Epstein-Barr virus DNA change level combined with tumor volume reduction ratio after inductive chemotherapy as a better prognostic predictor in locally advanced nasopharyngeal carcinoma

Plasma Metabolic Profiles-Based Prediction of Induction Chemotherapy Efficacy in Nasopharyngeal Carcinoma: Results of a Bidirectional Clinical Trial

PURPOSE

The efficacy of induction chemotherapy (IC) as a primary treatment for advanced nasopharyngeal carcinoma (NPC) remains a topic of debate, with a lack of dependable biomarkers for predicting its efficacy. This study seeks to establish a predictive classifier using plasma metabolomics profiles.

PATIENTS AND METHODS

A total of 166 NPC patients enrolled in the clinical trial NCT05682703 who were undergoing IC were included in the study. Plasma lipoprotein profiles were obtained using 1H-nuclear magnetic resonance before and after IC treatment. An artificial intelligence-assisted radiomics method was developed to effectively evaluate its efficacy. Metabolic biomarkers were identified through a machine learning approach based on a discovery cohort and subsequently validated in a validation cohort that mimicked the most unfavorable real-world scenario.

RESULTS

Our research findings indicate that the effectiveness of IC varies among individual patients, with a correlation observed between efficacy and changes in metabolite profiles. Using machine learning techniques, it was determined that the extreme gradient boosting model exhibited notable efficacy, attaining an area under the curve (AUC) value of 0.792 (95% CI, 0.668-0.913). In the validation cohort, the model exhibited strong stability and generalizability, with an AUC of 0.786 (95% CI, 0.533-0.922).

CONCLUSIONS

In this study, we found that dysregulation of plasma lipoprotein may result in resistance to IC in NPC patients. The prediction model constructed based on the plasma metabolites' profile has good predictive capabilities and potential for real-world generalization. This discovery has implications for the development of treatment strategies and may offer insight into potential targets for enhancing the effectiveness of IC.

Embracing Personalized Strategies in Radiotherapy for Nasopharyngeal Carcinoma: Beyond the Conventional Bounds of Fields and Borders

Radiotherapy is the primary treatment modality for non-metastatic nasopharyngeal carcinoma (NPC) across all TN-stages. Locoregional control rates have been impressive even from the 2D radiotherapy (RT) era, except when the ability to deliver optimal dose coverage to the tumor is compromised. However, short- and long-term complications following head and neck RT are potentially debilitating, and thus, there has been much research investigating technological advances in RT delivery over the past decades, with the primary goal of limiting normal tissue damage. On this note, with a plateau in gains of therapeutic ratio by modern RT techniques, future advances have to be focused on individualization of RT, both in terms of dose prescription and the delineation of target volumes. In this review, we analyzed the guidelines and evidence related to contouring methods, and dose prescription for early and locoregionally advanced (LA-) NPC. Next, with the preference for induction chemotherapy (IC) in patients with LA-NPC, we assessed the evidence concerning radiotherapy adaptations guided by IC response, as well as functional imaging and contour changes during treatment. Finally, we discussed on RT individualization that is guided by EBV DNA assessment, and its importance in the era of combinatorial immune checkpoint blockade therapy with RT.

The value of integrating tumor volume and plasma Epstein-Barr virus DNA load during sequential chemoradiotherapy for prognostic prediction and therapeutic guidance in high-risk locoregionally advanced nasopharyngeal carcinoma

OBJECTIVES

To investigate the value of integrating primary gross tumor volume (GTVp) and gross tumor volume of nodes (GTVn) after induction chemotherapy (IC) and dynamic changes in plasma cell-free Epstein-Barr virus DNA (cfEBV DNA) during sequential chemoradiotherapy (CRT) in high-risk locoregionally advanced nasopharyngeal carcinoma (LA-NPC).

MATERIALS AND METHODS

We retrospectively reviewed 988 patients with LA-NPC undergoing IC plus concurrent chemoradiotherapy (CCRT) between 2014 and 2018. The entire cohort was divided into four subgroups according to tumor volume and the cfEBV DNA load. Using a supervised statistical clustering approach, we stratified the subgroups into three clusters. Overall survival (OS), disease-free survival (DFS), distant metastasis-free survival (DMFS) and locoregional relapse-free survival (LRRFS) were calculated using Kaplan-Meier analysis and inter-group differences were compared using the log-rank test.

RESULTS

We observed that GTVp & GTVn and cfEBV DNApostIC & cfEBV DNApostCRT were powerful prognostic factors for OS (p = 0.004, p < 0.001, p < 0.001, and p < 0.001, respectively). The survival curves of the three clusters were significantly different. The 5-year OS for the low-risk, intermediate-risk and high-risk clusters were 97.0%, 86.2% and 77.1% (all P values < 0.001), respectively. The risk stratification system showed better predictive performance than the current tumor-node-metastasis (TNM) classification for OS (area under curve [AUC]: 0.653 versus 0.560, p < 0.001), DFS (AUC: 0.639 versus 0.540, p < 0.001), DMFS (AUC: 0.628 versus 0.535, p < 0.001) and LRRFS (AUC: 0.616 versus 0.513, p < 0.001).

CONCLUSION

Both tumor volume and the cfEBV DNA level during sequential CRT are effective prognostic indicators for patients with high-risk LA-NPC. The developed risk stratification system incorporating above factors improved survival prediction and demonstrated potential value in decision-making.