Evidence map›Paper›PMID 42334505›Full record

ArticleMolecular diversity2026

Multi-omics investigation of per- and polyfluoroalkyl substances in lung adenocarcinoma: comprehensive network toxicology, machine learning and molecular docking experiments.

Chunhong Li, Xin Zeng, Yuhua Mao, Yi Liu, Shirong Nong

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular diversity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Chunhong LiCentral Laboratory, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China. chunhongli@glmc.edu.cn.
Xin ZengCollege of Pharmacy, Guilin Medical University, Guilin, 541199, Guangxi, China.
Yuhua MaoDepartment of Obstetrics, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China.
Yi LiuDepartment of Obstetrics, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541199, Guangxi, China.
Shirong NongCollege of Animal Science, Guangxi Agricultural Engineering Vocational Technical College, Nanning, 530016, Guangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Growing concerns regarding per- and polyfluoroalkyl substances (PFAS) as pervasive environmental contaminants have prompted increasing scrutiny regarding their potential contributions to pulmonary diseases. Therefore, this study specifically investigates their implications in lung adenocarcinoma (LUAD) pathogenesis. We utilized the Comparative Toxicogenomics Database (CTD), GeneCards, and OMIM databases to collect LUAD-related targets, while PFAS-related targets were independently predicted from ChEMBL, SwissTargetPrediction, and PharmMapper databases using stringent criteria. The intersecting targets were subjected to protein-protein interaction (PPI) network construction, functional enrichment analysis and molecular docking. We then integrated multi-omics data using ten clustering algorithms to identify the consensus LUAD subtypes, which were subsequently employed in three machine learning algorithms to develop a consensus per- and polyfluoroalkyl substance-related signature (CPFASRS) for LUAD patients. Consequently, we identified six hub toxicological targets: HSP90AA1, EGFR, AKT1, ALB, SRC, and ESR1, highlighting their potential central roles in PFAS-driven LUAD pathogenesis. These targets are enriched in PPAR signaling pathway, chemical carcinogenesis-receptor, and thyroid hormone signaling pathway. The PFAS-toxicity classifiers and CPFASRS prognostic model serve as valuable tools for clinical stratification and personalized management of LUAD patients. Molecular docking suggested that Perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) bind tightly to core targets and weakly to other proteins, which may imply a potential role in PFAS-related LUAD toxicity. Therefore, this study clarifies how PFAS contribute to the development of LUAD and explores the molecular pathways involved, providing crucial insights into the toxicological effects of PFAS. Furthermore, it establishes a theoretical basis for devising preventive strategies and therapeutic approaches for pulmonary diseases related to PFAS exposure.

Indexed as

Lung adenocarcinomaMachine learningMolecular dockingNetwork toxicologyPer- and polyfluoroalkyl substance

Identifiers

PMID42334505

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.