Evidence map›Paper›PMID 33672990›Full record

ArticleBiology2021

A Novel Ferroptosis-Related Gene Signature Predicts Overall Survival of Breast Cancer Patients.

Haifeng Li, Lu Li, Cong Xue, Riqing Huang, Anqi Hu, Xin An, Yanxia Shi

Open access · goldAbstract read
In one paragraph

Article in Biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
3.5field-weighted citation impact, top 6% 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

20 citing papers in PubMed, 27 citations in OpenAlex.

  1. Review
  2. Article
  3. [Ferroptosis-related long non-coding RNA to predict the clinical outcome of non-small cell lung cancer after radiotherapy].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2025
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  8. Upregulation of the ferroptosis-relatedFrontiers in oncology · 2023
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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.

Haifeng LiDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou 510060, Guangdong, China.
Lu LiDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou 510060, Guangdong, China.
Cong XueDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou 510060, Guangdong, China.
Riqing HuangDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou 510060, Guangdong, China.
Anqi HuDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou 510060, Guangdong, China.
Xin AnDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou 510060, Guangdong, China.
Yanxia ShiDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou 510060, Guangdong, China.ORCID 0000-0002-5414-8049
Sun Yat-sen University · CN

Funding

National Natural Science Foundation of China 81773279Science and Technology Planning Project of Guangdong Province 2012B061700082Science and Technology Planning Project of Guangdong Province 2013B021800062Science and Technology Planning Project of Guangdong Province 2016A050502015Young Teacher Foundation of Sun Yat-sen University 17ykzd33
6 · The paper itself

Abstract

Breast cancer is the second leading cause of death in women, thus a reliable prognostic model for overall survival (OS) in breast cancer is needed to improve treatment and care. Ferroptosis is an iron-dependent cell death. It is already known that siramesine and lapatinib could induce ferroptosis in breast cancer cells, and some ferroptosis-related genes were closely related with the outcomes of treatments regarding breast cancer. The relationship between these genes and the prognosis of OS remains unclear. The data of gene expression and related clinical information was downloaded from public databases. Based on the TCGA-BRCA cohort, an 8-gene prediction model was established with the least absolute shrinkage and selection operator (LASSO) cox regression, and this model was validated in patients from the METABRIC cohort. Based on the median risk score obtained from the 8-gene model, patients were stratified into high- or low-risk groups. Cox regression analyses identified that the risk score was an independent predictor for OS. The findings from CIBERSORT and ssGSEA presented noticeable differences in enrichment scores for immune cells and pathways between the abovementioned two risk groups. To sum up, this prediction model has potential to be widely applied in future clinical settings.

Indexed as

breast cancerferroptosisgene signatureimmune statusprognosis

Identifiers

PMID33672990
PMCPMC7917807
OpenAlexW3133384087

What OpenQuestion holds

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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.