Evidence map›Paper›PMID 34790398›Full record

ArticleJournal of gastrointestinal oncology2021

Identification of heterogeneous nuclear ribonucleoprotein as a candidate biomarker for diagnosis and prognosis of hepatocellular carcinoma.

Youli Du, Xiaoou Ma, Dongxu Wang, Yuguang Wang, Tianyu Zhang, Lianjie Bai, Yunlong Liu, Shaosen Chen

Open access · diamondAbstract read
In one paragraph

Article in Journal of gastrointestinal oncology, 2021. 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
0.1field-weighted citation impact, top 47% 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, 2 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

8 authors at 1 institution in 1 country.

Youli DuDepartment of Interventional Medicine, The Second Affiliated Hospital of Qiqihar Medical College, Qiqihar, China.
Xiaoou MaDepartment of Interventional Medicine, The Second Affiliated Hospital of Qiqihar Medical College, Qiqihar, China.
Dongxu WangCT Room of the Second Affiliated Hospital of Qiqihar Medical College, Qiqihar, China.
Yuguang WangCT Room of the Second Affiliated Hospital of Qiqihar Medical College, Qiqihar, China.
Tianyu ZhangCT Room of the Second Affiliated Hospital of Qiqihar Medical College, Qiqihar, China.
Lianjie BaiThe Ultrasound Department of the Second Affiliated Hospital of Qiqihar Medical College, Qiqihar, China.
Yunlong LiuDepartment of Oncology, the Second Affiliated Hospital of Qiqihar Medical College, Qiqihar, China.
Shaosen ChenDepartment of Oncology, the Second Affiliated Hospital of Qiqihar Medical College, Qiqihar, China.
Qiqihar Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatocellular carcinoma (HCC) is the most common type of liver cancer with a high mortality rate. However, spliceosomal genes are still lacking in the diagnosis and prognosis of HCC.

methodsIdentification of differentially expressed genes (DEGs) was performed using the limma package in R software. Modules highly related to HCC were obtained by weighted gene co-expression network analysis (WGCNA), and the module genes were analyzed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. The biomarker for diagnosing HCC was determined by receiver operating characteristic (ROC) curve analysis, and the effect of the biomarker in the diagnosis of HCC was evaluated by performing five-fold cross-validation with logistic regression. HCC specimens from preoperatively treated patients were tested for biomarker by real-time quantitative polymerase chain reaction (RT-qPCR). Kaplan-Meier analysis was used to assess the relationship between biomarker and patient survival. The role of biomarker was evaluated using ESTIMATE analysis in the tumor microenvironment.

resultsIn this study, 389 DEGs were screened out from three Gene Expression Omnibus (GEO) datasets. We also found that the turquoise module of 123 genes from The Cancer Genome Atlas (TCGA) data was the key module with the highest correlation with HCC traits. Then, 123 genes were analyzed using the KEGG enrichment pathway, and eight genes were found to be most significantly related to the spliceosome pathway. We selected 8 genes and 389 DEGs shared genes, and finally got the only gene, heterogeneous nuclear ribonucleoprotein (hnRNPU). The high expression of hnRNPU was associated with poor prognosis of HCC, and hnRNPU was a biomarker for diagnosing HCC. In the tissues of patients with excellent HCC treatment hnRNPU messenger RNA (mRNA) was lower than in the tissues of patients with poor HCC treatment. High expression of hnRNPU was significantly increased in HCC patients with low stromal (P<0.05), low immune (P<0.05), and low estimation scores (P<0.05), and with high tumor purity (P<0.05) and high malignant progression (P<0.05) of the HCC.

conclusionsThe hnRNPU gene identified in this study may become a new biomarker for the diagnosis and prognosis of HCC.

Indexed as

Hepatocellular carcinoma (HCC)heterogeneous nuclear ribonucleoprotein (hnRNPU)molecular biomarker

Identifiers

PMID34790398
PMCPMC8576204
OpenAlexW3201162318

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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.