Evidence map›Paper›PMID 35685428›Full record

ArticleJournal of oncology2022

Identification of Prognostic Biomarkers of Glioblastoma Based on Multidatabase Integration and Its Correlation with Immune-Infiltration Cells.

Wencong Ding, Xian Zhou, Guoqiang Jiang, Weiwei Xu, Songkai Long, Fan Xiao, Yongshi Liao, Jia Liu

Open access · hybridAbstract read
In one paragraph

Article in Journal of oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.6field-weighted citation impact, top 32% 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

7 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Advancing glioblastoma therapy with surface-modified nanoparticles.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
    Review
  5. Article
  6. Article
  7. 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 1 institution in 1 country.

Wencong Ding *Department of Neurosurgery, the Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang 421002, Hunan, China.ORCID https://orcid.org/0000-0002-7840-2275
Xian Zhou *Department of Hepatobiliary Surgery, the Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang 421002, Hunan, China.
Guoqiang JiangDepartment of Clinical Laboratory, The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang 421002, Hunan, China.ORCID https://orcid.org/0000-0003-0859-1661
Weiwei XuDepartment of Neurosurgery, the Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang 421002, Hunan, China.
Songkai LongDepartment of Anesthesiology, Affiliated Nanhua Hospital, University of South China, Hengyang 421001, Hunan, China.ORCID https://orcid.org/0000-0003-4479-8272
Fan XiaoClinical Research Institute, Hunan Provincial Clinical Research Center for Metabolic Associated Fatty Liver Disease, the Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang 421002, Hunan, China.
Yongshi LiaoDepartment of Neurosurgery, the Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang 421002, Hunan, China.ORCID https://orcid.org/0000-0002-7252-7675
Jia LiuClinical Research Institute, Hunan Provincial Clinical Research Center for Metabolic Associated Fatty Liver Disease, the Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang 421002, Hunan, China.ORCID https://orcid.org/0000-0002-1021-9271
University of South China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Glioblastoma (GBM) is the most malignant of all known intracranial tumors; meanwhile, most patients have a poor prognosis. In order to improve the poor prognosis of GBM patients as much as possible, it is specifically significant to identify biomarkers related to the gene diagnosis and gene therapy. Methods: In this study, a total of 343 GBM specimens and 259 nontumor specimens were collected from four Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) database; then, we analyzed the differentially expressed genes (DEGs) from the above data. Through Venn diagram analysis, 54 common upregulated DEGs and 22 common downregulated DEGs were triumphantly recognized. Results: On the basis of the degree of formation communication in protein-protein interaction network (PPIN), the 10 upregulated central genes were ranked, incorporating LOX, IGFBP3, CD44, TIMP1, FN1, VEGFA, POSTN, COL1A1, COL1A2, and COL3A1. By combining the expression levels and the clinical features of GBM, we found that four hub genes (TIMP1, FN1, POSTN, and LOX) were significantly upregulated and related to poor prognosis of GBM. Meanwhile, univariate and multivariate Cox regression analysis suggested that TIMP1 could be one of the independent prognostic factors for GBM patients. Furthermore, TIMP1 was particularly correlated with the immune marker of macrophage M1, macrophage M2, neutrophils, tumor-associated macrophage, and Tregs. We then analyzed the role of TIMP1 in GBM cancer cell lines by relevant experiments, which indicated that TIMP1 knockdown resulted in the decreased cell proliferation, migration, and invasion. Conclusions: Taken together, these findings demonstrated that TIMP1 might be a new biomarker to determine prognosis and immune infiltration of GBM patients.

Identifiers

PMID35685428
PMCPMC9174005
OpenAlexW4281801776

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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.