Tumor antigens across cancer progression: from immune recognition and selection to precision cancer immunotherapy

Tumor antigens provide the molecular interface between malignant transformation and host immunity, but their biological significance is determined by more than their molecular existence. Antigen clonality, abundance, processing, human leukocyte antigen (HLA) presentation, dendritic-cell function, T-cell recognition, spatial immune organization, and the surrounding tumor microenvironment (TME) collectively determine whether an antigen becomes immunologically visible and therapeutically actionable. Across cancer progression, tumor-cell antigenic states and the TME undergo reciprocal selection: immune pressure can eliminate highly visible clones while favoring antigen-loss variants, HLA defects, immune exclusion, suppressive myeloid and stromal states, and treatment-resistant populations. Recent single-cell, spatial and three-dimensional imaging, as well as immunopeptidomic studies show that this evolution is heterogeneous across tumor regions and anatomical compartments rather than a uniform linear process. This review therefore advances an antigen-TME co-evolution framework linking primary tumors, lymphatic and nodal immune compartments, systemic dissemination, distant metastatic niches, therapy, minimal residual disease, and recurrence. It critically evaluates the strengths and limitations of the classical immunoediting model; compares melanoma, breast, colorectal, lung, prostate, sarcoma, and virus-associated cancers according to antigen source, clonality, presentation competence, immune architecture, and dominant therapeutic bottleneck; and examines clinical translation through checkpoint blockade, cellular therapy, vaccines, antibodies, antibody-drug conjugates, immunopeptidomics, and computational antigen prediction. Particular attention is given to the gap between predicted peptide binding and verified presentation or immunogenicity, the need for longitudinal rather than single-biopsy profiling, and the requirement for prospective validation of artificial-intelligence models. The central conclusion is that tumor antigens become clinically meaningful only when antigenic state and microenvironmental context are assessed together, providing a more rigorous foundation for precision cancer immunotherapy.