Evidence map›Paper›PMID 41469480›Full record

ArticleNPJ digital medicine2025

Machine learning-enabled spatial multi-omics uncovers lactate-driven targets and tumor microenvironmental reprogramming in cancer.

Yingzheng Tan, Wenliang Tan, Yanchao Liang, Yunzhu Long, Shuanghua Chen, Qihao Hu, Yangjing Ou, Jingli Fu, Huan Chen, Fangyuan Ren and 11 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Yingzheng Tan *Department of Infectious Disease, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Wenliang Tan *Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Yanchao Liang *Department of Respiratory and Critical Care Medicine, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Yunzhu Long *Department of Infectious Disease, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Shuanghua Chen *Department of Infectious Disease, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Qihao HuDepartment of Cardiothoracic Surgery, Changde Hospital Affiliated to Xiangya School of Medicine, Central South University, Changde, Hunan, China.
Yangjing OuDepartment of Infectious Disease, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Jingli FuDepartment of Infectious Disease, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Huan ChenDepartment of Rehabilitation Medicine, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Fangyuan RenZhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Jun YeTrauma Center, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Qing ZhouDepartment of Infectious Disease, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Sheng LiZhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Xiaojin HeDepartment of Infectious Disease, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Qianqian WangDepartment of Oncology, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Yueming ShenDepartment of Radiology, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China.
Haiyuan LuClinical Laboratory Department, Xiangya hospital, Central South University, Changsha, Hunan, China.
Daichao WuTumor ImmunoMetabolism Institute (TIMI), Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China. wudaichao@usc.edu.cn.
Anbo GaoTumor ImmunoMetabolism Institute (TIMI), Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China. gaoanbo@usc.edu.cn.
Xun ChenZhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China. chenxun@csu.edu.cn.
Yukun LiDepartment of Infectious Disease, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, Hunan, China. yukun_li@csu.edu.cn.

Funding

Health Research Project of Hunan Provincial Health Commission W20243173Major Scientific Research Project for High-level Talents in Health Care of Hunan Province R2023173Natural Science Foundation of China 82303246Natural Science Foundation of Hunan Province 2025JJ50493Natural Science Foundation of Hunan Province 2025JJ70052
6 · The paper itself

Abstract

Lactate accumulation is a central feature of tumor metabolic reprogramming, yet its spatial and cell-type-specific effects in cancer, such as lung adenocarcinoma (LUAD), remain poorly defined. We integrated single-cell transcriptomics, spatial transcriptomics, spatial metabolomics, and immunofluorescence with TCGA survival data and machine-learning models. High-lactate tumors exhibited increased epithelial and fibroblast abundances, whereas T/NK cells and monocytes/macrophages were enriched in low-lactate samples. Spatial metabolomics revealed cell-type-restricted lactate and pyruvate distributions, with endothelial cells showing minimal lactate accumulation. Endothelial subclusters in high-lactate tissues displayed angiogenic and stress-response signatures and were strongly associated with poor prognosis. Multiple machine-learning frameworks-including random forest, elastic-net regression, SVM, ANN, and decision-tree models-consistently identified endothelial and fibroblast programs as key determinants of high-lactate states and adverse clinical outcomes. Collectively, our multi-omics spatial profiling demonstrates that lactate reshapes the LUAD microenvironment by driving angiogenesis, immune suppression, and prognostic stratification, highlighting lactate-centered pathways as promising therapeutic targets.

Identifiers

PMID41469480
PMCPMC12864923

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.