中草药

S100A12在胃癌“炎-癌转化”恶性进程中的免疫调节作用及靶向中药小分子化合物筛选

PDF下载

中草药 | 数据挖掘与循证医学 2026,57(11): 4277-4290

收起

中草药 |数据挖掘与循证医学 2026 , 57 (11) : 4277 -4290

S100A12在胃癌“炎-癌转化”恶性进程中的免疫调节作用及靶向中药小分子化合物筛选

全屏

聂多锐¹, 康睿哲², 杨梅林², 杨冉¹

作者信息

通讯作者:

杨冉

作者简介:

聂多锐: 聂多锐，博士，住院医师，研究方向为中西医结合防治恶性肿瘤。E-mail:ndrise@hotmail.com

Immunomodulatory role of S100A12 in malignant progression of inflammation-cancer transformation in gastric cancer and screening of targeted traditional Chinese medicine-derived small molecules

NIE Duorui, KANG Ruizhe, YANG Meilin, YANG Ran

Affiliations

doi: 10.7501/j.issn.0253-2670.2026.11.017

文章导航

摘要

收起

目的基于多组学数据与孟德尔随机化（Mendelian randomization，MR）因果推断方法，筛选驱动胃黏膜“炎-癌转化”的特征基因，并探索针对这些基因的潜在中药干预策略。方法整合转录组数据与大规模遗传数据，通过差异分析、MR分析与蛋白质互作网络构建，筛选与胃癌风险存在因果关联的特征基因。对筛选出的基因进一步进行生存分析、免疫浸润分析及免疫中介机制解析。以核心特征基因为靶点，对中药小分子化合物库进行分子对接虚拟筛选，预测潜在活性成分。结果在“炎-癌转化”进程中鉴定出30个持续上调的差异基因；MR分析从中确定5个与胃癌风险呈正向因果关联的核心驱动基因（S100A8、CXCR1、S100A9、S100A12、ZBED2）。其中，S100A12的高表达与患者不良预后显著相关，且与中性粒细胞浸润正相关、与B细胞及CD4⁺ T细胞浸润负相关。中介分析提示S100A12可能通过负向调控CD25⁺CD4⁺ T细胞介导促癌效应。全表型组MR分析显示靶向S100A12具有较好的潜在安全性。虚拟筛选获得多个与S100A12蛋白具有高亲和力的中药小分子化合物（C-箭毒碱、酸浆苦味素D等）。结论 S100A12是连接慢性炎症与胃癌发生的关键特征基因，其通过重塑免疫微环境驱动“炎-癌转化”。针对该靶点的中药小分子筛选为干预胃癌前病变提供了先导化合物线索。

关键词

胃癌 / 炎癌转化 / S100A12 / 免疫浸润 / 孟德尔随机化 / C-箭毒碱、酸浆苦味素D

Abstract

收起

Objective To screen characteristic genes driving gastric mucosal “inflammation-cancer transformation” based on multi-omics data and Mendelian randomization (MR) causal inference methods, and to explore potential traditional Chinese medicine (TCM) intervention strategies. Methods Transcriptomic data and large-scale genetic data were integrated. Differential analysis, MR analysis, and protein-protein interaction network construction were performed to screen characteristic genes causally associated with gastric cancer risk. Subsequently, survival analysis, immune infiltration analysis, and immune mediation mechanism analysis were conducted on the identified genes. Finally, molecular docking-based virtual screening was performed on a TCM small-molecule compound library using core characteristic genes as targets to predict potential active components. Results A total of 30 continuously up-regulated differentially expressed genes were identified during the “inflammation-cancer transformation” process. MR analysis identified five core characteristic genes (S100A8, CXCR1, S100A9, S100A12, ZBED2) showing positive causal associations with gastric cancer risk. Among them, high expression of S100A12 was significantly associated with poor prognosis in patients, positively correlated with neutrophil infiltration, and negatively correlated with B-cell and CD4⁺ T-cell infiltration. Mediation analysis revealed that S100A12 may promote carcinogenic effects by negatively regulating CD25⁺CD4⁺ T cells (primarily regulatory T cells). Phenome-wide MR analysis suggested good potential safety for targeting S100A12. Virtual screening identified several TCM small-molecule compounds with high binding affinity to the S100A12 protein (e.g., C-curarine, physalin D). Conclusion S100A12 is a key characteristic gene linking chronic inflammation to gastric cancer development, driving “inflammation-cancer transformation” by reshaping the immune microenvironment. The screening of TCM small molecules targeting this gene provides lead compound candidates for intervening in gastric precancerous lesions. The established research framework integrating multi-omics and reverse drug screening offers a new approach for the precise prevention and drug development of gastric cancer.

Key words

gastric cancer / inflammation-cancer transformation / S100A12 / immune infiltration / Mendelian randomization / C-curarine / physalin D

引用本文

聂多锐, 康睿哲, 杨梅林, 杨冉. S100A12在胃癌“炎-癌转化”恶性进程中的免疫调节作用及靶向中药小分子化合物筛选. 中草药, 2026 , 57 (11) : 4277 -4290 . DOI: 10.7501/j.issn.0253-2670.2026.11.017

NIE Duorui, KANG Ruizhe, YANG Meilin, YANG Ran. Immunomodulatory role of S100A12 in malignant progression of inflammation-cancer transformation in gastric cancer and screening of targeted traditional Chinese medicine-derived small molecules[J]. Chinese Traditional and Herbal Drugs, 2026 , 57 (11) : 4277 -4290 . DOI: 10.7501/j.issn.0253-2670.2026.11.017

基金

收起

国家自然科学基金青年基金项目 (82505345)

参考文献

收起

文献

收起

参考文献引证文献

排序方式：

Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries [J]. CA, 2024,74(3):229-263.
Han B F, Zheng R S, Zeng H M, et al. Cancer incidence and mortality in China, 2022[J]. J Natl Cancer Cent, 2024, 4(1): 47-53.
Luan L, Yang L, Zhang Y T, et al. Highly sensitive multiplexed sensing of miRNAs in a gastric cancer patient’s liquid biopsy [J]. Anal Chem, 2024, 96(50): 20015-20025.
Valero-Almingol A, Montori S, Felípez N, et al. Targetable pathways for drug repurposing in gastric cancer [J]. World J Gastroenterol, 2025, 31(39): 110986.
Correa P. Human gastric carcinogenesis: A multistep and multifactorial process: First American Cancer Society Award Lecture on Cancer Epidemiology and Prevention [J]. Cancer Res, 1992, 52(24): 6735-6740.
Mülder D T, Hahn A I, Huang R J, et al. Prevalence of gastric precursor lesions in countries with differential gastric cancer burden: A systematic review and Meta-analysis [J]. Clin Gastroenterol Hepatol, 2024, 22(8): 1605-1617.e46.
Hahn A I, Mülder D T, Huang R J, et al. Global progression rates of precursor lesions for gastric cancer: A systematic review and Meta-analysis [J]. Clin Gastroenterol Hepatol, 2025, 23(9): 1514-1524.
Pimentel-Nunes P, Libânio D, Marcos-Pinto R, et al. Management of epithelial precancerous conditions and lesions in the stomach (MAPS II): European Society of Gastrointestinal Endoscopy (ESGE), European Helicobacter and Microbiota Study Group (EHMSG), European Society of Pathology (ESP), and Sociedade Portuguesa de Endoscopia Digestiva (SPED) guideline update 2019[J]. Endoscopy, 2019, 51(4): 365-388.
Yeoh K G, Tan P. Mapping the genomic Diaspora of gastric cancer [J]. Nat Rev Cancer, 2022, 22(2): 71-84.
Totoki Y, Saito-Adachi M, Shiraishi Y, et al. Multiancestry genomic and transcriptomic analysis of gastric cancer [J]. Nat Genet, 2023, 55(4): 581-594.
Kim J, Park C, Kim K H, et al. Single-cell analysis of gastric pre-cancerous and cancer lesions reveals cell lineage diversity and intratumoral heterogeneity [J]. NPJ Precis Oncol, 2022, 6(1): 9.
Kreitmaier P, Katsoula G, Zeggini E. Insights from multi-omics integration in complex disease primary tissues [J]. Trends Genet, 2023, 39(1): 46-58.
Emdin C A, Khera A V, Kathiresan S. Mendelian randomization [J]. Jama, 2017, 318(19): 1925.
蒋先伟, 王明航, 李慧茹, 等. 基于孟德尔随机化和GEO数据库识别支气管哮喘的潜在靶点及干预中药预测[J]. 中草药, 2025, 56(3): 919-932.
Thanassoulis G, O’Donnell C J. Mendelian randomization: Nature’s randomized trial in the post-genome era [J]. Jama, 2009, 301(22): 2386.
Yao C, Chen G, Song C, et al. Genome‐wide mapping of plasma protein QTLs identifies putatively causal genes and pathways for cardiovascular disease [J]. Nat Commun, 2018, 9: 3268.
Zhang N Q, Li Y N, Sundquist J, et al. Identifying actionable druggable targets for breast cancer: Mendelian randomization and population-based analyses [J]. EBioMedicine, 2023, 98: 104859.
Li K, Ma X Y, Li Z H, et al. A natural peptide from a traditional Chinese medicine has the potential to treat chronic atrophic gastritis by activating gastric stem cells [J]. Adv Sci, 2024, 11(20): 2304326.
Xu X, Feng L, Liu Y, et al. Differential gene expression profiling of gastric intraepithelial neoplasia and early-stage adenocarcinoma [J]. World J Gastroenterol, 2014, 20(47): 17883-17893.
Võsa U, Claringbould A, Westra H J, et al. Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression [J]. Nat Genet, 2021, 53(9): 1300-1310.
Kurki M I, Karjalainen J, Palta P, et al. FinnGen provides genetic insights from a well-phenotyped isolated population [J]. Nature, 2023, 613(7944): 508-518.
Szklarczyk D, Kirsch R, Koutrouli M, et al. The STRING database in 2023: Protein-protein association networks and functional enrichment analyses for any sequenced genome of interest [J]. Nucleic Acids Res, 2023, 51(D1): D638-D646.
Burgess S, Thompson S G, Collaboration C C G. Avoiding bias from weak instruments in Mendelian randomization studies [J]. Int J Epidemiol, 2011, 40(3): 755-764.
Bowden J, Davey Smith G, Haycock P C, et al. Consistent estimation in Mendelian randomization with some invalid instruments using a weighted Median estimator [J]. Genet Epidemiol, 2016, 40(4): 304-314.
Bowden J, Smith G D, Burgess S. Mendelian randomization with invalid instruments: Effect estimation and bias detection through Egger regression [J]. Int J Epidemiol, 2015, 44(2): 512-525.
Győrffy B. Integrated analysis of public datasets for the discovery and validation of survival-associated genes in solid tumors [J]. Innovation, 2024, 5(3): 100625.
Li B, Severson E, Pignon J C, et al. Comprehensive analyses of tumor immunity: Implications for cancer immunotherapy [J]. Genome Biol, 2016, 17(1): 174.
Orrù V, Steri M, Sidore C, et al. Complex genetic signatures in immune cells underlie autoimmunity and inform therapy [J]. Nat Genet, 2020, 52(10): 1036-1045.
Relton C L, Davey Smith G. Two-step epigenetic Mendelian randomization: A strategy for establishing the causal role of epigenetic processes in pathways to disease [J]. Int J Epidemiol, 2012, 41(1): 161-176.
Burgess S, Daniel R M, Butterworth A S, et al. Network Mendelian randomization: Using genetic variants as instrumental variables to investigate mediation in causal pathways [J]. Int J Epidemiol, 2015, 44(2): 484-495.
Gagliano Taliun S A, VandeHaar P, Boughton A P, et al. Exploring and visualizing large-scale genetic associations by using PheWeb [J]. Nat Genetics, 2020, 52(6): 550-552.
Wang Q L, Dhindsa R S, Carss K, et al. Rare variant contribution to human disease in 281, 104 UK Biobank exomes [J]. Nature, 2021, 597(7877): 527-532.
Xia P P, Ji X D, Yan L, et al. Roles of S100A8, S100A9 and S100A12 in infection, inflammation and immunity [J]. Immunology, 2024, 171(3): 365-376.
Leach S T, Mitchell H M, Geczy C L, et al. S100 calgranulin proteins S100A8, S100A9 and S100A12 are expressed in the inflamed gastric mucosa of Helicobacter pylori-infected children [J]. Can J Gastroenterol, 2008, 22(5): 461-464.
Giai Gianetto Q, Michel V, Douché T, et al. Plasma protein biomarkers to detect early gastric preneoplasia and cancer: A prospective study [J]. Int J Mol Sci, 2025, 26(20): 10114.
Karihtala P, Leivonen S K, Puistola U, et al. Serum protein profiling reveals an inflammation signature as a predictor of early breast cancer survival [J]. Breast Cancer Res, 2024, 26(1): 61.
Elamin A A, Klunkelfuß S, Kämpfer S, et al. A specific blood signature reveals higher levels of S100A12: A potential bladder cancer diagnostic biomarker along with urinary engrailed-2 protein detection [J]. Front Oncol, 2020, 9: 1484.
Thierolf M, Hagmann M L, Pfeffer M, et al. Towards a comprehensive proteome of normal and malignant human colon tissue by 2-D-LC-ESI-MS and 2-DE proteomics and identification of S100A12 as potential cancer biomarker [J]. Proteomics Clin Appl, 2008, 2(1): 11-22.
Holub M, Bartáková E, Stráníková A, et al. Calprotectin and calgranulin C as biomarkers of pancreatic tumors: Baseline levels and level changes after surgery [J]. Mediat Inflamm, 2019, 2019: 6985703.
Liu Z, Pu X F. Orosomucoid 1 interacts with S100A12 and activates ERK signalling to expedite the advancement of bladder cancer [J]. Cell Adh Migr, 2025, 19(1): 1-11.
Wang X J, Sun Z X, Tian W, et al. S100A12 is a promising biomarker in papillary thyroid cancer [J]. Sci Rep, 2020, 10(1): 1724.
Lu C H, Liu J, Yao M Z, et al. Downregulation of S100 calcium binding protein A12 inhibits the growth of glioma cells [J]. BMC Cancer, 2020, 20(1): 261.
Negura I, Pavel-Tanasa M, Danciu M. Regulatory T cells in gastric cancer: Key controllers from pathogenesis to therapy [J]. Cancer Treat Rev, 2023, 120: 102629.
Ma Y M, Han W, Li J, et al. Physalin B not only inhibits the ubiquitin-proteasome pathway but also induces incomplete autophagic response in human colon cancer cells in vitro [J]. Acta Pharmacol Sin, 2015, 36(4): 517-527.

2026年第57卷第11期

PDF下载

引用本文

BibTeX

文章信息

doi: 10.7501/j.issn.0253-2670.2026.11.017

接收时间：2026-01-04
首发时间：2026-09-09

补充材料

相关文章

文章信息

作者

出版历史

收稿日期：2026-01-04

基金

作者信息

参考文献

分享链接

https://castjournals.cast.org.cn/joweb/zcy/CN/10.7501/j.issn.0253-2670.2026.11.017

分享至

全文二维码

扫描看全文

引用本文

BibTeX

本文的引用情况

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

关闭全屏

BibTeX
EndNote
RefWorks
TxT