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HPV-16 long control region (LCR) has been shown to be the most variable region of the HPV-16 genome and may play important roles in viral persistence and the development of cervical cancer. This study aimed to assess the risk of HPV-16 LCR variants for cervical cancer in women of Southwest China. 2146 cervical scrapings of volunteer outpatients and 74 cervical cancer tissues were screened.14 entire HPV-16 LCRs from asymptomatic carriers and 34 entire HPV-16 LCRs from cervical cancer patients were successfully amplified and sequenced to align to others described. 58 different point mutations were detected in 54 nucleotide sites of HPV-16 LCR. G7193T and G7521A variants, accounting for 100% of the infections, were predicted to locate at the binding site for FOXA1 and SOX9, respectively. A7730C variant which showed a high mutation frequency in cervical cancer was predicted to be a binding site for the cellular transcription factor PHOX2A. In addition, phylogenetic analysis displayed a high prevalence of A lineage in HPV-16 LCR in this Southwest China population. This study may help understanding of the intrinsic geographical relatedness and the correlations between LCR mutations and the development of carcinogenic lesions in Southwest China population. And it provides useful data for the further study of the biological function of HPV-16 LCR variants.
Pubmed ID: 28767682
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Open source database of curated, non-redundant set of profiles derived from published collections of experimentally defined transcription factor binding sites for multicellular eukaryotes. Consists of open data access, non-redundancy and quality. JASPAR CORE is smaller set that is non-redundant and curated. Collection of transcription factor DNA-binding preferences, modeled as matrices. These can be converted into Position Weight Matrices (PWMs or PSSMs), used for scanning genomic sequences. Web interface for browsing, searching and subset selection, online sequence analysis utility and suite of programming tools for genome-wide and comparative genomic analysis of regulatory regions. New functions include clustering of matrix models by similarity, generation of random matrices by sampling from selected sets of existing models and a language-independent Web Service applications programming interface for matrix retrieval.
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