Evidence map›Paper›PMID 33281882›Full record

ArticleFrontiers in genetics2020

Immune-Related Gene-Based Novel Subtypes to Establish a Model Predicting the Risk of Prostate Cancer.

Enchong Zhang, Jieqian He, Hui Zhang, Liping Shan, Hongliang Wu, Mo Zhang, Yongsheng Song

Abstract read
In one paragraph

Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

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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

16 citing papers in PubMed.

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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.

Enchong ZhangDepartment of Urology, Shengjing Hospital of China Medical University, Shenyang, China.
Jieqian HeDepartment of Urology, Shengjing Hospital of China Medical University, Shenyang, China.
Hui ZhangDepartment of Urology, Shengjing Hospital of China Medical University, Shenyang, China.
Liping ShanDepartment of Urology, Shengjing Hospital of China Medical University, Shenyang, China.
Hongliang WuDepartment of Spine and Joint Surgery, Shengjing Hospital of China Medical University, Shenyang, China.
Mo ZhangDepartment of Urology, Shengjing Hospital of China Medical University, Shenyang, China.
Yongsheng SongDepartment of Urology, Shengjing Hospital of China Medical University, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is significant heterogeneity in prostate cancer (PCa), but immune status can reflect its prognosis. This study aimed to explore immune-related gene-based novel subtypes and to use them to create a model predicting the risk of PCa.

methodsWe downloaded the data of 487 PCa patients from The Cancer Genome Atlas (TCGA) database. We used immunologically relevant genes as input for consensus clustering and applied survival analysis and principal component analysis to determine the properties of the subtypes. We also explored differences of somatic variations, copy number variations,

resultsFour PCa subtypes (C1, C2, C3, and C4) were identified on immune status. Patients with the C3 subtype had the worst prognosis, while the other three groups did not differ significantly from each other in terms of their prognosis. Principal component analysis clearly distinguished high-risk (C3) and low-risk (C1 + 2 + 4) patients. Compared with the case in the low-risk subtype, the Speckle-type POZ Protein (

conclusionPCa can be divided into four subtypes based on immune-related genes, among which the C3 subtype is associated with a poor prognosis. Based on these subtypes, a risk predictive model was developed, which could indicate patient prognosis.

Indexed as

immunemachine learningmulti-omicsprognosisprostate cancersubtype

Identifiers

PMID33281882
PMCPMC7691641

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