Fuminori Sonohara1,2, Feng Gao3, Naoki Iwata2, Mitsuro Kanda2, Masahiko Koike2, Naoki Takahashi4, Yasuhide Yamada4, Yasuhiro Kodera2, Xin Wang3, Ajay Goel1. 1. Center for Gastrointestinal Research, Center for Translational Genomics and Oncology, Baylor Scott & White Research Institute, Charles A. Sammons Cancer Center, Baylor University Medical Center, Dallas, TX. 2. Department of Gastroenterological Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan. 3. Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, China. 4. Department of Gastrointestinal Medical Oncology, National Cancer Center Hospital, Tokyo, Japan.
Abstract
OBJECTIVE: This study aimed to develop a gene-expression signature for identification of lymph node (LN) metastasis in esophageal squamous cell carcinoma (ESCC) patients. SUMMARY OF BACKGROUND DATA: LN metastasis is recognized as the most important independent risk factor for therapeutic decision-making of ESCC patients. METHODS: A bioinformatic approach was used to analyze RNA sequencing profiles of ESCC patients, and to develop a gene-expression signature for identifying LN metastasis. The robustness of this panel was assessed in 2 independent patient cohorts (n = 56 and 224). RESULTS: We initially prioritized a 16-gene signature out of the total 20,531 mRNAs. The model estimated by these 16 genes discriminated LN status with an area under the curve (AUC) of 0.77 [95% confidence interval (95% CI), 0.68-0.87, 5-fold cross-validation]. Subsequently, a reduced and optimized 5-gene panel was trained in a clinical cohort, which effectively distinguished ESCC patients with LN metastasis (cohort-1: AUC, 0.74; 95% CI, 0.58-0.89; cohort-2, T1-T2: AUC, 0.74; 95% CI, 0.63-0.86), and was significantly superior to preoperative computed tomography (AUC, 0.61; 95% CI, 0.50-0.72). Furthermore, a combination signature comprising of the 5-gene panel together with the lymphatic vessel invasion (LVI) and venous invasion (VI) demonstrated a significantly improved diagnostic performance compared with individual clinical variables, in both cohorts (cohort-1: AUC, 0.87; 95% CI, 0.78-0.96; cohort-2: AUC, 0.76; 95% CI, 0.65-0.88). CONCLUSION: Our novel 5-gene panel is a robust diagnostic tool for LN metastasis, especially in early-T stage ESCC patients, with a promising clinical potential.
OBJECTIVE: This study aimed to develop a gene-expression signature for identification of lymph node (LN) metastasis in esophageal squamous cell carcinoma (ESCC) patients. SUMMARY OF BACKGROUND DATA: LN metastasis is recognized as the most important independent risk factor for therapeutic decision-making of ESCC patients. METHODS: A bioinformatic approach was used to analyze RNA sequencing profiles of ESCC patients, and to develop a gene-expression signature for identifying LN metastasis. The robustness of this panel was assessed in 2 independent patient cohorts (n = 56 and 224). RESULTS: We initially prioritized a 16-gene signature out of the total 20,531 mRNAs. The model estimated by these 16 genes discriminated LN status with an area under the curve (AUC) of 0.77 [95% confidence interval (95% CI), 0.68-0.87, 5-fold cross-validation]. Subsequently, a reduced and optimized 5-gene panel was trained in a clinical cohort, which effectively distinguished ESCC patients with LN metastasis (cohort-1: AUC, 0.74; 95% CI, 0.58-0.89; cohort-2, T1-T2: AUC, 0.74; 95% CI, 0.63-0.86), and was significantly superior to preoperative computed tomography (AUC, 0.61; 95% CI, 0.50-0.72). Furthermore, a combination signature comprising of the 5-gene panel together with the lymphatic vessel invasion (LVI) and venous invasion (VI) demonstrated a significantly improved diagnostic performance compared with individual clinical variables, in both cohorts (cohort-1: AUC, 0.87; 95% CI, 0.78-0.96; cohort-2: AUC, 0.76; 95% CI, 0.65-0.88). CONCLUSION: Our novel 5-gene panel is a robust diagnostic tool for LN metastasis, especially in early-T stage ESCC patients, with a promising clinical potential.