Biomarkers in Risk Prediction Model (RPM) Predicting Recurrence in Patients with Ductal Carcinoma in situ (DCIS)

Overview

Objectives/Goals DCIS is heterogeneous without clear prognostic indicators for recurrence defined in terms of DCIS or IC. While the Van Nuys Prognostic Index (VNPI) has been used clinically for predicting recurrence, there has been no good biomarker(s) that predict outcome in DCIS patients. Cancer Genome Atlas Network (Perou et al, Nature 2012) have identified specific novel gene mutations in GATA 3 and FOX A1 which exhibited strong association with Luminal A subtype. The purpose of study is to build a model that is based on a set of highly relevant biomarkers that could be used in predicting recurrence in DCIS patients. Methods/Materials Tumor blocks of 291 patients with DCIS were retrieved from tumor registry database. Out of these only 219 cases that had complete (clinical, radiological, treatment) follow up information were chosen for the study. The equipment used for study included microtome, Leica Bond Max Autostainer and Antibody kits. Formalin fixed, paraffin-embedded tumor blocks of tissue samples were cut by microtome to obtain blank sections. Immunohistochemistry (IHC) staining method was performed on these slides. IHC is the process of detecting antigen (protein) binding to antibody. Netica and Graph Pad Prism were used for statistical analysis Results We are reporting the results of biological marker expression in terms of recurrence and ER status. We have stratified patients into ER (+) and ER (-) groups since patients with ER (+) invasive cancers have exhibited longer disease free interval and overall survival than ER (-) patients. ER (-) patients have expressed lower GATA-3 expression (p<0.05), higher HER2 expression (p<0.05), and higher proliferation rate for Ki-67 (p<0.05) along with higher recurrence rate either as DCIS or IC. Conclusions/Discussion Our study was the first to analyze novel transcription factors FOX A1 and GATA 3 biomarkers in a large cohort of cases with 15+ years of follow up to predict recurrence in DCIS patients. The predictive model can be used (1) by physicians and patients in monitoring and aggressively pursuing treatment options without waiting for the onset of recurrence. (2) In developing targeted therapies for FOX A1 and GATA 3 biomarkers in patients.

Awards (1)

• Honorable Mention

Competition history

• CSEF 2014 Mammalian Biology · Entry S1202

Resources

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