A pathology-to-single-cell framework links SPP1+ M2 macrophages with NETs-prone high-risk niches in HCC

生物 计算生物学 推论 巨噬细胞极化 间质细胞 可药性 计算机科学 中性粒细胞胞外陷阱 优先次序 拉布 癌症研究 生态位 生物信息学 转录组 肝细胞癌 免疫疗法 判别式
作者
Rouxin Li,Yuheng Gu,Shi Huang,Shiya Zeng,Xuanchen Zhou,Weiqi Luo,Zhuo Wen,W Chen,Cheng Chen,Lantian Cui,Hongyu Duan,Mengfan Zhao
出处
期刊:Journal of Translational Medicine [BioMed Central]
卷期号:24 (1) 被引量:1
标识
DOI:10.1186/s12967-026-07892-x
摘要

Neutrophil extracellular traps (NETs) facilitate hepatocellular carcinoma (HCC) progression, but the upstream cellular organizers and the histopathological correlates of NETosis-prone niches remain poorly defined. We aimed to build a pathology-to-single-cell framework to (i) quantify NETs-associated risk from routine whole-slide images (WSI) and (ii) nominate candidate organizer cells and mechanisms, focusing on SPP1+ M2 macrophages. We integrated WSI, bulk transcriptomics, single-cell RNA-seq, spatial transcriptomics, and germline association data. NETs activity was quantified using gene-set scoring and aligned with WSI-derived morphology features (e.g. texture, stromal boundary disruption, and tumor–stroma interface complexity) to train and validate a prognostic model using regularized feature selection and survival machine learning. A 26,928-cell single-cell atlas was constructed to annotate macrophage states and neutrophil subsets, followed by trajectory inference to model macrophage polarization dynamics. Cell–cell communication was evaluated by ligand–receptor co-expression networks, and pathway/metabolic programs were inferred using multi-method enrichment and flux estimation. Spatial co-localization and neighborhood effects were assessed by deconvolution and spatial interaction modeling. Finally, network-based target prioritization was performed to highlight druggable nodes and candidate intervention pathways. The WSI-derived NETs risk score stratified overall survival in training and validation cohorts (HR ≈ 8.48 and ≈6.44; AUC > 0.78). Multi-omics integration prioritized SPP1 as a central hub. SPP1+ M2 macrophages and NETs+ neutrophils preferentially localized at the tumor–stroma interface, where inferred communication converged on OPN(SPP1)–CD44/integrins and ICAM1–β2-integrin axes with downstream FAK–PI3K–Akt and NF-κB/MAPK signaling. Metabolic inference suggested a shared hypoxia/glycolysis–lactate–glutathione/antioxidant program in SPP1+ M2 macrophages mirrored by NETs+ neutrophils, consistent with a NETosis-permissive niche. Germline mapping indicated an antagonistic association pattern for the SPP1+ M2 program. Network prioritization highlighted SRC, AKT1, and CEBPB and pathways including ECM–receptor interaction, FAK/PI3K–Akt, MAPK, and TNF/IL-17. Our framework links routine pathology morphology to NETs activity and nominates SPP1+ M2 macrophages as candidate organizers of NETosis-prone high-risk niches in HCC. Importantly, the proposed macrophage–NETs axis is supported by convergent multi-omics/spatial evidence but remains primarily associative and inference-based, not definitive causation. Future work should include functional validation (e.g. macrophage–neutrophil co-culture NETosis assays, SPP1/CD44/integrin or ICAM1–ITGB2 perturbation, and in vivo depletion/blockade studies), prospective multi-center evaluation of the WSI risk score, and testing whether this axis generalizes beyond HCC or is liver-specific. These results provide a quantitative pathology-based risk stratification approach and a set of mechanistically plausible, targetable signaling–metabolic nodes for therapeutic exploration.
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
琯柠完成签到 ,获得积分10
刚刚
Ava应助热心小松鼠采纳,获得10
刚刚
wshtcl发布了新的文献求助10
1秒前
千里眼给千里眼的求助进行了留言
3秒前
西格玛完成签到,获得积分10
5秒前
名字无法显示完成签到,获得积分10
7秒前
勤劳的夏天完成签到,获得积分10
11秒前
Fanfan完成签到 ,获得积分10
16秒前
明明如月完成签到 ,获得积分10
21秒前
冷傲迎梅完成签到 ,获得积分10
22秒前
顾君如完成签到,获得积分10
25秒前
WistingWang完成签到,获得积分10
27秒前
29秒前
羞涩的成仁完成签到 ,获得积分10
35秒前
dyt完成签到,获得积分10
37秒前
顺硕完成签到,获得积分10
38秒前
危机的秋双完成签到 ,获得积分10
41秒前
Brendan完成签到,获得积分10
41秒前
ZSZ完成签到,获得积分10
42秒前
怕黑的飞柏完成签到,获得积分10
44秒前
贪玩初彤完成签到 ,获得积分10
44秒前
Jally完成签到 ,获得积分10
47秒前
乐乐发布了新的文献求助10
47秒前
修仙中完成签到,获得积分0
49秒前
俊秀的问旋完成签到 ,获得积分10
52秒前
冷艳的太君完成签到 ,获得积分10
54秒前
熊逍完成签到 ,获得积分10
57秒前
壮观的睫毛完成签到 ,获得积分10
58秒前
梓树发布了新的文献求助10
59秒前
小蒋完成签到,获得积分10
1分钟前
XX完成签到 ,获得积分10
1分钟前
太阳当空照完成签到 ,获得积分10
1分钟前
迷路又菱完成签到,获得积分10
1分钟前
SciGPT应助科研通管家采纳,获得10
1分钟前
开心果完成签到,获得积分10
1分钟前
墨林云海完成签到,获得积分10
1分钟前
活力的鹰完成签到 ,获得积分10
1分钟前
wing完成签到 ,获得积分10
1分钟前
jenningseastera应助xiaowan采纳,获得10
1分钟前
阿姨洗铁路完成签到 ,获得积分10
1分钟前
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
Effects of Two Weeks of Red Light Therapy on Choroidal Thickness and Axial Length in Young Adults 700
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The Neuroscience of Language 400
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 400
Too Much of Two Good Things: Investment Protection and Environmental Protection in International Law 260
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 7673513
求助须知:如何正确求助?哪些是违规求助? 9239976
关于积分的说明 19903274
捐赠科研通 7243068
什么是DOI,文献DOI怎么找? 3285574
关于科研通互助平台的介绍 2443685
邀请新用户注册赠送积分活动 2287851