Evidence map›Paper›PMID 36353126›Full record

ArticleFrontiers in neurology2022

MELK is a prognostic biomarker and correlated with immune infiltration in glioma.

Haiyan Yang, Huandi Zhou, Guohui Wang, Lei Tian, Haonan Li, Yufeng Zhang, Xiaoying Xue

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurology, 2022. 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 23% 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, 13 citations in OpenAlex.

  1. Article
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  4. Targeting MELK in tumor cells and tumor microenvironment: from function and mechanism to therapeutic application.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
    Review
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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.

Haiyan YangDepartment of Pathology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Huandi ZhouDepartment of Radiotherapy, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Guohui WangDepartment of Radiotherapy, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Lei TianDepartment of Radiotherapy, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Haonan LiDepartment of Radiotherapy, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Yufeng ZhangDepartment of Radiotherapy, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Xiaoying XueDepartment of Radiotherapy, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Second Hospital of Hebei Medical University · CNHebei Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Glioma accounts for the vast majority of primary brain tumors with inevitable recurrence and poor prognosis. Maternal embryonic leucine zipper kinase (MELK) is overexpressed in multiple human tumors and could activate a variety of oncogenic-associated signal pathways. However, its role in the glioma microenvironment is still largely unknown. Methods: We collected the RNA sequence data and clinical information of gliomas from the Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) databases, and investigated MELK expression and its correlation with clinicopathologic features and prognosis in glioma. Moreover, the relationship between MELK expression and immune cell infiltration in the tumor microenvironment of gliomas was explored through single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT. In addition, gene set enrichment analysis (GSEA) and Metascape online analysis were performed to find out signaling pathways enriched by differentially expressed genes (DEGs) between high- and low-MELK expression groups. Finally, immunohistochemistry was performed to validate our findings. Results: Data analysis of CGGA and GEO datasets showed that MELK was significantly upregulated in gliomas than in normal brain tissues, and MELK expression was obviously correlated with clinicopathologic features, including age, WHO grade, histological subtype, IDH mutant status, 1p19q codeletion status, and PRS type. Stratified analysis, Cox regression analysis, and nomogram model revealed that high expression of MELK predicted poor survival; hence, MELK could serve as an independent prognostic biomarker for glioma. Moreover, results from enrichment pathway analysis indicated that the immune system process, angiogenesis, apoptosis, cell cycle, and other oncogenic-related signal pathways were significantly enriched between high- and low-MELK expression groups. Immune infiltration analysis demonstrated that increased MELK expression was significantly correlated with higher immune scores, higher fractions of immunocytes (T cells, NK cells resting, macrophages, resting mast cells, and neutrophils), and higher expression levels of immune checkpoints (B7-H3, CTLA4, LAG3, PD-1, PD-L1, and TIM3). Finally, immunohistochemistry analysis validated our findings that high expression of MELK relates to increased malignancy and poor prognosis of glioma. Conclusion: Our findings identified that MELK could act as an independent prognostic indicator and potential immunotherapy target for glioma. In conclusion, these findings suggested that DDOST mediated the immunosuppressive microenvironment of gliomas and could be an important biomarker in diagnosing and treating gliomas.

Indexed as

gliomaimmune infiltrationMELKprognosistumor microenvironment

Identifiers

PMID36353126
PMCPMC9637824
OpenAlexW4307264881

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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.