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

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 popula...

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Published in:OncoTargets and therapy Vol. 9; pp. 5931 - 5941
Main Authors: 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, 3rd, William E
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Published: New Zealand Dove Medical Press Limited 01-01-2016
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Abstract 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. 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. 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. 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.
AbstractList 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.
BACKGROUNDMicroRNAs (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. METHODSPlasma 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. RESULTSWith 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. CONCLUSIONIn 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.
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. 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. 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. 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.
Audience Academic
Author Wei, Lai
Uppati, Sarvani R
Bekaii-Saab, Tanios
Howard, J Harrison
Levine, Kala M
Zhang, Xiaoli
Regan, Kelly E
Hassani, John N
Olencki, Thomas
Lesinski, Gregory B
Markowitz, Joseph
Abrams, Zachary
Brooks, Taylor R
Kendra, Kari L
Carson, 3rd, William E
Jacob, Naduparambil K
Latchana, Nicholas
Payne, Philip R
AuthorAffiliation 2 Comprehensive Cancer Center, The Ohio State University, Columbus, OH
5 Department of Biomedical Informatics
3 Department of Oncologic Sciences, USF Morsani School of Medicine, Tampa, FL
4 Division of Medical Oncology, The Ohio State University Wexner Medical Center
6 Department of Radiation Oncology
7 Center for Biostatistics
1 Department of Cutaneous Oncology, Moffitt Cancer Center, Tampa, FL
8 Department of Surgery, The Ohio State University, Columbus, OH, USA
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/27729802$$D View this record in MEDLINE/PubMed
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2016. This work is licensed under https://creativecommons.org/licenses/by-nc/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
2016 Markowitz et al. This work is published and licensed by Dove Medical Press Limited 2016
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Keywords melanoma
miRNA
profiling
rank-based statistic
Language English
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Snippet MicroRNAs (miRNAs) are short noncoding RNAs that function to repress translation of mRNA transcripts and contribute to the development of cancer. We...
Background: MicroRNAs (miRNAs) are short noncoding RNAs that function to repress translation of mRNA transcripts and contribute to the development of cancer....
BACKGROUNDMicroRNAs (miRNAs) are short noncoding RNAs that function to repress translation of mRNA transcripts and contribute to the development of cancer. We...
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StartPage 5931
SubjectTerms Analysis
Bioinformatics
Biomarkers
Biometry
Blood
Blood plasma
Cancer therapies
Cell cycle
Clinical trials
Computational biology
Cyclin-dependent kinases
Disease
DNA microarrays
Health aspects
Informatics
Innovations
Kinases
Medical prognosis
Melanoma
Metastasis
MicroRNA
MicroRNAs
Oncology
Original Research
Patients
Phlebotomy
Principal components analysis
Skin cancer
Title MicroRNA profiling of patient plasma for clinical trials using bioinformatics and biostatistical approaches
URI https://www.ncbi.nlm.nih.gov/pubmed/27729802
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Volume 9
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