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Die HIV-1-Resistenztestung wird ein immer bedeutenderer Bestandteil des Monitorings der antiretroviralen Therapie und erfolgt in der Regel mittels Genotypisierung. Zur Zeit sind zwei Systeme kommerziell erhältlich und obwohl diese technisch nicht zu den einfach durchführbaren Methoden gehören, haben sie doch einen hohen Grad an Qualität erreicht. Modifikationen der Standardprotokolle sind für bestimmte Fragestellungen durchaus von Vorteil. Obwohl beide Systeme auf Entscheidungsregeln basierende Resistenz-Reports beinhalten, braucht es das zusätzliche Wissen und die Erfahrung des Anwenders, um die detektierten Mutationsmuster in klinisch brauchbare Resultate überführen zu können. Beide der hier detailliert beschriebenen Systeme haben ihre Vor- und Nachteile. Die Entscheidung für das eine oder andere System muss aufgrund der individuellen Bedürfnisse getroffen werden. Microarray-Systemen könnte der Markt der Zukunft gehören.
Survivin is a drug target and its suppressant YM155 a drug candidate mainly investigated for high-risk neuroblastoma. Findings from one YM155-adapted subline of the neuroblastoma cell line UKF-NB-3 had suggested that increased ABCB1 (mediates YM155 efflux) levels, decreased SLC35F2 (mediates YM155 uptake) levels, decreased survivin levels, and TP53 mutations indicate YM155 resistance. Here, the investigation of 10 additional YM155-adapted UKF-NB-3 sublines only confirmed the roles of ABCB1 and SLC35F2. However, cellular ABCB1 and SLC35F2 levels did not indicate YM155 sensitivity in YM155-naïve cells, as indicated by drug response data derived from the Cancer Therapeutics Response Portal (CTRP) and the Genomics of Drug Sensitivity in Cancer (GDSC) databases. Moreover, the resistant sublines were characterized by a remarkable heterogeneity. Only seven sublines developed on-target resistance as indicated by resistance to RNAi-mediated survivin depletion. The sublines also varied in their response to other anti-cancer drugs. In conclusion, cancer cell populations of limited intrinsic heterogeneity can develop various resistance phenotypes in response to treatment. Therefore, individualized therapies will require monitoring of cancer cell evolution in response to treatment. Moreover, biomarkers can indicate resistance formation in the acquired resistance setting, even when they are not predictive in the intrinsic resistance setting.
The former and current multiple sclerosis (MS) classifications are essential for describing different phenotypes and disease dynamics. To establish personalized treatment regimes, further clinical and paraclinical parameters have to be considered such as imaging, cerebrospinal fluid (CSF) findings, past disease-modifying therapies (DMTs), and disease activity under these therapies. In clinical practice, this information is often difficult to overview. Especially, patients with a long course of disease offer an extensive medical history so that comprehending all of the necessary information can be very time consuming.