Researchers from the Beckman Research Institute of City of Hope, California, have developed a liquid-biopsy based risk assay that can robustly predict resistance to neoadjuvant therapy (NAT) in patients with esophageal squamous cell carcinoma (ESCC). This study was recently published in the journal Annals of Surgery.
ESCC is one of the most aggressive type of esophageal cancer, and many patients do not respond to NAT. Early on, predicting this non-responsiveness can help clinicians choose other treatment options for resistant patients.
The researchers have developed a prediction model using 186 clinical ESCC samples, 128 formalin-fixed paraffin-embedded and a matched 58 serum samples from two independent centers. Using four microRNA and three messenger RNA biomarkers, the model could predict NAT resistance in ESCC patients (area under the curve [AUC]: 0.85). Adding more tumour size to this panel also increased the predictive potential of the model (AUC:0.92).
Validation of this model was done in an independent cohort where the model could accurately predict NAT resistance (AUC:0.81). This NAT resistance model was translated into a liquid biopsy assay (0.78), where a multivariate analysis of the model revealed this model as an independent predictor of NAT response (odds ratio: 6.10; P < 0.01).
The liquid biopsy assay provides a robust tool for predicting response to NAT in ESCC patients. Dr Goel and colleagues state “As we usher into the era of precision oncology, it is imperative that patients are offered treatment that have higher likelihood of benefit and minimal toxicity,”. Further, they mention, “Our study provides a proof-of-concept precision-medicine assay, for its further validation in future prospective clinical trials,” they say.
Okuno, Keisuke MD, PhD∗,†; Tokunaga, Masanori MD, PhD†; Kinugasa, Yusuke MD, PhD et al. A Transcriptomic Liquid Biopsy Assay for Predicting Resistance to Neoadjuvant Therapy in Esophageal Squamous Cell Carcinoma, Annals of Surgery: May 13, 2022 – Volume – Issue – 10.1097/SLA.0000000000005473