MicroRNA profiling of patient plasma for clinical trials using bioinformatics and biostatistical approaches

Abstract

Joseph Markowitz,1–4 Zachary Abrams,2,5 Naduparambil K Jacob,2,6 Xiaoli Zhang,2,7 John N Hassani,1 Nicholas Latchana,8 Lai Wei,2,7 Kelly E Regan,2,5 Taylor R Brooks,2 Sarvani R Uppati,2 Kala M Levine,2 Tanios Bekaii-Saab,2,4 Kari L Kendra,2,4 Gregory B Lesinski,2,4 J Harrison Howard,2,8 Thomas Olencki,2,4 Philip R Payne,2,5 William E Carson III2,8 1Department of Cutaneous Oncology, Moffitt Cancer Center, Tampa, FL, 2Comprehensive Cancer Center, The Ohio State University, Columbus, OH, 3Department of Oncologic Sciences, USF Morsani School of Medicine, Tampa, FL, 4Division of Medical Oncology, The Ohio State University Wexner Medical Center, 5Department of Biomedical Informatics, 6Department of Radiation Oncology, 7Center for Biostatistics, 8Department of Surgery, The Ohio State University, Columbus, OH, USA Background: MicroRNAs (miRNAs) are short noncoding RNAs that function to repress translation of mRNA transcripts and contribute to the development of cancer. We hypothesized that miRNA array-based technologies work best for miRNA profiling of patient-derived plasma samples when the techniques and patient populations are precisely defined.Methods: Plasma samples were obtained from five sources: melanoma clinical trial of interferon and bortezomib (12), purchased normal donor plasma samples (four), gastrointestinal tumor bank (nine), melanoma tumor bank (ten), or aged-matched normal donors (eight) for the tumor bank samples. Plasma samples were purified for miRNAs and quantified using NanoString® arrays or by the company Exiqon. Standard biostatistical array approaches were utilized for data analysis and compared to a rank-based analytical approach.Results: With the prospectively collected samples, fewer plasma samples demonstrated visible hemolysis due to increased attention to eliminating factors, such as increased pressure during phlebotomy, small gauge needles, and multiple punctures. Cancer patients enrolled in a melanoma clinical study exhibited the clearest pattern of miRNA expression as compared to normal donors in both the rank-based analytical method and standard biostatistical array approaches. For the patients from the tumor banks, fewer miRNAs (<5) were found to be differentially expressed and the false positive rate was relatively high.Conclusion: In order to obtain consistent results for NanoString miRNA arrays, it is imperative that patient cohorts have similar clinical characteristics with a uniform sample preparation procedure. A clinical workflow has been optimized to collect patient samples to study plasma miRNAs. Keywords: miRNA, profiling, melanoma, rank-based statistic

Keywords

• miRNA
• profiling
• melanoma
• rank-based statistic