Evidence map›Paper›PMID 31729963›Full record

ArticleBMC cancer2019

A gene expression-based study on immune cell subtypes and glioma prognosis.

Qiu-Yue Zhong, Er-Xi Fan, Guang-Yong Feng, Qi-Ying Chen, Xiao-Xia Gou, Guo-Jun Yue, Gui-Hai Zhang

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 1 pooled it
5.8field-weighted citation impact, top 3% 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

43 citing papers in PubMed, 1 synthesis or guideline pooled it, 87 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 1 institution in 1 country.

Qiu-Yue ZhongDepartment of Head and Neck Oncology, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou Province, People's Republic of China.
Er-Xi FanDepartment of Head and Neck Oncology, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou Province, People's Republic of China.
Guang-Yong FengDepartment of Head and Neck Oncology, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou Province, People's Republic of China.
Qi-Ying ChenDepartment of Head and Neck Oncology, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou Province, People's Republic of China.
Xiao-Xia GouDepartment of Head and Neck Oncology, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou Province, People's Republic of China.
Guo-Jun YueDepartment of Head and Neck Oncology, Zunyi Medical University, Zunyi, 563000, Guizhou Province, People's Republic of China. guojuny007@163.com.
Gui-Hai ZhangDepartment of Head and Neck Oncology, Zunyi Medical University, Zunyi, 563000, Guizhou Province, People's Republic of China. zghzhuhai@163.com.
Zunyi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectGlioma is a common malignant tumours in the central nervous system (CNS), that exhibits high morbidity, a low cure rate, and a high recurrence rate. Currently, immune cells are increasingly known to play roles in the suppression of tumourigenesis, progression and tumour growth in many tumours. Therefore, given this increasing evidence, we explored the levels of some immune cell genes for predicting the prognosis of patients with glioma.

methodsWe extracted glioma data from The Cancer Genome Atlas (TCGA). Using the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm, the relative proportions of 22 types of infiltrating immune cells were determined. In addition, the relationships between the scales of some immune cells and sex/age were also calculated by a series of analyses. A P-value was derived for the deconvolution of each sample, providing credibility for the data analysis (P < 0.05). All analyses were conducted using R version 3.5.2. Five-year overall survival (OS) also showed the effectiveness and prognostic value of each proportion of immune cells in glioma; a bar plot, correlation-based heatmap (corheatmap), and heatmap were used to represent the proportions of immune cells in each glioma sample.

resultsIn total, 703 transcriptomes from a clinical dataset of glioma patients were drawn from the TCGA database. The relative proportions of 22 types of infiltrating immune cells are presented in a bar plot and heatmap. In addition, we identified the levels of immune cells related to prognosis in patients with glioma. Activated dendritic cells (DCs), eosinophils, activated mast cells, monocytes and activated natural killer (NK) cells were positively related to prognosis in the patients with glioma; however, resting NK cells, CD8

conclusionWe performed a novel gene expression-based study of the levels of immune cell subtypes and prognosis in glioma, which has potential clinical prognostic value for patients with glioma.

Indexed as

Dendritic CellsFemaleGene Expression ProfilingGliomaHumansKiller Cells, NaturalLymphocytes, Tumor-InfiltratingMacrophagesMaleMiddle AgedPrognosisCIBERSORTGliomaPrognosisTumour-infiltrating immune cells (TIICs)

Identifiers

PMID31729963
PMCPMC6858694
OpenAlexW2986962832

What OpenQuestion holds

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LicenceCC BY
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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.