ArticleScience translational medicine2020
Aptamers against mouse and human tumor-infiltrating myeloid cells as reagents for targeted chemotherapy.
Article in Science translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 64 citations in OpenAlex.
- Application of the Nicoya OpenSPR to Studies of Biomolecular Binding: A Review of the Literature from 2016 to 2022.Sensors (Basel, Switzerland) · 2023Review
- Targeting treatment of bladder cancer using PTK7 aptamer-gemcitabine conjugate.Biomaterials research · 2022Article
- A heparan-sulfate-bearing syndecan-1 glycoform is a distinct surface marker for intra-tumoral myeloid-derived suppressor cells.iScience · 2021Article
- Aptamers: Cutting edge of cancer therapies.Molecular therapy : the journal of the American Society of Gene Therapy · 2021Review
- MDSC in Mice and Men: Mechanisms of Immunosuppression in Cancer.Journal of clinical medicine · 2021Review
- Immunosuppressive Effects of Myeloid-Derived Suppressor Cells in Cancer and Immunotherapy.Cells · 2021Review
- Immune Modulatory Short Noncoding RNAs Targeting the Glioblastoma Microenvironment.Frontiers in oncology · 2021Review
- Macrophage imaging and subset analysis using single-cell RNA sequencing.Nanotheranostics · 2021Article
- Identification of an Aptamer With Binding Specificity to Tumor-Homing Myeloid-Derived Suppressor Cells.Frontiers in pharmacology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 4 institutions in 2 countries.
Funding
Abstract
Local delivery of anticancer agents has the potential to maximize treatment efficacy and minimize the acute and long-term systemic toxicities. Here, we used unsupervised systematic evolution of ligands by exponential enrichment to identify four RNA aptamers that specifically recognized mouse and human myeloid cells infiltrating tumors but not their peripheral or circulating counterparts in multiple mouse models and from patients with head and neck squamous cell carcinoma (HNSCC). The use of these aptamers conjugated to doxorubicin enhanced the accumulation and bystander release of the chemotherapeutic drug in both primary and metastatic tumor sites in breast and fibrosarcoma mouse models. In the 4T1 mammary carcinoma model, these doxorubicin-conjugated aptamers outperformed Doxil, the first clinically approved highly optimized nanoparticle for targeted chemotherapy, promoting tumor regression after just three administrations with no detected changes in weight loss or blood chemistry. These RNA aptamers recognized tumor infiltrating myeloid cells in a variety of mouse tumors in vivo and from human HNSCC ex vivo. This work suggests the use of RNA aptamers for the detection of myeloid-derived suppressor cells in humans and for a targeted delivery of chemotherapy to the tumor microenvironment in multiple malignancies.
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.