Evidence map›Paper›PMID 33133165›Full record

ArticleFrontiers in genetics2020

Exploration of Sorafenib Influences on Gene Expression of Hepatocellular Carcinoma.

Huancheng Wang, Jia Liu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2020. 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 51% 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, 3 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

2 authors at 1 institution in 1 country.

Huancheng WangFirst Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Jia LiuFirst Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China.
First Teaching Hospital of Tianjin University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aim of this study was to develop a comprehensive differential gene profile for hepatocellular carcinoma (HCC) patients treated with sorafenib.

methodsThe RNA sequencing data and miRNA sequencing data of 114 HCC patients treated with sorafenib only and 326 HCC control patients treated without any chemotherapeutic drugs were studied using differential expression, functional enrichment, and protein-protein interaction analysis.

resultsCompared with HCC patients without any chemotherapy drugs, the sorafenib-treated patients develop 66 differentially expressed genes (DEGs), including 12 upregulated genes and 54 downregulated genes. Additionally, three differentially expressed miRNAs (DEMs) also show specific expression pattern. With further analysis, five primary genes including HTR2C, TRH, AGTR2, MCHR2, and SLC6A2 as well as three miRNAs (hsa-miR-4445, hsa-miR-466, and hsa-miR-2114) have been suggested as the potential targets for sorafenib. The specific gene expression of five genes has been validated in clinical HCC patients by ELISA method. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses indicate several significantly enriched biological processes (BPs), cellular components (CCs), and molecular functions (MFs).

conclusionSince sorafenib is becoming increasingly important in HCC treatment clinically, this study will help us understand the potential targets and eliminate diverse existing side effects of it as well as explore several potential clinical biomarkers with comprehensive analysis of differential gene expression profile.

Indexed as

GO and KEGG functional enrichmenthepatocellar carcinomahepatocellular carcinomaprotein–protein interaction analysissorafenib

Identifiers

PMID33133165
PMCPMC7578401
OpenAlexW3092364994

What OpenQuestion holds

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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.