Evidence map›Paper›PMID 28164252›Full record

ArticleMolecular diagnosis & therapy2017

SNAP-Tag Technology: A Promising Tool for Ex Vivo Immunophenotyping.

Swati Choudhary, Stefan Barth, Rama S Verma

Abstract read
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In one paragraph

Article in Molecular diagnosis & therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 45% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Human Antibody Fusion Proteins/Antibody Drug Conjugates in Breast and Ovarian Cancer.Transfusion medicine and hemotherapy : offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie · 2017
    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

3 authors at 2 institutions in 2 countries.

Swati ChoudharyDepartment of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, 600036, India.
Stefan BarthDepartment of Pharmaceutical Product Development, Fraunhofer Institute for Molecular Biology and Applied Ecology IME, 52074, Aachen, Germany. stefan.barth@uct.ac.za.
Rama S VermaDepartment of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, 600036, India. vermars@iitm.ac.in.
Indian Institute of Technology Madras · INFraunhofer Institute for Molecular Biology and Applied Ecology · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSNAP-tag, a self-labeling protein tag, is commonly used for in vitro and in vivo analysis of bound target proteins. We report the first evidence that SNAP-tag could be used for ex vivo detection of enriched biological markers.

methodsProof of concept was established for target c-kit receptor, a pathological and diagnostic marker for a variety of cancers. SNAP-tag conjugates with stem-cell factor (SCF) fusion proteins were designed and their binding and specificity was validated in vitro using flow cytometry and immunostaining.

resultsEx vivo diagnostic application of the fusion protein was demonstrated in comparison with anti-c-kit antibody for peripheral blood samples from leukemia patients and colorectal tissue specimens.

Indexed as

Cell LineColorectal NeoplasmsHumansImmunophenotypingLeukemia, Myeloid, AcuteO(6)-Methylguanine-DNA MethyltransferaseParaffin EmbeddingProto-Oncogene Proteins c-kitRecombinant Fusion ProteinsStem Cell FactorO(6)-Methylguanine-DNA MethyltransferaseProto-Oncogene Proteins c-kitRecombinant Fusion ProteinsStem Cell Factor

Identifiers

PMID28164252
OpenAlexW2583421539

What OpenQuestion holds

Textmetadata
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Registered trials

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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.