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=12 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 vesicle long RNAs (exLRs) were isolated and sequenced. An CRC diagnostic signature (d-signature) was established, and prognosis-associated cell components were evaluated.

Results

The exLR 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 positively associated with CRC prognosis while natural killer T-cells, naive B-cells, immature dendritic cells, and lymphatic endothelial cells were negatively associated with prognosis.

Conclusions

Our study identified that 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.