Graphene Oxide-Based Gene Delivery Strategies for Cancer-Specific Elimination in 3D Lung Tumor Models

Abstract

Solid tumors develop within highly complex three-dimensional (3D) microenvironments, in which cancer cells interact dynamically with stromal cells, immune populations, and extracellular matrix (ECM) components. These interactions critically regulate tumor progression, immune evasion, and therapeutic resistance, yet are not adequately captured by conventional two-dimensional (2D) in vitro models. Despite significant advances in anticancer therapies, the clinical translation of many promising strategies remains limited by the lack of selectivity for cancer cells. As a result, therapeutic efficacy is often overestimated, while resistance mechanisms and effects on non-target cell populations remain insufficiently understood. Gene therapy has emerged as a powerful approach to modulate cancer-associated pathways, particularly those governing immune evasion and apoptosis. By controlling gene expression in cancer cells, gene-based strategies can suppress tumor growth and enhance immune-mediated cancer cell elimination while reducing impacts on healthy tissues. Among emerging nanomaterials, graphene oxide (GO) has attracted increasing interest as a nanocarrier platform for gene delivery due to its high loading capacity, tunable surface functionalization, and promising biocompatibility. The goal of this doctoral work was to establish an integrated platform combining GO-based gene delivery with progressively complex 3D lung cancer models, enabling the rational design, evaluation, and refinement of cancer-specific therapeutic strategies. This work is structured around three interrelated pillars: nanocarrier engineering, tumor microenvironment modeling, and therapy strategy design, which are explored iteratively throughout the thesis. First, GO nanocarrier formulations were systematically engineered and evaluated to identify those providing optimal biocompatibility and transfection efficiency. The effects of nanocarrier size and surface modification with polyethylene glycol (PEG) and polyamidoamine (PAMAM) were assessed for small interfering RNA (siRNA) delivery in both conventional 2D cultures and 3D lung cancer spheroids. Cellular viability, apoptosis, and target protein modulation were analyzed to elucidate how nanocarrier physicochemical properties influence delivery performance. Building on this optimized delivery system, an increasingly physiologically relevant multicellular 3D lung tumor model was developed by integrating cancer cells, stromal fibroblasts, and macrophages within an ECM-mimetic scaffold. GO nanocarriers delivered distinct therapeutic cargos, including siRNA and plasmid DNA (pDNA), targeting immune evasion and apoptotic pathways through single-gene and co-delivery strategies. Analysis of nanocarrier uptake, gene and protein modulation, and cancer cell viability demonstrated that co-delivery approaches enhance cancer cell elimination while limiting off-target effects within a tumor-stroma-immune-rich microenvironment. Finally, the optimized nanocarrier and advanced 3D tumor model were unified into a single platform, enabling multi-gene delivery targeting cancer cells, stromal support, and immune-mediated responses simultaneously. To further enhance cancer cell specificity, GO was functionalized with an epidermal growth factor receptor (EGFR)-targeting peptide. Therapeutic outcomes were evaluated through cell type-specific nanocarrier uptake, targeted gene modulation, macrophage activation, stromal remodeling, and apoptosis induction. Coordinated modulation of multiple tumor components led to enhanced cancer-specific elimination, compared to single-target approaches. This thesis demonstrates that effective cancer-specific gene therapy requires the concurrent optimization of nanocarrier design, tumor model complexity, and multi-target therapeutic strategies. By integrating these elements within a unified 3D evaluation framework, this work establishes GO-based gene delivery systems as versatile, microenvironment-aware tools for preclinical evaluation and rational development of next-generation cancer therapies.