Significance of longitudinal Epstein–Barr virus DNA combined with multipoint tumor response for dynamic risk stratification and treatment adaptation in nasopharyngeal carcinoma

Dynamic therapy response is strongly associated with cancer outcomes. This study aimed to evaluate the significance of longitudinal Epstein–Barr virus (EBV) DNA and radiological tumor regression in risk stratification and response-adaptive treatment in locally-advanced nasopharyngeal carcinoma (LA-NPC). In total, 1312 patients from two centers were assigned to the training and validation cohorts. Based on the multipoint examination of EBV-DNA and tumor response, four post-induction chemotherapy, four mid-radiotherapy, and four post-radiotherapy subgroups were established. Then seven phenotypes were further generated according to different permutations and combinations. These phenotypes were subsequently congregated into four response clusters, which reflect distinct biological treatment responses. The four response clusters correlated with an evident 5-year progression-free survival in both the training and external validation cohorts (5-year: training cohort 91.1 %, 82.8 %, 30.6 %, and 10.0 %; external validation 94.4 %, 55.6 %, 40.0 %, and 12.7 %) had superior prognostic performance compared to TNM staging and nomogram model (concordance index: training cohort—0.825 vs. 0.603 vs. 0.756 and external validation—0.834 vs. 0.606 vs. 0.789). Importantly, the response clusters exhibited an excellent capability in selecting candidates who can benefit from adjuvant chemotherapy. In conclusion, risk stratification based on the dynamic assessment of both radiological and biological responses can significantly enhance prognostic insights and shed light on individualized treatment modifications in LA-NPCs. •Using longitudinal cfEBV DNA and tumor response, we identified four response clusters.•The clusters had superior prognostic performance compared to conventional models.•The clusters provided a potential avenue for optimizing real-time treatment selection.•Dynamic treatment response biomarkers enhance prognostic insight and tailored therapy.