Cancer Neuroscience: Decoding Neural Circuitry in Tumor Evolution for Targeted Therapy

神经科学 串扰 重编程 生物 肿瘤微环境 轴突引导 神经发育 癌症 轴突 遗传学 生物化学 基因 光学 物理 细胞
作者
Mengyu Yuan,Rongjiao Xi,Yong Kang,Mingjie Kuang,Xiaoyuan Ji
出处
期刊:Advanced Science [Wiley]
卷期号:12 (38): e06813-e06813 被引量:4
标识
DOI:10.1002/advs.202506813
摘要

Recent breakthroughs in tumor biology have redefined the tumor microenvironment as a dynamic ecosystem in which the nervous system has emerged as a pivotal regulator of oncogenesis. In addition to their classical developmental roles, neural‒tumor interactions orchestrate a sophisticated network that drives cancer initiation, stemness maintenance, metabolic reprogramming, and therapeutic evasion. This crosstalk operates through multimodal mechanisms, including paracrine signaling, electrophysiological interactions, and structural innervation guided by axon-derived guidance molecules. Key discoveries reveal that tumors actively recruit and remodel local neurons, hijacking neurodevelopmental pathways to foster invasive growth. Moreover, malignant cells exhibit neuronal-like plasticity, adopting electrophysiological properties that increase survival under therapeutic stress. These findings position neural mimicry as a hallmark of aggressive cancers. The expanding field of cancer neuroscience seeks to unravel the essential signaling factors that drive the complex communication between cancer and the nervous system, utilizing these findings to enhance precision therapies for cancer management. In this Review, we highlight considerable advancements in cancer neuroscience studies, sparking further discussions on various research possibilities and outlining a direction for future investigations. Additionally, we explored promising therapeutic strategies rooted in neural-tumor interactions that could synergize with conventional standard treatments, offering renewed therapeutic vigor for many refractory malignancies.
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
cc完成签到,获得积分10
1秒前
小天才发布了新的文献求助10
3秒前
Orange应助爱是无限大采纳,获得10
3秒前
牧青发布了新的文献求助10
4秒前
4秒前
齐天大圣发布了新的文献求助10
5秒前
5秒前
忧郁致远发布了新的文献求助30
6秒前
在水一方应助water1201采纳,获得10
6秒前
wei发布了新的文献求助10
6秒前
6秒前
我是老大应助机灵香芦采纳,获得10
7秒前
欢喜迎蓉完成签到,获得积分10
8秒前
Shawsky完成签到,获得积分10
9秒前
春春发布了新的文献求助10
10秒前
hc发布了新的文献求助10
10秒前
成为一只会科研的猫完成签到 ,获得积分10
11秒前
丸子发布了新的文献求助10
12秒前
DW应助呆桃啵啵采纳,获得10
12秒前
萌萌1关注了科研通微信公众号
13秒前
丘比特应助坚定岂愈采纳,获得30
13秒前
折颜发布了新的文献求助10
14秒前
打打应助zsh采纳,获得10
15秒前
俞俊敏完成签到,获得积分10
16秒前
17秒前
19秒前
19秒前
19秒前
20秒前
20秒前
科研通AI6.4应助迷路沁采纳,获得10
20秒前
林子鸿完成签到 ,获得积分10
20秒前
20秒前
20秒前
21秒前
哆啦完成签到 ,获得积分10
22秒前
阿枫完成签到,获得积分10
23秒前
23秒前
23秒前
water1201发布了新的文献求助10
24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
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Navigating Normative Orders. Interdisciplinary Perspectives 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
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 7753639
求助须知:如何正确求助?哪些是违规求助? 9300333
关于积分的说明 20257453
捐赠科研通 7336117
什么是DOI,文献DOI怎么找? 3310567
关于科研通互助平台的介绍 2461805
邀请新用户注册赠送积分活动 2323629