Liver cancer significantly contributes to the global cancer burden, with hepatocellular carcinoma (HCC) incidence rates increasing particularly in Asia. Despite this rise, a deep understanding of HCC remains elusive, impacting the efficacy of emerging therapies like immunotherapy. Although promising in treating various cancers, immunotherapy benefits only 20-40% of cancer patients, often due to poorly understood mechanisms and inaccurate patient selection, which highlights the urgent need for reliable biomarkers. To bridge this gap, our study leverages advanced spatial omics techniques to delineate molecular pathways crucial for determining responses to immunotherapy. We employ a comprehensive multi-omics approach, integrating single-cell cytokine profiling, multiplexed immunofluorescence (IF), and Digital Spatial Profiling (DSP) GeoMx data. This approach uniquely identifies "super responders" from progressors and non-responders, unlike traditional bulk omics analyses which fail to differentiate between these groups. Super responder-enriched gene markers, initially identified through DSP, were validated using the Visium spatial gene expression platform. More interestingly, these gene enrichment was specific to tumor and stromal regions but not non-neoplastic region. Additionally, we applied multiplexed IF and the Tumor-Immune Partitioning and Clustering (TIPC) tool to validate the significance of the CXCL9-CXCR3 axis in HCC, a hypothesis previously suggested by abundance studies. Moreover, by examining CD8+ cell transcriptomic profiles via DSP GeoMx, we identified a unique transcriptomic signature and associated immune pathways in super responders, distinguishing them from progressors and non-responders. Overall, our study highlights the benefits of integrating multiple omics datasets. Our results provide new insights and suggest potential improvements in the effectiveness of immunotherapy for HCC, leading to more targeted and precise treatment strategies.