Evidence map›Paper›PMID 30809593›Full record

ReviewHealth science reports2019

Applications of SNAP-tag technology in skin cancer therapy.

Eden Rebecca Padayachee, Henry Ademola Adeola, Jennifer Catherine Van Wyk, Fleury Augustine Nsole Biteghe, Shivan Chetty, Nonhlanhla Patience Khumalo, Stefan Barth

Open access · goldAbstract readReview
In one paragraph

Review in Health science reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 24% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Frontiers in bioengineering and biotechnology · 2022
    Review
  3. Review
  4. Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Eden Rebecca PadayacheeDepartment of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences University of Cape Town Cape Town South Africa.
Henry Ademola AdeolaThe Hair and Skin Research Lab, Division of Dermatology, Department of Medicine, Faculty of Health Sciences University of Cape Town and Groote Schuur Hospital Cape Town South Africa.ORCID https://orcid.org/0000-0003-2896-0583
Jennifer Catherine Van WykThe Hair and Skin Research Lab, Division of Dermatology, Department of Medicine, Faculty of Health Sciences University of Cape Town and Groote Schuur Hospital Cape Town South Africa.
Fleury Augustine Nsole BitegheDepartment of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences University of Cape Town Cape Town South Africa.
Shivan ChettyDepartment of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences University of Cape Town Cape Town South Africa.
Nonhlanhla Patience KhumaloThe Hair and Skin Research Lab, Division of Dermatology, Department of Medicine, Faculty of Health Sciences University of Cape Town and Groote Schuur Hospital Cape Town South Africa.
Stefan BarthDepartment of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences University of Cape Town Cape Town South Africa.
University of Cape Town · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCancer treatment in the 21st century has seen immense advances in optical imaging and immunotherapy. Significant progress has been made in the bioengineering and production of immunoconjugates to achieve the goal of specifically targeting tumors. DISCUSSION: In the 21st century, antibody drug conjugates (ADCs) have been the focus of immunotherapeutic strategies in cancer. ADCs combine the unique targeting of monoclonal antibodies (mAbs) with the cancer killing ability of cytotoxic drugs. However, due to random conjugation methods of drug to antibody, ADCs are associated with poor antigen specificity and low cytotoxicity, resulting in a drug to antibody ratio (DAR) >1. This means that the cytotoxic drugs in ADCs are conjugated randomly to antibodies, by cysteine or lysine residues. This generates heterogeneous ADC populations with 0 to 8 drugs per an antibody, each with distinct pharmacokinetic, efficacy, and toxicity properties. Additionally, heterogeneity is created not only by different antibody to ligand ratios but also by different sites of conjugation. Hence, much effort has been made to find and establish antibody conjugation strategies that enable us to better control stoichiometry and site-specificity. This includes utilizing protein self-labeling tags as fusion partners to the original protein. Site-specific conjugation is a significant characteristic of these engineered proteins. SNAP-tag is one such engineered self-labeling protein tag shown to have promising potential in cancer treatment. The SNAP-tag is fused to an antibody of choice and covalently reacts specifically in a 1:1 ratio with benzylguanine (BG) substrates, eg, fluorophores or photosensitizers, to target skin cancer. This makes SNAP-tag a versatile technique in optical imaging and photoimmunotherapy of skin cancer.

conclusionSNAP-tag technology has the potential to contribute greatly to a broad range of molecular oncological applications because it combines efficacious tumor targeting, minimized local and systemic toxicity, and noninvasive assessment of diagnostic/prognostic molecular biomarkers of cancer.

Indexed as

antibody drug conjugatesbenzylguanineskin cancerSNAP‐tagtargeted therapies

Identifiers

PMID30809593
PMCPMC6375544
OpenAlexW2908598815

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.