Neural state as a determinant of tumor immunity in lung cancer

肺癌 医学 癌症研究 免疫 肺肿瘤 癌症 免疫学 免疫系统 肺病
作者
Jinglu Yu,Jialong Qi,Zujun Que,Xiaoni Kong,Feng Yu
出处
期刊:Pharmacological Research [Elsevier BV]
卷期号:230: 108261-108261
标识
DOI:10.1016/j.phrs.2026.108261
摘要

Immune checkpoint blockade has reshaped lung cancer therapy, yet durable benefit remains confined to a minority of patients, and resistance often emerges even in initially responsive disease. An increasingly coherent explanation is that neural state-encoded through hierarchical neuroimmune interactions-can profoundly recalibrate anti-tumor immunity and influence treatment responsiveness. In this Review, we synthesize evidence across three integrated levels of neuro-immune regulation in lung cancer. First, lung tumors engage in local neural-immune-tumor interactions, including synapse-like coupling, neuronal mimicry, perineural niches shaped by injury signaling, tumor-induced neurogenesis and neuroendocrine transitions driven by therapy. These local interfaces concentrate catecholaminergic, cholinergic and sensory neuropeptide signaling within spatial microdomains, repeatedly targeting immune bottlenecks. Second, tumor-initiated peripheral-to-central neural circuits link vagal tumor sensing to brainstem autonomic integration, creating a feedback loop that reshapes peripheral immune status. Third, at the systemic level, psychological stress and circadian disruptions impose neuroendocrine constraints through the hypothalamic-pituitary-adrenal axis and sympathetic nervous system, further amplifying immune heterogeneity and clinical variability. By framing "neural state" as a measurable and actionable clinical variable, this unified three-layered neural-immune model clarifies opportunities for patient stratification, mechanism-informed combinations, and neuromodulatory interventions to optimize immunotherapy efficacy in lung cancer.
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
上官若男应助科研通管家采纳,获得10
1秒前
积极钧发布了新的文献求助10
1秒前
22336应助科研通管家采纳,获得20
1秒前
v0id应助科研通管家采纳,获得10
1秒前
张欢馨应助科研通管家采纳,获得10
1秒前
Alex应助科研通管家采纳,获得40
1秒前
佰斯特威应助科研通管家采纳,获得10
1秒前
2秒前
Orange应助科研通管家采纳,获得10
2秒前
赘婿应助cchenn采纳,获得10
2秒前
夏小胖发布了新的文献求助30
4秒前
GL发布了新的文献求助10
5秒前
lingli发布了新的文献求助20
5秒前
5秒前
nitsuj发布了新的文献求助10
6秒前
zhdjk发布了新的文献求助10
6秒前
8秒前
only发布了新的文献求助10
9秒前
10秒前
12秒前
李二完成签到 ,获得积分20
12秒前
yy完成签到 ,获得积分10
13秒前
LR发布了新的文献求助10
14秒前
yjh123应助sherrydj采纳,获得50
14秒前
15秒前
xmn发布了新的文献求助10
15秒前
abaobao完成签到 ,获得积分20
15秒前
123456qqqq发布了新的文献求助30
16秒前
Animus完成签到,获得积分10
16秒前
18秒前
nn发布了新的文献求助20
18秒前
大模型应助零点起步采纳,获得10
18秒前
abaobao关注了科研通微信公众号
19秒前
小红勇闯科研界完成签到,获得积分10
19秒前
20秒前
only完成签到,获得积分10
20秒前
22秒前
22秒前
地球发布了新的文献求助10
23秒前
Shuwen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
APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior 1000
全员动态考核,锚定高质量发展:读懂同济大学教师人事改革新政的深层价值 900
Health Psychology 800
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
Römisch-Germanische Forschungen 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 7595044
求助须知:如何正确求助?哪些是违规求助? 9171857
关于积分的说明 19633474
捐赠科研通 7172469
什么是DOI,文献DOI怎么找? 3267793
关于科研通互助平台的介绍 2432572
邀请新用户注册赠送积分活动 2260806