Evidence map›Paper›PMID 34539726›Full record

ArticleFrontiers in genetics2021

Identification of Key Genes Associated With the Process of Hepatitis B Inflammation and Cancer Transformation by Integrated Bioinformatics Analysis.

Jingyuan Zhang, Xinkui Liu, Wei Zhou, Shan Lu, Chao Wu, Zhishan Wu, Runping Liu, Xiaojiaoyang Li, Jiarui Wu, Yingying Liu and 4 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2021. 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
2.2field-weighted citation impact, top 11% 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

15 citing papers in PubMed, 22 citations in OpenAlex.

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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

14 authors at 1 institution in 1 country.

Jingyuan ZhangSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Xinkui LiuSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Wei ZhouSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Shan LuSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Chao WuSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Zhishan WuSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Runping LiuSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Xiaojiaoyang LiSchool of Life Sciences, Beijing University of Chinese Medicine, Beijing, China.
Jiarui WuSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Yingying LiuSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Siyu GuoSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Shanshan JiaSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Xiaomeng ZhangSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Miaomiao WangSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Beijing University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatocellular carcinoma (HCC) has become the main cause of cancer death worldwide. More than half of hepatocellular carcinoma developed from hepatitis B virus infection (HBV). The purpose of this study is to find the key genes in the transformation process of liver inflammation and cancer and to inhibit the development of chronic inflammation and the transformation from disease to cancer.

methodsTwo groups of GEO data (including normal/HBV and HBV/HBV-HCC) were selected for differential expression analysis. The differential expression genes of HBV-HCC in TCGA were verified to coincide with the above genes to obtain overlapping genes. Then, functional enrichment analysis, modular analysis, and survival analysis were carried out on the key genes.

resultsWe identified nine central genes (CDK1, MAD2L1, CCNA2, PTTG1, NEK2) that may be closely related to the transformation of hepatitis B. The survival and prognosis gene markers composed of PTTG1, MAD2L1, RRM2, TPX2, CDK1, NEK2, DEPDC1, and ZWINT were constructed, which performed well in predicting the overall survival rate.

conclusionThe findings of this study have certain guiding significance for further research on the transformation of hepatitis B inflammatory cancer, inhibition of chronic inflammation, and molecular targeted therapy of cancer.

Indexed as

bioinformaticsbiomarkersdifferentially expressed geneshepatitis Bhepatocellular carcinomainflammation and cancer transformationsurvival rate

Identifiers

PMID34539726
PMCPMC8440810
OpenAlexW3196645117

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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.