ReviewAdvances in cancer research2014
Targeting hyaluronic acid family for cancer chemoprevention and therapy.
Review in Advances in cancer research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 1 of them a synthesis that pooled it.
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
79 citing papers in PubMed, 1 synthesis or guideline pooled it, 161 citations in OpenAlex.
- Identification of drug responsible glycogene signature in liver carcinoma from meta-analysis using RNA-seq data.Glycoconjugate journal · 2024Pooled it
- Molecular and Immune Mechanisms Governing Cancer Metastasis, Including Dormancy, Microenvironmental Niches, and Tumor-Specific Programs.International journal of molecular sciences · 2026Review
- Multi-Functional Polydopamine-Mucin Hollow Particles Provide Tunable Shell Permeability, ROS Scavenging, Tissue Adhesion, and Lubricity for Biomedical Applications.Small (Weinheim an der Bergstrasse, Germany) · 2025Article
- Overcoming cancer treatment resistance: Unraveling the role of cancer-associated fibroblasts.Journal of the National Cancer Center · 2025Review
- Review
- Advances in bioengineered CAR T/NK cell therapy for glioblastoma: Overcoming immunosuppression and nanotechnology-based strategies for enhanced CAR T/NK cell therapy.Bioengineering & translational medicine · 2025Review
- A conditionally replicative adenovirus vector containing the synNotch receptor gene for the treatment of muscle-invasive bladder cancer.Cancer gene therapy · 2025Article
- The roles of hyaluronan in kidney development, physiology and disease.Nature reviews. Nephrology · 2024Review
- Targeted Cancer Therapy-on-A-Chip.Advanced healthcare materials · 2024Review
- Advances in active targeting of ligand-directed polymeric nanomicellesRSC advances · 2024Review
- Review on Hyaluronic Acid Functionalized Sulfur and Nitrogen Co-Doped Graphene Quantum Dots Nano Conjugates for Targeting of Specific Type of Cancer.Advanced pharmaceutical bulletin · 2024Review
- Crosstalk between glioblastoma and tumor microenvironment drives proneural-mesenchymal transition through ligand-receptor interactions.Genes & diseases · 2024Review
- Knockdown of Hyaluronan synthase 2 suppresses liver fibrosis in mice via induction of transcriptomic changes similar to 4MU treatment.Scientific reports · 2024Article
- Ligand-conjugated multiwalled carbon nanotubes for cancer targeted drug delivery.Frontiers in pharmacology · 2024Review
- Application of Nanomaterials Targeting Immune Cells in the Treatment of Chronic Inflammation.International journal of nanomedicine · 2024Review
- Tumor-derived systems as novel biomedical tools-turning the enemy into an ally.Biomaterials research · 2023Review
- Inhibition of hyaluronic acid degradation pathway suppresses glioma progression by inducing apoptosis and cell cycle arrest.Cancer cell international · 2023Article
- A pH‑responsive hyaluronic acid nano‑vehicle co‑encapsulating doxorubicin and all‑trans retinoic acid for the inhibition of hepatic stellate cell‑induced tumor growth and metastasis.Molecular medicine reports · 2023Article
- High molecular weight hyaluronic acid drastically reduces chemotherapy-induced mucositis and apoptotic cell death.Cell death & disease · 2023Article
- Structural Analysis and Classification of Low-Molecular-Weight Hyaluronic Acid by Near-Infrared Spectroscopy: A Comparison between Traditional Machine Learning and Deep Learning.Molecules (Basel, Switzerland) · 2023Article
19 more citing papers are in PubMed but not listed here.
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 at 1 institution in 1 country.
Funding
Abstract
Hyaluronic acid or hyaluronan (HA) is perhaps one of the most uncomplicated large polymers that regulates several normal physiological processes and, at the same time, contributes to the manifestation of a variety of chronic and acute diseases, including cancer. Members of the HA signaling pathway (HA synthases, HA receptors, and HYAL-1 hyaluronidase) have been experimentally shown to promote tumor growth, metastasis, and angiogenesis, and hence each of them is a potential target for cancer therapy. Furthermore, as these members are also overexpressed in a variety of carcinomas, targeting of the HA family is clinically relevant. A variety of targeted approaches have been developed to target various HA family members, including small-molecule inhibitors and antibody and vaccine therapies. These treatment approaches inhibit HA-mediated intracellular signaling that promotes tumor cell proliferation, motility, and invasion, as well as induction of endothelial cell functions. Being nontoxic, nonimmunogenic, and versatile for modifications, HA has been used in nanoparticle preparations for the targeted delivery of chemotherapy drugs and other anticancer compounds to tumor cells through interaction with cell-surface HA receptors. This review discusses basic and clinical translational aspects of targeting each HA family member and respective treatment approaches that have been described in the literature.
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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.