{{get_dataset_fail}}




{{section.text}} {{section.text}} {{section.text}} {{section.text}} {{dataset.name}}


The effect of preventive vaccination against Human Papillomavirus (HPV) in reducing the burden of cervical cancer (CC) will not be seen before 30 years. It is still necessary to improve the procedures of screening and treatment against CC. Current methods for screening have low sensitivity (Pap test) or specificity (HPV tests) to detect high-grade cervical intraepithelial neoplasias (CIN) and CC (CIN2+). The objective of this study was the identification and characterization of cellular targets present in most CC and absent in normal cervical tissue that can be considered as potential markers for screening or therapeutic targets. Methods and Findings. A pyramidal strategy was used. Initially the expression of 8,638 genes was compared between 43 HPV16-positive CC and 12 healthy cervical epitheliums using the HG-Focus microarray. The expression intensity of 8,370 genes was validated in 24 samples with a second microarray (HG-ST1.0). A total of 997 genes were deregulated in CC and the 21 best ranked were validated and confirmed by qRT-PCR in 67 CC and 25 controls. According to the ROC analysis and the fold change (FC), the best (AUC ≥ 0.97 and FC ≥ 10) six genes (CCNB2, CDC20, PRC1, SYCP2, NUSAP1, CDKN3) belong to the mitosis pathway. They were further explored by qRT-PCR in 29 CIN1 and 21 CIN2/3 lesions to investigate whether they could differentiate CIN2+ from CIN1 and healthy cervical epitheliums (CIN1-). Three of these genes were associated exclusively with invasive tumors (CCNB2, PRC1, SYCP2) and three (CDC20, NUSAP1, CDKN3) also with CIN2/3. The sensitivity and specificity of CDKN3 and NUSAP1, along with CDKN2A, to detect CIN2+ was around 90%. The protein codified by these genes was confirmed by immunohistochemistry in CC. The effect of these markers on the survival was investigated in 40 CC patients followed by 42 months. Only high-expression level of CDKN3 was associated with a poor survival (20%; p = 2 x 10-4, Long-rank test) and it was independent from FIGO staging. Conclusions. CDKN3 and NUSAP1, together with CDKN2A, may be potential targets for development of screening methods. However, further studies are needed from a screening population to define the optimal trade-off between sensitivity and specificity for detection of CIN2+. CDKN3 may be also considered as a survival marker. Inhibition of mitosis is a well-known strategy to combat cancers. Therefore, CDKN3 may be a potential therapeutic target in CC. However, it´s still necessary to demonstrate whether it´s indispensable for tumor growth. cervical cancer vs. healthy cervix

ABSTRACT: {{section.text}} {{section.text}} {{section.text}} {{section.text}} {{abstract_sections[abstract_sections.length-1].tobeReduced=='true'?"... [more]":""}} [less]

SAMPLE PROTOCOL: {{section.text}} {{section.text}} {{section.text}} {{section.text}} {{sample_protocol_sections[sample_protocol_sections.length-1].tobeReduced=='true'?"... [more]":""}} [less]

DATA PROTOCOL: {{section.text}} {{section.text}} {{section.text}} {{section.text}} {{data_protocol_sections[data_protocol_sections.length-1].tobeReduced=='true'?"... [more]":""}} [less]

REANALYSIS of: {{reanalysis_item.accession}}

REANALYZED by: {{reanalyzed_item.accession}}

OTHER RELATED OMICS DATASETS IN: {{reanalysis_item.accession}}

INSTRUMENT(S): {{instrument+';'}}

ORGANISM(S): {{organism.name + ';'}}

TISSUE(S): {{tissue+';'}}

DISEASE(S): {{disease+';'}}

SUBMITTER: {{dataset['submitter']}}

PROVIDER: {{acc}} | {{repositories[domain]}} | {{dataset['publicationDate']}}

{{publication_info[publication_index_info[dataset.publicationIds[current_publication]]].title}}

{{author.fullname.substr(0,author.fullname.length-2)}} ,

{{publication_info[publication_index_info[dataset.publicationIds[current_publication]]].citation}}


Sorry, this publication's infomation has not been loaded in the Indexer, please go directly to PUBMED or Altmetric.

ABSTRACT: {{publication_info[publication_index_info[dataset.publicationIds[current_publication]]].pub_abstract[0]}}
{{publication_info[publication_index_info[dataset.publicationIds[current_publication]]].pub_abstract[1]}} [less]

ABSTRACT: {{publication_info[publication_index_info[dataset.publicationIds[current_publication]]].pub_abstract[0]|limitTo:500}} {{publication_info[publication_index_info[dataset.publicationIds[current_publication]]].pub_abstract[0].length>500?"... [more]":""}}

Publication: {{current_publication +1}}/{{dataset.publicationIds.length}}

{{dataset.publicationIds[current_publication].publicationDate}}


Only show the datasets with similarity scores above:{{threshold}}

Threshold:
    {{threshold}}
     

The biological similarity score is calculated based on the number of molecules (Proteins, Metabolites, Genes) common between two different projects.

Similar Datasets

  • Organism: {{organism["name"]}} Not available
    {{relatedDataset['publicationDate'].substr(0,4)+"-"+relatedDataset['publicationDate'].substr(4,2)+"-"+relatedDataset['publicationDate'].substr(6,2)}}| {{relatedDataset.id}} | {{repositories[relatedDataset.source]}}