AUTHOR=Guo Tian-An , Lai Hong-Yan , Li Cong , Li Yan , Li Yu-Chen , Jin Yu-Tong , Zhang Zhao-Zhen , Huang Hao-Bo , Huang Sheng-Lin , Xu Ye 

TITLE=Plasma Extracellular Vesicle Long RNAs Have Potential as Biomarkers in Early Detection of Colorectal Cancer

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.829230

DOI=10.3389/fonc.2022.829230

ISSN=2234-943X

ABSTRACT=Background: Early detection of colorectal cancer (CRC) is crucial to the treatment and prognosis of patients. Traditional screening methods have disadvantages.
Methods: 231 blood samples were collected from 86 CRC, 56 colorectal adenoma (CRA) and 89 healthy individuals, from which extracellular vesicles long RNAs (exLRs) were isolated and sequenced. An CRC diagnostic signature (d-signature) was established and prognosis-associated cell components were evaluated.
Results: The exLRs d-signature for CRC was established based on 17 of the differentially expressed exLRs. The d-signature showed high diagnostic efficiency of CRC and control (CRA and healthy) samples with an area under the curve (AUC) of 0.938 in the training cohort, 0.943 in the validation cohort and 0.947 in an independent cohort. The d-signature could effectively differentiate early stage (stage I-II) CRC from healthy individuals (AUC 0.990), as well as differentiating CEA-negative CRC from healthy individuals (AUC 0.988). A CRA d-signature was also generated and could differentiate CRA from healthy individuals both in the training (AUC 0.993) and validation (AUC 0.978) cohorts. The enrichment of class-switched memory B-cells, B-cells, naive B-cells and mast cells showed increasing trends between CRC, CRA and healthy cohorts. Class-switched memory B-cells, mast cells and basophils were positive associated with CRC prognosis while natural killer T-cells, naive B-cells, immature dendritic cells and lymphatic endothelial cells were negative associated with prognosis.
Conclusions: Our study identified the exLR d-signature could differentiate CRC from CRA and healthy individuals with high efficiency and exLR profiling also has potential in CRA screening and CRC prognosis prediction.