Evidence map›Paper›PMID 41193924›Full record

ArticleClinical and experimental medicine2025

Exploring the prognostic value of T cell exhaustion and mitochondrial dysfunction related genes in breast cancer through bioinformatics analysis and RT-qPCR validation.

Hong Wan, Angqing Li, Han Jiang, Zichen Ling, Rongsheng Su, Xuwen Hao, Jing Pei, Xiaowei Yang

Abstract read
In one paragraph

Article in Clinical and experimental medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Hong Wan *Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, 230061, Anhui, China.
Angqing Li *Department of General Surgery, The Third Affiliated Hospital of Anhui Medical University (The First People's Hospital of Hefei), Hefei, 230061, Anhui, China.
Han Jiang *Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, 230061, Anhui, China.
Zichen LingDepartment of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, 230061, Anhui, China.
Rongsheng SuDepartment of General Surgery, The Third Affiliated Hospital of Anhui Medical University (The First People's Hospital of Hefei), Hefei, 230061, Anhui, China.
Xuwen HaoDepartment of General Surgery, The Third Affiliated Hospital of Anhui Medical University (The First People's Hospital of Hefei), Hefei, 230061, Anhui, China.
Jing PeiDepartment of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, 230061, Anhui, China. peijing@ahmu.edu.cn.ORCID http://orcid.org/0009-0002-7500-3444
Xiaowei YangDepartment of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, 230061, Anhui, China. yangxiaowei@ahmu.edu.cn.ORCID https://orcid.org/0000-0003-1629-128X

Funding

the Health Research Program of Anhui AHWJ2024BAg20003the Health Soft Science Research Project of Anhui Province 2020WR02004the Scientific Research Fund of Anhui Medical University 2022xkj054
6 · The paper itself

Abstract

Breast cancer (BRCA) is a complex cancer with heterogeneous molecular mechanisms. This study aimed to identify prognostic genes related to T cell exhaustion and mitochondrial dysfunction in BRCA, and to construct a prognostic model. First, transcriptomic and clinical data for both tumor and normal samples were retrieved from public databases. Next, differentially expressed genes (DEGs) were identified. These DEGs were then intersected with 2030 mitochondrial-related genes and 683 T cell exhaustion-related genes obtained from relevant databases to pinpoint candidate genes. Moreover, regression analyses were carried out to refine the prognostic genes. A risk model was established to assess the risk score of BRCA patients. Cox regression analyses were utilized to determine the independent prognostic factors. Then a prognostic model was constructed. In addition, immune infiltration, drug sensitivity, and single-cell transcriptomics were integrated to dissect mechanisms. The expression of these genes in BRCA was validated by quantitative reverse transcription polymerase chain reaction (RT-qPCR). From 5041 DEGs, regression identified 7 prognostic genes (BCL2A1, GZMB, IRF7, MTHFD2, TFRC, JUN, and PPP1R15A). The accurate risk model stratified patients: high-risk correlated with suppressed immunity (p < 2.2e-16), elevated TIDE (p = 5.4e-14), and higher CI.1040 IC50 (cor = 0.63, p < 0.0001). Single-cell analysis revealed 6 types and MIF-(CD74 + CD44) crosstalk. RT-qPCR confirmed MTHFD2, TFRC, IRF7, BCL2A1 upregulation in tumor (p < 0.05). Risk score, age, race, N/M-stage were independent factors. Seven prognostic genes effectively predicted BRCA prognosis with independent prognostic factors.

Indexed as

Breast NeoplasmsMitochondriaT-LymphocytesBiomarkers, TumorComputational BiologyFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMiddle AgedPrognosisReal-Time Polymerase Chain ReactionT-Cell ExhaustionTranscriptomeBiomarkers, TumorBreast cancerMitochondrial dysfunctionPrognostic modelT cell exhaustionTumor microenvironment

Identifiers

PMID41193924
PMCPMC12589231

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.