Evidence map›Paper›PMID 41935997›Full record

ArticleNaunyn-Schmiedeberg's archives of pharmacology2026

Integration of multi-omics and machine learning to identify core genes in PANoptosisof lung adenocarcinoma and their mechanisms in the tumor microenvironment and therapeutic potential.

Zhi Chen, Xuehua Deng, Yiyong Yu, Ting Zhang, Cui Liu

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Article in Naunyn-Schmiedeberg's archives of pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Zhi ChenDepartment of Respiratory and Critical Care Medicine, Qionglai Hospital of Traditional Chinese Medicine , Qionglai City, Sichuan Province, China.
Xuehua DengCardiovascular Medicine, Anyue County People's Hospital, Ziyang City, Sichuan Province, China.
Yiyong YuDepartment of Respiratory and Critical Care Medicine, Anyue County People's Hospital, Ziyang City, Sichuan Province, China.
Ting ZhangDepartment of Rehabilitation Medicine, Suining Central Hospital, Suining City, Sichuan Province, China. 18382442787@163.com.
Cui LiuDepartment of Rehabilitation Medicine, Suining Central Hospital, Suining City, Sichuan Province, China. 15828875683@163.com.

Funding

Suining Health Commission, Suining Traditional Chinese Medicine Administration Bureau, name: Study on the effect of Zushi Ba Duan Jin in rapid recovery of postoperative esophageal cancer patients SN2025A10Suining Health Science and Technology Plan Project, name: Observation of the perioperative efficacy of preoperative respiratory muscle warm-up combined with exercise training in patients with lung cancer complicated with mild to moderate chronic obstructive pulmonary disease 25ZDJB09
6 · The paper itself

Abstract

Lung adenocarcinoma (LUAD) is one of the leading causes of cancer-related deaths worldwide, and its complex tumor microenvironment (TME) is a key barrier to treatment. PANoptosis is a novel programmed cell death mechanism that integrates features of pyroptosis, apoptosis, and necroptosis. However, its core regulatory network and cell specific role in LUAD are still unclear. This study integrated three LUAD transcriptome datasets, screened differentially expressed genes through bioinformatics analysis, and intersected with PANoptosis-related genes to construct a protein interaction network, using a combination of 113 machine learning algorithms to screen and validate core genes and using CIBERSORT and single-cell transcriptome data to analyze the spatial expression characteristics of immune cell infiltration and core genes. Finally, the intervention mechanism of core targets and ginsenosides was validated through molecular docking, immunohistochemistry, and cell experiments (CCK-8, Western Blot). Six core genes of LUAD PANoptosis, including IRF1, NLRP3, CASP1, TIMP1, S100A8, and TLR4, were identified in the study. Single-cell analysis revealed that these genes were significantly enriched in M2 macrophages. Functional enrichment indicates that they jointly regulate death- and inflammation-related pathways such as NF-κB signaling and NOD-like receptor signaling. In vitro experiments have confirmed that ginsenosides can induce PANoptosis, promote tumor cell death, or inhibit LUAD cell proliferation by upregulating the ZBP1/AIM2/RIPK3/CASP1 death complex and inhibiting the TLR4/NLRP3 survival signaling axis. This study systematically revealed a PANoptosis core gene network centered on M2 macrophages in LUAD, elucidating a new mechanism by which ginsenosides induce integrated cell death by regulating this network. This provides new potential targets and theoretical basis for the immunotherapy of LUAD and the development of traditional Chinese medicine monomers.

Indexed as

Adenocarcinoma of LungLung NeoplasmsMachine LearningTumor MicroenvironmentApoptosisCell Line, TumorGene Expression Regulation, NeoplasticGinsenosidesHumansMolecular Docking SimulationMultiomicsNecroptosisProtein Interaction MapsTranscriptomeGinsenosidesGinsenosidesLung adenocarcinomaM2 macrophagesMulti-omicsPANoptosis

Identifiers

PMID41935997

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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.