Computational Design and Structure-Guided Optimization of Anti-Osteopontin Monoclonal Antibodies at the Intersection of Obesity, Type 2 Diabetes, and Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality, and obesity and type 2 diabetes (T2D) are recognized metabolic risk factors for its development. In this study, disease-associated gene lists for T2D and obesity were integrated with differentially expressed genes from the Cancer Genome Atlas Liver Hepatocellular Carcinoma cohort (TCGA-LIHC). Analysis of 371 primary HCC and 50 solid-tissue normal samples identified 2123 differentially expressed genes, including 715 upregulated and 1408 downregulated genes. The intersection of the 715 upregulated genes with 2055 T2D-associated and 1944 obesity-associated protein-coding genes identified 29 common candidates. Functional annotation identified 14 extracellular-region genes, which were evaluated using protein–protein interaction analysis and ranked using the maximal clique centrality algorithm. SPP1, encoding Osteopontin (OPN), was the highest-ranked candidate. SPP1 expression distinguished HCC from non-tumor tissues with an area under the receiver operating characteristic curve of 0.714 (95% confidence interval: 0.666–0.760). High SPP1 expression was associated with poorer overall survival, and continuous log2-transformed SPP1 expression remained independently associated with survival after adjustment for age, sex, and pathological stage. OPN was subsequently subjected to structural modeling, molecular dynamics simulation, B-cell epitope prediction, and the structure-guided optimization of anti-OPN monoclonal antibodies. Molecular docking and binding affinity analyses revealed that optimized mAbs exhibited predicted Kd values corresponding to approximately 10- to 650-fold stronger binding affinity and increased predicted hydrogen bonding at the interface. These findings support SPP1 as a promising immunotherapeutic target in metabolically driven HCC, warranting further experimental validation.