Evidence map›Paper›PMID 42434863›Full record

ArticleMediators of inflammation2026

LDHA, BIK, and CNIH4 Are Diagnostic Markers of Endoplasmic Reticulum Stress in Lung Cancer Comorbid With Sepsis: Integrating Machine Learning and Single-Cell Analysis of Immune Signaling.

Yifeng Pan, Xiaoru Liu, Jiawen Wang, Jing Yan

Abstract read
In one paragraph

Article in Mediators of inflammation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Yifeng PanThe Eighth Clinical Medical College of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China.ORCID https://orcid.org/0009-0006-3265-3091
Xiaoru LiuThe Eighth Clinical Medical College of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China.ORCID https://orcid.org/0009-0006-8748-7908
Jiawen WangThe Eighth Clinical Medical College of Guangzhou University of Chinese Medicine, Foshan, 528000, Guangdong, China.ORCID https://orcid.org/0009-0001-4892-0389
Jing YanGraduate School of Guangxi University of Chinese Medicine, Nanning, 530200, Guangxi, China.ORCID https://orcid.org/0009-0005-2023-7093

Funding

Joint University-Affiliated Hospital Scientific and Technological Innovation Fund of Guangzhou University of Chinese Medicine GZYFS2024G01
6 · The paper itself

Abstract

backgroundLung cancer is intricately associated with the onset of sepsis. Endoplasmic reticulum (ER) stress (ERS) is a cellular stress response to aberrant protein folding in the ER, closely associated with the cellular immune response. Currently, numerous research have elucidated the correlation between ERS and lung cancer, as well as sepsis. The mechanism of ERS in lung cancer comorbid with sepsis requires more investigation.

objectivesThis study aimed to investigate the interacting mechanisms between ERS and the immune response, explore prospective ERS-related diagnostic biomarkers for lung cancer comorbid with sepsis, and elucidate their underlying pathological roles.

methodsDatasets for lung cancer and sepsis were sourced from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) and weighted gene coexpression network analysis (WGCNA) modules were intersected with ERS-related genes. Protein-protein interaction (PPI) and enrichment analyses were conducted. A genetic diagnostic model was developed using exhaustive machine learning algorithms, with accuracy assessed by receiver operating characteristic (ROC) curves and confusion matrices. Hub genes (area under the curve [AUC] ≥ 0.7) were analyzed for immune cell infiltration and cross-validated using single-cell RNA sequencing datasets. Crucially, the expression and functional roles of the hub genes were experimentally validated by western blot in clinical tissue cohorts (adjacent normal, lung cancer, and lung cancer with sepsis) and via wound healing and Transwell assays in PC9 lung cancer cells. Finally, prospective therapeutic agents were identified through molecular docking.

resultsMachine learning identified lactate dehydrogenase A (LDHA), Bcl-2 interacting killer (BIK), and cornichon homolog 4 (CNIH4) as robust diagnostic biomarkers. Western blot analysis confirmed that the protein expression levels of LDHA, BIK, and CNIH4 were significantly upregulated in lung cancer and further elevated in the lung cancer comorbid with sepsis group. In vitro functional assays demonstrated that silencing these genes significantly inhibited the migration and invasion capabilities of PC9 cells. Single-cell analysis revealed that these markers exhibit cell-type-specific expression in malignant cells and regulate immune dysregulation, particularly correlating with the functions of plasma cells and monocytes. Molecular docking indicated that tetrahydro-NAD and amikacin are promising therapeutic candidates.

conclusionsWe identified and experimentally validated LDHA, BIK, and CNIH4 as specific ERS-associated diagnostic biomarkers for lung cancer comorbid with sepsis. These markers drive tumor progression and modulate cellular immune responses, providing novel insights and therapeutic targets for this comorbidity.

Indexed as

Endoplasmic Reticulum StressLung NeoplasmsMachine LearningSepsisHumansProtein Interaction MapsSignal Transductionendoplasmic reticulum stress diagnostic markersimmune cell infiltrationlung cancersepsis

Identifiers

PMID42434863
PMCPMC13355311

What Socratic holds

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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.