Evidence map›Paper›PMID 39730892›Full record

ArticleScientific reports2024

Identification of a novel immune checkpoint-related gene signature predicts prognosis and immunotherapy in breast cancer and experiment verification.

Ke Yin, Yangyang Guo, Jinqiu Wang, Shenchao Guo, Chunxu Zhang, Yongping Dai, Yu Guo, Chen Dai

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

8 authors.

Ke Yin *Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Yangyang Guo *Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Jinqiu WangDepartment of Thyroid and Breast Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Shenchao GuoDepartment of Thyroid and Breast Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Chunxu ZhangDepartment of Thyroid and Breast Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Yongping DaiDepartment of Thyroid and Breast Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China. dypnbyy@163.com.
Yu GuoDepartment of Thyroid and Breast Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China. guoyu308@163.com.
Chen DaiDigestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, China. daichen0408@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer (BRCA) is one of the pivotal causes of female death worldwide. And the morbidity and mortality of breast cancer have increased rapidly. Immune checkpoints are important to maintain immune tolerance and are regarded as important therapeutic targets. However, research for BRCA were limited to single immune checkpoint-related gene (ICG) and few studies have systematically explored expression profile of Immune checkpoint-related genes or attempted to construct a prognostic gene risk model based on immune checkpoint-related genes. We identified immune checkpoint-related differentially expressed genes (DEGs) in BRCA and normal breast tissues from TCGA database. A 7-gene signature was created by utilizing the univariate Cox regression model with least absolute shrinkage and selection operator (LASSO) Cox regression method. In addition, we conducted a nomogram to predict the prognostic significance. This tool enables quantitative prediction of patient prognosis, serving as a valuable reference for clinical decision-making, thereby improving patient outcomes. Relationships between our risk model and clinical indicators, TME (Tumor Microenvironment), immune cell infiltration, immune response and drug susceptibility were investigated. A set of in vitro cell assays was conducted to decipher the relationship between MAP2K6 and proliferation, invasion, migration, colony formation and apoptosis rate of breast cancer cells. As a result, we established a prognostic model composed of seven ICGs in BRCA. Based on the median risk score, BRCA patients were equally assigned into two groups of high- and low-risk. High-risk BRCA patients have poorer OS (overall survival) than low-risk patients. In addition, there were remarkable differences between these two groups in clinicopathological features, TME, immune cell infiltration, immune response and drug susceptibility. The results of GO and KEGG analyses indicated that DEGs between the high- and low-risk groups were involved in immune-related biological processes and pathways. GSEA analysis also showed that a number of immune-related pathways were notably enriched in the low-risk group. Finally, results of cell-based assays indicated that MAP2K6 may play a pivotal role in the initiation and progression of breast cancer as a tumor suppressor gene. In conclusion, we created a novel ICG signature that has the potential to predict the survival and drug sensitivity of BRCA patients. Furthermore, this study indicated that MAP2K6 may serve as a novel target for BRCA therapy.

Indexed as

Breast NeoplasmsGene Expression Regulation, NeoplasticImmunotherapyBiomarkers, TumorFemaleGene Expression ProfilingHumansImmune Checkpoint ProteinsNomogramsPrognosisTranscriptomeTumor MicroenvironmentBiomarkers, TumorImmune Checkpoint ProteinsBRCACell experimentsDrug susceptibilityImmune cell infiltrationImmune checkpointPrognosis

Identifiers

PMID39730892
PMCPMC11680899

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.