A Transcriptomic Liquid Biopsy Assay for Predicting Resistance to Neoadjuvant Therapy in Esophageal Squamous Cell Carcinoma. Issue 1 (12th July 2022)

• Record Type: Journal Article
• Authors: Okuno, Keisuke; Tokunaga, Masanori; Kinugasa, Yusuke; Baba, Hideo; Kodera, Yasuhiro; Goel, Ajay
• Is Part Of: Annals of surgery. Volume 276:Issue 1(2022)
• Page Start: 101
• Page End: 110
• Publication Date: 2022-07-12
• Subjects: esophageal squamous cell carcinoma -- neoadjuvant therapy -- predictive biomarker -- biomarker signature -- chemo-resistance; Surgery -- Periodicals; 617.005
• DOI: 10.1097/SLA.0000000000005473
• Languages: English
• ISSNs: 0003-4932

Abstract

Abstract : Objective: The aim of this study was to establish a liquid-biopsy assay to predict response to neoadjuvant therapy (NAT) in esophageal squamous cell carcinoma (ESCC) patients. Summary Background Data: Pretreatment prediction of resistance to NAT is of great significance for the selection of treatment options in ESCC patients. In this study, we comprehensively translated tissue-based microRNA (miRNA) and messenger RNA (mRNA) expression biomarkers into a liquid biopsy assay. Methods: We analyzed 186 clinical ESCC samples, which included 128 formalin-fixed paraffin-embedded and a matched subset of 58 serum samples, from 2 independent institutions. We performed quantitative reverse-transcription polymerase chain reaction, and developed a resistance-prediction model using the logistic regression analyses. Results: We first evaluated the potential of 4-miRNAs and 3-mRNAs panel, which robustly predicted resistance to NAT [area under the curve (AUC): 0.85]. Moreover, addition of tumor size to this panel increased predictive potential to establish a combination signature (AUC: 0.92). We successfully validated this signature performance in independent cohort, and our model was more accurate when the signature was combined with clinical predictors (AUC: 0.81) to establish a NAT resistance risk (NATRR) model. Finally, we successfully translated our NATRR model into a liquid biopsy assay (AUC: 0.78), and a multivariate regression analysis revealed this model as an independent predictor for response to NAT (odds ratio: 6.10; P < 0.01). Conclusions: We successfully developed a liquid biopsy-based assay that allows robust prediction of response to NAT in ESCC patients, and our assay provides fundamentals of developing precision-medicine.