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◇ VCU Scholars Compass (Virginia Commonwealth University)2026-08-21· Immune system

From Hepatic Immune Responses to Functional Patient Cohorts: Systems Immunology Approaches in Hepatocellular Carcinoma

Nicholas Koelsch

原始摘要(英文原文)· Original abstract
Metabolic dysfunction-associated fatty liver disease (MAFLD) frequently progresses to hepatocellular carcinoma (HCC), exhibiting sex-specific disparities. Traditional reductionist frameworks often fail to capture the complex, multi-cellular interactions driving this progression, while group-averaged analyses mask critical individual variation. This dissertation addresses these limitations by applying systems immunology to model MAFLD-induced HCC as a dynamic, individualized process governed by intercellular communication networks, biological sex, and patient-specific immune states. Using the DIAMOND mouse model, Chapter One demonstrates that dietary intervention leads to divergent outcomes of hepatic recovery or tumor progression. Rather than cellular abundance alone, the integrity of multicellular communication networks, particularly involving monocytes and structural cells, distinguishes recovery from disease. Chapter Two expands this framework to explore sex-specific disparities and individual variation in isogenic cohorts. Female mice exhibited lower entropy-informed network disorganization and robust regulatory programs, consistently achieving recovery. Conversely, males displayed high network instability and variable tumor progression. Chapter Three translates this individualized framework to human HCC single-cell datasets. A customizable R package, scFunctionalCohorts, was developed to integrate malignant programs, cellular composition, and intercellular communication into a unified stratification framework, identifying novel biological functional patient cohorts masked by group-averaged clinical classifications. Collectively, this work demonstrates that HCC progression and recovery are emergent properties of complex cellular networks rather than single molecular axes. By preserving individual-level variation, modeling network entropy, and optimizing translational profiling tools, this dissertation provides a dynamic foundation for shifting the tumor microenvironment from a chaotic, tumor-permissive state toward coordinated, host-favorable immune control, tissue repair, and clinical cancer regression.
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