Gutenberg Open Science: Prediction of cancer drug resistance and implications for personalized medicine

Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-7747

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DC Field	Value	Language
dc.contributor.author	Volm, Manfred	-
dc.contributor.author	Efferth, Thomas	-
dc.date.accessioned	2022-09-14T07:52:50Z	-
dc.date.available	2022-09-14T07:52:50Z	-
dc.date.issued	2015
dc.identifier.uri	https://openscience.ub.uni-mainz.de/handle/20.500.12030/7762	-
dc.description.abstract	Drug resistance still impedes successful cancer chemotherapy. A major goal of early concepts in individualized therapy was to develop in vitro tests to predict tumors’ drug responsiveness. We have developed an in vitro short-term test based on nucleic acid precursor incorporation to determine clinical drug resistance. This test detects inherent and acquired resistance in vitro and transplantable syngeneic and xenografted tumors in vivo. In several clinical trials, clinical resistance was predictable with more than 90% accuracy, while drug sensitivity was detected with less accuracy (~60%). Remarkably, clinical cross-resistance to numerous drugs (multidrug-resistance, broad spectrum resistance) was detectable by a single compound, doxorubicin, due to its multifactorial modes of action. The results of our predictive test were in good agreement with predictive assays of other authors. As no predictive test has been established as yet for clinical diagnostics, the identification of sensitive drugs may not reach sufficiently high reliability for clinical routine. We propose a rethinking of the “chemosensitivity” concept. Instead, predictive in vitro tests may reliably identify drug-resistant tumors. The clinical consequence imply to subject resistant tumors not to chemotherapy, but to other new treatment options such as antibody therapy, adoptive immune therapy, hyperthermia, gene therapy etc. The high accuracy to predict resistant tumors may be exploited to develop new strategies for individualized cancer therapy. This new concept bears the potential of a revival of predictive tests for personalized medicine.	en_GB
dc.description.sponsorship	DFG, Open Access-Publizieren Universität Mainz / Universitätsmedizin	de
dc.language.iso	eng	de
dc.rights	CC BY	*
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/	*
dc.subject.ddc	570 Biowissenschaften	de_DE
dc.subject.ddc	570 Life sciences	en_GB
dc.title	Prediction of cancer drug resistance and implications for personalized medicine	en_GB
dc.type	Zeitschriftenaufsatz	de
dc.identifier.doi	http://doi.org/10.25358/openscience-7747	-
jgu.type.dinitype	article	en_GB
jgu.type.version	Published version	de
jgu.type.resource	Text	de
jgu.organisation.department	FB 09 Chemie, Pharmazie u. Geowissensch.	de
jgu.organisation.number	7950	-
jgu.organisation.name	Johannes Gutenberg-Universität Mainz	-
jgu.rights.accessrights	openAccess	-
jgu.journal.title	Frontiers in oncology	de
jgu.journal.volume	5	de
jgu.pages.alternative	Art. 282	de
jgu.publisher.year	2015	-
jgu.publisher.name	Frontiers Media	de
jgu.publisher.place	Lausanne	de
jgu.publisher.uri	http://dx.doi.org/10.3389/fonc.2015.00282	de
jgu.publisher.issn	2234-943X	de
jgu.organisation.place	Mainz	-
jgu.subject.ddccode	570	de
opus.date.modified	2017-05-12T09:19:50Z
opus.subject.dfgcode	00-000
opus.organisation.string	FB 09: Chemie, Pharmazie und Geowissenschaften: Institut für Pharmazie	de_DE
opus.identifier.opusid	52603
opus.institute.number	0908
opus.metadataonly	false
opus.type.contenttype	Keine	de_DE
opus.type.contenttype	None	en_EN
opus.affiliated	Efferth, Thomas
jgu.publisher.doi	10.3389/fonc.2015.00282	de
jgu.organisation.ror	https://ror.org/023b0x485	-
Appears in collections:	DFG-OA-Publizieren (2012 - 2017)

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