Evidence map›Paper›PMID 34157940›Full record

ArticleBioengineered2021

Constructing a new prognostic signature of gastric cancer based on multiple data sets.

Liqiang Zhou, Hao Lu, Fei Zeng, Qi Zhou, Shihao Li, You Wu, Yiwu Yuan, Lin Xin

Abstract read
In one paragraph

Article in Bioengineered, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Trial
  2. Article
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  4. CMTM4 inhibits gastric tumorigenesis and metastasis.Journal of gastrointestinal oncology · 2024
    Article
  5. Article
  6. Article
  7. Article
  8. Article
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  12. A prognostic gene signature for gastric cancer and the immune infiltration-associated mechanism underlying the signature gene, PLG.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023
    Article
  13. Review
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  15. 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

8 authors.

Liqiang ZhouDepartment of General Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, P.R China.ORCID 0000-0002-3713-258X
Hao LuDepartment of General Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, P.R China.
Fei ZengDepartment of General Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, P.R China.
Qi ZhouDepartment of General Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, P.R China.
Shihao LiDepartment of General Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, P.R China.
You WuDepartment of General Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, P.R China.
Yiwu YuanDepartment of General Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, P.R China.
Lin XinDepartment of General Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, P.R China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to explore new prediction methods and key genes for gastric cancer. Firstly, we downloaded the 6 original sequencing data of gastric cancer on the Illumina HumanHT-12 platform from Array Expression and Gene Expression Omnibus, and used bioinformatics methods to identify 109 up-regulated genes and 271 down-regulated genes. Further, we performed univariate Cox regression analysis of prognostic-related genes, then used Lasso regression to remove collinearity, and finally used multivariate Cox regression to analyze independent prognostic genes (MT1M, AKR1C2, HEYL, KLK11, EEF1A2, MMP7, THBS1, KRT17, RPESP, CMTM4, UGT2B17, CGNL1, TNFRSF17, REG1A). Based on these, we constructed a prognostic risk proportion signature, and found that patients with high-risk gastric cancer have a high degree of malignancy. Subsequently, we used the GSE15459 data set to verify the signature. By calculating the area under the recipient operator characteristic curve of 5-year survival rate, the test set and verification set are 0.739 and 0.681, respectively, suggesting that the prognostic signature has a moderate prognostic ability. The nomogram is used to visualize the prognostic sig-nature, and the calibration curve verification showed that the prediction accuracy is higher. Finally, we verified the expression and prognosis of the hub gene, and suggested that HEYL, MMP7, THBS1, and KRT17 may be potential prognostic biomarkers.

Indexed as

NomogramsStomach NeoplasmsBiomarkers, TumorComputational BiologyDatabases, GeneticHumansTranscriptomeBiomarkers, TumorbioinformaticsGastric cancernomogramprognostic signature

Identifiers

PMID34157940
PMCPMC8806649

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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.