Evidence map›Paper›PMID 30320360›Full record

ArticleOncology reports2019

GLIS2 redundancy causes chemoresistance and poor prognosis of gastric cancer based on co‑expression network analysis.

Jingsheng Yuan, Lulu Tan, Zhijie Yin, Kaixiong Tao, Guobing Wang, Wenjia Shi, Jinbo Gao

Open access · hybridAbstract read
In one paragraph

Article in Oncology 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
1.1field-weighted citation impact, top 20% 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

11 citing papers in PubMed, 19 citations in OpenAlex.

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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

7 authors at 2 institutions in 1 country.

Jingsheng YuanDepartment of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China.
Lulu TanDepartment of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China.
Zhijie YinDepartment of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China.
Kaixiong TaoDepartment of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China.
Guobing WangDepartment of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China.
Wenjia ShiDepartment of Paediatric Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China.
Jinbo GaoDepartment of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China.
Huazhong University of Science and Technology · CNUnion Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastric cancer is currently the fourth most common cancer and the third leading cause of cancer‑associated mortality worldwide. Studies have identified that certain biomarkers contribute to the prognosis, diagnosis and treatment of gastric cancer. However, the biomarkers of gastric cancer are rarely used clinically. Therefore, it is imperative to define novel molecular networks and key genes to guide the further study and clinical treatment of gastric cancer. In the present study, raw RNA sequencing data and clinicopathological information on patients with gastric cancer were downloaded from The Cancer Genome Atlas, and a weighted gene co‑expression network analysis was conducted. Additionally, functional enrichment and protein‑protein interaction analyses were implemented to further examine the significant modules. As a result, 16 modules of highly correlated genes were acquired and colour coded, and the yellow module containing 174 genes associated with chemotherapy resistance and prognosis in gastric cancer was further analysed. The biological processes of the yellow module were primarily associated with cell adhesion, vasculature development and the regulation of cell proliferation. In addition, the Kyoto Encyclopedia of Genes and Genomes pathways primarily involved the transforming growth factor‑β signalling pathway, the cellular tumour antigen p53 signalling pathway, extracellular matrix‑receptor interactions and focal adhesions. Notably, survival analysis and cell verification confirmed that high expression of GLIS family zinc finger 2 is significantly associated with chemoresistance and a worse prognosis in gastric cancer, and that this high expression is likely to be an important biomarker for the guidance of clinical treatment and prognostic evaluation.

Indexed as

Drug Resistance, NeoplasmCell Line, TumorFemaleGene Expression ProfilingGene Regulatory NetworksHumansKruppel-Like Transcription FactorsMaleOligonucleotide Array Sequence AnalysisPrognosisSequence Analysis, RNAStomach NeoplasmsSurvival AnalysisGLIS2 protein, humanKruppel-Like Transcription Factors

Identifiers

PMID30320360
PMCPMC6278374
OpenAlexW2896407843

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.