Evidence map›Paper›PMID 37315449›Full record

SynthesisEBioMedicine2023

A comprehensive evaluation of full-spectrum cell-free RNAs highlights cell-free RNA fragments for early-stage hepatocellular carcinoma detection.

Chun Ning, Peng Cai, Xiaofan Liu, Guangtao Li, Pengfei Bao, Lu Yan, Meng Ning, Kaichen Tang, Yi Luo, Hua Guo and 5 more

Abstract readSystematic Review
In one paragraph

Synthesis in EBioMedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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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

15 authors.

Chun NingChinese Academy of Medical Sciences & Peking Union Medical College, No. 9 Dongdansantiao, Beijing, 100730, China; MOE Key Laboratory of Bioinformatics, Centre for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Peng CaiDepartment of Epidemiology, Naval Medical University, Key Laboratory of Biosafety Defense, Ministry of Education, Shanghai, 200433, China.
Xiaofan LiuMOE Key Laboratory of Bioinformatics, Centre for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Guangtao LiDepartment of Hepatobiliary Cancer, Liver Cancer Research Centre, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Centre for Cancer, Tianjin, 300060, China.
Pengfei BaoMOE Key Laboratory of Bioinformatics, Centre for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Lu YanMOE Key Laboratory of Bioinformatics, Centre for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Meng NingTianjin Third Central Hospital, 83 Jintang Road, Hedong District, Tianjin, 300170, China.
Kaichen TangChinese Academy of Medical Sciences & Peking Union Medical College, No. 9 Dongdansantiao, Beijing, 100730, China; MOE Key Laboratory of Bioinformatics, Centre for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Yi LuoDepartment of Hepatobiliary Cancer, Liver Cancer Research Centre, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Centre for Cancer, Tianjin, 300060, China.
Hua GuoDepartment of Hepatobiliary Cancer, Liver Cancer Research Centre, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Centre for Cancer, Tianjin, 300060, China.
Yunjiu WangDepartment of Clinical Laboratory, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 200433, China.
Zhuoran WangDepartment of Surgery, Eastern Hepatobiliary Surgery Hospital, Navy Medical University, Shanghai, 200433, China.
Lu ChenDepartment of Hepatobiliary Cancer, Liver Cancer Research Centre, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Centre for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Centre for Cancer, Tianjin, 300060, China. Electronic address: chenlu@tmu.edu.cn.
Zhi John LuMOE Key Laboratory of Bioinformatics, Centre for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, 100084, China. Electronic address: zhilu@tsinghua.edu.cn.
Jianhua YinDepartment of Epidemiology, Naval Medical University, Key Laboratory of Biosafety Defense, Ministry of Education, Shanghai, 200433, China. Electronic address: hawkyjh163@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVarious studies have reported cell-free RNAs (cfRNAs) as noninvasive biomarkers for detecting hepatocellular carcinoma (HCC). However, they have not been independently validated, and some results are contradictory. We provided a comprehensive evaluation of various types of cfRNA biomarkers and a full mining of the biomarker potential of new features of cfRNA.

methodsWe first systematically reviewed reported cfRNA biomarkers and calculated dysregulated post-transcriptional events and cfRNA fragments. In 3 independent multicentre cohorts, we further selected 6 cfRNAs using RT-qPCR, built a panel called HCCMDP with AFP using machine learning, and internally and externally validated HCCMDP's performance.

findingsWe identified 23 cfRNA biomarker candidates from a systematic review and analysis of 5 cfRNA-seq datasets. Notably, we defined the cfRNA domain to describe cfRNA fragments systematically. In the verification cohort (n = 183), cfRNA fragments were more likely to be verified, while circRNA and chimeric RNA candidates were neither abundant nor stable as qPCR-based biomarkers. In the algorithm development cohort (n = 287), we build and test the panel HCCMDP with 6 cfRNA markers and AFP. In the independent validation cohort (n = 171), HCCMDP can distinguish HCC patients from control groups (all: AUC = 0.925; CHB: AUC = 0.909; LC: AUC = 0.916), and performs well in distinguishing early-stage HCC patients (all: AUC = 0.936; CHB: AUC = 0.917; LC: AUC = 0.928).

interpretationThis study comprehensively evaluated full-spectrum cfRNA biomarker types for HCC detection, highlighted the cfRNA fragment as a promising biomarker type in HCC detection, and provided a panel HCCMDP.

fundingNational Natural Science Foundation of China, and The National Key Basic Research Program (973 program).

Indexed as

Carcinoma, HepatocellularCell-Free Nucleic AcidsLiver NeoplasmsMicroRNAsalpha-FetoproteinsBiomarkers, TumorHumansROC Curvealpha-FetoproteinsBiomarkers, TumorCell-Free Nucleic AcidsMicroRNAscfRNA biomarkerEarly cancer detectionLiquid biopsyLiver neoplasms

Identifiers

PMID37315449
PMCPMC10363443

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.