Evidence map›Paper›PMID 33614706›Full record

ArticleFrontiers in molecular biosciences2020

A Risk Prediction Model for Breast Cancer Based on Immune Genes Related to Early Growth Response Proteins Family.

Xin Zhou, Fang-Yuan Zhang, Yan Liu, Dong-Xin Wei

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

5 citing papers in PubMed, 5 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

4 authors at 1 institution in 1 country.

Xin ZhouDepartment of Breast Surgery, Zibo Maternal and Child Health Hospital, Zibo, China.
Fang-Yuan ZhangDepartment of Breast Surgery, Zibo Maternal and Child Health Hospital, Zibo, China.
Yan LiuDepartment of Breast Surgery, Zibo Maternal and Child Health Hospital, Zibo, China.
Dong-Xin WeiDepartment of Breast Surgery, Zibo Maternal and Child Health Hospital, Zibo, China.
The Fourth People's Hospital of Zibo City · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early growth response proteins (EGRs), a transcriptional regulatory family comprised of EGR1, EGR2, EGR3, and EGR 4, are reportedly involved in a vast array of functions. However, EGRs, as a whole, are rarely studied in breast cancer cases. This research was performed based on public datasets. The results demonstrated that, except EGR4, the other EGRs were differentially expressed genes in breast cancer. Subsequently, this study determined the prognosis significance of the EGR family, higher expression levels of EGRs indicating better overall survival (OS) and disease-free survival (DFS), except EGR4. So we attempted to explore the potential mechanism behind the prognostic value of EGRs. At the DNA level, however, neither DNA methylation status nor genetic alterations of EGRs contributed to the prognosis significance. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that EGRs were involved in several immune-related functions. Afterward, we assessed the correlation between EGRs and the immune system before establishing a risk prediction model with a 14-gene immune signature associated with EGRs, a prognostic nomogram predicting individuals' 1-, 3-, and 5-year survival probabilities. The risk score was an independent prognosis predictor in the breast cancer cohorts. This study evidenced EGRs' significance for tumor immunity, demonstrating that the EGR family may be a potential immunotherapeutic target for breast cancer. The 14-gene immune signature is a promising prognostic biomarker in breast cancer.

Indexed as

breast cancerDNA methylationEGR familygenetic alterationimmune cellsnomogramprognosis

Identifiers

PMID33614706
PMCPMC7887293
OpenAlexW3128235090

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.