Browsing by Subject "biological marker"

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Open Access
Phenotype-based variation as a biomarker of sensitivity to molecularly targeted therapy in melanoma
(Royal Society of Chemistry, 2017) Senses, K. M.; Ghasemi M.; Akbar, M. W.; Isbilen, M.; Fallacara, A. L.; Frankenburg, S.; Schenone, S.; Lotem, M.; Botta, M.; Gure, A. O.
Transcriptomic phenotypes defined for melanoma have been reported to correlate with sensitivity to various drugs. In this study, we aimed to define a minimal signature that could be used to distinguish melanoma sub-types in vitro, and to determine suitable drugs by which these sub-types can be targeted. By using primary melanoma cell lines, as well as commercially available melanoma cell lines, we find that the evaluation of MLANA and INHBA expression is as capable as one based on a combined analysis performed with genes for stemness, EMT and invasion/proliferation, in identifying melanoma subtypes that differ in their sensitivity to molecularly targeted drugs. Using this approach, we find that 75% of melanoma cell lines can be treated with either the MEK inhibitor AZD6244 or the HSP90 inhibitor 17AAG.
Open Access
A ranking-based meta-analysis reveals let-7 family as a meta-signature for grade classification in breast cancer
(Public Library of Science, 2015) Oztemur, Y.; Bekmez, T.; Aydos, A.; Yulug I.G.; Bozkurt, B.; Dedeoglu, B.G.
Breast cancer is one of the most important causes of cancer-related deaths worldwide in women. In addition to gene expression studies, the progressing work in the miRNA area including miRNA microarray studies, brings new aspects to the research on the cancer development and progression. Microarray technology has been widely used to find new biomarkers in research and many transcriptomic microarray studies are available in public databases. In this study, the breast cancer miRNA and mRNA microarray studies were collected according to the availability of their data and clinical information, and combined by a newly developed ranking-based meta-analysis approach to find out candidate miRNA biomarkers (meta-miRNAs) that classify breast cancers according to their grades and explain the relation between miRNAs and mRNAs. This approach provided meta-miRNAs specific to breast cancer grades, pointing out let-7 family members as grade classifiers. The qRTPCR studies performed with independent breast tumors confirmed the potential biomarker role of let-7 family members (meta-miRNAs). The concordance between the meta-mRNAs and miRNA target genes specific to tumor grade (common genes) supported the idea of mRNAs as miRNA targets. The pathway analysis results showed that most of the let-7 family miRNA targets, and also common genes, were significantly taking part in cancer-related pathways. The qRT-PCR studies, together with bioinformatic analyses, confirmed the results of meta-analysis approach, which is dynamic and allows combining datasets from different platforms. © 2015 Oztemur et al.