GW AIDS and Cancer Specimen Resource Designing a Fit-for-Purpose Study to Assess the Effect of Storage Time and Cancer Type on the Quality of Formalin Fixed Paraffin Embedded Tissues Anna Yakovleva1, Jordan Plieskatt1, Sarah Jensen1, Nidia Kitice1, Razan Humeida2, Jonathan Lang2, Sylvia Silver1,2, Jeffrey Bethony1,2 1Department of Microbiology, Immunology and Tropical Medicine; School of Medicine and Health Science; George Washington University; Washington; DC; 2GW AIDS and Cancer Specimen Resource; School of Medicine and Health Science; George Washington University; Washington; DC Introduction Results Prior to 2014 fit-for-purpose (FFP) studies were limited to assessing the quality of a single molecular extract (e.g., DNA) on very small sample sizes from formalin fixed paraffin embedded (FFPE) tissues. To enhance the design and outcomes for a more robust FFP study, especially relevant to biorepositories, we improved on previous studies by taking the following approaches: Significantly increased sample size. Simultaneously assessed the quality of multiple molecular extracts (DNA, RNA, miRNA and protein) for a single FFPE tissue block. Provided quality assessments that are relevant to downstream laboratory workflows. Objective: To elucidate the impact of storage time and cancer type on the quality of DNA, RNA, and protein extracted from FFPE tissues. Quality Measures of DNA Extracted from Papillary Carcinoma Cases DNA Concentration (ng/mL) Quality Measures of DNA Extracted from Adenocarcinoma Cases Quality Measures of DNA Extracted from Squamous Carcinoma Cases 260/280 Absorption Ration of DNA Data Analysis with Categorical Quality Measures Enhances Applicability of Available Information An example with quality measures of DNA extracted from FFPE by age and carcinoma Limitations Associated with Comparing Means and Standard Deviations of Quality Measures in Analyzing Impact of Carcinoma Type and Storage Duration Range of data points provides no information about the number of cases that will provide molecular extracts that meet the specific requirements of next generation genomic technologies or applications. Differences in means between groups will not assist in executing the laboratory workflows. Outliers may severely skew analysis. Methods Sampling Scheme – Stratified Simple Random Sample Figure 1. Information obtained from continuous measures of DNA quality has limited applicability to the decision making processes required in the work-flows of various next generation technologies. Box plots depict means, medians, and ranges of two quality measures of extracted DNA by carcinoma type and storage duration. The whiskers represent the minimum and the maximum observations from the data. The box captures the inter-quartile range between the 25th and 75th percentiles. All ACSR Specimens Carcinomas with at least 100 unique cases available for selection Equal allocation for maximal power Selected 40 cases each from adeno-, papillary, and squamous carcinomas. 80% power to detect an effect size Equal allocation based on storage time ½ of cases stored for > 11 years (1996-2001); ½ of cases stored for < 11 years (2002-2013). Inclusion criteria: Greater than 3x10 μm available for sectioning (purification) Tissue area occupies > 4 mm2 Information Made Available by Categorical Quality Measures Enhances Laboratory Workflow Figure 2. Model of effects from carcinoma type and storage duration on the odds of extracted DNA falling into specific categories of concentration quality measures. Logistic Regression Model for Multiple Category Measures of Quality An example with quality measures of DNA extracted from FFPE by age and carcinoma Quality Measure: DNA Concentration Figure 3. Model of effects from carcinoma type and storage duration on the odds of extracted DNA falling into specific categories of 260/280 absorbance ratio quality measures. Quality Measure: 260/280 Absorbance Ratio of Extracted DNA 1990 – 2001 (n = 20) 2002 – 2013 DNA 260/280 Absorbance Ratio BEST (n) NOT IN RANGE Papillary 13 7 Adenocarcinoma 17 3 5 Squamous 14 6 DNA Concentration < 10 ng recovered 10 – 49 ng recovered >50 ng recovered 10 – 49 ng 4 12 2 15 1 8 11 Summary of molecular extracts Samples DNA RNA miRNA Protein Extraction Technique Qiagen QIAamp FFPE Rneasy miRNeasy Qproteome FFPE Measure 1 SpectraDrop (Molecular Devices) Concentration-Absorbance Ratios 2 Agilent 2200 Tapestation Genomic DNA DIN-Concentration Agilent 2100 BioAnalyzer RNA 6000 RIN-Concentration Small RNA Concentration Protein 230 Concentration-Size Profile Table 1. Measures of quality of DNA, extracted from cases included in the study, differentiated by specific next generation technology requirements. The number of cases falling into each specified category of quality measure provides information about the possible expected number of cases that will produce molecular extracts of various measures of quality. Conclusions & Applications Next Steps Rationale for Analyzing ‘Quality Measures’ as Categorical Variables In the laboratory, quality measures are used for “decision making” about the work flow involving the extracted products: There are specific threshold values or necessary amounts of RNA, DNA, or protein required for certain processes Information about variation in quality measures of extracted product not as informative as the expected number of ‘high quality’ or usable samples in the selected set. Information about expected frequencies will assist with developing a research plan. Reproduce Protocol for quality measures and sampling scheme for other biobanks and biorepositories. Perform a fit-for-purpose study by cancer and location (e.g., lung, cervical, anal, etc.) and age or for other stored materials (e.g., plasma). Expected frequencies of the number of quality extracts from various FFPE tissues are useful in assisting biorepositories and researchers in the initial phases of study design, such as sample size and power calculations. When quality measures are assessed independently, storage duration and carcinoma type do not affect the quality of extracted DNA and RNA. This sampling scheme, study design, and analytical method may be applied to analyze other factors that may affect the quality of products extracted from FFPE tissue samples Acknowledgements: We would like to acknowledge the support, guidance, and expertise of The AIDs and Cancer Specimen Resource (ACSR) Executive Committee and the Coordinating Data and Operations Center Research (CODCC).  This work was supported by the National Cancer Institute, National Institutes of Health, under award UM1CA181255.