Evidence map›Paper›PMID 41706247›Full record

ArticleDiscover oncology2026

A pathomics-based pyroptosis signature predicts survival in clear cell renal cell carcinoma.

Kaibin Wang, Shiyao Wei, Dingkun Hou, Lili Wang, Lijuan Kang, Hongzheng Li, Changying Li, Haitao Wang

Abstract read
In one paragraph

Article in Discover oncology, 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
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0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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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.

Kaibin Wang *Department of Oncology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Shiyao Wei *Sichuan Tianfu New Area People's Hospital, Chengdu, Sichuan, China.
Dingkun HouDepartment of Oncology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Lili WangDepartment of Oncology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Lijuan KangDepartment of Oncology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Hongzheng LiDepartment of Oncology, The Second Hospital of Tianjin Medical University, Tianjin, China.
Changying LiDepartment of Oncology, The Second Hospital of Tianjin Medical University, Tianjin, China. cli_cvrl@tmu.edu.cn.
Haitao WangDepartment of Oncology, The Second Hospital of Tianjin Medical University, Tianjin, China. wanght@tmu.edu.cn.

Funding

Clinical Research of Tianjin Medical University No: 2018kylc004Tianjin Key Medical DisciplineConstruction Project Grant No.TJYXZDXK-3-003A
6 · The paper itself

Abstract

Better prognostic tools are needed to improve the clinical management of clear cell renal cell carcinoma (ccRCC). To address this, we developed a novel prognostic model by integrating pathomics features with pyroptosis-related signaling, a strategy not previously explored in ccRCC. Analysis of The Cancer Genome Atlas (TCGA) whole-slide images identified 59 quantitative image features significantly correlated with a pyroptosis gene set. Based on these features, a prognostic risk score was developed using the StepCox[forward]+Lasso algorithm and validated as an independent predictor of patient survival. This model demonstrated robust predictive performance, with time-dependent AUCs of 0.744, 0.729, and 0.716 for 1-, 3-, and 5-year survival and C-indexes of 0.71 and 0.64 in the training and validation sets. This model implicates key pyroptosis-related genes (e.g., GSDMD, GSDME, CASP5, and several CHMP family genes), whose expression links pathological phenotypes to patient outcomes. Single-cell sequencing revealed their specific expression patterns in the ccRCC microenvironment, and functional exploration highlighted GSDMD's potential role. By providing a novel, biologically integrated signature, this model offers a refined tool for prognostic assessment that complements conventional clinical parameters. Ultimately, this pyroptosis-based pathomics model could help guide personalized treatment strategies for ccRCC patients in the future.

Indexed as

ccRCCPathomicsPrognosisPyroptosis

Identifiers

PMID41706247
PMCPMC13022123

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.