Evidence map›Paper›PMID 34721975›Full record

ArticlePeerJ2021

Identification and validation of a novel zinc finger protein-related gene-based prognostic model for breast cancer.

Min Ye, Liang Li, Donghua Liu, Qiuming Wang, Yunuo Zhang, Jinfeng Zhang

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2021. 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
2.5field-weighted citation impact, top 10% 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, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Identification of immune infiltration-related ZNF480 for predicting prognosis in breast cancer.American journal of clinical and experimental immunology · 2025
    Article
  6. Article
  7. Heliyon · 2023
    Article
  8. Article
  9. Transcriptomic Profile of Canine Mammary Ductal Carcinoma.International journal of molecular sciences · 2023
    Article
  10. Article
  11. Article
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.

Min YeDepartment of Medical Oncology 3, The Meizhou People's Hospital, Meizhou, China.
Liang LiDepartment of Medical Oncology 3, The Meizhou People's Hospital, Meizhou, China.
Donghua LiuDepartment of Medical Oncology 3, The Meizhou People's Hospital, Meizhou, China.
Qiuming WangDepartment of Medical Oncology 3, The Meizhou People's Hospital, Meizhou, China.
Yunuo ZhangDepartment of Medical Oncology 3, The Meizhou People's Hospital, Meizhou, China.
Jinfeng ZhangDepartment of Medical Oncology 3, The Meizhou People's Hospital, Meizhou, China.
Meizhou City People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast invasive carcinoma (BRCA) is a commonly occurring malignant tumor. Zinc finger proteins (ZNFs) constitute the largest transcription factor family in the human genome and play a mechanistic role in many cancers' development. The prognostic value of ZNFs has yet to be approached systematically for BRCA.

methodsWe analyzed the data of a training set from The Cancer Genome Atlas (TCGA) database and two validation cohort from GSE20685 and METABRIC datasets, composed of 3,231 BRCA patients. After screening the differentially expressed ZNFs, univariate Cox regression, LASSO, and multiple Cox regression analysis were performed to construct a risk-based predictive model. ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and gene set enrichment analyses (GSEA) were utilized to assess the potential relations among the tumor immune microenvironment and ZNFs in BRCA.

resultsIn this study, we profiled ZNF expression in TCGA based BRCA cohort and developed a novel prognostic model based on 14 genes with ZNF relations. This model was composed of high and low-score groups for BRCA classification. Based upon Kaplan-Meier survival curves, risk-status-based prognosis illustrated significant differences. We integrated the 14 ZNF-gene signature with patient clinicopathological data for nomogram construction with accurate 1-, 3-, and 5-overall survival predictive capabilities. We then accessed the Genomics of Drug Sensitivity in Cancer database for therapeutic drug response prediction of signature-defined BRCA patient groupings for our selected TCGA population. The signature also predicts sensitivity to chemotherapeutic and molecular-targeted agents in high- and low-risk patients afflicted with BRCA. Functional analysis suggested JAK STAT, VEGF, MAPK, NOTCH TOLL-like receptor, NOD-like receptor signaling pathways, apoptosis, and cancer-based pathways could be key for ZNF-related BRCA development. Interestingly, based on the results of ESTIMATE, ssGSEA, and GSEA analysis, we elucidated that our ZNF-gene signature had pivotal regulatory effects on the tumor immune microenvironment for BRCA.

conclusionOur findings shed light on the potential contribution of ZNFs to the pathogenesis of BRCA and may inform clinical practice to guide individualized treatment.

Indexed as

BioinformaticsBreast cancerPrognosticTumor microenvironmentZinc finger proteins

Identifiers

PMID34721975
PMCPMC8530103
OpenAlexW3207972506

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.