Harnessing Proteogenomics to Advance Precision Oncology: From Melanoma and Hepatocellular Carcinoma Perspective

Genomic profiling has significantly advanced precision oncology; however, relying solely on genome-driven approaches is often insufficient to capture the full molecular complexity of cancer. Proteogenomics integrates proteomics, transcriptomics, and genomic analyses to provide a more holistic view of tumor biology by revealing how genetic alterations translate into functional consequences at the protein level. This multidimensional framework enhances the ability to identify clinically actionable biomarkers, uncover dysregulated pathways, and understand tumor heterogeneity with greater precision. By advancing tumor molecular profiling, proteogenomics offers the potential to refine tumor classification, improve diagnostic accuracy, and better tailor therapeutic strategies to individual patient needs. This review examines the expanding role of proteogenomics as an essential tool in personalized cancer management. Key analytical platforms, including mass spectrometry–based proteomics and phosphoproteomics, next-generation sequencing, and integrative computational pipelines, are discussed. We also highlight illustrative applications across diverse malignancies, including melanoma and hepatocarcinoma (HCC), where proteogenomic insights have informed therapeutic decision-making, revealed novel drug targets, and improved understanding of treatment resistance mechanisms; challenges and future prospects were also discussed. These advancements collectively highlight the increasing significance of proteogenomics in the evolution of precision oncology and the centrality of integrated molecular profiling in personalized cancer treatment. Proteogenomics is an integrative multi-omics paradigm that combines genomics, transcriptomics, and mass spectrometry–based proteomics to provide a holistic view of tumor heterogeneity, capturing functional consequences at the protein level that genomics alone often misses. Genomics, utilizing technologies like next-generation sequencing (NGS) and CRISPR-based tools, has been instrumental in cataloging somatic mutations and developing targeted therapies by providing a comprehensive genomic profile for cancer patients. Transcriptomics, through methods such as bulk RNA-Seq, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics, provides functional annotation of the genome, offering dynamic patterns of gene expression and insights into the cellular heterogeneity and spatial context of tumors. Proteomics and phosphoproteomics, relying on mass spectrometry, are vital for directly measuring protein expression, post-translational modifications, and protein network rewiring, which are the principal effectors of cellular function and the targets of most anticancer therapies. The approach is essential for advancing precision oncology by refining tumor classification, identifying clinically actionable biomarkers, and better tailoring therapeutic strategies to individual patient needs, focusing on melanoma and hepatocellular carcinoma (HCC).