Basement membranes in lung metastasis growth and progression

基底膜 转移 癌症研究 医学 病理 化学 内科学 癌症 生物化学
作者
Irene Torre-Cea,Patricia Berlana-Galán,Elena Guerra-Paes,Daniel Cáceres-Calle,Iván Carrera-Aguado,Laura Marcos-Zazo,Fernando Sánchez‐Juanes,José M. Muñoz‐Félix
出处
期刊:Matrix Biology [Elsevier BV]
卷期号:135: 135-152 被引量:2
标识
DOI:10.1016/j.matbio.2024.12.008
摘要

The lung is a highly vascularized tissue that often harbors metastases from various extrathoracic malignancies. Lung parenchyma consists of a complex network of alveolar epithelial cells and microvessels, structured within an architecture defined by basement membranes. Consequently, understanding the role of the extracellular matrix (ECM) in the growth of lung metastases is essential to uncover the biology of this pathology and developing targeted therapies. These basement membranes play a critical role in the progression of lung metastases, influencing multiple stages of the metastatic cascade, from the acquisition of an aggressive phenotype to intravasation, extravasation and colonization of secondary sites. This review examines the biological composition of basement membranes, focusing on their core components-collagens, fibronectin, and laminin-and their specific roles in cancer progression. Additionally, we discuss the function of integrins as primary mediators of cell adhesion and signaling between tumor cells, basement membranes and the extracellular matrix, as well as their implications for metastatic growth in the lung. We also explore vascular co-option (VCO) as a form of tumor growth resistance linked to basement membranes and tumor vasculature. Finally, the review covers current clinical therapies targeting tumor adhesion, extracellular matrix remodeling, and vascular development, aiming to improve the precision and effectiveness of treatments against lung metastases.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
Aerin完成签到,获得积分10
2秒前
2秒前
852应助韩立采纳,获得10
3秒前
冰雪发布了新的文献求助10
4秒前
小鱼发布了新的文献求助10
4秒前
平淡悲发布了新的文献求助10
5秒前
6秒前
Nature完成签到 ,获得积分10
6秒前
赘婿应助fgghhh采纳,获得10
8秒前
8秒前
小魏哥哥发布了新的文献求助10
9秒前
9秒前
11秒前
雪白书蝶完成签到,获得积分10
11秒前
斯梵德发布了新的文献求助10
11秒前
12秒前
13秒前
13秒前
Mei发布了新的文献求助20
14秒前
kyt完成签到 ,获得积分10
15秒前
sci发布了新的文献求助10
16秒前
17秒前
靓丽红牛发布了新的文献求助10
17秒前
格物致知完成签到,获得积分0
19秒前
19秒前
丰富语蕊应助小魏哥哥采纳,获得10
19秒前
纯真的青雪完成签到,获得积分10
20秒前
AireenBeryl531完成签到,获得积分0
20秒前
刘威发布了新的文献求助10
20秒前
24秒前
24秒前
执名之念发布了新的文献求助20
25秒前
26秒前
在水一方应助easymoneysniper采纳,获得10
28秒前
28秒前
OK发布了新的文献求助10
29秒前
kjysbw完成签到 ,获得积分10
30秒前
李总要发财小苏发文章完成签到,获得积分10
31秒前
32秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
An Introduction to Foreign Language Learning and Teaching 750
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
煤炭地下气化渗流燃烧方法的研究 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7631723
求助须知:如何正确求助?哪些是违规求助? 9206171
关于积分的说明 19743661
捐赠科研通 7200936
什么是DOI,文献DOI怎么找? 3274669
关于科研通互助平台的介绍 2436569
邀请新用户注册赠送积分活动 2271265