Abstract

9529 Background: Fine needle aspiration biopsy (FNAB) is increasingly used to arrive at cancer diagnosis. It can be limited by low specificity and sensitivity with high indeterminate rate. Pathologists may differ in general acceptance based on lack of clearcut microscopic diagnostic criteria. Incorporating mutational analysis into FNAP evaluation offers the potential to improve diagnostic accuracy and provide valuable prognostic information. We report a novel integrated molecular pathology approach for clinical FNAP diagnosis. Methods: Residual FNAB material was collected ex vivo from 17 patients with solid organ cancers (lung [4], esophagus [3], stomach [1], colon [4], breast [2], kidney [2] and soft tissue [1]). Corresponding tissue sections of the resected organ were gathered for correlative mutational profiling. Three types of representative FNAB samples were obtained consisting of 1) 10–25 ul of original FNAB cellular fluid {OCF}, 2) 15–30 mls of residual liquid based cytology fluid {LCF} and 3) microdissected individual cell clusters from cytology slides {MCC}. The DNA from each sample was extracted and PCR amplified for a broad panel of markers targeting 1p,3p,5q,9p,10q,17p, and k-ras-2. Cumulative amount of LOH and point mutational change was determined as well as timeline of mutation acquisition for each sample using high through-put electrophoresis. Results: A total of 221 individual genotyping reactions were performed resulting in 155 informative results and 83 detectable mutations. The range of concordance rate for mutational change was OCF: 76- 92%, LCF: 83- 94%, MCC: 74- 92%, all three methods: 91- 99%. The time course of mutation acquisition could be established by each method and was similar to that defined in resected tissue in all cases. Molecular analysis did not interfere with traditional cytology practice for evaluating these specimens. Conclusions: Integrated mutational analysis performed before, during and following cytology evaluation, using residual samples can provide highly discriminating information to diagnose, classify and prognosticate cancer and related lesions while complementing pathology practice. Author Disclosure Employment or Leadership Consultant or Advisory Role Stock Ownership Honoraria Research Funding Expert Testimony Other Remuneration RedPath Integrated Pathology RedPath Integrated Pathology RedPath Integrated Pathology

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