Evidence map›Paper›PMID 36661663›Full record

ArticleCurrent oncology (Toronto, Ont.)2022

Identification of a Two-Gene Signature and Establishment of a Prognostic Nomogram Predicting Overall Survival in Diffuse-Type Gastric Cancer.

Songyao Chen, Jiannan Xu, Songcheng Yin, Huabin Wang, Guangyao Liu, Xinghan Jin, Junchang Zhang, Huijin Wang, Han Wang, Huan Li and 3 more

Abstract read
In one paragraph

Article in Current oncology (Toronto, Ont.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

2 citing papers in PubMed.

  1. Article
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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

13 authors.

Songyao ChenDigestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.ORCID 0000-0002-7474-9845
Jiannan XuDepartment of Thoracic Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China.
Songcheng YinDigestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.
Huabin WangDivision of Hematology/Oncology, Department of Pediatrics, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.
Guangyao LiuDigestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.
Xinghan JinDigestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.
Junchang ZhangDigestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.
Huijin WangDigestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.
Han WangDigestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.
Huan LiDigestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.
Jianming LiangDigestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.
Yulong HeDigestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.
Changhua ZhangDigestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.ORCID 0000-0003-4358-4096

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt is widely acknowledged that the molecular biological characteristics of diffuse-type gastric cancer are different from intestinal-type gastric cancer. Notwithstanding that significant progress in high-throughput sequencing technology has been made, there is a paucity of effective prognostic biomarkers for diffuse gastric cancer for clinical practice.

methodsWe downloaded four GEO datasets (GSE22377, GSE38749, GSE47007 and GSE62254) to establish and validate a prognostic two-gene signature for diffuse gastric cancer. The TGCA-STAD dataset was used for external validation. The optimal gene signature was established by using Cox regression analysis. Receiver operating characteristic (ROC) methodology was used to find the best prognostic model. Gene set enrichment analysis was used to analyze the possible signaling pathways of the two genes (MEF2C and TRIM15).

resultsA total of four differently expressed genes (DEGs) (two upregulated and two downregulated) were identified. After a comprehensive analysis, two DEGs (MEF2C and TRIM15) were utilized to construct a prognostic model. A prognostic prediction model was constructed according to T stage, N stage, M stage and the expression of MEF2C and TRIM15. The area under the time-dependent receiver operator characteristic was used to evaluate the performance of the prognosis model in the GSE62254 dataset.

conclusionsWe demonstrated that MEF2C and TRIM15 might be key genes. We also established a prognostic nomogram based on the two-gene signature that yielded a good performance for predicting overall survival in diffuse-type gastric cancer.

Indexed as

NomogramsStomach NeoplasmsHigh-Throughput Nucleotide SequencingHumansPrognosisdiffuse-type gastric cancergene signaturenomogramprognosis

Identifiers

PMID36661663
PMCPMC9857582

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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.