Evidence map›Paper›PMID 35719954›Full record

ArticleFrontiers in oncology2022

Development and Verification of a Prognostic Ferroptosis-Related Gene Model in Triple-Negative Breast Cancer.

Song Wu, Ruilin Pan, Jibu Lu, Xiaoling Wu, Jingdong Xie, Hailin Tang, Xing Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
5.2field-weighted citation impact, top 3% 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

19 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Review
  13. Review
  14. Article
  15. Article
  16. Review
  17. Article
  18. Review
  19. 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

7 authors at 4 institutions in 1 country.

Song WuState Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Ruilin PanDepartment of Breast Surgery, The First People's Hospital of Foshan, Foshan, China.
Jibu LuDepartment of Breast Surgery, The First People's Hospital of Foshan, Foshan, China.
Xiaoling WuThe First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China.
Jingdong XieState Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Hailin TangState Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Xing LiState Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Sun Yat-sen University Cancer Center · CNFirst People's Hospital of Foshan · CNFirst Affiliated Hospital of Zhengzhou University · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC) is the subtype with the worst prognosis of breast cancer. Ferroptosis, a novel iron-dependent programmed cell death, has an increasingly important role in tumorigenesis and development. However, there is still a lack of research on the relationship between ferroptosis-related genes and the prognosis of TNBC. In this study, we obtained the gene expression profile of TNBC patients and matched clinical data from The Cancer Genome Atlas (TCGA) database. Univariate Cox analysis was used to screen out ferroptosis-related genes associated with TNBC prognosis. Then, the least absolute shrinkage and selection operator (LASSO) regression analysis was employed to establish a prognostic prediction model. A 15-ferroptosis-related gene prognostic prediction model was developed, which classified patients into low-risk (LR) or high-risk (HR) groups. Kaplan-Meier analysis results showed that the prognosis of the LR group was better. The receiver operating characteristic (ROC) curve also confirmed the satisfactory predictive ability of this model. Evaluation of the immune microenvironment of TNBC patients in the HR and LR group suggested these 15 ferroptosis-related genes might affect the prognosis of TNBC by regulating the tumor microenvironment. Our prognostic model can provide a theoretical basis for accurate prognosis prediction of TNBC in clinical practice.

Indexed as

ferroptosismRNA signatureprognostic modeltriple-negative breast cancer (TNBC)tumor microenvironment

Identifiers

PMID35719954
PMCPMC9202593
OpenAlexW4281646768

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.