This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Statement of the problem: Approximately 90% of all endocrine cancers are thyroid carcinomas (Hundahl et al., 1998;Correra et al., 1995). Over 33,500 new cases of thyroid cancer (TC) are expected this year, and 1,530 Americans are expected to die from the disease (Jemal et al., 2007). Early detection can increase survival rate. Currently, most patients diagnosed with a thyroid nodule are referred for fine needle aspirate (FNA) biopsy to determine if the nodule is malignant or not. This method is helpful in determining if the nodule consists of benign follicular epithelium cells. In many cases of follicular neoplasms, due to similarity in cytologic features, benign tumor cannot be differentiated from malignant cancer during examination of FNA specimen. It is impossible to evaluate capsular and vascular invasion in FNA samples. In these cases, surgery is routinely recommended for the treatment of thyroid nodules from which a suspicious aspiration has been obtained. In fact, as many as 80% of the undetermined cases are identified as benign tumors during histological examinations after the surgery is performed (Deveci et al., 2006). The development of rapid, sensitive, specific, reliable, and inexpensive methods to differentially diagnose cancers and to monitor remission after treatment is necessary. If successful, it would reduce or even eliminate unnecessary thyroidectomies in many patients with suspicious FNA results. We believe that the study proposed here will lead to development of such a tool. The objective of the study is to explore a set of proteomic and genomic biomarkers specific to the type of TC using RNA and proteins extracted from the blood serum and plasma and from FNA specimens. These results would later be compared with a set of proteomic and genomic biomarkers from tumor samples excised during the surgery and with the corresponding post surgical histo-pathological diagnosis. As a result, a smaller subset of suitable genomic and proteomic markers will be determined. This will help design a larger follow-up experiment to identify biomarker profiles of mixed cell populations from thyroid biopsies from patients with known clinical outcomes. Focusing on fewer protein chip types will allow increasing the number of replications from different TC types and obtaining results that will be much more statistically significant. In the long run, a system of rapid TC diagnostics may be developed. The specific hypothesis behind the proposed research is that each type of TC can be characterized by a specific set of biomarkers. Methods: FNAs are preformed for diagnostic purposes and not specifically for this study. For this study, additional aspirates would be collected during the routine FNA procedure to be used in the proteomic study. Blood serum would be collected from the patients consenting to this procedure. If surgery is performed, a fragment of tissue saved for histo-pathological evaluation would be used in this study. FNA procedure: is performed with or without local anesthesia. About 1-6 aspirations are collected using 27-25 gauge needle. After the procedure patient may expect slight discomfort and skin discoloration or hematoma. The procedure is performed by experienced endocrinologist or pathologist. Blood collection: approximately 15-20ml of blood will be collected from each patient Tumor sample: if the surgery is performed, a fragment of the removed tumor (approx. 250-500mg) will be snap frozen and stored in -80C) for further analysis. Sample processing and data analysis: RNA and protein samples will be extracted from FNA and tissue samples and stored in -80C until processed using microarray chips SELDI-TOF chips respectively.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
General Clinical Research Centers Program (M01)
Project #
5M01RR000109-46
Application #
8166996
Study Section
National Center for Research Resources Initial Review Group (RIRG)
Project Start
2010-03-01
Project End
2011-02-28
Budget Start
2010-03-01
Budget End
2011-02-28
Support Year
46
Fiscal Year
2010
Total Cost
$11,125
Indirect Cost
Name
University of Vermont & St Agric College
Department
Type
Schools of Medicine
DUNS #
066811191
City
Burlington
State
VT
Country
United States
Zip Code
05405
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