ReviewFrontiers in oncology2025
"Molecular pigeon" network of lncRNA and miRNA: decoding metabolic reprogramming in patients with lung cancer.
Review in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Multimodal machine learning and deep graph neural networks for the prediction of molecular inhibitory activity and disease associations.Journal of computer-aided molecular design · 2026Article
- Non-coding RNAs-regulated SLC7A11 modulates ferroptosis: a new strategy for cancer therapy.Functional & integrative genomics · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, with the advancement of RNA analysis techniques, such as single-cell RNA sequencing, noncoding RNAs have demonstrated substantial potential in regulating gene expression, encoding peptides and proteins, constructing the cellular microenvironment, and modulating cell function. They can serve as potential therapeutic targets and diagnostic markers for various diseases, offering novel avenues for diagnosis and treatment. Among them, long noncoding RNAs (lncRNAs) represent a principal component. Through the competing endogenous RNA mechanism, lncRNAs sequester microRNAs (miRNAs), interact with metabolic enzymes or transcription factors, regulate gene expression, and participate in the metabolic communication network within the tumor microenvironment. This process significantly promotes the growth, proliferation, and metastasis of lung cancer cells by reprogramming core metabolic pathways-including glucose utilization, lipid homeostasis, and amino acid flux. This article reviews the key roles of lncRNAs and miRNAs in the metabolic reprogramming of patients with lung cancer, elucidates the complex lncRNA-miRNA network involved, and provides mechanistic insights into metabolic vulnerabilities and translational opportunities for targeted interventions in the diagnosis and treatment of lung cancer.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.