• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

相似文献

1
Models for measuring metabolic chemical changes in the metastasis of high grade serous ovarian cancer: fallopian tube, ovary, and omentum.用于测量高级别浆液性卵巢癌转移代谢化学变化的模型:输卵管、卵巢和大网膜。
Mol Omics. 2021 Dec 6;17(6):819-832. doi: 10.1039/d1mo00074h.
2
The Many Microenvironments of Ovarian Cancer.卵巢癌的多种微环境
Adv Exp Med Biol. 2020;1296:199-213. doi: 10.1007/978-3-030-59038-3_12.
3
Ex Vivo Ovarian Culture to Model the Initial Metastasis in Ovarian Cancer.离体卵巢培养模型模拟卵巢癌的早期转移。
Methods Mol Biol. 2022;2424:189-198. doi: 10.1007/978-1-0716-1956-8_13.
4
Fallopian tube initiation of high grade serous ovarian cancer and ovarian metastasis: Mechanisms and therapeutic implications.输卵管起始部高级别浆液性卵巢癌及卵巢转移:机制与治疗意义。
Cancer Lett. 2020 Apr 28;476:152-160. doi: 10.1016/j.canlet.2020.02.017. Epub 2020 Feb 15.
5
High-grade serous ovarian cancer arises from fallopian tube in a mouse model.高级别浆液性卵巢癌源于小鼠模型中的输卵管。
Proc Natl Acad Sci U S A. 2012 Mar 6;109(10):3921-6. doi: 10.1073/pnas.1117135109. Epub 2012 Feb 13.
6
Extracellular matrix in high-grade serous ovarian cancer: Advances in understanding of carcinogenesis and cancer biology.高级别浆液性卵巢癌中的细胞外基质:对致癌作用和癌症生物学认识的进展
Matrix Biol. 2023 Apr;118:16-46. doi: 10.1016/j.matbio.2023.02.004. Epub 2023 Feb 11.
7
Imaging Mass Spectrometry Reveals Crosstalk between the Fallopian Tube and the Ovary that Drives Primary Metastasis of Ovarian Cancer.成像质谱揭示了输卵管与卵巢之间的串扰,这种串扰驱动卵巢癌的原发性转移。
ACS Cent Sci. 2018 Oct 24;4(10):1360-1370. doi: 10.1021/acscentsci.8b00405. Epub 2018 Oct 9.
8
Modeling high-grade serous ovarian carcinogenesis from the fallopian tube.从输卵管建模高级别浆液性卵巢癌发生。
Proc Natl Acad Sci U S A. 2011 May 3;108(18):7547-52. doi: 10.1073/pnas.1017300108. Epub 2011 Apr 18.
9
[Significance and expression of PAX8, PAX2, p53 and RAS in ovary and fallopian tubes to origin of ovarian high grade serous carcinoma].[PAX8、PAX2、p53和RAS在卵巢及输卵管中的表达及其对卵巢高级别浆液性癌起源的意义]
Zhonghua Fu Chan Ke Za Zhi. 2017 Oct 25;52(10):687-696. doi: 10.3760/cma.j.issn.0529-567X.2017.10.008.
10
GATA3 as a master regulator for interactions of tumor-associated macrophages with high-grade serous ovarian carcinoma.GATA3 作为肿瘤相关巨噬细胞与高级别浆液性卵巢癌相互作用的主调控因子。
Cell Signal. 2020 Apr;68:109539. doi: 10.1016/j.cellsig.2020.109539. Epub 2020 Jan 11.

引用本文的文献

1
Comparative proteomic analysis of the ECM composition of the human omentum and mesentery, the main sites of ovarian cancer metastasis.人网膜和肠系膜(卵巢癌转移的主要部位)细胞外基质成分的比较蛋白质组学分析。
bioRxiv. 2025 Jul 31:2025.07.28.667199. doi: 10.1101/2025.07.28.667199.
2
Branched-Chain Amino Acid Catabolism Promotes Ovarian Cancer Cell Proliferation via Phosphorylation of mTOR.支链氨基酸分解代谢通过mTOR磷酸化促进卵巢癌细胞增殖。
Cancer Res Commun. 2025 Apr 1;5(4):569-579. doi: 10.1158/2767-9764.CRC-24-0532.
3
Branched-chain amino acid catabolism promotes ovarian cancer cell proliferation via phosphorylation of mTOR.支链氨基酸分解代谢通过mTOR磷酸化促进卵巢癌细胞增殖。
bioRxiv. 2024 Oct 18:2024.10.15.618560. doi: 10.1101/2024.10.15.618560.
4
Machine Learning Reveals Lipidome Remodeling Dynamics in a Mouse Model of Ovarian Cancer.机器学习揭示了卵巢癌小鼠模型中的脂质组重塑动态。
J Proteome Res. 2023 Jun 2;22(6):2092-2108. doi: 10.1021/acs.jproteome.3c00226. Epub 2023 May 23.
5
Machine Learning Reveals Lipidome Remodeling Dynamics in a Mouse Model of Ovarian Cancer.机器学习揭示卵巢癌小鼠模型中的脂质组重塑动态
bioRxiv. 2023 Jan 4:2023.01.04.520434. doi: 10.1101/2023.01.04.520434.
6
Home-Built Spinning Apparatus for Drying Agarose-Based Imaging Mass Spectrometry Samples.自制旋转装置,用于干燥基于琼脂糖的成像质谱样品。
J Am Soc Mass Spectrom. 2022 Jul 6;33(7):1325-1328. doi: 10.1021/jasms.2c00044. Epub 2022 May 31.

本文引用的文献

1
Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries.《全球癌症统计数据 2020:全球 185 个国家和地区 36 种癌症的发病率和死亡率估计》。
CA Cancer J Clin. 2021 May;71(3):209-249. doi: 10.3322/caac.21660. Epub 2021 Feb 4.
2
Ovulatory Follicular Fluid Facilitates the Full Transformation Process for the Development of High-Grade Serous Carcinoma.排卵滤泡液促进高级别浆液性癌发生发展的完整转化过程。
Cancers (Basel). 2021 Jan 26;13(3):468. doi: 10.3390/cancers13030468.
3
Cancer Statistics, 2021.癌症统计数据,2021.
CA Cancer J Clin. 2021 Jan;71(1):7-33. doi: 10.3322/caac.21654. Epub 2021 Jan 12.
4
Targeting progesterone signaling prevents metastatic ovarian cancer.靶向孕激素信号通路可预防转移性卵巢癌。
Proc Natl Acad Sci U S A. 2020 Dec 15;117(50):31993-32004. doi: 10.1073/pnas.2013595117. Epub 2020 Dec 1.
5
H-NMR spectroscopy metabonomics of reactive, ovarian carcinoma and hepatocellular carcinoma ascites.反应性、卵巢癌和肝细胞癌腹水的氢核磁共振波谱代谢组学
Pleura Peritoneum. 2020 May 12;5(2):20200113. doi: 10.1515/pp-2020-0113. eCollection 2020 Jun 1.
6
Ovarian BDNF promotes survival, migration, and attachment of tumor precursors originated from p53 mutant fallopian tube epithelial cells.卵巢中的脑源性神经营养因子可促进源自p53突变型输卵管上皮细胞的肿瘤前体细胞的存活、迁移和黏附。
Oncogenesis. 2020 May 29;9(5):55. doi: 10.1038/s41389-020-0243-y.
7
Colorectal cancer statistics, 2020.2020 年结直肠癌统计数据。
CA Cancer J Clin. 2020 May;70(3):145-164. doi: 10.3322/caac.21601. Epub 2020 Mar 5.
8
Adipocyte-Induced FABP4 Expression in Ovarian Cancer Cells Promotes Metastasis and Mediates Carboplatin Resistance.脂肪细胞诱导卵巢癌细胞中 FABP4 的表达促进转移并介导卡铂耐药性。
Cancer Res. 2020 Apr 15;80(8):1748-1761. doi: 10.1158/0008-5472.CAN-19-1999. Epub 2020 Feb 13.
9
Air-liquid interface cell culture: From airway epithelium to the female reproductive tract.气液界面细胞培养:从气道上皮到女性生殖道
Reprod Domest Anim. 2019 Sep;54 Suppl 3:38-45. doi: 10.1111/rda.13481.
10
Targeting of lipid metabolism with a metabolic inhibitor cocktail eradicates peritoneal metastases in ovarian cancer cells.用代谢抑制剂鸡尾酒靶向脂质代谢可根除卵巢癌细胞的腹腔转移。
Commun Biol. 2019 Jul 31;2:281. doi: 10.1038/s42003-019-0508-1. eCollection 2019.

用于测量高级别浆液性卵巢癌转移代谢化学变化的模型:输卵管、卵巢和大网膜。

Models for measuring metabolic chemical changes in the metastasis of high grade serous ovarian cancer: fallopian tube, ovary, and omentum.

机构信息

Department of Chemistry and Biochemistry, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA, 95064, USA.

Department of Pharmaceutical Sciences, University of Illinois at Chicago, 900 S Ashland Ave., Chicago, IL, 60607, USA.

出版信息

Mol Omics. 2021 Dec 6;17(6):819-832. doi: 10.1039/d1mo00074h.

DOI:10.1039/d1mo00074h
PMID:34338690
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8649074/
Abstract

Ovarian cancer (OC) is the most lethal gynecologic malignancy and high grade serous ovarian cancer (HGSOC) is the most common and deadly subtype, accounting for 70-80% of OC deaths. HGSOC has a distinct pattern of metastasis as many believe it originates in the fallopian tube and then it metastasizes first to the ovary, and later to the adipose-rich omentum. Metabolomics has been heavily utilized to investigate metabolite changes in HGSOC tumors and metastasis. Generally, metabolomics studies have traditionally been applied to biospecimens from patients or animal models; a number of recent studies have combined metabolomics with innovative cell-culture techniques to model the HGSOC metastatic microenvironment for the investigation of cell-to-cell communication. The purpose of this review is to serve as a tool for researchers aiming to model the metastasis of HGSOC for metabolomics analyses. It will provide a comprehensive overview of current knowledge on the origin and pattern of metastasis of HGSOC and discuss the advantages and limitations of different model systems to help investigators choose the best model for their research goals, with a special emphasis on compatibility with different metabolomics modalities. It will also examine what is presently known about the role of small molecules in the origin and metastasis of HGSOC.

摘要

卵巢癌 (OC) 是最致命的妇科恶性肿瘤,高级别浆液性卵巢癌 (HGSOC) 是最常见和最致命的亚型,占 OC 死亡人数的 70-80%。HGSOC 的转移模式很明显,因为许多人认为它起源于输卵管,然后首先转移到卵巢,然后转移到富含脂肪的大网膜。代谢组学被广泛用于研究 HGSOC 肿瘤和转移中的代谢物变化。通常,代谢组学研究传统上应用于来自患者或动物模型的生物样本;最近的一些研究将代谢组学与创新的细胞培养技术相结合,以模拟 HGSOC 转移的微环境,用于研究细胞间的通讯。本综述的目的是为旨在进行 HGSOC 转移代谢组学分析的研究人员提供工具。它将全面概述 HGSOC 转移的起源和模式的现有知识,并讨论不同模型系统的优势和局限性,以帮助研究人员根据自己的研究目标选择最佳模型,特别强调与不同代谢组学模式的兼容性。它还将研究目前已知的小分子在 HGSOC 起源和转移中的作用。