Development of a Novel Serum Exosomal MicroRNA Nomogram for the Preoperative Prediction of Lymph Node Metastasis in Esophageal Squamous Cell Carcinoma

Tong Liu; Lu-Tao Du; Yun-Shan Wang; Shan-Yu Gao; Juan Li; Pei-Long Li; Zhao-Wei Sun; Helen Binang; Chuan-Xin Wang

doi:10.3389/fonc.2020.573501

Development of a Novel Serum Exosomal MicroRNA Nomogram for the Preoperative Prediction of Lymph Node Metastasis in Esophageal Squamous Cell Carcinoma

Front Oncol. 2020 Oct 6:10:573501. doi: 10.3389/fonc.2020.573501. eCollection 2020.

Authors

Tong Liu¹, Lu-Tao Du^{1

2

3}, Yun-Shan Wang^{1

2

3}, Shan-Yu Gao⁴, Juan Li^{1

2

3}, Pei-Long Li^{1

2

3}, Zhao-Wei Sun⁵, Helen Binang¹, Chuan-Xin Wang^{1

2

3}

Affiliations

¹ Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
² Shandong Engineering & Technology Research Center for Tumor Marker Detection, Jinan, China.
³ Shandong Provincial Clinical Medicine Research Center for Clinical Laboratory, Jinan, China.
⁴ Department of Surgery, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China.
⁵ Department of Surgery, The Affiliated Hospital of Medical College Qingdao University, Qingdao, China.

Abstract

Preoperative prediction of lymph node (LN) metastasis is accepted as a crucial independent risk factor for treatment decision-making for esophageal squamous cell carcinoma (ESCC) patients. Our study aimed to establish a non-invasive nomogram to identify LN metastasis preoperatively in ESCC patients. Construction of the nomogram involved three sequential phases with independent patient cohorts. In the discovery phase (N = 20), LN metastasis-associated microRNAs (miRNAs) were selected from next-generation sequencing (NGS) assay of human ESCC serum exosome samples. In the training phase (N = 178), a nomogram that incorporated exosomal miRNA model and clinicopathologic was developed by multivariate logistic regression analysis to preoperatively predict LN status. In the validation phase (n = 188), we validated the predicted nomogram's calibration, discrimination, and clinical usefulness. Four differently expressed miRNAs (chr 8-23234-3p, chr 1-17695-5p, chr 8-2743-5p, and miR-432-5p) were tested and selected in the serum exosome samples from ESCC patients who have or do not have LN metastasis. Subsequently, an optimized four-exosomal miRNA model was constructed and validated in the clinical samples, which could effectively identify ESCC patients with LN metastasis, and was significantly superior to preoperative computed tomography (CT) report. In addition, a clinical nomogram consisting of the four-exosomal miRNA model and CT report was established in training cohort, which showed high predictive value in both training and validation cohorts [area under the receiver operating characteristic curve (AUC): 0.880 and 0.869, respectively]. The Hosmer-Lemeshow test and decision curve analysis implied the nomogram's clinical applicability. Our novel non-invasive nomogram is a robust prediction tool with promising clinical potential for preoperative LN metastasis prediction of ESCC patients, especially in T1 stage.

Keywords: esophageal squamous cell carcinoma; exosomal biomarker; lymph node metastasis; microRNA; nomogram.