Evidence map›Paper›PMID 37596527›Full record

Trial reportBMC cancer2023

A novel super-enhancer-related gene signature predicts prognosis and immune microenvironment for breast cancer.

Qing Wu, Xuan Tao, Yang Luo, Shiyao Zheng, Nan Lin, Xianhe Xie

Open access · goldAbstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in BMC cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
5.2field-weighted citation impact, top 4% 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

10 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
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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

6 authors at 1 institution in 1 country.

Qing Wu *Department of Oncology, Molecular Oncology Research Institute, The First Affiliated Hospital of Fujian Medical University, No. 20 Chazhong Road, Fuzhou, 350005, China.
Xuan Tao *Department of Pathology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Yang Luo *Department of Oncology, Molecular Oncology Research Institute, The First Affiliated Hospital of Fujian Medical University, No. 20 Chazhong Road, Fuzhou, 350005, China.
Shiyao ZhengCollege of Clinical Medicine for Oncology, Fujian Medical University, Fuzhou, Fujian, China.
Nan LinFuzong Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, China.
Xianhe XieDepartment of Oncology, Molecular Oncology Research Institute, The First Affiliated Hospital of Fujian Medical University, No. 20 Chazhong Road, Fuzhou, 350005, China. xiexianhe@fjmu.edu.cn.ORCID https://orcid.org/0000-0002-4134-5887
Fujian Medical University · CN

Funding

Startup Fund for Scientific Research of Fujian Medical University No. 2020QH1018Youth Scientific Research Project of Fujian Provincial Health Commission No. 2020QNA046
6 · The paper itself

Abstract

backgroundThis study targeted at developing a robust, prognostic signature based on super-enhancer-related genes (SERGs) to reveal survival prognosis and immune microenvironment of breast cancer.

methodsRNA-sequencing data of breast cancer were retrieved from The Cancer Genome Atlas (TCGA), 1069 patients of which were randomly assigned into training or testing set in 1:1 ratio. SERGs were downloaded from Super-Enhancer Database (SEdb). After which, a SERGs signature was established based on the training set, with its prognostic value further validated in the testing set. Subsequently, we identified the potential function enrichment and tumor immune infiltration of the model. Moreover, in vitro experiments were completed to further explore the biological functions of ZIC2 gene (one of the risk genes in the prognostic model) in breast cancer.

resultsA risk score system of prognostic value was constructed with 6 SERGs (ZIC2, NFE2, FOXJ1, KLF15, POU3F2 and SPIB) to find patients in high-risk group with significantly worse prognosis in both training and testing sets. In addition, a multivariate regression was established via integrating the 6 genes with age and N stage, indicating well performance by calibration, time-dependent receiver operating characteristic (ROC) analysis and decision curve analysis (DCA). Further analysis demonstrated that tumor-associated pathological processes and pathways were significantly enriched in the high-risk group. In general, the novel SERGs signature could be applied to screen breast cancer with immunosuppressive microenvironment for the risk score was negatively correlated with ESTIMATE score, tumor-infiltration lymphocytes (such as CD4 + and CD8 + T cell), immune checkpoints and chemotactic factors. Furthermore, down-regulation of ZIC2 gene expression inhibited the cell viability, cellular migration and cell cycle of breast cancer cells.

conclusionsThe novel SERGs signature could predict the prognosis of breast cancer; and SERGs might serve as potential therapeutic targets for breast cancer.

Indexed as

Breast NeoplasmsCalibrationCD8-Positive T-LymphocytesFemaleHumansPrognosisRegulatory Sequences, Nucleic AcidTumor MicroenvironmentBreast cancerImmune checkpointsOverall survivalSuper-enhancerTumor immune microenvironment

Identifiers

PMID37596527
PMCPMC10439574
OpenAlexW4385986873

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.