Evidence map›Paper›PMID 32631357›Full record

ArticleJournal of translational medicine2020

A novel signature based on microvascular invasion predicts the recurrence of HCC.

Binbin Du, Fang Wang, Beers Jarad, Zhihui Wang, Yanzhou Zhang

Abstract read
In one paragraph

Article in Journal of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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  8. [Research progress of radiomics in the evaluation of microvascular invasion in hepatocellular carcinoma].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2023
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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

5 authors.

Binbin DuDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Fang WangDepartment of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Beers JaradThomas Jefferson University, Philadelphia, PA, USA.
Zhihui WangDepartment of Liver and Gall, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Yanzhou ZhangDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China. yanzhouzhang8619@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesIn hepatocellular carcinoma (HCC) patients, microvascular invasion (MVI) is associated with worse outcomes regardless of treatment. No single reliable preoperative factor exists to predict MVI. The aim of the work described here was to develop a new MVI- based mRNA biomarker to differentiate between high and low risk patients.

methodsUsing The Cancer Genome Atlas (TCGA) database, we collected data from 315 HCC patients, including mRNA expression and complete clinical data. We generated a seven-mRNA signature to predict patient outcomes. The mRNA signature was validated using the GSE36376 cohort. Finally, we tested the formula in our own 53 HCC patients using qPCR for the seven mRNAs and analyzing the computed tomography (CT) features.

resultsThis seven-mRNA signature significantly correlated with length of recurrence-free survival (RFS) and overall survival (OS) for both the training and validation groups. RFS and OS were briefer in high risk versus low risk patients. A Kaplan-Meier analysis also indicated that survival time was significantly shortened in the high risk group versus the low risk group. Time-dependent receiver operating characteristic analysis demonstrated good predictive performance for the seven-mRNA signature. The mRNA signature also acts as an independent factor according to a Multivariate analysis. Our results are consistent with the seven-mRNA formula risk score.

conclusionOur research showed a novel seven-mRNA biomarker based on MVI predicting RFS and OS in HCC patients. This mRNA signature can stratify patients into subgroups based on their risk of recurrence to help guide individualized treatment and precision management in HCC.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsHumansNeoplasm Recurrence, LocalPrognosisRetrospective StudiesMicrovascular invasionmRNASignature hepatocellular carcinoma

Identifiers

PMID32631357
PMCPMC7336478

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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.