RT Journal Article
SR Electronic
T1 Host gene expression profiling of cervical smear is eligible for cancer risk evaluation
JF Journal of Clinical Pathology
JO J Clin Pathol
FD BMJ Publishing Group Ltd and Association of Clinical Pathologists
SP 282
OP 285
DO 10.1136/jclinpath-2012-201313
VO 66
IS 4
A1 Bourmenskaya, Olga
A1 Shubina, Ekaterina
A1 Trofimov, Dmitry
A1 Rebrikov, Denis
A1 Sabdulaeva, Elina
A1 Nepsha, Oksana
A1 Bozhenko, Vladimir
A1 Rogovskaya, Svetlana
A1 Sukhikh, Gennady
YR 2013
UL http://jcp.bmj.com/content/66/4/282.abstract
AB Aims Uterine cervical carcinoma (CC) is known to be a delayed consequence of human papillomavirus (HPV) infection. Considering the reported influence of HPV on host genome activity, we conceived an approach to capture human gene expression profiles corresponding to increased risks of carcinogenesis. Methods A sample set of 143 female participants included a ‘control’ group of 23, a ‘pathology’ group of 83 (cervical abnormalities of varied grade including 10 cases of CC), and a ‘HPV carrier’ group of 37 (infected but manifesting normal cytology). HPV detection, viral load measurements and gene expression profiling were performed by real-time PCR assays. Results Gradual increase in expression of proliferation markers and a decrease in expression of proapoptotic genes, some receptors, PTEN and PTGS2 were demonstrated for progressive grades of cervical intraepithelial neoplasia leading to cancer. All reported trends were statistically significant, for instance, correlation of gene expression values for MKI67, CCNB1 and BIRC5. A model was proposed that employed mRNA concentrations for genes MKI67, CDKN2A, PGR and BAX. Prompt distinction between the norm and the cancer, provided by initial calculation, suggested that positive values of the function could indicate the higher individual risks. Indeed, all patients assigned to high risk by calculation were HPV infected and showed elevated viral E6, E7 mRNA concentration known to be associated with CC onset. Conclusions The research was concentrated on dynamical gene expression profiling upon pathological changes ultimately leading to CC. Differences of normalised mRNA concentrations were used for quantitative model design and its primary approbation.