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Updated: Feb 9, 2026

Identification of Circular RNAs using RNA Sequencing
Published on: November 14, 2019
RNA sequencing enables systematic identification of platelet transcriptomic alterations in NSCLC patients
Qun Zhang1, Huan Hu1, Hongda Liu2
1Department of Respiratory Medicine, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China.
Abstract:
Platelets are implicated as key players in the metastatic dissemination of tumor cells. Previous evidence demonstrated platelets retained cytoplasmic RNAs with physiologically activity, splicing pre-mRNA to mRNA and translating into functional proteins in response to external stimulation. Recently, platelets gene profile of healthy or diseased individuals were characterized with the help of RNA sequencing (RNA-Seq) in some studies, leading to new insights into the mechanisms underlying disease pathogenesis. In this study, we performed RNA-seq in platelets from 7 healthy individuals and 15 non-small cell lung cancer (NSCLC) patients. Our data revealed a subset of near universal differently expressed gene (DEG) profiles in platelets of metastatic NSCLC compared to healthy individuals, including 626 up-regulated RNAs (mRNAs and ncRNAs) and 1497 down-regulated genes. The significant over-expressed genes showed enrichment in focal adhesion, platelets activation, gap junction and adherens junction pathways. The DEGs also included previously reported tumor-related genes such as PDGFR, VEGF, EGF, etc., verifying the consistence and significance of platelet RNA-Seq in oncology study. We also validated several up-regulated DEGs involved in tumor cell-induced platelet aggregation (TCIPA) and tumorigenesis. Additionally, transcriptomic comparison analyses of NSCLC subgroups were conducted. Between non-metastatic and metastatic NSCLC patients, 526 platelet DEGs were identified with the most altered expression. The outcomes from subgroup analysis between lung adenocarcinoma and lung squamous cell carcinoma demonstrated the diagnostic potential of platelet RNA-Seq on distinguishing tumor histological types.
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