Impact of microbiota on AIDS-Kaposi’s sarcoma development and therapy

微生物群对艾滋病-卡波西肉瘤发展和治疗的影响

• 批准号: 10753890
• 负责人: Shou-Jiang Gao
• 金额: $ 79.31万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-08 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10753890
• 关键词: Acquired Immunodeficiency Syndrome; Address; Affect; Africa; African; Animal Model; Antibodies; Bacteria; Biology; Blood; CD14 gene; Cell Communication; Cell Proliferation; Cells; Clinical; Clinical Research; Clinical Sciences; Complex; Computational Biology; Data; Development; Disease Outcome; Epidemiology; Flagellin; Gene Expression Profile; Genes; Goals; HIV; HIV Infections; Herpesviridae Infections; Human; Human Herpesvirus 8; Immune; Immune response; Immunocompromised Host; Immunologics; In Situ; Infection; Inflammation; Inflammatory; Innate Immune Response; Kaposi Sarcoma; Laboratories; Lipopolysaccharides; Longitudinal cohort; Machine Learning; Malignant Neoplasms; Methods; Modeling; Molecular; Morbidity - disease rate; Oral; Outcome; Palate Kaposi' s Sarcoma; Pathogenesis; Patients; Population; Poverty; Predictive Factor; Prevention; Preventive; Prognostic Marker; Research Personnel; Role; Societies; Specimen; TLR4 gene; Technology; Therapeutic; Therapeutic Agents; Time; Tobacco use; Translational Research; Underrepresented Populations; Validation; Visceral; Work; antiretroviral therapy; cancer specimen resource; case control; co-infection; cohort; comorbidity; complement pathway; cytokine; dysbiosis; health disparity; innovation; insight; lipopolysaccharide-binding protein; longitudinal analysis; machine learning algorithm; metaplastic cell transformation; microbial; microbiome; microbiota; mortality; novel; pre-clinical; predictive marker; prognostic; prognostic value; response; single cell sequencing; skin organogenesis; statistics; therapeutic target; therapeutically effective; therapy outcome; tumor; tumorigenesis

Project Abstract Microbiota imbalance impacts the development and therapeutic outcome of cancer by altering host immune response and inflammation. Kaposi’s sarcoma (KS) is the most common cancer in HIV-infected patients caused by infection of Kaposi’s sarcoma-associated herpesvirus (KSHV). Despite antiretroviral therapy, KS remains common among HIV-infected patients. It remains unclear what factors might influence the development and therapeutic outcome of AIDS-KS? In response to RFA-CA-22-056 entitled: “Basic/Translational Research on Health Disparities in Underrepresented People Living with HIV (PLWH) and Cancer”, this application specifically addresses the underserved African populations that have high numbers of new HIV infections with the long- term goal is to delineate the pathogenesis of AIDS-associated KS (AIDS-KS), and identify effective therapeutic targets and agents as well as prognostic biomarkers. We have recently shown the impoverishment of oral microbial diversity and enrichment of specific microbiota in oral AIDS-KS, and demonstrated that bacteria and their products lipopolysaccharide and flagellin promote KSHV-induced tumorigenesis by enhancing inflammation in a preclinical KSHV-induced KS animal model. Our hypothesis is that specific microbiota regulates inflammation to impact KS development and therapeutic outcome in AIDS-KS patients. We have assembled a strong collaborative team with diverse expertise in HIV infection, KSHV biology, microbiome, clinical sciences, epidemiology, statistics, computational biology and machine learning. We will take advantage of the long-term clinical studies in Africa with well-defined cross-sectional, case-control and longitudinal cohorts of large HIV-infected and AIDS-KS populations directed by investigators of this project. We will determine the impact of specific microbiota on inflammation and AIDS-KS development by performing case-control analyses in naïve AIDS-KS and HIV/KSHV patients without KS (Aim 1); and examine the impact of specific microbiota on the therapeutic outcome of KS by case-control longitudinal analyses of AIDS-KS patients undergoing anti-retroviral therapy followed by validation analyses in an independent cohort (Aim 2). This interdisciplinary project will analyze the molecular, virological, microbial, immunological, single cell spatial omics, and clinical features of AIDS-KS patients using advanced machine learning approaches. We expect to identify factors that influence the development and therapeutic outcome of AIDS-KS patients. The proposed work is highly significant, and will have prognostic, preventive and therapeutic impacts on AIDS-KS patients. This will be the first time that the role of microbiota will be systematically examined in AIDS-KS patients from well-characterized cohorts. The proposed innovative approaches such as spatial single cell sequencing and machine learning will generate unique and unprecedented results, providing novel insights into the pathogenesis and therapeutic outcome of AIDS-KS.

项目摘要