ArticleAsian Pacific journal of cancer prevention : APJCP2019
Risk Categorization with Different Grades of Cervical Pre-Neoplastic Lesions - High Risk HPV Associations and Expression of p53 and RARβ
Article in Asian Pacific journal of cancer prevention : APJCP, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 5 citations in OpenAlex.
- Endogenous YAP1 activation drives immediate onset of cervical carcinoma in situ in mice.Cancer science · 2020Article
- ROC-Analysis Derived Immunohistochemical P53 Cut-Off Scores as an Adjunct to Routine Histopathology for Better Diagnostic Compartmentalisation of Cervical Lesions.International journal of applied & basic medical researchArticle
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To identify high risk HPV associations by evaluating linked p16 overexpression and also the expression of p53 and RARβ together with histopathology for risk categorization of cervical pre-neoplastic lesions. Materials and Methods: Immunohistochemical staining was performed on 100 cases of cervical pre- neoplastic lesions for expression of biomarkers like p16, p53 and RARβ for comparison with haematoxylin/eosin (HE) findings. All the experimentally generated data were statistically analyzed. Results: In this study 70% cases showed overexpression of p16INK4A increasing progressively from CIN I to CIN II but reduced in CIN III (p <0.01). p53 oncoprotein expression was seen in 51% cases, again with increments from CIN I to CIN II with slight reduction in CIN III (p<0.01). Some 24% cases showed negative immunoreactivity for the putative tumor suppressor gene RARβ (p>0.05). Conclusion: Our study provides support for the idea that p16 can be used to identify associations with HPV , as well as having potential along with p53 and RARβ for categorizing cervical pre-neoplastic cases having a higher risk of neoplastic conversion. Thus it may be concluded that accurate risk categorization can be achieved with the help of genetic markers as well as histopathology.
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