Exhaled volatile organic compounds as predictors of chemoradiotherapy response in locally advanced ESCC: A prospective study
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PUBLIC SUMMARY
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Volatile organic compounds (VOCs) predict outcomes in esophageal squamous cell carcinoma (ESCC).
VOCs dynamically change during chemoradiotherapy (CRT) and vary between complete response (CR) and non-CR.
Breath-based biomarkers may help monitor ESCC in real time and guide personalized therapy.
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ABSTRACT
Definitive or neoadjuvant chemoradiotherapy (CRT) is a standard treatment for locally advanced esophageal squamous cell carcinoma (ESCC). However, noninvasive biomarkers for treatment response assessment remain lacking. We investigated the predictive value of exhaled volatile organic compounds (VOCs) in ESCC patients undergoing CRT. In this prospective observational study, exhaled VOCs were analyzed using high-pressure photon ionization time-of-flight mass spectrometry before, during, and after CRT. Patients were classified as complete responders (CR) or non-complete responders (non-CR) based on pathological or imaging assessment. VOCs were selected through univariate analysis, least absolute shrinkage and selection operator regression, and recursive feature elimination. Machine learning models integrating VOCs and clinical variables were developed. Survival outcomes were evaluated using Cox regression and Kaplan–Meier analysis. Among 72 patients enrolled between Oct 8, 2022, and Aug 23, 2023, 44 achieved CR and 28 were classified as non-CR after CRT. Four VOCs and three clinical characteristics were identified as response predictors. Among four machine learning algorithms, the random forest model showed the best performance (AUC, 0.873; sensitivity, 90.9%; specificity, 60.7%; accuracy, 79.2%). The multivariable Cox model predicted 12-month overall survival with an AUC of 0.945. Exhaled VOC profiling represents a promising noninvasive approach for predicting treatment response and survival in ESCC patients receiving CRT. -
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REFERENCES
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Gao Y., Cheng X., Chen B., et al. (2026). Exhaled volatile organic compounds as predictors of chemoradiotherapy response in locally advanced ESCC: A prospective study. The Innovation Oncology 1:100040. https://doi.org/10.59717/j.xinn-oncol.2026.100040
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Gao Y., Cheng X., Chen B., et al. (2026). Exhaled volatile organic compounds as predictors of chemoradiotherapy response in locally advanced ESCC: A prospective study. The Innovation Oncology 1:100040. https://doi.org/10.59717/j.xinn-oncol.2026.100040
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Figure 1.
Patient recruitment and sample collection procedures
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Figure 2.
Receiver operating characteristic curves of machine learning models for predicting CR
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Figure 3.
Feature-ranking plots (A) and beeswarm plots (B) of the random forest model for predicting CR
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Figure 4.
Prognostic model for overall survival constructed using the variables selected in the RF model
