Evidence map›Paper›PMID 36660425›Full record

ArticleFrontiers in molecular biosciences2022

An integrated analysis of prognostic mRNA signature in early- and progressive-stage gastric adenocarcinoma.

Xiaoling Hong, Kai Zhuang, Na Xu, Jiang Wang, Yong Liu, Siqi Tang, Junzhang Zhao, Zunnan Huang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2022. 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
0.7field-weighted citation impact, top 25% 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

8 authors at 2 institutions in 1 country.

Xiaoling HongThe First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan, China.
Kai ZhuangKey Laboratory of Big Data Mining and Precision Drug Design, Guangdong Medical University, Dongguan, China.
Na XuKey Laboratory of Big Data Mining and Precision Drug Design, Guangdong Medical University, Dongguan, China.
Jiang WangSchool of Biomedical Engineering, Guangdong Medical University, Zhanjiang, China.
Yong LiuKey Laboratory of Big Data Mining and Precision Drug Design, Guangdong Medical University, Dongguan, China.
Siqi TangKey Laboratory of Big Data Mining and Precision Drug Design, Guangdong Medical University, Dongguan, China.
Junzhang ZhaoDepartment of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangdong, Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, National Key Clinical Discipline, Guangzhou, China.
Zunnan HuangThe First Dongguan Affiliated Hospital, Guangdong Medical University, Dongguan, China.
Guangdong Medical College · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pathogenesis and vital factors of early and progressive stages of stomach adenocarcinoma (STAD) have not been fully elucidated. In order to discover novel and potential targets to guide effective treatment strategies, a comprehensive bioinformatics study was performed, and the representative results were then validated by quantitative polymerase chain reaction (qPCR) and immunohistochemical (IMC) staining in clinical samples. A total of 4,627, 4,715, and 3,465 differentially expressed genes (DEGs) from overall-, early-, and progressive-stage STAD were identified, respectively. Prognostic models of 5-year OS were established for overall-, early-, and progressive-stage STAD, and ROC curves demonstrated AUC values for each model were 0.73, 0.87, and 0.92, respectively. Function analysis revealed that mRNAs of early-stage STAD were enriched in chemical stimulus-related pathways, whereas remarkable enrichment of mRNAs in progressive-stage STAD mainly lay in immune-related pathways. Both qPCR and IHC data confirmed the up-regulation of IGFBP1 in the early-stage and CHAF1A in progressive-stage STAD compared with their matched normal tissues, indicating that these two representative targets could be used to predict the prognostic status of the patients in these two distinct STAD stages, respectively. In addition, seven mRNAs (F2, GRID2, TF, APOB, KIF18B, INCENP, and GCG) could be potential novel biomarkers for STAD at different stages from this study. These results contributed to identifying STAD patients at high-risk, thus guiding targeted treatment with efficacy in these patients.

Indexed as

diagnosismRNAnovel biomarkersprognostic modelSTAD

Identifiers

PMID36660425
PMCPMC9846543
OpenAlexW4313585499

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.