Evidence mapPaperPMID 42305482Full record

ArticleTranslational cancer research2026

Cation homeostasis-related prognostic genes uncovered by transcriptomic analysis in breast cancer.

Mingxing Xu, Zhihao Ye, Weimin Hong, Liquan Zhu, Chaoqi He, Zhuotao Yang, Junsi Hu, Da Qian, Xuli Meng, Zhuozhuo Ren

Abstract read
In one paragraph

Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Mingxing Xu *The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China.
Zhihao Ye *General Surgery, Cancer Center, Department of Breast Surgery, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China.
Weimin Hong *Department of Pharmacy, The Third Affiliated Hospital (The Affiliated Luohu Hospital) of Shenzhen University, Shenzhen, China.
Liquan ZhuGeneral Surgery, Cancer Center, Department of Breast Surgery, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China.
Chaoqi HeGeneral Surgery, Cancer Center, Department of Breast Surgery, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China.
Zhuotao YangThe Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China.
Junsi HuThe Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China.
Da QianCentral Laboratory, Changshu Hospital Affiliated to Soochow University, Changshu No. 1 People's Hospital, Changshu, China.
Xuli MengGeneral Surgery, Cancer Center, Department of Breast Surgery, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China.
Zhuozhuo RenDepartment of Medical Engineering, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Disruption of cation homeostasis is increasingly recognized as a driver of breast cancer (BC) progression, yet a clinically actionable gene signature that quantifies this disturbance has been lacking. This study aims to systematically explore the value of cation homeostasis-related genes in the prognosis assessment of BC through bioinformatics analysis, construct and validate a prognostic model based on these genes, and integrate immune mechanism and drug sensitivity analyses to provide novel biomarkers and potential therapeutic targets for precise prognosis evaluation and individualized treatment of BC. Methods: There are 4,006 cation-homeostasis-related genes (CHRGs) integrated with transcriptomic profiles of 1,081 The Cancer Genome Atlas-breast invasive carcinoma (TCGA-BRCA) tumors and 99 normal breast tissues. After differential-expression filtering [|log2fold change (FC)| >2, false discovery rate (FDR) <0.05], 477 CHRGs were retained. Univariate-Cox, least absolute shrinkage and selection operator (LASSO) and multivariable modelling identified an 8-gene signature ( Results: The 8-gene signature stratified patients into high- and low-risk groups with significantly divergent 5-year overall survival probabilities [hazard ratio (HR) =2.34, 95 % confidence interval (CI): 1.79-3.06, P<0.0001; area under the curve (AUC)5-year =0.74]. Multivariable analysis confirmed the risk score as an independent prognostic factor together with age and N-stage (P<0.001). Mechanistically, high-risk tumors exhibited N-/O-glycan reprogramming, TNF-α/NF-κB hyper-activation, CD8 Conclusions: Our study provided the first CHRG-based prognostic model that simultaneously captures tumor-intrinsic aggressiveness and immune-evasive capacity in BC, offering quantitative biomarkers and actionable therapeutic targets for precision oncology.

Indexed as

Breast cancer (BC)cation steady-stateprognostic genesprognostic model

Identifiers

PMID42305482
PMCPMC13265182

What Socratic 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 Socratic graph.