Evidence map›Paper›PMID 41490727›Full record

ArticleJournal of Zhejiang University. Science. B2025

Constructing a PANoptosis-based prognostic signature to evaluate the immune landscape and therapeutic response in clear cell renal cell carcinoma.

Yu Dong, Zitong Yang, Zhinan Xia, Jiahao Liao, Zhiming Cui, Shenhao Xu, Bing Liu, Liangliang Ren, Tengda Wang, Wei Guo and 3 more

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PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of Zhejiang University. Science. B, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Yu DongDepartment of Urology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu 322000, China.
Zitong YangDepartment of Urology, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou 310022, China.
Zhinan XiaDepartment of Urology, The Fourth Affiliated Hospital, Harbin Medical University, Harbin 150081, China.
Jiahao LiaoDepartment of Urology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu 322000, China.
Zhiming CuiDepartment of Radiology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu 322000, China.
Shenhao XuDepartment of Urology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu 322000, China.
Bing LiuDepartment of Urology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu 322000, China.
Liangliang RenDepartment of Urology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu 322000, China.
Tengda WangDepartment of Urology, Guizhou Provincial People's Hospital, Guiyang 550002, China.
Wei GuoDepartment of Urology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu 322000, China.
Shuwen WangDepartment of Urology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu 322000, China.
Yuyong WangDepartment of Urology, Affiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou 310006, China. b1518118@zju.edu.cn.
Cheng ZhangDepartment of Urology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu 322000, China. zhangcheng13836182568@zju.edu.cn.

Funding

the Zhejiang Medical Science and Technology Project 2022RC059 and 2023KY931the Zhejiang Provincial Natural Science Foundation of China LZ22H160008
6 · The paper itself

Abstract

objectiveTo identify pyroptosis, apoptosis, and necroptosis (PANoptosis)-related genes (PRGs) in clear cell renal cell carcinoma (ccRCC) for patient stratification and prognosis prediction.

methodsWe used differential expression analysis and weighted gene co-expression network analysis (WGCNA) to identify ccRCC-specific PRGs. A prognostic model, the PANoptosis-index (PANI), was constructed using least absolute shrinkage and selection operator (LASSO) and Cox regression. The PANI model, comprising PRGs, was validated through single-cell RNA-sequencing (scRNA-seq), immunohistochemistry, and reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Patient cohorts were categorized into high- and low-PANI groups, and the model's performance was appraised using various metrics. External validation was performed with the E-MTAB-1980 dataset. Functional and gene set enrichment analyses distinguished biological differences between groups. Mutational landscapes and tumor immune microenvironments were compared. Sensitivity to immunotherapy and antineoplastic drugs was also predicted using PANI. The effects of Z-DNA-binding protein 1 (

resultsWe identified five PRGs (

conclusionsPANI provides precise prognosis and immunotherapy response predictions for ccRCC patients, facilitating individualized treatment strategies.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsApoptosisCell Line, TumorCell MovementCell ProliferationFemaleGene Expression Regulation, NeoplasticHumansImmunotherapyMaleMiddle AgedPrognosisTumor MicroenvironmentClear cell renal cell carcinoma (ccRCC)Immunotherapy responsePrognosisPyroptosis, apoptosis, and necroptosis (PANoptosis)Tumor immune microenvironment

Identifiers

PMID41490727
PMCPMC12768572

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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.