• 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

微转移灶形成:一种概率模型。

Micrometastases formation: a probabilistic model.

作者信息

Liotta L A, Delisi C, Saidel G, Kleinerman J

出版信息

Cancer Lett. 1977 Sep;3(3-4):203-8. doi: 10.1016/s0304-3835(77)95675-0.

DOI:10.1016/s0304-3835(77)95675-0
PMID:902256
Abstract

A mathematical model of the process of metastases is formulated in which the hematogenous metastatic process from a solid tumor is considered to consist of a series of stages. A mathematical expression is obtained for the probability that no metastases will have been established by a characteristic time interval after tumor initiation. The murine T241 fibrosarcoma that rapidly and reproduceably produces pulmonary metastases was studied. Estimates of parameters required for the expression of probability of metastases formation were derived experimentally. The probability remains close to one for a characteristic time at which point it drops to zero. This indicates that at least in this experimental system there is a predictable critical time period beyond which micrometastases are virtually certain to have been formed.

摘要

建立了转移过程的数学模型,其中实体瘤的血行转移过程被认为由一系列阶段组成。得出了肿瘤发生后在特征时间间隔内未形成转移的概率的数学表达式。对能快速且可重复产生肺转移的小鼠T241纤维肉瘤进行了研究。通过实验得出了转移形成概率表达式所需参数的估计值。在特征时间内概率接近1,之后降至零。这表明至少在这个实验系统中存在一个可预测的关键时间段,超过这个时间段微转移几乎肯定已经形成。

相似文献

1
Micrometastases formation: a probabilistic model.微转移灶形成:一种概率模型。
Cancer Lett. 1977 Sep;3(3-4):203-8. doi: 10.1016/s0304-3835(77)95675-0.
2
Stochastic model of metastases formation.转移形成的随机模型。
Biometrics. 1976 Sep;32(3):535-50.
3
The significance of hematogenous tumor cell clumps in the metastatic process.
Cancer Res. 1976 Mar;36(3):889-94.
4
Degradation of basement membrane by murine tumor cells.
J Natl Cancer Inst. 1977 May;58(5):1427-31. doi: 10.1093/jnci/58.5.1427.
5
Modeling growth kinetics and statistical distribution of oligometastases.寡转移瘤生长动力学和统计分布建模。
Semin Radiat Oncol. 2006 Apr;16(2):111-9. doi: 10.1016/j.semradonc.2005.12.006.
6
Enhanced metastatic potential of tumor cells harvested from spontaneous metastases of heterogeneous murine tumors.从异质性小鼠肿瘤的自发性转移灶中收获的肿瘤细胞具有增强的转移潜能。
J Natl Cancer Inst. 1982 Oct;69(4):975-80.
7
The antibody to plasminogen activator inhibitor-1 suppresses pulmonary metastases of human fibrosarcoma in athymic mice.纤溶酶原激活物抑制剂-1抗体可抑制无胸腺小鼠体内人纤维肉瘤的肺转移。
Gen Diagn Pathol. 1995 May;141(1):41-8.
8
In vivo isolation of a metastatic tumor cell variant involving selective and nonadaptive processes.通过体内方法分离出一种涉及选择性和非适应性过程的转移性肿瘤细胞变体。
J Natl Cancer Inst. 1981 Jan;66(1):183-9.
9
Fibrosarcoma: the biomathematical approach to late metastases: a case report.纤维肉瘤:晚期转移的生物数学方法:一例报告
Mt Sinai J Med. 1979 Mar-Apr;46(2):255-60.
10
[Experimental studies on growth inhibition and regression of cancer metastases].[癌症转移生长抑制与消退的实验研究]
Gan To Kagaku Ryoho. 1985 Jun;12(6):1196-209.

引用本文的文献

1
Cell-cell fusion in cancer: The next cancer hallmark?细胞融合与癌症:下一个癌症标志?
Int J Biochem Cell Biol. 2024 Oct;175:106649. doi: 10.1016/j.biocel.2024.106649. Epub 2024 Aug 24.
2
Intermetastatic and Intrametastatic Heterogeneity Shapes Adaptive Therapy Cycling Dynamics.转移灶间和转移灶内异质性塑造适应性治疗循环动力学。
Cancer Res. 2023 Aug 15;83(16):2775-2789. doi: 10.1158/0008-5472.CAN-22-2558.
3
CD44v6 may influence ovarian cancer cell invasion and migration by regulating the NF-κB pathway.CD44v6可能通过调节NF-κB信号通路影响卵巢癌细胞的侵袭和迁移。
Oncol Lett. 2019 Jul;18(1):298-306. doi: 10.3892/ol.2019.10306. Epub 2019 May 3.
4
Inferring rates of metastatic dissemination using stochastic network models.使用随机网络模型推断转移扩散率。
PLoS Comput Biol. 2019 Apr 1;15(4):e1006868. doi: 10.1371/journal.pcbi.1006868. eCollection 2019 Apr.
5
A Mathematical Framework for Modelling the Metastatic Spread of Cancer.用于癌症转移扩散建模的数学框架
Bull Math Biol. 2019 Jun;81(6):1965-2010. doi: 10.1007/s11538-019-00597-x. Epub 2019 Mar 22.
6
Correlation of CD44v6 expression with ovarian cancer progression and recurrence.CD44v6 表达与卵巢癌进展和复发的相关性。
BMC Cancer. 2013 Apr 8;13:182. doi: 10.1186/1471-2407-13-182.