From tumor regression grading to interpretable endpoints in neoadjuvant oncology

Neoadjuvant therapy is expanding rapidly across tumor types, yet efficacy endpoints remain anchored in subjective tumor regression grading systems developed for cytotoxic therapy. We argue that post-treatment histopathology should evolve toward quantitative and biologically interpretable metrics integrating tumor burden, immune contexture, and spatial organization. We outline a validation pathway distinguishing prognostic biomarkers from true surrogate endpoints and propose a tumor- and regimen-aware framework for developing reproducible histologic endpoints in neoadjuvant oncology.