ArticleACS nano2020
Differentiation of Cancer Stem Cells through Nanoparticle Surface Engineering.
Article in ACS nano, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 42 citations in OpenAlex.
- Tumor evolution: signaling pathways, molecular mechanisms and therapeutic targets.Signal transduction and targeted therapy · 2026Review
- Cascade specific endogenous FeNational science review · 2025Article
- Mixed host co-assembled systems for broad-scope analyte sensing.Chemical science · 2024Article
- Nanobiotechnology augmented cancer stem cell guided management of cancer: liquid-biopsy, imaging, and treatment.Journal of nanobiotechnology · 2024Review
- The calcium channel TRPC6 promotes chemotherapy-induced persistence by regulating integrin α6 mRNA splicing.Cell reports · 2023Article
- Inhibition of VEGF binding to neuropilin-2 enhances chemosensitivity and inhibits metastasis in triple-negative breast cancer.Science translational medicine · 2023Article
- Inorganic nanoparticles as scaffolds for bioorthogonal catalysts.Advanced drug delivery reviews · 2023Review
- Review: Mechanisms and perspective treatment of radioresistance in non-small cell lung cancer.Frontiers in immunology · 2023Review
- Cell-Based Chemical Safety Assessment and Therapeutic Discovery Using Array-Based Sensors.International journal of molecular sciences · 2022Review
- An array-based nanosensor for detecting cellular responses in macrophages induced by femtomolar levels of pesticides.Chemical communications (Cambridge, England) · 2022Article
- High affinity protein surface binding through co-engineering of nanoparticles and proteins.Nanoscale · 2022Article
- O-linked α2,3 sialylation defines stem cell populations in breast cancer.Science advances · 2022Article
- Tumor microenvironment penetrating chitosan nanoparticles for elimination of cancer relapse and minimal residual disease.Frontiers in oncology · 2022Review
- Cancer Stem Cell for Tumor Therapy.Cancers · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
Cancer stem cells (CSCs) are a crucial therapeutic target because of their role in resistance to chemo- and radiation therapy, metastasis, and tumor recurrence. Differentiation therapy presents a potential strategy for "defanging" CSCs. To date, only a limited number of small-molecule and nanomaterial-based differentiating agents have been identified. We report here the integrated use of nanoparticle engineering and hypothesis-free sensing to identify nanoparticles capable of efficient differentiation of CSCs into non-CSC phenotypes. Using this strategy, we identified a nanoparticle that induces CSC differentiation by increasing intracellular reactive oxygen species levels. Importantly, this unreported phenotype is more susceptible to drug treatment than either CSCs or non-CSCs, demonstrating a potentially powerful strategy for anticancer therapeutics.
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.