Integrated Multi-Omics Profiling Maps Ferroptosis–Cuproptosis Diversity in Cervical Cancer and Identifies a PDGFRB-Driven Monocyte Fibrotic Program Targeted by Sorafenib

Background: Ferroptosis and cuproptosis are two distinct forms of metal-dependent regulated cell death that have emerged as important mechanisms in tumor biology. However, the crosstalk between these pathways and their clinical relevance in cervical cancer remain largely unexplored. Methods: Using the TCGA-CESC cohort (n = 304), we quantified ferroptosis- and cuproptosis-related pathway activities by ssGSEA/GSVA and constructed a Metal Death Activity Score (MDAS). Weighted gene co-expression network analysis (WGCNA) was applied to identify MDAS-associated modules and hub genes. We further integrated single-cell RNA sequencing (scRNA-seq) data comprising 74,454 cells to characterize the cellular heterogeneity and dynamic evolution of metal death phenotypes within the tumor microenvironment. Core genes causally associated with cervical cancer risk were screened using two-sample Mendelian randomization (MR), and the optimal model among 74 machine-learning algorithms was selected to construct a Metal Death Risk Score (MDRS). At the therapeutic level, potential targeted agents were identified via network pharmacology, and PDGFRB–drug interactions were validated using molecular docking, molecular dynamics simulations, and MM/PBSA binding free energy calculations. To bridge molecular-scale evidence with tissue- and single-cell–scale effects, we developed a structure–context–coupled network propagation (SINP) model and performed single-cell pharmacodynamic simulations using scTenifoldKnk, enabling cross-scale mechanistic inference and validation. Results: MDAS was significantly elevated in cervical cancer tissues, while ferroptosis and cuproptosis were largely independent at the global level (r = 0.053, P = 0.355). WGCNA identified 293 hub genes across five MDAS-associated modules. Single-cell analyses revealed higher MDAS activation in myeloid cells and tumor epithelial cells, with a progressive decline along the epithelial malignant transformation trajectory (ρ = −0.231, P = 3.5×10^-44). MR analysis identified eight causal genes, including four risk factors (DACT1, PDGFRB, PRSS23, MYO15B) and four protective factors (MSRB3, CALD1, DAB2, BNC2). The optimal MDRS model (Elastic Net) achieved a C-index of 0.736 after integration with clinical variables and significantly improved risk reclassification (NRI = 0.073, P = 0.044). High-risk patients exhibited enhanced epithelial–mesenchymal transition (EMT), angiogenesis, and suppressed oxidative phosphorylation. Network pharmacology identified sorafenib as a dual-function candidate drug capable of both targeting PDGFRB and inducing ferroptosis. Molecular docking indicated stable binding of sorafenib to the ATP-binding pocket of the PDGFRB kinase domain (Vina score = −10.1 kcal/mol), which was further supported by molecular dynamics simulations, MM/PBSA analysis (ΔG_PB = −34.09 ± 0.26 kcal/mol), and surface plasmon resonance (SPR) validation (KD = 1.95 μM). At the tissue scale, SINP predicted that PDGFRB inhibition markedly suppresses collagen-enriched extracellular matrix (ECM) programs. scTenifoldKnk simulations further demonstrated cell context–dependent effects, revealing that PDGFRB drives pro-fibrotic reprogramming in monocytes and triggers collapse of the collagen network. Cross-scale consistency analysis converged on seven shared ECM core genes (COL1A1, COL1A2, COL3A1, COL5A2, COL6A3, LUM, A2M), establishing the PDGFRB–monocyte–collagen axis as a key mechanistic pathway linking the high-MDRS phenotype, stromal stiffening, and EMT. Conclusions: This study establishes an integrative framework encompassing metal death pathway activity scoring, causal gene identification, machine-learning–based risk stratification, and multiscale mechanistic simulation. MDRS enables clinical risk stratification in cervical cancer patients and highlights sorafenib as a potential precision therapeutic candidate for high-MDRS patients, with mechanisms likely involving PDGFRB inhibition, ferroptosis induction, and microenvironmental remodeling through suppression of monocyte-driven pro-fibrotic programs.