Evidence map›Paper›PMID 39897849›Full record

ArticleHeliyon2025

Identification and analysis of prognostic ion homeostasis characteristics in kidney renal clear cell carcinoma.

Xiangmin Zhang, Xiongxian Qian, Yong Zhao, Maofei Ye, Liyang Li, Jian Chu

Abstract read
In one paragraph

Article in Heliyon, 2025. 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

6 authors.

Xiangmin ZhangDepartment of Urology, Shanghai Baoshan Luodian Hospital, Baoshan District, Shanghai, 201908, China.
Xiongxian QianDepartment of Urology, Shanghai Baoshan Luodian Hospital, Baoshan District, Shanghai, 201908, China.
Yong ZhaoDepartment of Urology, Shanghai Baoshan Luodian Hospital, Baoshan District, Shanghai, 201908, China.
Maofei YeDepartment of Urology, Shanghai Baoshan Luodian Hospital, Baoshan District, Shanghai, 201908, China.
Liyang LiDepartment of Urology, Shanghai Baoshan Luodian Hospital, Baoshan District, Shanghai, 201908, China.
Jian ChuDepartment of Urology, Shanghai Baoshan Luodian Hospital, Baoshan District, Shanghai, 201908, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kidney renal clear cell carcinoma (KIRC), a prevalent primary malignant tumor within the urinary system, is characterized by significant heterogeneity. It has been shown that ion channels are important targets for anti-tumor therapy. In this study, we screened 70 selected KIRC related ion homeostasis genes with significant differential expression. We established diagnostic and prognostic models for 15 genes (PDK4, JPH4, ATP1A3, CCL7, CYP27B1, ABCB6, TNFSF11, MCHR1, TNNI3, ANGPTL3, Ednrb, SAA1, Chrna9, TMPRSS6, CCL14) by LASSO regression in the TCGA-KIRC cohort. We also provided a nomogram based on ion homeostasis for clinicians to explore the combined effect of the risk model on clinical variables. Patients in the low-risk group have a significant survival advantage. The potential clinical benefit of our predicted 15 gene signatures in clinical strategies was validated by Calibration Curves and DCA curves. Ultimately, the immune microenvironment and enrichment pathways were analyzed among individuals categorized as high-risk and low-risk. The predictable ion homeostasis-associated 15 gene signature established in this study predicts overall survival outcomes in patients with KIRC, to some extent helping clinicians to select personalized treatment regimens.

Indexed as

BioinformaticsKidney renal clear cell carcinomaOncologySignature

Identifiers

PMID39897849
PMCPMC11782977

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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.