ReviewDiscover oncology2025
RNA-binding proteins and autophagy in lung cancer: mechanistic insights and therapeutic perspectives.
Review in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- CELF family of RNA-binding proteins: roles in disease biology and potential for therapeutic intervention.Cell communication and signaling : CCS · 2026Review
- Investigating autophagy and miRNAs as therapeutic targets in leukemia.Discover oncology · 2026Review
- RNA Regulatory Networks: Key Hubs in the Panorama of Cancer and Emerging Therapeutic Targets.MedComm · 2026Review
- The Regulatory Role of LncRNAs in Modulating Autophagy and Drug Resistance in Non-Small-Cell Lung Cancer: Focus on Targeted Therapeutic Approaches.Biomolecules · 2025Review
- Cuproptosis: a novel therapeutic mechanism in lung cancer.Cancer cell international · 2025Review
- Targeting RNA-binding proteins with small molecules: perspectives and challenges.Frontiers in chemistry · 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
3 authors.
Funding
Abstract
backgroundLung cancer remains a leading cause of cancer-related mortality worldwide. Its progression is intricately associated with the dynamic regulation of autophagy and RNA-binding proteins (RBPs), which play crucial roles in mRNA stability, alternative splicing, and cellular stress responses.
objectivesThis review aims to systematically analyze the mechanisms through which RBPs and autophagy contribute to lung cancer progression and explore potential therapeutic strategies targeting these pathways.
methodsWe reviewed recent studies on the molecular mechanisms by which RBPs regulate tumor proliferation, metabolic adaptation, and their interaction with autophagy. The review also examines the dual roles of autophagy in lung cancer, highlighting its context-dependent effects on cell survival and death.
resultsThe interactions and regulatory networks between RBPs and autophagy involve multiple levels of regulation. RBPs can directly influence autophagy processes and act as microRNA (miRNA) sponges to regulate mRNA stability. The modulation of RBPs affects the expression of autophagy-related genes (ATGs) and autophagosome formation. Additionally, RBPs participate in complex regulatory interactions with non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and other proteins.
conclusionsThis review proposes innovative therapeutic strategies that combine RBP-targeting approaches (e.g., small molecule inhibitors, CRISPR gene editing) with autophagy modulators (e.g., mTOR inhibitors, chloroquine) to enhance treatment efficacy. Nanoparticle drug delivery systems and epigenetic regulation offer further opportunities for targeted interventions. This review lays a theoretical foundation for advancing lung cancer research and provides novel insights into synergistic therapies that target both RBPs and autophagy to improve treatment outcomes for lung cancer.
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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.