Show simple item record

dc.contributor.authorBeddowes, Emmaen
dc.contributor.authorSammut, Stephenen
dc.contributor.authorGao, Men
dc.contributor.authorCaldas, Carlosen
dc.date.accessioned2017-07-04T13:33:57Z
dc.date.available2017-07-04T13:33:57Z
dc.date.issued2017-03en
dc.identifier.issn0960-9776
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/265156
dc.description.abstractThe use of circulating DNA(ctDNA) to provide a non-invasive, personalised genomic snapshot of a patients’ tumour has huge potential. Over the past five years this area of research has gained huge momentum. A number of studies in metastatic breast cancer have shown the potential of ctDNA to predict prognosis and treatment response using ctDNA. Further developments have included deeper sequencing using whole exome and shallow whole genome approaches which has the potential to identify new mutations and chromosomal copy number changes which appear upon resistance to treatment. In early breast cancer, recent work utilising personalised digital PCR probes has shown huge potential in predicting disease relapse and the detection of micrometastatic disease which could lead to improved treatment and outcome for these patients. Specific pathways of resistance can also be monitored and liquid biopsy approaches for the detection of ESR1 mutations have been used which could identify patients who have become resistant to particular endocrine therapies. The identification of PIK3CA mutations in plasma has also been shown to predict a higher response rate to specific PI3K inhibitors and could be used as a non-invasive screening tool prior to treatment. Further work on the detection of exosomal miRNA and hypermethylated DNA in plasma have shown promise in terms of specificity for early breast cancer detection and could be used to monitor treatment response. This review will focus on technological advances in the field, early detection of relapse and the detection of tumour-specific genomc alterations which could predict treatment response and resistance in patients with breast cancer.
dc.languageEnglishen
dc.language.isoenen
dc.publisherElsevier
dc.titlePredicting treatment resistance and relapse through circulating DNAen
dc.typeArticle
prism.endingPageS4
prism.publicationDate2017en
prism.publicationNameBREASTen
prism.startingPageS4
prism.volume32en
dc.identifier.doi10.17863/CAM.11210
dcterms.dateAccepted2017-06-21en
rioxxterms.versionAMen
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2017-03en
dc.contributor.orcidBeddowes, Emma [0000-0001-7649-2863]
dc.contributor.orcidSammut, Stephen [0000-0003-4472-904X]
dc.contributor.orcidCaldas, Carlos [0000-0003-3547-1489]
dc.identifier.eissn1532-3080
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idWELLCOME TRUST (106566/Z/14/Z)
pubs.funder-project-idCancer Research UK (CB4140)
pubs.funder-project-idCambridge University Hospitals NHS Foundation Trust (CUH) (RG51913)
pubs.funder-project-idDepartment of Health (via National Institute for Health Research (NIHR)) (unknown)
cam.orpheus.successThu Jan 30 12:53:35 GMT 2020 - Embargo updated*
rioxxterms.freetoread.startdate2018-03-31


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record