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A Decade of Global mRNA and miRNA Profiling of HPV-Positive Cell Lines and Clinical Specimens

For more than a decade, global gene expression profiling has been extensively used to elucidate the biology of human papillomaviruses (HPV) and their role in cervical- and head-and-neck cancers. Since 2008, the expression profiling of miRNAs has been reported in multiple HPV studies. Two major strat...

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Detalles Bibliográficos
Autores principales: Kaczkowski, Bogumil, Morevati, Marya, Rossing, Maria, Cilius, Finn, Norrild, Bodil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bentham Open 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3547333/
https://www.ncbi.nlm.nih.gov/pubmed/23341857
http://dx.doi.org/10.2174/1874357901206010216
Descripción
Sumario:For more than a decade, global gene expression profiling has been extensively used to elucidate the biology of human papillomaviruses (HPV) and their role in cervical- and head-and-neck cancers. Since 2008, the expression profiling of miRNAs has been reported in multiple HPV studies. Two major strategies have been employed in the gene and miRNA profiling studies: In the first approach, HPV positive tumors were compared to normal tissues or to HPV negative tumors. The second strategy relied on analysis of cell cultures transfected with single HPV oncogenes or with HPV genomes compared to untransfected cells considered as models for the development of premalignant and malignant transformations. In this review, we summarize what we have learned from a decade of global expression profiling studies. We performed comprehensive analysis of the overlap of the lists of differentially expressed genes and microRNAs, in both tissue samples and cell culture based studies. The review focuses mainly on HPV16, however reports from other HPV species are used as references. We discuss the low degree of consensus among different studies and the limitation of differential expression analysis as well as the fragmented miRNA-mRNA target correlation evidence. Furthermore, we propose an approach for future research to include more comprehensive miRNA-mRNA target correlation analysis and to apply systems biology/gene networks methodology.