A Review on Patient-Derived 3D Micro Cancer Approach for Drug Screen in Personalized Cancer Medicine
Copyright© Bentham Science Publishers; For any queries, please email at epubbenthamscience.net..
Precision medicine in oncology aims to identify an individualized treatment plan based on genomic alterations in a patient's tumor. It helps to select the most beneficial therapy for an individual patient. As it is now known that no patient's cancer is the same, and therefore, different patients may respond differently to conventional treatments, precision medicine, which replaces the one-size-fits-all approach, supports the development of tailored treatments for specific cancers of different patients. Patient-specific organoid or spheroid models as 3D cell culture models are very promising for predicting resistance to anti-cancer drugs and for identifying the most effective cancer therapy for high-throughput drug screening combined with genomic analysis in personalized medicine. Because tumor spheroids incorporate many features of solid tumors and reflect resistance to drugs and radiation, as in human cancers, they are widely used in drug screening studies. Testing patient-derived 3D cancer spheroids with some anticancer drugs based on information from molecular profiling can reveal the sensitivity of tumor cells to drugs and provide the right compounds to be effective against resistant cells. Given that many patients do not respond to standard treatments, patient-specific treatments will be more effective, less toxic. They will affect survival better compared to the standard approach used for all patients.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2024 |
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Erschienen: |
2024 |
Enthalten in: |
Zur Gesamtaufnahme - year:2024 |
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Enthalten in: |
Current cancer drug targets - (2024) vom: 05. März |
Sprache: |
Englisch |
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Beteiligte Personen: |
Atlı Şekeroğlu, Zülal [VerfasserIn] |
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Links: |
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Themen: |
3D culture |
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Anmerkungen: |
Date Revised 06.03.2024 published: Print-Electronic Citation Status Publisher |
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doi: |
10.2174/0115680096285910240206044830 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM369355237 |
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