Evidence map›Paper›PMID 30720105›Full record

ArticleMolecular medicine reports2019

Prediction and analysis of weighted genes in hepatocellular carcinoma using bioinformatics analysis.

Qifan Zhang, Shibo Sun, Chen Zhu, Yujian Zheng, Qing Cai, Xiaolu Liang, Haorong Xie, Jie Zhou

Abstract read
In one paragraph

Article in Molecular medicine reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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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

11 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

8 authors.

Qifan ZhangDepartment of Hepatobiliary Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China.
Shibo SunDepartment of Hepatobiliary Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China.
Chen ZhuDepartment of Anesthesia, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China.
Yujian ZhengDepartment of Hepatobiliary Surgery and Liver Transplantation Center, Guangzhou General Hospital of Guangzhou Military Area, Guangzhou, Guangdong 510515, P.R. China.
Qing CaiDepartment of Hepatobiliary Surgery and Liver Transplantation Center, Guangzhou General Hospital of Guangzhou Military Area, Guangzhou, Guangdong 510515, P.R. China.
Xiaolu LiangDepartment of Hepatobiliary Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China.
Haorong XieDepartment of Hepatobiliary Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China.
Jie ZhouDepartment of Hepatobiliary Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of the present study was to identify the differentially expressed genes (DEGs) between primary tumor tissue and adjacent non‑tumor tissue of hepatocellular carcinoma (HCC) samples in order to investigate the mechanisms of HCC. The microarray data of the datasets GSE76427, GSE84005 and GSE57957 were downloaded from the Gene Expression Omnibus database. DEGs were identified using the limma package in the R programming language. Following the intersection of the DEGs screened from the three datasets, 218 genes were selected for further study. A protein‑protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes database. The construction and analysis of modules were performed using Cytoscape and the module with the highest score was selected for further analysis. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were conducted for genes involved in the PPI network and the selected subnetwork. The network of the enriched pathways and their associated genes was constructed using Cytoscape. For the genes in the global PPI network, metabolism‑associated pathways were significantly enriched; whereas, for the genes in the subnetwork, 'cell cycle', 'oocyte meiosis' and 'DNA replication' pathways were significantly enriched. To demonstrate the portability and repeatability of the prognostic value of the weighted genes, a validation cohort was obtained from datasets of The Cancer Genome Atlas and Kaplan‑Meier survival analysis was conducted. Evidence is presented that the expression levels of aldehyde dehydrogenase 2 family member, cytochrome P450 family 2 subfamily C member 8, alcohol dehydrogenase 4 (class II), pi polypeptide, alcohol dehydrogenase 1B (class I), β polypeptide and cytochrome P450 family 2 subfamily C member 9 were associated with the overall survival of patients with HCC and that the expression levels of pituitary tumor‑transforming 1, cell division cycle 20, DNA topoisomerase II α and cyclin B2 were negatively associated with the overall survival of patients with HCC. In conclusion, 9 weighted genes, involved in the development and progression of HCC, were identified using bioinformatics and survival analyses.

Indexed as

Computational BiologyGene Expression ProfilingTranscriptomeCarcinoma, HepatocellularGene Expression Regulation, NeoplasticGene OntologyGene Regulatory NetworksHumansKaplan-Meier EstimateLiver NeoplasmsPrognosisProtein Interaction MappingProtein Interaction Maps

Identifiers

PMID30720105
PMCPMC6423588

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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.