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MicroRNA profiling of patient plasma for clinical trials using bioinformatics and biostatistical approaches.
Markowitz, Joseph; Abrams, Zachary; Jacob, Naduparambil K; Zhang, Xiaoli; Hassani, John N; Latchana, Nicholas; Wei, Lai; Regan, Kelly E; Brooks, Taylor R; Uppati, Sarvani R; Levine, Kala M; Bekaii-Saab, Tanios; Kendra, Kari L; Lesinski, Gregory B; Howard, J Harrison; Olencki, Thomas; Payne, Philip R; Carson, William E.
Affiliation
  • Markowitz J; Department of Cutaneous Oncology, Moffitt Cancer Center, Tampa, FL; Comprehensive Cancer Center, The Ohio State University, Columbus, OH; Department of Oncologic Sciences, USF Morsani School of Medicine, Tampa, FL; Division of Medical Oncology, The Ohio State University Wexner Medical Center.
  • Abrams Z; Comprehensive Cancer Center, The Ohio State University, Columbus, OH; Department of Biomedical Informatics.
  • Jacob NK; Comprehensive Cancer Center, The Ohio State University, Columbus, OH; Department of Radiation Oncology.
  • Zhang X; Comprehensive Cancer Center, The Ohio State University, Columbus, OH; Center for Biostatistics.
  • Hassani JN; Department of Cutaneous Oncology, Moffitt Cancer Center, Tampa, FL.
  • Latchana N; Department of Surgery, The Ohio State University, Columbus, OH, USA.
  • Wei L; Comprehensive Cancer Center, The Ohio State University, Columbus, OH; Center for Biostatistics.
  • Regan KE; Comprehensive Cancer Center, The Ohio State University, Columbus, OH; Department of Biomedical Informatics.
  • Brooks TR; Comprehensive Cancer Center, The Ohio State University, Columbus, OH.
  • Uppati SR; Comprehensive Cancer Center, The Ohio State University, Columbus, OH.
  • Levine KM; Comprehensive Cancer Center, The Ohio State University, Columbus, OH.
  • Bekaii-Saab T; Comprehensive Cancer Center, The Ohio State University, Columbus, OH; Division of Medical Oncology, The Ohio State University Wexner Medical Center.
  • Kendra KL; Comprehensive Cancer Center, The Ohio State University, Columbus, OH; Division of Medical Oncology, The Ohio State University Wexner Medical Center.
  • Lesinski GB; Comprehensive Cancer Center, The Ohio State University, Columbus, OH; Division of Medical Oncology, The Ohio State University Wexner Medical Center.
  • Howard JH; Comprehensive Cancer Center, The Ohio State University, Columbus, OH; Department of Surgery, The Ohio State University, Columbus, OH, USA.
  • Olencki T; Comprehensive Cancer Center, The Ohio State University, Columbus, OH; Division of Medical Oncology, The Ohio State University Wexner Medical Center.
  • Payne PR; Comprehensive Cancer Center, The Ohio State University, Columbus, OH; Department of Biomedical Informatics.
  • Carson WE; Comprehensive Cancer Center, The Ohio State University, Columbus, OH; Department of Surgery, The Ohio State University, Columbus, OH, USA.
Onco Targets Ther ; 9: 5931-5941, 2016.
Article in En | MEDLINE | ID: mdl-27729802
ABSTRACT

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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Onco Targets Ther Year: 2016 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Onco Targets Ther Year: 2016 Document type: Article