Integrative analysis of long extracellular RNAs reveals a detection panel of noncoding RNAs for liver cancer

Abstract

Rationale: Long extracellular RNAs (exRNAs) in plasma can be profiled by new sequencing technologies, even with low abundance. However, cancer-related exRNAs and their variations remain understudied. Methods: We investigated different variations (i.e. differential expression, alternative splicing, alternative polyadenylation, and differential editing) in diverse long exRNA species (e.g. long noncoding RNAs and circular RNAs) using 79 plasma exosomal RNA-seq (exoRNA-seq) datasets of multiple cancer types. We then integrated 53 exoRNA-seq datasets and 65 self-profiled cell-free RNA-seq (cfRNA-seq) datasets to identify recurrent variations in liver cancer patients. We further combined TCGA tissue RNA-seq datasets and validated biomarker candidates by RT-qPCR in an individual cohort of more than 100 plasma samples. Finally, we used machine learning models to identify a signature of 3 noncoding RNAs for the detection of liver cancer. Results: We found that different types of RNA variations identified from exoRNA-seq data were enriched in pathways related to tumorigenesis and metastasis, immune, and metabolism, suggesting that cancer signals can be detected from long exRNAs. Subsequently, we identified more than 100 recurrent variations in plasma from liver cancer patients by integrating exoRNA-seq and cfRNA-seq datasets. From these datasets, 5 significantly up-regulated long exRNAs were confirmed by TCGA data and validated by RT-qPCR in an independent cohort. When using machine learning models to combine two of these validated circular and structured RNAs ( SNORD3B-1, circ-0080695 ) with a miRNA ( miR-122 ) as a panel to classify liver cancer patients from healthy donors, the average AUROC of the cross-validation was 89.4%. The selected 3-RNA panel successfully detected 79.2% AFP-negative samples and 77.1% early-stage liver cancer samples in the testing and validation sets. Conclusions: Our study revealed that different types of RNA variations related to cancer can be detected in plasma and identified a 3-RNA detection panel for liver cancer, especially for AFP-negative and early-stage patients.

Cancer Type Classification Using Plasma Cell Free RNAs Derived From Human and Microbes

“…In addition to 35 datasets for liver cancer and 30 datasets for healthy donors we published previously (GSE142987) 21 , 230 raw FASTQ les supporting the ndings of this study are available in the Gene Expression Omnibus (GEO: GSE174302).…”

“…The cohort in this study included 295 plasma samples in total. Except for 65 previously published samples (GSE142987: 35 liver cancer patients and 30 healthy donors) [21] , we sequenced the total cfRNAs (>50nt) in 230 additional plasma samples (54 colorectal cancer, 37 stomach cancer, 27 liver cancer, 35 lung cancer, 31 esophageal cancer and 46 HDs).…”

Construction of a Ferroptosis-Related Nine-lncRNA Signature for Predicting Prognosis and Immune Response in Hepatocellular Carcinoma

“…Long non-coding RNAs (lncRNAs) are non-coding transcripts of 200 nucleotides in length, which could regulate the expression of various cancer-associated genes. Recently, Zhu et al comprehensively investigated the molecular profiles of lncRNAs in plasma samples from HCC patients and revealed that the differentially expressed lncRNAs were mainly enriched in the biological functions related to tumorigenesis, such as cell metastasis, immune response, and metabolism regulation (11). A high level of LINC00958 aggravated HCC lipogenesis and progression through sponging miR-3619-5p, further upregulating the hepatoma-derived growth factor expression (12).…”

(In)Distinctive Role of Long Non-Coding RNAs in Common and Rare Ovarian Cancers

“…As single markers sometimes lack sensitivity and specificity, designing biomarker panels has been suggested as a good option for early detection, diagnosis, and prediction of recurrence. Such panels of lncRNAs have already been proposed for hepatocellular [253], liver [254], bladder [255,256], breast and cervical cancer [257]. A lncRNA panel as a candidate prognostic biomarker for OC has been proposed by Zhan et al [258], but the focus was mainly on the construction of panels that can assess the response to therapy of OC patients, for example for platinum-based chemoresistance [259,260] or paclitaxel resistance [261].…”