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Tiroid kanseri görülme sıklığı yüksek olan ve ölümcül bir kanser türüdür. Dolayısıyla tiroid kanserinde etkin rol alan moleküllerin belirlenmesi hastalığın erken tanı ve tedavi stratejilerinin oluşturulması için çok önemlidir. Bu çalışmada yüksek boyutlu işlevsel genomiks verilerinin sistem biyolojisi araçları ile bütünleştirilerek analizi sonucu tiroid kanserine özgü moleküler hedefler ve biyoişaretçi adaylar belirlenmiştir. Zenginleştirme analizi sonucunda önemli kanser yolaklarının, metabolik yolakların ve immun sistem ilgili yolların aktifleştiği belirlenmiştir. İleri istatistiksel analizler ile belirlenen gen anlatımı farklılık gösteren genlerin protein etkileşim ağı oluşturulmuş ve tiroid kanserine özgü moleküler hedefler ve biyoişaretçi adaylar JUN, LRRK2, BCL2, CCND1, TLE1, MET, ICAM1, DDB2 ve RXRG olarak belirlenmiştir. Bağımsız bir veri setinin analizi ile, bu genlerin tümör ve normal dokuları ayırt edebileceği belirlenmiştir. Bu proteinler arasından JUN, TLE1 ve DBB2’nin yeni moleküler hedef ve biyoişaretçi aday olabileceği bulunmuştur. Belirlenen hedeflerin papiller tiroid kanserinin teşhis ve tedavi stratejilerinin oluşturulmasında kullanılabileceği öngörülmektedir. Ancak söz konusu adayların eş zamanlı PCR ile deneysel çalışmalarının yapılması gerekmektedir.
Thyroid cancer is a high frequency and fatal type of cancer. Therefore, the determination of the molecules that play an effective role in thyroid cancer is very important for the development of early diagnosis and treatment strategies of the disease. In this study, the analysis of the high-dimensional functional genomic data integrated with the system biology tools resulted in specific molecular targets and bio-signatory candidates for thyroid cancer. The analysis of enrichment has determined the activation of significant cancer pathways, metabolic pathways and related pathways of the immune system. The protein interaction network of genes that differentiate genetically identified by advanced statistical analyses has been created and the specific molecular targets and bio-signal candidates for thyroid cancer have been identified as JUN, LRRK2, BCL2, CCND1, TLE1, MET, ICAM1, DDB2 and RXRG. By analyzing an independent set of data, it has been determined that these genes can distinguish tumor and normal tissues. Among these proteins, JUN, TLE1 and DBB2 may be a new molecular target and biosignal candidate. It is predicted that the set goals can be used in the development of diagnostic and treatment strategies for papillary thyroid cancer. However, the candidates concerned must be conducted with simultaneous PCR experimental studies.
Thyroid cancer is a fatal disease has a high incidence. Therefore, the determination of molecules involved in thyroid cancer is very crucial for early diagnosis and treatment strategies of the disease. In this study, high-dimensional functional genomic data were integrated with system biology tools and the molecular targets and signatures in thyroid cancer were determined. As a result of enrichment analysis, it was determined that important cancer pathways, metabolic pathways and immune system related pathways were activated. The protein- protein interaction network was reconstructed using differential gene expression is determined by advanced statistical analysis and the molecular targets and signatures in thyroid cancer were determined as JUN, LRRK2, BCL2, CCND1, TLE1, MET, ICAM1, DDB2 and RXRG. It was determined that these genes can differentiate tumor samples and normal thyroid tissues via independent data analysis. Among these proteins, JUN, TLE1 and DBB2 were found to be novel molecular targets. It is predicted that these molecular targets can be used in the diagnosis and treatment strategies of papillary thyroid cancer. However, it is necessary to perform experimental studies with real time-PCR.
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