RNA Sequencing of Tumor-Educated Platelets Reveals a Three-Gene Diagnostic Signature in Esophageal Squamous Cell Carcinoma.

Abstract

There is no cost-effective, accurate, and non-invasive method for the detection of esophageal squamous cell carcinoma (ESCC) in clinical practice. We aimed to investigate the diagnostic potential of tumor-educated platelets in ESCC. In this study, seventy-one ESCC patients and eighty healthy individuals were enrolled and divided into a training cohort (23 patients and 27 healthy individuals) and a validation cohort (48 patients and 53 healthy individuals). Next-generation RNA sequencing was performed on platelets isolated from peripheral blood of all participants, and a support vector machine/leave-one-out cross validation (SVM/LOOCV) approach was used for binary classification. A diagnostic signature composed of ARID1A, GTF2H2, and PRKRIR discriminated ESCC patients from healthy individuals with 91.3% sensitivity and 85.2% specificity in the training cohort and 87.5% sensitivity and 81.1% specificity in the validation cohort. The AUC was 0.924 (95% CI, 0.845-0.956) and 0.893 (95% CI, 0.821-0.966), respectively, in the training cohort and validation cohort. This 3-gene platelet RNA signature could effectively discriminate ESCC from healthy control. Our data highlighted the potential of tumor-educated platelets for the noninvasive diagnosis of ESCC. Moreover, we found that keratin and collagen protein families and ECM-related pathways might be involved in tumor progression and metastasis of ESCC, which might provide insights to understand ESCC pathobiology and advance novel therapeutics.

• Authors: Tiejun Liu, Xin Wang, Wei Guo, Fei Shao, Zitong Li, Yang Zhou, Zhihong Zhao, Liyan Xue, Xiaoli Feng, Yin Li, Fengwei Tan, Kai Zhang, Qi Xue, Shugeng Gao, Yibo Gao, Jie He
• Journal: Frontiers in oncology (Front Oncol) Vol. 12 Pg. 824354 ( 2022) ISSN: 2234-943X [Print] Switzerland
• PMID: 35615147 (Publication Type: Journal Article)
• Copyright: Copyright © 2022 Liu, Wang, Guo, Shao, Li, Zhou, Zhao, Xue, Feng, Li, Tan, Zhang, Xue, Gao, Gao and He.