Article(id=1201177213946257565, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1201177206518145841, articleNumber=null, orderNo=null, doi=10.16438/j.0513-4870.2023-0417, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1680624000000, receivedDateStr=2023-04-05, revisedDate=1687104000000, revisedDateStr=2023-06-19, acceptedDate=null, acceptedDateStr=null, onlineDate=1764312564598, onlineDateStr=2025-11-28, pubDate=1704988800000, pubDateStr=2024-01-12, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1764312564598, onlineIssueDateStr=2025-11-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1764312564598, creator=13701087609, updateTime=1764312564598, updator=13701087609, issue=Issue{id=1201177206518145841, tenantId=1146029695717560320, journalId=1189982191388893191, year='2024', volume='59', issue='1', pageStart='1', pageEnd='268', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1764312562826, creator=13701087609, updateTime=1764312760268, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1201178034725417827, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1201177206518145841, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1201178034725417828, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1201177206518145841, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=214, endPage=224, ext={EN=ArticleExt(id=1201177214411825354, articleId=1201177213946257565, tenantId=1146029695717560320, journalId=1189982191388893191, language=EN, title=Exploring the mechanism of Xihuang Pill's anti-hyperplasia of mammary glands effect based on UPLC-Q-orbitrap-MS technology, columnId=1190335348761793317, journalTitle=Acta Pharmaceutica Sinica, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=

Based on UPLC-Q-orbitrap-MS and biological network analysis tools, the mechanism of Xihuang Pill in improving hyperplasia of mammary glands was systematically analyzed. The rat model of hyperplasia of mammary glands was established by intramuscular injection of estradiol benzoate and progesterone. LC-MS tissue metabolomics was used to explore the key metabolites and metabolic pathways of Xihuang Pill in improving hyperplasia of mammary glands in rat. The network analysis of the key metabolites regulated by Xihuang Pill was carried out by integrating biological network analysis tools, focusing on the key metabolic pathways, and exploring the potential targets of Xihuang Pill to improve hyperplasia of mammary glands. Compared with the control group, there were significant differences in the content of 49 differential metabolites in the tissues of the model group (P < 0.05). Xihuang Pills could significantly call back 17 metabolites such as L-alanine, threonine, indole-3-carboxylic aldehyde, lysine, arginine, alanylleucine, glycyltyrosine, γ-glutamyl leucine, vitamin B3, serine leucine, threonine leucine, isoleucine glutamic acid, γ-glutamyl tyrosine, decanoyl-L-carnitine, uric acid, leucylleucine, S-adenosyl-methionine. Further network analysis and literature research on the key metabolites regulated by Xihuang Pills showed that the AGE-RAGE signaling pathway may be one of the important pathways for Xihuang Pills to improve hyperplasia of mammary glands. STAT3, MAPK1, EGFR, CASP3, CASP8, PRKCA and JUN in the AGE-RAGE signaling pathway may be potential targets for Xihuang Pills to improve hyperplasia of mammary glands. The animal experiment operations involved in this paper follow the provisions of the Animal Ethics Committee of Gansu University of Traditional Chinese Medicine and pass the ethical review of animal experiments (approval number: 2022-705).

, correspAuthors=Tao HAN, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2024 Acta Pharmaceutica Sinica. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Jing-rui WANG, Rui TAO, Xue-li MA, Jun-liang WANG, Tao HAN), CN=ArticleExt(id=1201177216769024429, articleId=1201177213946257565, tenantId=1146029695717560320, journalId=1189982191388893191, language=CN, title=基于UPLC-Q-orbitrap-MS技术探究西黄丸抗乳腺增生的作用机制, columnId=1190335348896011050, journalTitle=药学学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

基于UPLC-Q-orbitrap-MS与生物网络分析工具系统分析西黄丸改善乳腺组织增生的作用机制。肌注苯甲酸雌二醇和黄体酮建立乳腺增生大鼠模型, 采用LC-MS的组织代谢组学探索西黄丸改善乳腺组织增生的关键代谢物和代谢途径。整合生物网络分析工具对西黄丸调节的关键代谢物进行网络分析, 聚焦关键代谢通路, 挖掘西黄丸改善乳腺组织增生的潜在靶点。与空白组比, 模型组大鼠组织中有49种差异代谢物含量有显著差异(P < 0.05), 西黄丸能显著回调L-丙氨酸、苏氨酸、吲哚-3-羧酸醛、赖氨酸、精氨酸、丙氨酰亮氨酸、甘氨酰络氨酸、γ-谷氨酰亮氨酸、维生素B3、丝氨酰亮氨酸、苏氨酰亮氨酸、异亮氨酰谷氨酸、γ-谷氨酰酪氨酸、癸酰-L-肉碱、2, 6, 8-三羟基嘌呤、亮氨酰亮氨酸、S-腺苷-蛋氨酸等17种代谢物。对西黄丸调控的关键代谢物进一步网络分析及文献研究表明, 晚期糖基化终末产物(AGE)-晚期糖基化终产物受体(RAGE)信号通路可能是西黄丸改善乳腺组织增生的重要通路之一, AGE-RAGE信号通路上的STAT3、MAPK1、EGFR、CASP3、CASP8、PRKCA、JUN等7个蛋白可能为西黄丸改善乳腺组织增生的潜在作用靶点。本文涉及的动物实验操作均遵循甘肃中医药大学动物伦理委员会的规定并通过动物实验伦理审查(批号: 2022-705)。

, correspAuthors=韩涛, authorNote=null, correspAuthorsNote=
*韩涛, E-mail:
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Key Laboratory of Pharmacology and Toxicology of TCM of Gansu Province, Lanzhou 730000, China), AuthorCompanyExt(id=1201177217188454868, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, companyId=1201177217171677650, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.甘肃省中药药理与毒理学重点实验室, 甘肃 兰州 730000)])], figs=[ArticleFig(id=1201177219948307110, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=EN, label=null, caption=null, figureFileSmall=YfAyKvOO8lIs46UZW6++Xw==, figureFileBig=kpungVT5tKxaJxiB6ryPWA==, tableContent=null), ArticleFig(id=1201177220036387504, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=CN, label=Figure 1, caption= The average diameter and height of rat breast tissue (mm). A and B: The average diameter and height of nipple. K: Control group; M: Model group; G: Xihuang Pill group. <i>n</i> = 6, <span class="mag-xml-inline-formula"><tex-math id="M1">$ \overline{x} $</tex-math></span> ± <i>s</i>. <sup>**</sup><i>P</i> < 0.01 <i>vs</i> K; <sup>△</sup><i>P</i> < 0.05, <sup>△△</sup><i>P</i> < 0.01 <i>vs</i> M , figureFileSmall=YfAyKvOO8lIs46UZW6++Xw==, figureFileBig=kpungVT5tKxaJxiB6ryPWA==, tableContent=null), ArticleFig(id=1201177220292240063, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=EN, label=null, caption=null, figureFileSmall=9NCFets/f4E0o1e1jvvXGQ==, figureFileBig=Fg0K1GXdY5708nOGiy+HtA==, tableContent=null), ArticleFig(id=1201177220384514754, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=CN, label=Figure 2, caption= Effects of Xihuang Pill on histopathological changes of mammary glands in rats. Red arrows mean the acinar epithelial vacuolar degeneration , figureFileSmall=9NCFets/f4E0o1e1jvvXGQ==, figureFileBig=Fg0K1GXdY5708nOGiy+HtA==, tableContent=null), ArticleFig(id=1201177220522926794, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=EN, label=null, caption=null, figureFileSmall=C0YCxwJlJFa7wdBHX8vkVg==, figureFileBig=KI3z3TYxIVJD0dZtBNhRLQ==, tableContent=null), ArticleFig(id=1201177220623590096, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=CN, label=Figure 3, caption= PCA score plots of QC samples. A: Positive ion detection modes; B: Negative ion detection modes , figureFileSmall=C0YCxwJlJFa7wdBHX8vkVg==, figureFileBig=KI3z3TYxIVJD0dZtBNhRLQ==, tableContent=null), ArticleFig(id=1201177220724253398, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=EN, label=null, caption=null, figureFileSmall=vmydwW51NFl0iN8FkmN16Q==, figureFileBig=1iBr5doTBW+PaAYwgwn0xg==, tableContent=null), ArticleFig(id=1201177220858471130, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=CN, label=Figure 4, caption= Metabolomics profiling analysis in positive and negative ion detection modes of organization. A, B: PLS-DA score plots; C, D: PLS-DA validation plots; E, F: OPLS-DA score plots , figureFileSmall=vmydwW51NFl0iN8FkmN16Q==, figureFileBig=1iBr5doTBW+PaAYwgwn0xg==, tableContent=null), ArticleFig(id=1201177220954940128, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=EN, label=null, caption=null, figureFileSmall=L3A/5EecY4DcgXKXtwoGGg==, figureFileBig=hBwKVYN/CoGMyuCO+QMFuA==, tableContent=null), ArticleFig(id=1201177221034631906, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=CN, label=Figure 5, caption= Relative peak areas of the potential biomarkers in organization regulated by Xihuang Pill. <i>n</i> = 6, <span class="mag-xml-inline-formula"><tex-math id="M2">$ \overline{x} $</tex-math></span> ± <i>s</i>. <sup>*</sup><i>P</i> < 0.05, <sup>**</sup><i>P</i> < 0.01, <sup>***</sup><i>P</i> < 0.001 , figureFileSmall=L3A/5EecY4DcgXKXtwoGGg==, figureFileBig=hBwKVYN/CoGMyuCO+QMFuA==, tableContent=null), ArticleFig(id=1201177221122712295, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=EN, label=null, caption=null, figureFileSmall=s9slVcfMrWL9KheFhRNE0Q==, figureFileBig=DChial6ew9rQ3IIwsqORCQ==, tableContent=null), ArticleFig(id=1201177221214986988, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=CN, label=Figure 6, caption= Metabolic pathway analysis of differential metabolites. A: Model group <i>vs</i> control group; B: Xihuang Pill group <i>vs</i> model group. a: Riboflavin metabolism; b: Arachidonic acid Metabolism; c: Glycine, serine and threoinemetabolism; d: Aminoacyl-tRNA biosynthesis; e: Tyrosine metabolism; f: Pyrimidine metabolism; g: Arginine biosynthesis; h: Cysteine and methionine metabolism; i: Arginine and proline metabolism; j: Glycerophospholipid metabolism , figureFileSmall=s9slVcfMrWL9KheFhRNE0Q==, figureFileBig=DChial6ew9rQ3IIwsqORCQ==, tableContent=null), ArticleFig(id=1201177221311455989, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=EN, label=null, caption=null, figureFileSmall=wOa0I2F/MNoGCyS+JNFffg==, figureFileBig=VAJL9p6IavtbtvxTsE7JEg==, tableContent=null), ArticleFig(id=1201177221395342075, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=CN, label=Figure 7, caption= The network of analysis of KEGG for the anti-breast hyperplasia effect of Xihuang Pill. The top six pathways are AGE-RAGE signaling pathway in diabetic complications, bladder cancer, proteoglycans in cancer, lipid and atherosclerosis, human cytomegalovirus infection, and renin secretion , figureFileSmall=wOa0I2F/MNoGCyS+JNFffg==, figureFileBig=VAJL9p6IavtbtvxTsE7JEg==, tableContent=null), ArticleFig(id=1201177221542142722, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=EN, label=null, caption=null, figureFileSmall=igQ/oWRcijuKjhN/+dYPbA==, figureFileBig=i9VQrHaGVtdri070H3bMqw==, tableContent=null), ArticleFig(id=1201177221630223112, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=CN, label=Figure 8, caption= Protein-protein interaction network diagram of related targets of Xihuang Pill in the treatment of breast hyperplasia. STAT3: Signal transducer and activator of transcription 3; MAPK1: Mitogen-activated protein kinase kinase 1; SRC: Proto-oncogene tyrosine-protein kinase Src; EGFR: Epidermal growth factor receptor; CASP3: Cysteine aspartate-specific protease 3; CASP8: Cysteine aspartate-specific protease 8; PRKCA: Protein kinase C-alpha; JUN: Transcription factor AP-1; LCK: Lymphocyte specific protein tyrosine kinase; ITGB1: Integrin beta1 , figureFileSmall=igQ/oWRcijuKjhN/+dYPbA==, figureFileBig=i9VQrHaGVtdri070H3bMqw==, tableContent=null), ArticleFig(id=1201177221739275022, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=EN, label=null, caption=null, figureFileSmall=pK7BFWeis+E598epG3vysg==, figureFileBig=+Tl4z5L9ftGZn/dYcdAmcg==, tableContent=null), ArticleFig(id=1201177221831549719, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=CN, label=Figure 9, caption= The prediction results of biological network and metabolomics, the pathogenesis of breast hyperplasia, and the corresponding mechanism diagram of the previous research results of the research group. NF-<i>κ</i>B: Nuclear factor <i>κ</i>B; ROS: Reactive oxygen species; PI3K/Akt/mTOR: Phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin; VEGF: Vascular endothelial growth factor; ER<i>α</i>: Estrogen receptor <i>α</i>; PR: Progestrone receptor; MDA: Malondialdehyde; SOD: Superoxide dismutase; <i>Bax</i>/<i>Bcl</i>-2: <i>Bcl</i>-associated x protein/B cell lymphoma-2; bFGF: Basic fibroblast growth factor; PCNA: Proliferating cell nuclear antigen , figureFileSmall=pK7BFWeis+E598epG3vysg==, figureFileBig=+Tl4z5L9ftGZn/dYcdAmcg==, tableContent=null), ArticleFig(id=1201177221978350371, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
NameHMDB IDtR/minm/zAdduct typeFormulaPVIPTrend
Pyroglutamic acid00002672.89128.03[M-H]-C5H7NO30.043*1.53
Arginine00005171.25175.12[M+H]+C6H14N4O20.002**2.07
Tryptophan00136095.36205.10[M+H]+C11H12N2O20.023*1.69
Phosphoric acid00014291.4996.96[M-H]-H3O4P0.026*1.60
Uracil00003004.25113.03[M+H]+C4H4N2O20.037*1.57
16-Hydroxyhexadecanoic acid000629411.03271.23[M-H]-C16H32O30.003**2.00
Glutamine00034231.26147.08[M+H]+C5H10N2O30.015*1.75
Threonine00001671.28120.07[M+H]+C4H9NO30.008**1.85
sn-Glycero-3-phosphocholine00000861.28258.11[M]+C8H21NO6P0.039*1.54
Uric acid00002892.80169.03[M+H]+C5H4N4O30.032*1.59
Piperine00293772.93286.15[M+H-H2O]+C17H19NO30.013*1.72
1-Hexylamine003232313.39102.13[M+H]+C6H15N0.026*1.66
Lysine03017571.11147.11[M+H]+C6H14N2O20.002**2.07
γ-Glutamyl leucine00111715.33261.14[M+H]+C11H20N2O50.002**2.07
Serine00001871.24104.03[M-H]-C3H7NO30.029*1.60
2-Hydroxybutyric acid00000084.00103.04[M-H]-C4H8O30.043*1.52
Pantothenic acid00002105.2320.12[M+H]+C9H17NO50.000**2.20
3, 4-Dihydroxy-L-phenylalanine00001811.33198.08[M+Na]+C9H11NO40.022*1.64
Arachidonic acid000104311.30305.25[M+H]+C20H32O20.026*1.61
Indole-3-carboxyaldehyde00297375.35146.06[M+H]+C9H7NO0.004**2.00
Azelaic acid00007846.55187.10[M-H]-C9H16O40.023*1.65
Melibiose00000481.35365.10[M+Na]+C12H22O110.015*1.74
Threonyl leucine00290655.24233.15[M+H]+C10H20N2O40.004**1.94
Alanyl leucine00286915.20203.14[M+H]+C9H18N2O30.019*1.69
Serylleucine00290435.21219.13[M+H]+C9H18N2O40.003**2.01
N-Acetylneuraminic acid00002301.37308.10[M-H]-C11H19NO90.024*1.65
5, 6-Dihydro-5-methyluracil00000791.38129.07[M+H]+C5H8N2O20.007**1.87
N, N-Dimethylarginine00015391.40203.15[M+H]+C8H18N4O20.011*1.82
Isatin00619332.54148.04[M+H]+C8H5NO20.018*1.72
S-Adenosyl-methionine00011851.34399.14[M+H]+C15H22N6O5S0.010*1.86
Rhodinyl acetate00371867.14216.20[M+NH4]+C12H22O20.003**1.99
1-Hydroxypyrene00131391.23219.08[M+NH4]+C16H10O0.038*1.62
L-Alanine00001611.2788.04[M-H]-C3H7NO20.005**1.90
Dehydrotumulosic acid025096011.98485.36[M+Na]+C31H48O40.023*1.68
Quinic acid00030725.08193.07[M+K]2+C7H12O60.023*1.67
Riboflavin00002445.58377.14[M+H]+C17H20N4O60.012*1.78
Glutamylthreoine00288291.88249.11[M+H]+C9H16N2O60.015*1.75
Leucylleucine00289335.48245.19[M+H]+C12H24N2O30.002**2.08
Glycyltyrosine00288535.13239.10[M+H]+C11H14N2O40.010*1.84
1, 3, 7-Trimethyluric acid00021231.40209.07[M+Hac-H]-C8H10N4O30.032*1.59
Isoleucylglutamate00289065.11261.14[M+H]+C11H20N2O50.035*1.59
γ-Glutamyl tyrosine00117415.18311.12[M+H]+C14H18N2O60.009**1.84
Propyl gallate00338351.23235.06[M+Na]+C10H12O50.027*1.68
Decanoyl-L-carnitine00006517.49316.25[M+H]+C17H33NO40.016*1.71
Creatine phosphate00015111.31212.04[M+H]+C4H10N3O5P0.028*1.65
Isorhamnetin 3-galactoside03017611.36477.14[M-H]-C22H22O120.007**1.89
Medicagenic acid003455110.22501.32[M-H]-C30H46O60.007**1.90
Pyrrhoxanthinol00356966.42570.34[M+2H]2+C37H46O50.018*1.70
5-O-methyllicoricidin00341848.76437.24[M-H]-C27H34O50.028*1.59
), ArticleFig(id=1201177222062236456, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1201177213946257565, language=CN, label=Table 1, caption=

Differential metabolites in organization which were associated with hyperplasia of mammary glands detected by UPLC-MS/MS. ↓ or ↑ means the changes of metabolites in model group compared with control group; *P < 0.05, **P < 0.01, model group vs control group; VIP: Variable importance in the projection

, figureFileSmall=null, figureFileBig=null, tableContent=
NameHMDB IDtR/minm/zAdduct typeFormulaPVIPTrend
Pyroglutamic acid00002672.89128.03[M-H]-C5H7NO30.043*1.53
Arginine00005171.25175.12[M+H]+C6H14N4O20.002**2.07
Tryptophan00136095.36205.10[M+H]+C11H12N2O20.023*1.69
Phosphoric acid00014291.4996.96[M-H]-H3O4P0.026*1.60
Uracil00003004.25113.03[M+H]+C4H4N2O20.037*1.57
16-Hydroxyhexadecanoic acid000629411.03271.23[M-H]-C16H32O30.003**2.00
Glutamine00034231.26147.08[M+H]+C5H10N2O30.015*1.75
Threonine00001671.28120.07[M+H]+C4H9NO30.008**1.85
sn-Glycero-3-phosphocholine00000861.28258.11[M]+C8H21NO6P0.039*1.54
Uric acid00002892.80169.03[M+H]+C5H4N4O30.032*1.59
Piperine00293772.93286.15[M+H-H2O]+C17H19NO30.013*1.72
1-Hexylamine003232313.39102.13[M+H]+C6H15N0.026*1.66
Lysine03017571.11147.11[M+H]+C6H14N2O20.002**2.07
γ-Glutamyl leucine00111715.33261.14[M+H]+C11H20N2O50.002**2.07
Serine00001871.24104.03[M-H]-C3H7NO30.029*1.60
2-Hydroxybutyric acid00000084.00103.04[M-H]-C4H8O30.043*1.52
Pantothenic acid00002105.2320.12[M+H]+C9H17NO50.000**2.20
3, 4-Dihydroxy-L-phenylalanine00001811.33198.08[M+Na]+C9H11NO40.022*1.64
Arachidonic acid000104311.30305.25[M+H]+C20H32O20.026*1.61
Indole-3-carboxyaldehyde00297375.35146.06[M+H]+C9H7NO0.004**2.00
Azelaic acid00007846.55187.10[M-H]-C9H16O40.023*1.65
Melibiose00000481.35365.10[M+Na]+C12H22O110.015*1.74
Threonyl leucine00290655.24233.15[M+H]+C10H20N2O40.004**1.94
Alanyl leucine00286915.20203.14[M+H]+C9H18N2O30.019*1.69
Serylleucine00290435.21219.13[M+H]+C9H18N2O40.003**2.01
N-Acetylneuraminic acid00002301.37308.10[M-H]-C11H19NO90.024*1.65
5, 6-Dihydro-5-methyluracil00000791.38129.07[M+H]+C5H8N2O20.007**1.87
N, N-Dimethylarginine00015391.40203.15[M+H]+C8H18N4O20.011*1.82
Isatin00619332.54148.04[M+H]+C8H5NO20.018*1.72
S-Adenosyl-methionine00011851.34399.14[M+H]+C15H22N6O5S0.010*1.86
Rhodinyl acetate00371867.14216.20[M+NH4]+C12H22O20.003**1.99
1-Hydroxypyrene00131391.23219.08[M+NH4]+C16H10O0.038*1.62
L-Alanine00001611.2788.04[M-H]-C3H7NO20.005**1.90
Dehydrotumulosic acid025096011.98485.36[M+Na]+C31H48O40.023*1.68
Quinic acid00030725.08193.07[M+K]2+C7H12O60.023*1.67
Riboflavin00002445.58377.14[M+H]+C17H20N4O60.012*1.78
Glutamylthreoine00288291.88249.11[M+H]+C9H16N2O60.015*1.75
Leucylleucine00289335.48245.19[M+H]+C12H24N2O30.002**2.08
Glycyltyrosine00288535.13239.10[M+H]+C11H14N2O40.010*1.84
1, 3, 7-Trimethyluric acid00021231.40209.07[M+Hac-H]-C8H10N4O30.032*1.59
Isoleucylglutamate00289065.11261.14[M+H]+C11H20N2O50.035*1.59
γ-Glutamyl tyrosine00117415.18311.12[M+H]+C14H18N2O60.009**1.84
Propyl gallate00338351.23235.06[M+Na]+C10H12O50.027*1.68
Decanoyl-L-carnitine00006517.49316.25[M+H]+C17H33NO40.016*1.71
Creatine phosphate00015111.31212.04[M+H]+C4H10N3O5P0.028*1.65
Isorhamnetin 3-galactoside03017611.36477.14[M-H]-C22H22O120.007**1.89
Medicagenic acid003455110.22501.32[M-H]-C30H46O60.007**1.90
Pyrrhoxanthinol00356966.42570.34[M+2H]2+C37H46O50.018*1.70
5-O-methyllicoricidin00341848.76437.24[M-H]-C27H34O50.028*1.59
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基于UPLC-Q-orbitrap-MS技术探究西黄丸抗乳腺增生的作用机制
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王婧瑞 1 , 陶蕊 1 , 马学莉 1 , 王俊亮 1 , 韩涛 1, 2, *
药学学报 | 研究论文 2024,59(1): 214-224
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药学学报 | 研究论文 2024, 59(1): 214-224
基于UPLC-Q-orbitrap-MS技术探究西黄丸抗乳腺增生的作用机制
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王婧瑞1, 陶蕊1, 马学莉1, 王俊亮1, 韩涛1, 2, *
作者信息
  • 1.甘肃中医药大学药学院, 甘肃 兰州 730000
  • 2.甘肃省中药药理与毒理学重点实验室, 甘肃 兰州 730000

通讯作者:

*韩涛, E-mail:
Exploring the mechanism of Xihuang Pill's anti-hyperplasia of mammary glands effect based on UPLC-Q-orbitrap-MS technology
Jing-rui WANG1, Rui TAO1, Xue-li MA1, Jun-liang WANG1, Tao HAN1, 2, *
Affiliations
  • 1. School of pharmacy, Gansu University of Traditional Chinese Medicine (TCM), Lanzhou 730000, China
  • 2. Key Laboratory of Pharmacology and Toxicology of TCM of Gansu Province, Lanzhou 730000, China
出版时间: 2024-01-12 doi: 10.16438/j.0513-4870.2023-0417
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基于UPLC-Q-orbitrap-MS与生物网络分析工具系统分析西黄丸改善乳腺组织增生的作用机制。肌注苯甲酸雌二醇和黄体酮建立乳腺增生大鼠模型, 采用LC-MS的组织代谢组学探索西黄丸改善乳腺组织增生的关键代谢物和代谢途径。整合生物网络分析工具对西黄丸调节的关键代谢物进行网络分析, 聚焦关键代谢通路, 挖掘西黄丸改善乳腺组织增生的潜在靶点。与空白组比, 模型组大鼠组织中有49种差异代谢物含量有显著差异(P < 0.05), 西黄丸能显著回调L-丙氨酸、苏氨酸、吲哚-3-羧酸醛、赖氨酸、精氨酸、丙氨酰亮氨酸、甘氨酰络氨酸、γ-谷氨酰亮氨酸、维生素B3、丝氨酰亮氨酸、苏氨酰亮氨酸、异亮氨酰谷氨酸、γ-谷氨酰酪氨酸、癸酰-L-肉碱、2, 6, 8-三羟基嘌呤、亮氨酰亮氨酸、S-腺苷-蛋氨酸等17种代谢物。对西黄丸调控的关键代谢物进一步网络分析及文献研究表明, 晚期糖基化终末产物(AGE)-晚期糖基化终产物受体(RAGE)信号通路可能是西黄丸改善乳腺组织增生的重要通路之一, AGE-RAGE信号通路上的STAT3、MAPK1、EGFR、CASP3、CASP8、PRKCA、JUN等7个蛋白可能为西黄丸改善乳腺组织增生的潜在作用靶点。本文涉及的动物实验操作均遵循甘肃中医药大学动物伦理委员会的规定并通过动物实验伦理审查(批号: 2022-705)。

乳腺增生  /  UPLC-Q-orbitrap-MS  /  AGE-RAGE信号通路  /  西黄丸

Based on UPLC-Q-orbitrap-MS and biological network analysis tools, the mechanism of Xihuang Pill in improving hyperplasia of mammary glands was systematically analyzed. The rat model of hyperplasia of mammary glands was established by intramuscular injection of estradiol benzoate and progesterone. LC-MS tissue metabolomics was used to explore the key metabolites and metabolic pathways of Xihuang Pill in improving hyperplasia of mammary glands in rat. The network analysis of the key metabolites regulated by Xihuang Pill was carried out by integrating biological network analysis tools, focusing on the key metabolic pathways, and exploring the potential targets of Xihuang Pill to improve hyperplasia of mammary glands. Compared with the control group, there were significant differences in the content of 49 differential metabolites in the tissues of the model group (P < 0.05). Xihuang Pills could significantly call back 17 metabolites such as L-alanine, threonine, indole-3-carboxylic aldehyde, lysine, arginine, alanylleucine, glycyltyrosine, γ-glutamyl leucine, vitamin B3, serine leucine, threonine leucine, isoleucine glutamic acid, γ-glutamyl tyrosine, decanoyl-L-carnitine, uric acid, leucylleucine, S-adenosyl-methionine. Further network analysis and literature research on the key metabolites regulated by Xihuang Pills showed that the AGE-RAGE signaling pathway may be one of the important pathways for Xihuang Pills to improve hyperplasia of mammary glands. STAT3, MAPK1, EGFR, CASP3, CASP8, PRKCA and JUN in the AGE-RAGE signaling pathway may be potential targets for Xihuang Pills to improve hyperplasia of mammary glands. The animal experiment operations involved in this paper follow the provisions of the Animal Ethics Committee of Gansu University of Traditional Chinese Medicine and pass the ethical review of animal experiments (approval number: 2022-705).

hyperplasia of mammary glands  /  UPLC-Q-orbitrap-MS  /  AGE-RAGE signaling pathway  /  Xihuang Pill
王婧瑞, 陶蕊, 马学莉, 王俊亮, 韩涛. 基于UPLC-Q-orbitrap-MS技术探究西黄丸抗乳腺增生的作用机制. 药学学报, 2024 , 59 (1) : 214 -224 . DOI: 10.16438/j.0513-4870.2023-0417
Jing-rui WANG, Rui TAO, Xue-li MA, Jun-liang WANG, Tao HAN. Exploring the mechanism of Xihuang Pill's anti-hyperplasia of mammary glands effect based on UPLC-Q-orbitrap-MS technology[J]. Acta Pharmaceutica Sinica, 2024 , 59 (1) : 214 -224 . DOI: 10.16438/j.0513-4870.2023-0417
乳腺增生(hyperplasia of mammary glands, HMG), 是乳腺组织的增生性病变, 伴有乳腺肿块和疼痛症状, 在40岁以上绝经前妇女群体中发病率高达90%。乳腺增生发病机制与乳腺癌相似, 癌变率1.25%~50%[1, 2], 严重影响患者的日常生活[3]。传统中药是替代医学和补充医学不可或缺的组成部分[4]。本研究选用清代王洪绪《外科证治全生集•卷四》的西黄丸, 由牛黄、麝香、乳香和没药4味药组成。牛黄性寒芳香、清热解毒豁痰, 麝香辛香活血化瘀, 佐以乳香、没药活血行气止痛, 主治乳岩、瘰疬、痰核等, 现代临床治疗乳腺增生具有疗效突出、不良反应小的优势[5, 6]
代谢组学是最接近表型的组学, 能对生物体相对分子质量小于1 000的内源性代谢物进行定性、定量及动态监测[7], 提供与机体状态或者疾病相关的代谢特征[8]。其中非靶向代谢检测技术, 能够反映代谢物之间的复杂的相互作用, 具有信息覆盖范围广、确定新生物标志物等优点[9]。以网络理论和系统生物学为基础的分析方法, 是探索药物作用机制和发现新药物的实用工具, 与中药复方多成分、多靶点、多样化的特点相符[10]。课题组前期研究结果表明: 西黄丸可以改善雌孕激素诱导大鼠乳腺增生组织的增生形态, 增强免疫清除功能, 调节自由基代谢、改善微环境[11], 但具体机制不明。本研究旨在利用代谢组学及生物网络分析工具深入探索西黄丸在改善乳腺组织增生过程中可能存在的生物活性化合物和潜在的作用机制, 以期为乳腺增生今后的临床治疗和研究提供新思路。
动物  SPF级SD雌性未孕大鼠(200 ± 20 g) 购于甘肃中医药大学实验动物中心[许可证号: SCXK (甘) 2020-0001]。实验开始前适应性饲养7天, 饲养环境温度为(25 ± 2) ℃, 湿度为(55 ± 5) %, 12 h明暗交替光照, 实验期间动物自由摄食和饮用水。动物实验遵循甘肃中医药大学动物伦理委员会的规定并通过动物实验伦理审查(批号: 2022-705)。
药物  西黄丸(规格: 每20丸为1 g, 北京同仁堂科技发展股份有限公司制药厂, 批号: 19041292); 苯甲酸雌二醇注射液(规格: 2 mL: 4 mg, 宁波第二激素厂, 批号: 220301); 黄体酮注射液(规格: 2 mL: 20 mg, 宁波第二激素厂, 批号: 220224)。
仪器与主要试剂  质谱仪(型号: Q Exactive Plus, 美国Thermo Scientific公司); 超高压液相色谱仪(型号: Nexera X2 LC-30AD, 日本Shimadzu公司); 色谱柱(型号: ACQUITY UPLC® HSS T3) (100 mm × 2.1 mm, 1.8 µm) (美国Waters公司); 超声波系统(型号: Bioruptor, 比利时Diagenode公司); 离心机(型号: Centrifuge 5424R, 德国Eppendorf公司); 冰冻切片机(型号: CRYOSTAR NX50, 赛默飞世尔科技有限公司); 正置光学显微镜(型号: NIKON ECLIPSE E100, 日本尼康); 乙腈、甲醇、甲酸(美国Millipore公司, 批号:JB127130、11215607、C12122679); 氨水(德国Merck公司, 批号: 2180047); 无水乙醇、二甲苯(国药集团化学试剂有限公司, 批号: 100092683、10023418)。
分组与给药  SPF级SD雌性未孕大鼠18只, 随机分为空白组、模型组、西黄丸组2.16 g·kg-1 (此剂量参照本课题组前期的药效研究[11-13]), 每组6只。空白组和模型组ig等体积的生理盐水。
西黄丸临床用量每天6 g (一次1瓶, 每瓶3 g, 一日2次), 本研究用研钵将西黄丸磨细, 蒸馏水配制成剂量为2.16 g·kg-1剂量的混悬溶液(西黄丸0.54 g·kg-1相当于人临床等效剂量)。
乳腺增生大鼠模型的建立  参照课题组前期造模方法[11-13]。空白组im等量生理盐水每天0.05 mL。模型组连续25天肌肉注射苯甲酸雌二醇注射液0.5 mg·kg-1, 然后肌肉注射黄体酮注射液5 mg·kg-1, 连续5天, 共30天, 建立乳腺增生大鼠模型。
表观及组织病理指标  游标卡尺精确测量大鼠第3对乳头直径和高度, 取大鼠第3对乳腺组织于4%多聚甲醛溶液固定, 常规HE染色(hematoxylin-eosin staining), 光镜下观察乳腺组织病理形态。
LC-MS代谢组学数据收集
大鼠组织样本的采集  末次给药后, 摘取大鼠第2对乳腺组织用冰生理盐水漂洗至无血色, 吸水纸吸干, 剪成小块后在液氮中迅速冷却, 转移至-80 ℃冰箱冻存待后续代谢组学的分析。
组织代谢样本的制备  取组织样品于4 ℃解冻, 称取50 mg组织样本, 加入200 μL甲醇-乙腈-水(2∶2∶1) 研磨, 再加800 μL甲醇-乙腈-水(2∶2∶1) 混匀。冰浴超声30 min, -20 ℃静置2 h, 16 000 ×g、4 ℃离心20 min, 取上清。质谱检测时加入80 μL甲醇-水溶液(1∶1) 复溶, 20 000 ×g、4 ℃离心20 min, 取上清进样分析。进样时每6个样本插入一个质量控制(quality control, QC) 样本, QC样本为所有样品等量混合的样本, 用于平衡色谱-质谱系统及测定仪器状态。
色谱条件  整个分析过程中样品置于4 ℃自动进样器。Waters ACQUITY UPLC® HSS T3 (100 mm × 2.1 mm, 1.8 µm) 色谱柱。进样量6 μL, 柱温40 ℃, 流速0.3 mL·min-1。色谱流动相(A) 0.1%甲酸水溶液-(B) 乙腈, 色谱梯度(0~2 min, 0% B; 2~6 min, 0%~48% B; 6~10 min, 48%~100% B; 10~12 min, 100% B; 12~12.1 min, 100%~0% B; 12.1~15 min, 0% B)。
质谱条件  每例样品分别采用电喷雾电离(ESI) 进行正离子(+) 和负离子(-) 模式检测。样品经UPLC分离后用QE Plus质谱仪进行质谱分析, 使用HESI源进行离子化, 喷雾电压: 3.8 kV (+) 和3.2 kV (-); 毛细管温度: 320 ℃; 鞘气流速: 30 arb; 辅助气流速: 5 arb; 质谱检测采集范围: m/z 70~1 050。
LC-MS数据处理  原始数据采用MSDIAL软件进行峰对齐、保留时间校正和提取峰面积。代谢物结构鉴定采用精确质量数匹配(质量偏差 < 20 ppm) 和二级谱图匹配(质量偏差 < 0.02 Da) 的方式, 检索HMDB、MassBank等公共数据库。对提取得到的数据, 删除组内缺失值> 50%的离子峰不参与后续统计分析; 对正负离子数据分别进行总峰面积归一化, 整合正负离子峰并应用R软件进行模式识别。数据经Unit Variance Scaling (UV) 预处理后进行主成分分析(principal component analysis, PCA)、偏最小二乘法判别分析(partial least squares discrimination analysis, PLS-DA) 和正交偏最小二乘法判别分析(orthogonal partial least squares discriminant analysis, OPLS-DA)。结合OPLS-DA分析的VIP (variable importance in the projection) > 1及t检验(P < 0.05) 筛选空白对照组与乳腺增生模型组之间显著改变的差异变量。结合二级碎片离子和在线数据库HMDB对筛选出的差异代谢物进行指认鉴定。
关键代谢物生物网络的构建与分析  将西黄丸调节的关键代谢物导入Pubchem数据库(http://pubchem.ncbi.nlm.nih.gov) 查询相应成分的Canonical SMILE号, 利用Swiss TargetPrediction数据库(http://www.swisstargetprediction.ch/) 进行靶点基因预测。通过GeneCards数据库(https://genecards.weizmann.ac.il/v3/) 输入关键词“hyperplasia of mammary glands (乳腺增生)”收集疾病基因, 通过韦恩图(Venn diagram) 求关键代谢物相关基因和疾病基因的交集。共有基因利用Cytoscape 3.9.1软件插件Cluego进行KEGG富集分析。利用STRING (https://string-db.org/) 在线数据库对共有基因进行蛋白质-蛋白质相互作用网络(protein-protein interaction, PPI) 的构建, 构建网络导入Cytoscape 3.9.1软件, 利用插件CytoHubba的degree算法筛选得到交互作用评分在前10的基因, 提示这些基因可能在西黄丸治疗乳腺增生中发挥重要作用。利用MetaboAnalyst 5.0网站的Joint-Pathways Analyst板块, 对得到的10个潜在靶点进行联合通路分析, 分析靶点和通路的关系。
统计学分析  GraphPad Prism 9软件作图。数据以平均值± SEM表示, 采用SPSS 26.0软件进行统计分析, 通过t检验比较两组之间的统计学差异, 通过单因素方差分析(One-Way ANOVA) 比较多组之间的统计学差异, P < 0.05被认为数据之间存在显著性差异。
与空白组比较, 模型组大鼠的乳头直径、高度均增大, 差异具有统计学意义(P < 0.01); 与模型组比较, 西黄丸组大鼠乳头直径和高度明显减小, 差异具有统计学意义(P < 0.05、P < 0.01) (图 1)。
HE染色结果显示, 空白组乳腺小叶和腺泡结构正常, 腺泡数量少, 管腔未见扩张, 乳腺间质未见纤维组织增生; 模型组乳腺小叶体积增大, 腺泡数量增多, 大量腺泡上皮空泡变性, 较多腺腔扩张, 管腔中可见脱落的上皮细胞及其大量分泌物; 西黄丸组乳腺组织增生程度较轻, 腺泡数减少, 腺泡上皮空泡变性减少, 腺泡腔和腺导管腔扩张不明显, 分泌物减少(图 2)。
将QC样本正、负离子检测模式下的质谱总离子流图采用无监督PCA模式进行聚类分析考察仪器系统的稳定性(图 3AB)。结果表明空白组、模型组与西黄丸组分离明显, QC样品聚类良好, 表明建立的代谢组学分析方法稳定, 数据质量可靠。
对大鼠组织样本代谢轮廓进行PLS-DA分析(图 4AB)。空白组、模型组和西黄丸组显著分开, 表明乳腺增生大鼠组织代谢轮廓发生明显变化, 造模成功且西黄丸能改善乳腺增生大鼠组织代谢异常。所有组进行PLS-DA代谢轮廓分析后, 对空白组和模型组进行正负离子模型验证(图 4CD)。正、负离子模式下评价指标分别为R2Y (模型对Y矩阵的解释率) = 0.998, Q2 (模型预测能力) = 0.761; R2Y = 0.998, Q2 = 0.680, 表明模型拟合性好, 预测具有可靠性。此外, 用OPLS-DA分析评估空白组和模型组之间的代谢物正负离子模式下的差异, 在组织中空白组和模型组之间差异明显(图 4EF)。综上结果, 西黄丸可以改善乳腺增生诱发的代谢紊乱。
根据组织代谢物的质荷比、分子式、二级碎片离子、保留时间, 并结合在线数据库HMDB对空白组与模型组之间显著变化的代谢物进行鉴定, 共指认出49个差异代谢物(表 1), 与空白组相比有43种差异代谢物增加, 6种差异代谢物减少。其中有17种代谢物在西黄丸给药后显著回调(P < 0.05), 包括L-丙氨酸、苏氨酸、吲哚-3-羧酸醛、赖氨酸、精氨酸、丙氨酰亮氨酸、甘氨酰络氨酸、γ-谷氨酰亮氨酸、维生素B3、丝氨酰亮氨酸、苏氨酰亮氨酸、异亮氨酰谷氨酸、γ-谷氨酰酪氨酸、癸酰-L-肉碱、2, 6, 8-三羟基嘌呤、亮氨酰亮氨酸、S-腺苷-蛋氨酸等(图 5)。
将差异代谢物导入Metaboanalyst 5.0数据库中进行代谢通路分析。代谢通路影响值(impact value) > 0.05的通路被视为贡献值最大的代谢通路。共筛选得到10条与乳腺增生显著相关的代谢通路(图 6A), 主要包括核黄素代谢; 花生四烯酸代谢; 甘氨酸、丝氨酸和苏氨酸代谢; 氨酰-tRNA生物合成; 酪氨酸代谢; 嘧啶代谢; 精氨酸生物合成; 半胱氨酸和甲硫氨酸代谢; 精氨酸和脯氨酸代谢; 甘油磷脂代谢。在乳腺增生模型影响的10条代谢通路中, 西黄丸能调节其中的3条, 主要包括精氨酸生物合成; 半胱氨酸和甲硫氨酸代谢; 精氨酸和脯氨酸代谢(图 6B)。
运用PubChem数据库检索西黄丸调节的17种差异代谢物相应的Canonical SMILES号, 运用Swiss TargetPrediction进行靶点预测, 去重后得354种。通过Gene-Cards网站输入关键词“hyperplasia of mammary glands”搜索疾病基因靶点, 共得到5 028种。通过Venny 2.1.0对代谢物和疾病基因靶点做交集分析, 得二者共有靶点228种。应用Cytoscape软件插件Cluego对筛选出228种共有靶点进行KEGG富集分析(图 7)。KEGG富集分析结果显示西黄丸调节的主要通路包括代谢并发症中的AGE-RAGE信号通路、脂质和动脉粥样硬化、癌症中的蛋白聚糖、膀胱癌、人巨细胞病毒感染和肾素分泌等。
将韦恩图所得228种共有靶点导入STRING在线数据库分析, 得到PPI网络(图 8)。将此PPI网络导入Cytoscape软件, 利用其CytoHubba插件对网络中的节点进行排名, 以degree算法获得排名前十的蛋白靶点STAT3、MAPK1、SRC、EGFR、CASP3、CASP8、PRKCA、JUN、LCK、ITGB1, 其中STAT3、MAPK1、EGFR、CASP3、CASP8、PRKCA、JUN主要分布在代谢并发症的AGE-RAGE信号通路。通过查阅大量文献及课题组前期研究结果, 建立生物网络与代谢组学的预测结果、乳腺增生发病机制、课题组前期研究结果的对应机制图(图 9)。将代谢结果、可能发挥作用的通路蛋白靶点、抗氧化及炎症、细胞异常自噬凋亡和血液黏稠度等与乳腺增生发病机制相关的三个层面建立有效联系, 为今后乳腺增生病的防治提供理论依据。
课题组前期研究结果表明西黄丸可以减小乳腺增生大鼠的乳头直径和高度, 改善乳腺增生组织的病理变化。本研究利用UPLC-Q-orbitrap-MS技术和多元统计分析方法, 发现西黄丸可以显著回调由雌孕激素诱导乳腺增生模型大鼠体内的17种内源性差异代谢物, 还可调节由乳腺增生模型影响3条代谢通路, 包括精氨酸生物合成; 半胱氨酸和甲硫氨酸代谢; 精氨酸和脯氨酸代谢。精氨酸是人体必需氨基酸, 在一氧化氮合酶(NOS) 作用下转化为一氧化氮。低浓度的一氧化氮可以保护细胞, 过量导致凋亡[14]。精氨酸代谢在炎症、细胞激活和细胞生长等基本过程中的作用已被证明与肿瘤发生密切相关[15, 16], 且精氨酸酶在乳腺癌中的表达和活性呈增长趋势[17]。将西黄丸调节的17种关键代谢物的作用靶点与乳腺增生疾病靶点取交集, 并对主要交集靶点进行生物网络工具分析, 推断AGE-RAGE信号通路为西黄丸改善乳腺增生组织的主要通路之一, 主要靶点为STAT3、MAPK1、EGFR、CASP3、CASP8、PRKCA、JUN等。
AGEs能促进乳腺癌细胞的增殖和迁移[18]。RAGE及其配体是组织疾病进展及严重化程度的潜在生物标志物[19], 能通过限制细胞凋亡促进血管生成、细胞迁移、增殖、侵袭和转移[20-22]。AGEs与RAGE的非特异性表面受体相互作用, 可激活与细胞存活、炎症和癌症相关的细胞核因子-κB (NF-κB)、MAP激酶(MAPKs) 通路和PI3K/AKT/mTOR信号通路[23], 并在不同病理的发展过程中发挥作用[24-26]
研究表明, 炎症和氧化应激机制在乳腺增生的发生发展中至关重要[27]。NF-κB的激活、促炎症细胞因子的释放和氧化应激与AGEs、RAGE的积累有关。AGE是癌症病变进展中的关键促炎症因子之一, 协同诱导MAPK激活NF-κB, 上调炎症细胞因子[28]。ROS水平的升高是AGE-RAGE轴诱导细胞凋亡的主要介质之一, 与促凋亡因子和caspase级联反应相关[29, 30]。ROS的积累也会加速NF-κB的激活, 增加表达和释放促炎细胞因子导致细胞损伤[31]。前期研究表明, 西黄丸可通过调节雌激素受体亚型ERα、PR的表达, 减弱激素在靶细胞上的生物学效应, 增强SOD活性来抑制脂质过氧化反应, 起到抗乳腺增生的作用[13]
AGEs-RAGE信号的激活会诱导细胞死亡以平衡组织稳态, 同时它自身促生存自噬会限制癌细胞的凋亡[31]。乳腺上皮细胞增殖过度及凋亡减弱会加重乳腺增生的病症甚至癌化[32]。AGEs诱导的氧化应激会激活MAPKs通路[33, 34]。MAPKs是参与凋亡信号传导的丝氨酸/苏氨酸激酶家族。AGEs与ROS结合也会激活p38 MAPK, 进而协调促凋亡的caspase-3级联反应[34]。Caspase-3能特异性地切割, 导致DNA断裂和细胞凋亡, 是细胞凋亡的主要执行者[35, 36]。PI3K/AKT/mTOR信号传导通路, 也是细胞自噬调控的主要节点[37, 38]。PI3K通过糖酵解和脂肪生成为癌细胞的生长提供基本代谢物[39]。AKT持续激活可能有助于肿瘤细胞的存活[40, 41]。活化的AKT通过磷酸化mTOR的Ser-448位点激活mTOR, 被激活的mTOR将大大提高RNA的翻译效率, 从而调节细胞生长[42]。有研究表明, 牛黄-麝香联合可以抑制PI3K/AKT/mTOR信号通路, 进而抑制抗凋亡基因Bcl-2的表达[43]。前期研究表明, 西黄丸可以通过上调抗细胞凋亡蛋白Bax/Bcl-2的转录促进乳腺细胞凋亡[32]
血管是机体输送所需物质的基础[44], 乳腺增生组织存在丰富的新生血管, 为乳腺增生提供所需物质[45]。研究表明, 乳腺增生与血液黏稠度有关, 血液黏度增大, 血行不畅, 阻于乳络易引起乳房疼痛, 造成乳腺增生病的发生[46, 47]。AGE配体与其受体的协同作用与VEGF和金属蛋白酶2 (MMP-2) 的上调以及ve-钙黏蛋白/连环蛋白复合物的破坏有关, 这可能有利于血管生成[48]。前期研究结果表明, 西黄丸能够降低乳腺增生大鼠血液黏度, 保持血行畅通, 并且能够降低乳腺组织VEGF、bFGF、PCNA表达, 抑制乳腺组织新生血管生成和乳腺上皮细胞增殖[6]
综上, 利用代谢组学技术对大鼠乳腺组织样本进行分析, 西黄丸能显著回调的17种关键代谢物。通过生物网络分析工具对西黄丸调节的17种关键代谢物进行网络分析, 并结合相关文献推断AGE-RAGE信号通路可能通过激活NF-κB、MAPK、PI3K/Akt/mTOR及VEGF等多种通路, 从抗氧化及炎症、细胞异常自噬凋亡和血液黏稠度三个与乳腺增生机制相关的层面去发挥作用。此推断与利用UPLC-Q-orbitrap-MS技术和多元统计分析方法得出乳腺增生大鼠组织主要以精氨酸代谢为主, 且精氨酸代谢通路已被证明在炎症、细胞激活和细胞生长等基本过程发挥的作用与肿瘤密切相关相应证, 并与课题组前期西黄丸的疗效结果紧密对应。但是这些通路之间往往不是单独发挥作用, 协同的机理并不是很明确。本课题组之后的研究将深入挖掘这些不同通路之间相互作用的原理, 进一步明确西黄丸改善乳腺增生过程与结果之间的作用机制。
作者贡献: 韩涛负责研究思路的提出; 王婧瑞进行实验、处理数据和撰写草稿; 韩涛、王婧瑞修改论文; 陶蕊、马学莉和王俊亮查阅部分文献。所有作者阅读并认可的终稿。
利益冲突: 本文不存在任何利益冲突。
  • 国家自然科学基金资助项目(82160853)
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doi: 10.16438/j.0513-4870.2023-0417
  • 接收时间:2023-04-05
  • 首发时间:2025-11-28
  • 出版时间:2024-01-12
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  • 收稿日期:2023-04-05
  • 修回日期:2023-06-19
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国家自然科学基金资助项目(82160853)
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    1.甘肃中医药大学药学院, 甘肃 兰州 730000
    2.甘肃省中药药理与毒理学重点实验室, 甘肃 兰州 730000

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2种不同金属材料的力学参数

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genus
种数
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Percentage of
total species (%)

Genus
种数
Number of
species
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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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