Evidence map›Paper›PMID 38221614›Full record

ArticleBMC gastroenterology2024

Identification of a vascular invasion-related signature based on lncRNA pairs for predicting prognosis in hepatocellular carcinoma.

Nan Zhao, Chunsheng Ni, Danfang Zhang, Na Che, Yanlei Li, Xiao Wang

Open access · goldAbstract read
In one paragraph

Article in BMC gastroenterology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 45% of its field
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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

6 authors at 2 institutions in 1 country.

Nan Zhao *Department of Pathology, Tianjin Medical University, No.22 Qixiangtai Road, Heping District, Tianjin, 300070, China. zhaonantj@tmu.edu.cn.
Chunsheng Ni *Department of Pathology, Tianjin Medical University, No.22 Qixiangtai Road, Heping District, Tianjin, 300070, China.
Danfang ZhangDepartment of Pathology, Tianjin Medical University, No.22 Qixiangtai Road, Heping District, Tianjin, 300070, China.
Na CheDepartment of Pathology, Tianjin Medical University, No.22 Qixiangtai Road, Heping District, Tianjin, 300070, China.
Yanlei LiDepartment of Pathology, Tianjin Medical University, No.22 Qixiangtai Road, Heping District, Tianjin, 300070, China.
Xiao WangDepartment of Pathology, Tianjin Medical University, No.22 Qixiangtai Road, Heping District, Tianjin, 300070, China.
Tianjin Medical University General Hospital · CNTianjin Medical University · CN

Funding

Beijing,Tianjin and Hebei basic research cooperation project No. 20JCZXJC00160Nature Science Foundation of Tianjin 19JCYBJC25800
6 · The paper itself

Abstract

objectivesMost signatures are constructed on the basis of RNA or protein expression levels. The value of vascular invasion-related signatures based on lncRNA pairs, regardless of their specific expression level in hepatocellular carcinoma (HCC), is not yet clear.

methodsVascular invasion-related differentially expressed lncRNA (DElncRNA) pairs were identified with a two-lncRNA combination strategy by using a novel modeling algorithm. Based on the optimal cutoff value of the ROC curve, patients with HCC were classified into high- and low-risk subgroups. We used KM survival analysis to evaluate the overall survival rate of patients in the high- and low-risk subgroups. The independent indicators of survival were identified using univariate and multivariate Cox analyses.

resultsFive pairs of vascular invasion-related DElncRNAs were selected to develop a predictive model for HCC. High-risk subgroups were closely associated with aggressive clinicopathological characteristics and genes, chemotherapeutic sensitivity, and highly expressed immune checkpoint inhibitors.

conclusionsWe identified a signature composed of 5 pairs of vascular invasion-related lncRNAs that does not require absolute expression levels of lncRNAs and shows promising clinical predictive value for HCC prognosis. This predictive model provides deep insight into the value of vascular invasion-related lncRNAs in prognosis.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsRNA, Long NoncodingAlgorithmsHumansPrognosisRNA, Long NoncodingHCClncRNA pairsPrognosisVascular invasion

Identifiers

PMID38221614
PMCPMC10788995
OpenAlexW4390863766

What OpenQuestion holds

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LicenceCC BY
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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.