Evidence map›Paper›PMID 34854867›Full record

ArticleNanoscale2021

Mass spectrometric detection of KRAS protein mutations using molecular imprinting.

Rachel L Norman, Rajinder Singh, Frederick W Muskett, Emma L Parrott, Alessandro Rufini, James I Langridge, Franscois Runau, Ashley Dennison, Jacqui A Shaw, Elena Piletska and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Nanoscale, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

6 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. 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

14 authors at 2 institutions in 1 country.

Rachel L NormanLeicester Cancer Research Centre, Leicester Royal Infirmary, University of Leicester, Leicester, LE1 5WW, UK. Djlj1@le.ac.uk.
Rajinder SinghLeicester Cancer Research Centre, Leicester Royal Infirmary, University of Leicester, Leicester, LE1 5WW, UK. Djlj1@le.ac.uk.
Frederick W MuskettDepartment of Molecular and Cell Biology, University of Leicester, LE1 7RH Leicester, UK.
Emma L ParrottLeicester Cancer Research Centre, Leicester Royal Infirmary, University of Leicester, Leicester, LE1 5WW, UK. Djlj1@le.ac.uk.
Alessandro RufiniLeicester Cancer Research Centre, Leicester Royal Infirmary, University of Leicester, Leicester, LE1 5WW, UK. Djlj1@le.ac.uk.
James I LangridgeWaters Corporation, Wilmslow, SK9 4AX, UK.
Franscois RunauLeicester Cancer Research Centre, Leicester Royal Infirmary, University of Leicester, Leicester, LE1 5WW, UK. Djlj1@le.ac.uk.
Ashley DennisonLeicester Cancer Research Centre, Leicester Royal Infirmary, University of Leicester, Leicester, LE1 5WW, UK. Djlj1@le.ac.uk.
Jacqui A ShawLeicester Cancer Research Centre, Leicester Royal Infirmary, University of Leicester, Leicester, LE1 5WW, UK. Djlj1@le.ac.uk.
Elena PiletskaMIP Diagnostics, The Exchange Building, Colworth Park, MK44 1LQ, Bedford, UK.
Francesco CanfarottaMIP Diagnostics, The Exchange Building, Colworth Park, MK44 1LQ, Bedford, UK.
Leong L NgDepartment of Cardiovascular Sciences, University of Leicester and National Institute for Health Research Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, LE1 7RH, UK.
Sergey PiletskyMIP Diagnostics, The Exchange Building, Colworth Park, MK44 1LQ, Bedford, UK.
Donald J L JonesLeicester Cancer Research Centre, Leicester Royal Infirmary, University of Leicester, Leicester, LE1 5WW, UK. Djlj1@le.ac.uk.ORCID http://orcid.org/0000-0001-6583-870X
University of Leicester · GBWaters (United Kingdom) · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is a disease of cellular evolution where single base changes in the genetic code can have significant impact on the translation of proteins and their activity. Thus, in cancer research there is significant interest in methods that can determine mutations and identify the significant binding sites (epitopes) of antibodies to proteins in order to develop novel therapies. Nano molecularly imprinted polymers (nanoMIPs) provide an alternative to antibodies as reagents capable of specifically capturing target molecules depending on their structure. In this study, we used nanoMIPs to capture KRAS, a critical oncogene, to identify mutations which when present are indicative of oncological progress. Herein, coupling nanoMIPs (capture) and liquid chromatography-mass spectrometry (detection), LC-MS has allowed us to investigate mutational assignment and epitope discovery. Specifically, we have shown epitope discovery by generating nanoMIPs to a recombinant KRAS protein and identifying three regions of the protein which have been previously assigned as epitopes using much more time-consuming protocols. The mutation status of the released tryptic peptide was identified by LC-MS following capture of the conserved region of KRAS using nanoMIPS, which were tryptically digested, thus releasing the sequence of a non-conserved (mutated) region. This approach was tested in cell lines where we showed the effective genotyping of a KRAS cell line and in the plasma of cancer patients, thus demonstrating its ability to diagnose precisely the mutational status of a patient. This work provides a clear line-of-sight for the use of nanoMIPs to its translation from research into diagnostic and clinical utility.

Indexed as

Molecular ImprintingNanoparticlesHumansMass SpectrometryMutationProto-Oncogene Proteins p21(ras)KRAS protein, humanProto-Oncogene Proteins p21(ras)

Identifiers

PMID34854867
PMCPMC8675027
OpenAlexW3215944988

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.