ICEECE2012 Poster Presentations Thyroid cancer (108 abstracts)
Prognostic markers in Papillary Thyroid Cancer by immunohistochemistry
E. Castelblanco 1, , P. Gallel 1, , M. Martinez 3 , L. Barrera 1 , I. Capel 4 , P. Moreno 5 , G. Giménez 6 , M. Puig-Domingo 7 , R. Bella 4 , M. Porta 8 , I. Halperín 8 , S. López 1, , R. Orellana 4 , J. Cameselle 9 , X. Matias-Guiu 1, , D. Mauricio 1, , M. Robledo 10 & J. Maravall 1,
Centro Nacional de Investigaciones Oncoló gicas, Madrid, Spain.
Papillary thyroid cancer (PTC) is the most common endocrine malignancy. Its management has not changed significantly in recent decades, and most patients receive the same treatment. Moreover, there are not alternative treatments for low response or aggressive neoplasias. The availability of reliable prognostic markers that would allow the PTC to be identified based on their aggressiveness at the time of diagnosis would derive in an individualized treatment. In a previous study, our group identified a transcript profile by DNA microarray that allows a prognostic classification with an accuracy level of 95% over its evolution. The current study aimed to establish an immunohistochemical profile to help determine the prognosis of evolution of the PTC
Materials and methods: We have performed Tissue Microarrays immunohistochemistry in a large series of 184 cases of PTC, clinically well characterized, with 17 antibodies (Ab) against proteins encoded by some of the genes identified in our previous study. For statistical analysis, we used the intra-individual mean obtained from four experimental replicates to measure Ab expression. We used the Mann-Whitney U to compare the values of the histoscore group as defined by the prognosis, and adjusted logistic regression model to identify those that contribute significantly to explain tumor poor prognosis
Results: Preliminary analysis of the samples showed differences between groups defined according to forecasts for 12 Ab. The multivariate logistic regression model to explain and distinguish poor from good prognosis showed that five Ab achieved an area under the curve of 0.85 [0.79, 0.90] and an optimal cut-off levels of sensitivity of 90% and specificity of 59%
Conclusions: The preliminary results provide promising results for differentiating good and poor prognosis of PTC. The combination of Ab identified may contribute to the prognostic stratification of PTC (with potential clinical applications)
Fx1
Declaration of interest: The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project.
Funding: This work was supported, however funding details unavailable.
Article tools
My recent searches
My recently viewed abstracts
Authors
Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
© Bioscientifica 2024 |
Privacy policy |
Cookie settings
BiosciAbstracts
Bioscientifica Abstracts is the gateway to a series of products that provide a permanent, citable record of abstracts for biomedical and life science conferences.
Find out more