基于泛凋亡的预后标志物构建预测模型以评估肾透明细胞癌的免疫景观和治疗反应

董宇; 杨紫彤; 夏志楠; 廖家豪; 崔志明; 徐沈灏; 刘兵; 任亮亮; 王腾达; 郭炜; 王书文; 王于勇; 张诚

doi:10.1631/jzus.B2400132

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基于泛凋亡的预后标志物构建预测模型以评估肾透明细胞癌的免疫景观和治疗反应

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Research Article | Updated：2025-12-31

基于泛凋亡的预后标志物构建预测模型以评估肾透明细胞癌的免疫景观和治疗反应
Constructing a PANoptosis-based prognostic signature to evaluate the immune landscape and therapeutic response in clear cell renal cell carcinoma
浙江大学学报（英文版）（B辑：生物医学和生物技术） 2025年26卷第12期页码：1192-1215
Affiliations：

1.Department of Urology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu 322000, China
2.Department of Urology, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou 310022, China
3.Department of Urology, The Fourth Affiliated Hospital, Harbin Medical University, Harbin 150081, China
4.Department of Radiology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu 322000, China
5.Department of Urology, Guizhou Provincial People’s Hospital, Guiyang 550002, China
6.Department of Urology, Affiliated Hangzhou First People’s Hospital, School of Medicine, Westlake University, Hangzhou 310006, China
7.The Fourth School of Medicine Affiliated to Zhejiang Chinese Medical University, Hangzhou 310006, China
Funds：

the Zhejiang Provincial Natural Science Foundation of China(LZ22H160008);the Zhejiang Medical Science and Technology Project(2022RC059;2023KY931)
DOI：10.1631/jzus.B2400132
中图分类号：
CSTR：
收稿：2024-03-07，

修回：2024-11-29，

纸质出版：2025-12-31
Accepted：

董宇,杨紫彤,夏志楠等.基于泛凋亡的预后标志物构建预测模型以评估肾透明细胞癌的免疫景观和治疗反应[J].浙江大学学报（英文版）（B辑：生物医学和生物技术）,2025,26(12):1192-1215.

Yu DONG, Zitong YANG, Zhinan XIA, et al. Constructing a PANoptosis-based prognostic signature to evaluate the immune landscape and therapeutic response in clear cell renal cell carcinoma[J]. Journal of Zhejiang University-SCIENCE B, 2025, 26(12): 1192-1215.
董宇,杨紫彤,夏志楠等.基于泛凋亡的预后标志物构建预测模型以评估肾透明细胞癌的免疫景观和治疗反应[J].浙江大学学报（英文版）（B辑：生物医学和生物技术）,2025,26(12):1192-1215. DOI： 10.1631/jzus.B2400132.

Yu DONG, Zitong YANG, Zhinan XIA, et al. Constructing a PANoptosis-based prognostic signature to evaluate the immune landscape and therapeutic response in clear cell renal cell carcinoma[J]. Journal of Zhejiang University-SCIENCE B, 2025, 26(12): 1192-1215. DOI： 10.1631/jzus.B2400132.

摘要

目的：识别与肾透明细胞癌（ccRCC）中泛凋亡（PANoptosis）相关的基因（PRGs），以用于患者分层和预后评估。方法：通过差异表达分析与加权基因共表达网络分析（WGCNA）筛选ccRCC特异的PRGs，并利用LASSO和Cox回归构建预后模型，即PANoptosis指数（PANI）。该模型在单细胞RNA测序（scRNA-seq）、免疫组化和实时荧光定量逆转录聚合酶链反应（RT-qPCR）中得到验证。根据PANI将患者队列分为高低两组，使用多种指标评估该模型性能，并在E-MTAB-1980数据集中进行外部验证。通过功能和基因集富集分析揭示两组间的生物学差异，并比较了突变景观和肿瘤免疫微环境。进一步基于PANI预测患者对免疫疗法和抗肿瘤药物的敏感性。此外，通过CCK-8和Transwell实验评估

ZBP1

对ccRCC细胞增殖和迁移能力的影响。结果：筛选出

ZBP1

、

TNFSF14

、

CDKN3

、

PTHLH

和

HMOX1

共5个PRGs构建PANI模型，该模型与ccRCC患者预后独立相关。通过与临床因素的结合，基于PANI的Nomogram显示出高度的预测准确性。高PANI患者在ccRCC驱动基因中表现出独特的共突变模式和较低的生存概率，且免疫相关功能特征丰富，提示其肿瘤免疫微环境处于激活状态；该组患者对免疫疗法和抗肿瘤药物的敏感性也有所增加。敲低

ZBP1

能显著抑制ccRCC细胞的增殖和迁移能力。结论：PANI可作为ccRCC患者预后和免疫疗法反应预测的有效工具，有助于制定个体化治疗策略。

Abstract

Objective:To identify pyroptosis

apoptosis

and necro

ptosis (PANoptosis)-related genes (PRGs) in clear cell renal cell carcinoma (ccRCC) for patient stratification and prognosis prediction. Methods: We 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 (

ZBP1

) on cell proliferation and migration were assessed by cell counting kit-8 (CCK-8) and Transwell assays.Results:We identified five PRGs (

ZBP1

tumor necrosis factor superfamily protein 14 (

TNFSF14

)

cyclin-dependent kinase inhibitor 3 (

CDKN3

)

parathyroid hormone-like hormone (

PTHLH

)

and heme-oxygenase 1 (

HMOX1

)) constituting PANI

independently associated with ccRCC patient prognosis. The PANI-based nomogram

integrated with clinical factors

demonstrated high predictive accuracy for prognosis. High-PANI patients exhibited distinct co-mutation patterns in ccRCC driver genes and lower survival probabilities

with an enriched immune-related functional profile

indicating an activated immune environment. These patients also showed increased sensitivity to immunotherapy and antineoplastic drugs. The knockdown o

ZBP1

a key PRG in the PANI

significantly reduced ccRCC cell proliferation and migration. Conclusions:PANI provides precise prognosis and immunotherapy response predictions for ccRCC patients

facilitating individualized treatment strategies.

关键词

Keywords

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