ArticleNature communications2017
Cooperative tumour cell membrane targeted phototherapy.
Article in Nature communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Recent Advances and Future Prospects in Biological-Membrane-Targeted Polymers.Polymer science & technology (Washington, D.C.) · 2025Review
- Thylakoids for enhanced photodynamic therapy in hypoxic tumours.Science and technology of advanced materials · 2025Review
- Advancements in Nanocarrier Delivery Systems for Photodynamic Therapy in Lung Cancer.International journal of nanomedicine · 2025Review
- Biomimetic-Nanoparticle-Enhanced Photothermal Immunotherapy: Targeted Delivery of Near-Infrared Region II Agents and Immunoadjuvants for Tumor Immunogenicity.Biomaterials research · 2025Article
- Article
- Membrane fusogenic nanoparticle-based HLA-peptide-addressing universal T cell receptor-engineered T (HAUL TCR-T) cell therapy in solid tumor.Bioengineering & translational medicine · 2023Article
- Advances in Liposome-Encapsulated Phthalocyanines for Photodynamic Therapy.Life (Basel, Switzerland) · 2023Review
- Organism-Generated Biological Vesicles In Situ: An Emerging Drug Delivery Strategy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Review
- In situ antigen modification-based target-redirected universal chimeric antigen receptor T (TRUE CAR-T) cell therapy in solid tumors.Journal of hematology & oncology · 2022Article
- Photodynamic Therapy-Current Limitations and Novel Approaches.Frontiers in chemistry · 2021Review
- Precise cell behaviors manipulation through light-responsive nano-regulators: recent advance and perspective.Theranostics · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The targeted delivery of therapeutics using antibodies or nanomaterials has improved the precision and safety of cancer therapy. However, the paucity and heterogeneity of identified molecular targets within tumours have resulted in poor and uneven distribution of targeted agents, thus compromising treatment outcomes. Here, we construct a cooperative targeting system in which synthetic and biological nanocomponents participate together in the tumour cell membrane-selective localization of synthetic receptor-lipid conjugates (SR-lipids) to amplify the subsequent targeting of therapeutics. The SR-lipids are first delivered selectively to tumour cell membranes in the perivascular region using fusogenic liposomes. By hitchhiking with extracellular vesicles secreted by the cells, the SR-lipids are transferred to neighbouring cells and further spread throughout the tumour tissues where the molecular targets are limited. We show that this tumour cell membrane-targeted delivery of SR-lipids leads to uniform distribution and enhanced phototherapeutic efficacy of the targeted photosensitizer.
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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.