Evidence map›Paper›PMID 36059470›Full record

ArticleFrontiers in immunology2022

Identification of necroptosis-related subtypes and prognosis model in triple negative breast cancer.

Shengyu Pu, Yudong Zhou, Peiling Xie, Xiaoqian Gao, Yang Liu, Yu Ren, Jianjun He, Na Hao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed, 24 citations in OpenAlex.

  1. Review
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  11. Biomarkers derived from CmP signal network in triple negative breast cancers.Translational breast cancer research : a journal focusing on translational research in breast cancer · 2023
    Review
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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

8 authors at 1 institution in 1 country.

Shengyu PuDepartment of Breast Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Yudong ZhouDepartment of Breast Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Peiling XieDepartment of Breast Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Xiaoqian GaoDepartment of Breast Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Yang LiuDepartment of Breast Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Yu RenDepartment of Breast Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Jianjun HeDepartment of Breast Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Na HaoDepartment of Breast Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
First Affiliated Hospital of Xi'an Jiaotong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Necroptosis is considered to be a new form of programmed necrotic cell death, which is associated with metastasis, progression and prognosis of various types of tumors. However, the potential role of necroptosis-related genes (NRGs) in the triple negative breast cancer (TNBC) is unclear. Methods: We extracted the gene expression and relevant clinicopathological data of TNBC from The Cancer Genome Atlas (TCGA) databases and the Gene Expression Omnibus (GEO) databases. We analyzed the expression, somatic mutation, and copy number variation (CNV) of 67 NRGs in TNBC, and then observed their interaction, biological functions, and prognosis value. By performing Lasso and COX regression analysis, a NRGs-related risk model for predicting overall survival (OS) was constructed and its predictive capabilities were verified. Finally, the relationship between risk_score and immune cell infiltration, tumor microenvironment (TME), immune checkpoint, and tumor mutation burden (TMB), cancer stem cell (CSC) index, and drug sensitivity were analyzed. Results: A total 67 NRGs were identified in our analysis. A small number of genes (23.81%) detected somatic mutation, most genes appeared to have a high frequency of CNV, and there was a close interaction between them. These genes were remarkably enriched in immune-related process. A seven-gene risk_score was generated, containing Conclusion: Our research identified the significant impact of NRGs on immunity and prognosis in TNBC. These findings were expected to provide a new strategy for personalize the treatment of TNBC and improve its clinical benefit.

Indexed as

Triple Negative Breast NeoplasmsBiomarkers, TumorDNA Copy Number VariationsHumansNecroptosisNerve Tissue ProteinsPrognosisReceptors, G-Protein-CoupledReceptors, NeurotransmitterTumor MicroenvironmentBiomarkers, TumorGPR19 protein, humanNerve Tissue ProteinsReceptors, G-Protein-CoupledReceptors, NeurotransmitterimmunenecroptosisprognosisTCGAtriple negative breast cancer

Identifiers

PMID36059470
PMCPMC9437322
OpenAlexW4292551420

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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.