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基于白细胞介素家族的特征与胰腺癌中癌症相关成纤维细胞的空间分布及免疫治疗反应相关。

Interleukin Family-Based Signature Relates to Cancer-Associated Fibroblasts Spatial Distribution and Immune Therapy Response in Pancreatic Carcinoma.

作者信息

Cheng Yang, Xiao Shuzhe, Li Xiangzhao, Wang Biao, Lei Yi, Sun Penghui, Ma Li, Zhu Yun

机构信息

Department of Infectious Diseases, Nanfang Hospital, Southern Medical University; State Key Laboratory of Organ Failure Research; Key Laboratory of Infectious Diseases Research in South China, Ministry of Education; Guangdong Provincial Key Laboratory for Prevention and Control of Major Liver Diseases; Guangdong Provincial Clinical Research Center for Viral Hepatitis; Guangdong Institute of Hepatology; Guangdong Provincial Research Center for Liver Fibrosis Engineering and Technology, Guangzhou, Guangdong, 510515, People's Republic of China.

Digestive Department, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong, 510623, People's Republic of China.

出版信息

J Inflamm Res. 2025 Jul 29;18:10129-10146. doi: 10.2147/JIR.S532651. eCollection 2025.

DOI:10.2147/JIR.S532651
PMID:40761382
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12318838/
Abstract

BACKGROUND

Cancer-associated fibroblasts (CAFs) and interleukins (ILs) family play crucial roles in pancreatic carcinoma (PC) immune response. However, the correlation between the IL family, CAFs infiltration, and PC prognosis remains uninvestigated.

METHODS

An IL family expression pattern for prognosis was constructed using a stepwise Cox proportional hazards regression model using TCGA data. Clinical data and validations from seven independent public cohort datasets were conducted to confirm the performance of the model. CAFs infiltrating abundance and spatial distribution in PC, and their correlation with patient prognosis were detected. Correlation between IL expression pattern, CAF infiltration, and immunotherapy response was evaluated using clinical tissue samples.

RESULTS

This study constructed the first IL family expression pattern to predict CAFs infiltration and prognosis in PC. The model was validated using clinical data and a meta-analysis of seven public PC datasets (HR= 1.27). IL high-risk patients had shorter survival, advanced tumors and lymph node metastasis compared to low-risk patients. Patients with unfavorable immunotherapy response had significantly higher IL risk scores (P=0.015). The IL expression pattern distinguished CAFs infiltration characteristics in PC, showing greater infiltration of CAFs, antigen-presenting CAFs (apCAFs) and inflammatory CAFs in the high-risk group. IL high-risk group also exhibited increased apCAF/tumor cell and apCAF/Tregs engagement, resulting in suppressed immune responses, crippled T-cell function and B-cell function, and elevated levels of biomarkers associated with poor immune response.

CONCLUSION

This study constructed the first IL expression pattern related to CAFs infiltration, immunotherapy response, and prognosis in PC patients. This might promote precise immunotherapy and facilitate treatment options for PC.

摘要

背景

癌症相关成纤维细胞(CAFs)和白细胞介素(ILs)家族在胰腺癌(PC)免疫反应中起关键作用。然而,IL家族、CAFs浸润与PC预后之间的相关性仍未得到研究。

方法

使用TCGA数据,通过逐步Cox比例风险回归模型构建用于预后的IL家族表达模式。对来自七个独立公共队列数据集的临床数据和验证进行分析,以确认该模型的性能。检测PC中CAFs浸润的丰度和空间分布及其与患者预后的相关性。使用临床组织样本评估IL表达模式、CAF浸润与免疫治疗反应之间的相关性。

结果

本研究构建了首个预测PC中CAFs浸润和预后的IL家族表达模式。该模型通过临床数据和对七个公共PC数据集的荟萃分析进行了验证(HR = 1.27)。与低风险患者相比,IL高风险患者的生存期较短,肿瘤进展且有淋巴结转移。免疫治疗反应不佳的患者IL风险评分显著更高(P = 0.015)。IL表达模式区分了PC中CAFs的浸润特征,显示高风险组中CAFs、抗原呈递CAFs(apCAFs)和炎性CAFs的浸润更多。IL高风险组还表现出apCAF/肿瘤细胞和apCAF/Tregs相互作用增加,导致免疫反应受到抑制、T细胞功能和B细胞功能受损,以及与不良免疫反应相关的生物标志物水平升高。

结论

本研究构建了首个与PC患者的CAFs浸润、免疫治疗反应和预后相关的IL表达模式。这可能会促进精准免疫治疗,并为PC提供更多治疗选择。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab8/12318838/2978eea044d0/JIR-18-10129-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab8/12318838/1221e707a149/JIR-18-10129-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab8/12318838/ad8e6fc210c4/JIR-18-10129-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab8/12318838/6243721d2794/JIR-18-10129-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab8/12318838/43c19a80529b/JIR-18-10129-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab8/12318838/c2fe329e0fc7/JIR-18-10129-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab8/12318838/2978eea044d0/JIR-18-10129-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab8/12318838/1221e707a149/JIR-18-10129-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab8/12318838/ad8e6fc210c4/JIR-18-10129-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab8/12318838/6243721d2794/JIR-18-10129-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab8/12318838/43c19a80529b/JIR-18-10129-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab8/12318838/c2fe329e0fc7/JIR-18-10129-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab8/12318838/2978eea044d0/JIR-18-10129-g0006.jpg

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