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胰腺腺癌预后基因IFI27的生物信息学分析和实验验证及中药治疗预测

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秦冰冰, 李娜, 李静, 周瑞生, 唐莹

中草药 | 数据挖掘与循证医学 2026,57(6): 2198-2215

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中草药 |数据挖掘与循证医学 2026 , 57 (6) : 2198 -2215

胰腺腺癌预后基因IFI27的生物信息学分析和实验验证及中药治疗预测

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秦冰冰, 李娜, 李静, 周瑞生, 唐莹

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秦冰冰: 秦冰冰,博士研究生,主治医师,从事中西医结合防治肿瘤研究。E-mail:837653629@qq.com

Bioinformatics analysis and experimental validation of prognostic gene IFI27 in pancreatic adenocarcinoma with prediction of traditional Chinese medicine treatment

QIN Bingbing, LI Na, LI Jing, ZHOU Ruisheng, TANG Ying

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doi: 10.7501/j.issn.0253-2670.2026.06.017

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目的基于生物信息学筛选胰腺腺癌（pancreatic adenocarcinoma，PAAD）预后基因，并预测调控特征基因的活性成分及中药。方法整合TCGA、GTEx和GEO数据库数据集，通过差异基因分析、Cox回归分析和生存分析等筛选预后基因；对关键基因进行预后效能分析及表达趋势验证；同时进行基因本体（gene ontology，GO）功能和京都基因与基因组百科全书（Kyoto encyclopedia of genes and genomes，KEGG）通路富集分析以及基因集富集分析（gene set enrichment analysis，GSEA），明确潜在通路和生物过程。分析特征基因对免疫细胞浸润状态的影响以及免疫检查点相关性，预测肿瘤免疫逃逸能力、肿瘤突变负荷。从单细胞层面验证基因的表达模式。利用DSigDB、CTD和HERB数据库预测潜在的中药活性成分并进行分子对接，通过Swiss ADME进行类药性分析，利用Coremine Medical数据库进行中药预测并分析。通过细胞实验验证关键活性成分对特征基因的调控作用。结果筛选出预后基因干扰素α诱导蛋白27（interferon alpha inducible protein 27，IFI27），其在PAAD中表达显著上调，且低表达患者具有更长的总生存期，提示其作为预后标志物的潜力。富集分析显示IFI27可能参与调控细胞凋亡、细胞外基质（extracellular matrix，ECM）-受体相互作用、T细胞活化调节、巨噬细胞迁移等生物学过程以及磷脂酰肌醇-3-羟激酶（phosphatidylinositol-3-hydroxykinase，PI3K）-蛋白激酶B（protein kinase B，Akt）、核因子-κB（nuclear factor-κB，NF-κB）等信号通路。免疫浸润分析表明IFI27可能调控初始B细胞、CD8⁺ T细胞、调节性T细胞和M0型巨噬细胞等免疫细胞浸润状态，表明其具有调控肿瘤免疫微环境的重要功能。同时，IFI27表达与诸多免疫检查点分子呈显著正相关，且IFI27低表达与免疫治疗响应显著相关，支持其作为治疗靶点的价值。单细胞RNA测序证实IFI27在PAAD中上调，并定位于巨噬细胞等免疫细胞中。实验证实漆黄素可显著下调胰腺癌细胞中IFI27的mRNA及蛋白表达水平。此外，预测姜黄、皂角刺、郁金等22味中药具有潜在治疗作用，中药药性以寒温，苦、甘、辛为主，多归肝、脾、胃经，功效包括活血化瘀、行气止痛、清热解毒，兼以补虚及利水等。结论 IFI27可能作为胰腺腺癌免疫相关的预后基因，漆黄素及多种中药可能作为潜在的治疗药物。

关键词

胰腺腺癌 / 生物信息学 / 干扰素α诱导蛋白27 / 肿瘤微环境 / 免疫治疗 / 分子对接 / 漆黄素 / 姜黄 / 皂角刺 / 郁金

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Objective The study employed bioinformatics to identify prognostic genes associated with pancreatic adenocarcinoma (PAAD) and predict Chinese medicines and active ingredients that regulate these genes. Methods The integration of data from the TCGA, GTEx, and GEO databases was conducted, then screening the prognostic genes through differential gene analysis, COX regression analysis, and survival analysis. The subsequent step involves prognostic efficacy analysis and a verification of the expression trends of the identified key genes. Concurrently perform gene ontology (GO) functional and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses, as well as gene set enrichment analysis (GSEA), to identify potential pathways and biological processes. The impact of feature genes on the infiltration status of immune cells was analyzed, and their correlation with immune checkpoints was further investigated, and tumor immune escape capacity and tumor mutation burden were predicted. Validation of gene expression patterns at the single-cell level. The DSigDB, CTD, and HERB databases are used to predict the potential active ingredients of Chinese medicine and perform molecular docking. Additionally, pharmacokinetic analysis is conducted using Swiss ADME and prediction and analysis of Chinese medicine by Coremine Medical database. Cellular experiments were conducted to validate the regulatory effect of the key active ingredient on the characteristic gene. Results The investigation ultimately led to the identification of the key gene interferon alpha inducible protein 27 (IFI27), which exhibited significantly elevated expression levels in PAAD tissues. Patients exhibiting low IFI27 gene expression demonstrated superior overall survival. Enrichment analysis indicated its potential involvement in various biological processes, including apoptosis, ECM-receptor interaction, regulation of T cell activation, macrophage migration, and signaling pathways such as PI3K-Akt and NF-κB. Immune infiltration analysis indicates that IFI27 may regulate the infiltration status of various immune cells, such as B cells naive, T cells CD8⁺, T cells regulatory (Tregs), and macrophages M0, suggesting that it has an important function in regulating the tumor immune microenvironment. Meanwhile, the expression of IFI27 showed significant positive correlations with multiple immune checkpoint molecules. Further studies have revealed that low expression of IFI27 is significantly associated with the response to immunotherapy, supporting its value as a therapeutic target. Single-cell RNA sequencing verified IFI27 upregulation in PAAD, pinpointing its expression to macrophages and other immune cells. Experiments confirmed that fisetin significantly downregulated both mRNA and protein expression levels of IFI27 in pancreatic cancer cells. Furthermore, a total of 22 Chinese medicines, including Jianghuang (Curcumae Longae Rhizoma), Zaojiaoci (Gleditsiae Spina), and Yujin (Curcumae Radix), were predicted. The four qi encompass cold and warm, and the five flavors are primarily bitter, sweet, and pungent, with a focus on the liver, spleen, and stomach meridians. The main effects are activating blood and resolving stasis, moving qi to relieve pain, and clearing heat and detoxifying, combined with tonifying and inducing diuresis. Conclusion The results of this study imply that IFI27 may serve as a prognostic gene related to PAAD immunity, while fisetin and various Chinese medicines may serve as potential therapeutic drugs.

Key words

pancreatic adenocarcinoma / bioinformatics / IFI27 / tumor microenvironment / immunotherapy / molecular docking / fisetin / Curcumae Longae Rhizoma / Gleditsiae Spina / Curcumae Radix

引用本文

秦冰冰, 李娜, 李静, 周瑞生, 唐莹. 胰腺腺癌预后基因IFI27的生物信息学分析和实验验证及中药治疗预测. 中草药, 2026 , 57 (6) : 2198 -2215 . DOI: 10.7501/j.issn.0253-2670.2026.06.017

QIN Bingbing, LI Na, LI Jing, ZHOU Ruisheng, TANG Ying. Bioinformatics analysis and experimental validation of prognostic gene IFI27 in pancreatic adenocarcinoma with prediction of traditional Chinese medicine treatment[J]. Chinese Traditional and Herbal Drugs, 2026 , 57 (6) : 2198 -2215 . DOI: 10.7501/j.issn.0253-2670.2026.06.017

基金

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中医证候全国重点实验室项目 (SKLKY2024B0013); 广东中医药研究促进会项目 (E4-6401-245-453-001)

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2026年第57卷第6期

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doi: 10.7501/j.issn.0253-2670.2026.06.017

接收时间：2025-11-13
首发时间：2026-09-09

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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