Evidence map›Paper›PMID 41508022›Full record

ArticleJournal of translational medicine2026

Novel serum small extracellular vesicle miRNAs with multi-target RCA-CRISPR sensor for liver cancer detection.

Tingting Fan, Bo Zhou, Hui Chen, Li-Ping Liu, Yong Ni, Wei Zhang, Lizhen Ye, Yifei Chen, Dandan Zhang, Shiqi Yang and 10 more

Abstract read
In one paragraph

Article in Journal of translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Tingting Fan *Guangdong Provincial Key Laboratory of Chinese Medicine Ingredients and Gut Microbiomics, Institute of Biomedical Health Technology and Engineering, Shenzhen Bay Laboratory, Shenzhen, 518000, China. fantt@szbl.ac.cn.ORCID 0000-0003-3338-4154
Bo Zhou *School of Pharmacy, Shenzhen University Medical School, Shenzhen University, Shenzhen, 518055, China.
Hui Chen *State Key Laboratory of Chemical Oncogenomics, Tsinghua Shenzhen International Graduate School, Shenzhen, 518055, China.
Li-Ping LiuDepartment of Hepatobiliary and Pancrease Surgery, Shenzhen People's Hospital, Shenzhen, 518020, China.
Yong NiDepartment of Hepatopancreatobiliary Surgery, Shenzhen Second People's Hospital, Shenzhen, 518035, China.
Wei ZhangDepartment of Hepatobiliary and Pancrease Surgery, Shenzhen People's Hospital, Shenzhen, 518020, China.
Lizhen YeState Key Laboratory of Chemical Oncogenomics, Tsinghua Shenzhen International Graduate School, Shenzhen, 518055, China.
Yifei ChenState Key Laboratory of Chemical Oncogenomics, Tsinghua Shenzhen International Graduate School, Shenzhen, 518055, China.
Dandan ZhangGuangdong Provincial Key Laboratory of Chinese Medicine Ingredients and Gut Microbiomics, Institute of Biomedical Health Technology and Engineering, Shenzhen Bay Laboratory, Shenzhen, 518000, China.
Shiqi YangGuangdong Provincial Key Laboratory of Chinese Medicine Ingredients and Gut Microbiomics, Institute of Biomedical Health Technology and Engineering, Shenzhen Bay Laboratory, Shenzhen, 518000, China.
Yu BaiDepartment of Hepatobiliary and Pancrease Surgery, Shenzhen People's Hospital, Shenzhen, 518020, China.
Funian LiuGuangdong Provincial Key Laboratory of Chinese Medicine Ingredients and Gut Microbiomics, Institute of Biomedical Health Technology and Engineering, Shenzhen Bay Laboratory, Shenzhen, 518000, China.
Cailian ZhiGuangdong Provincial Key Laboratory of Chinese Medicine Ingredients and Gut Microbiomics, Institute of Biomedical Health Technology and Engineering, Shenzhen Bay Laboratory, Shenzhen, 518000, China.
Guanghong XuState Key Laboratory of Chemical Oncogenomics, Tsinghua Shenzhen International Graduate School, Shenzhen, 518055, China.
Bo ZhengGuangdong Provincial Key Laboratory of Chinese Medicine Ingredients and Gut Microbiomics, Institute of Biomedical Health Technology and Engineering, Shenzhen Bay Laboratory, Shenzhen, 518000, China.
Songlin LuGuangdong Provincial Key Laboratory of Chinese Medicine Ingredients and Gut Microbiomics, Institute of Biomedical Health Technology and Engineering, Shenzhen Bay Laboratory, Shenzhen, 518000, China.
Cheng QiuState Key Laboratory of Chemical Oncogenomics, Tsinghua Shenzhen International Graduate School, Shenzhen, 518055, China.
Zijian DingState Key Laboratory of Chemical Oncogenomics, Tsinghua Shenzhen International Graduate School, Shenzhen, 518055, China.
Yan ChenSchool of Pharmacy, Shenzhen University Medical School, Shenzhen University, Shenzhen, 518055, China. chenyan@szu.edu.cn.
Yuyang JiangGuangdong Provincial Key Laboratory of Chinese Medicine Ingredients and Gut Microbiomics, Institute of Biomedical Health Technology and Engineering, Shenzhen Bay Laboratory, Shenzhen, 518000, China. jiangyy@sz.tsinghua.edu.cn.

Funding

Development and Reform Commission of Shenzhen Municipality 2019156Startup Fund from Shenzhen Bay Laboratory 21310051
6 · The paper itself

Abstract

backgroundDetecting liver cancer (LC) remains a significant challenge in clinical practice. Small extracellular vesicle (sEV) miRNAs show promise as non-invasive biomarkers for LC detection, yet their diagnostic potential remains largely unexplored. This study aimed to identify specific sEV miRNA signatures for LC detection and develop a novel synchronized multi-miRNA detection platform to enhance diagnostic efficiency and sensitivity.

methodsHigh-throughput sequencing was conducted across four distinct cohorts: normal controls (NC), hepatitis B virus (HBV) patients, liver cirrhosis patients, and LC patients. This sequencing process identified miRNAs with differential expression, followed by RT-qPCR validation in serum sEV miRNAs from LC patients and NC. An innovative detection method, RCA-CRISPR, was introduced, combining rolling circle amplification (RCA) with CRISPR/Cas12a (RCA-CRISPR) for quick and sensitive miRNAs detection.

resultsSequencing results showed a consistent elevation of hsa-miR-203b-5p, hsa-miR-4661-5p, and hsa-miR-219a-2-3p across all cohorts. RT-qPCR validations confirmed significant upregulation of these miRNAs in serum sEVs from LC patients, and the combined three-miRNA panel exhibited high diagnostic accuracy (p = 0.0003; AUC = 0.81). The RCA-CRISPR method demonstrated a detection limit of 3.12 pM for simultaneous multi-target miRNA detection, highlighting its exceptional sensitivity.

conclusionsOur study identifies hsa-miR-203b-5p, hsa-miR-4661-5p, and hsa-miR-219a-2-3p as promising sEV miRNA biomarkers for LC detection. The developed RCA-CRISPR sensor provides a robust tool for multi-miRNA analysis, potentially advancing non-invasive LC diagnostics. Future validation in larger, prospectively collected cohorts is essential to establish the clinical utility and performance of this biomarker panel and RCA-CRISPR sensor.

Indexed as

Biosensing TechniquesClustered Regularly Interspaced Short Palindromic RepeatsCRISPR-Cas SystemsExtracellular VesiclesLiver NeoplasmsMicroRNAsBase SequenceBiomarkers, TumorHumansReproducibility of ResultsBiomarkers, TumorMicroRNAsLiver cancerMulti-target detectionRCA-CRISPR biosensorsEV miRNA biomarker

Identifiers

PMID41508022
PMCPMC12874900

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.