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dc.contributor.authorYiğitbaşı, Türkan
dc.contributor.authorÇalıbaşı Kocal, Gizem
dc.contributor.authorBüyükuslu, Nihal
dc.contributor.authorAtahan, Murat Kemal
dc.contributor.authorKüpeli, Hakan
dc.contributor.authorYiğit, Seyran
dc.contributor.authorTarcan, Ercüment
dc.contributor.authorBaskın, Yasemin
dc.date.accessioned10.07.201910:49:13
dc.date.accessioned2019-07-10T19:51:45Z
dc.date.available10.07.201910:49:13
dc.date.available2019-07-10T19:51:45Z
dc.date.issued2018en_US
dc.identifier.citationYiğitbaşı, T., Çalıbaşı Kocal, G., Büyükuslu, N., Atahan, M., Küpeli, H., Yiğit, S. ... Baskın, Y. (2018). Seldi-tof-ms profiling of metastatic phenotype in histopathological subtypes of breast cancer. Current Proteomics, 15(3), 214-220. https://dx.doi.org/10.2174/1570164615666180309154038en_US
dc.identifier.issn1570-1646
dc.identifier.issn1875-6247
dc.identifier.urihttps://dx.doi.org/10.2174/1570164615666180309154038
dc.identifier.urihttps://hdl.handle.net/20.500.12511/2278
dc.descriptionWOS: 000437989600007en_US
dc.description.abstractBackground: Early detection of breast cancer is a key to the success of breast cancer management. Serum proteome analysis using Surface-Enhanced Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (SELDI-TOF-MS) generates useful information that can be utilized to describe exclusive prognostic and diagnostic biomarkers. Objective: This study aimed to use proteomics and bioinformatics to identify new biomarkers during the metastatic process of breast cancers that were classified as invasive lobular cancer or invasive ductal cancer. Method: Blood samples from 64 breast cancer patients [36 with invasive ductal cancer (14 of whom were lymph node positive); 28 with invasive lobular cancer (8 of whom were lymph node positive] were analyzed using IMAC 30 protein chips. The data acquired from the spectra were processed with univariate statistical analysis (Protein Chip Data Manager Software). Results: One-hundred-eighteen clusters were generated from the individual serum samples. Thirty-six proteins of the metastatic phenotype were found to be diagnostically accurate in cluster analysis. In the breast cancer group, a single candidate peak (m/z 1090.8) that was able to discriminate the metastatic progression was identified as a metastatic phenotype marker. Fifteen protein peaks were identified as markers to separate the histopathological subtypes as either invasive ductal cancer or invasive lobular cancer. Conclusion: In recent years, proteomic methods have rapidly become widespread in breast cancer research. This study revealed the pattern of a group of proteins that were not previously identified and are recommended as candidate markers to diagnose metastatic progression.en_US
dc.language.isoengen_US
dc.publisherBentham Science Publishers Ltden_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBreast Canceren_US
dc.subjectHistopathological Subtypesen_US
dc.subjectSELDI-TOF-MSen_US
dc.subjectProfilingen_US
dc.subjectSerum Proteomeen_US
dc.subjectMetastatic Phenotypeen_US
dc.titleSeldi-tof-ms profiling of metastatic phenotype in histopathological subtypes of breast canceren_US
dc.typearticleen_US
dc.relation.ispartofCurrent Proteomicsen_US
dc.departmentİstanbul Medipol Üniversitesi, Tıp Fakültesi, Temel Tıp Bilimleri Bölümü, Tıbbi Biyokimya Ana Bilim Dalıen_US
dc.departmentİstanbul Medipol Üniversitesi, Sağlık Bilimleri Fakültesi, Beslenme ve Diyetetik Bölümüen_US
dc.authorid0000-0002-0675-1839en_US
dc.identifier.volume15en_US
dc.identifier.issue3en_US
dc.identifier.startpage214en_US
dc.identifier.endpage220en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.2174/1570164615666180309154038en_US
dc.identifier.wosqualityQ4en_US
dc.identifier.scopusqualityQ4en_US


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