-derived neoantigens are a potential source of highly immunogenic neoantigens and hold great promise for cancer immunotherapy. However, the lack of fusion protein sequence resources and knowledge prevents this application. We introduce 'FusionNeoAntigen', a dedicated resource for fusion-specific neoantigens, accessible at https://compbio.uth.edu/FusionNeoAntigen. In this resource, we provide fusion gene breakpoint crossing neoantigens focused on ∼43K fusion proteins of ∼16K in-frame …