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使用生物信息学和生物统计学方法对用于临床试验的患者血浆进行微小RNA分析。

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

作者信息

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

机构信息

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.

Comprehensive Cancer Center, The Ohio State University, Columbus, OH; Department of Biomedical Informatics.

出版信息

Onco Targets Ther. 2016 Sep 29;9:5931-5941. doi: 10.2147/OTT.S106288. eCollection 2016.

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.

摘要

背景

微小RNA(miRNA)是短链非编码RNA,其功能是抑制mRNA转录本的翻译,并参与癌症的发展。我们假设,当技术和患者群体精确定义时,基于miRNA阵列的技术最适合用于患者来源血浆样本的miRNA谱分析。

方法

血浆样本来自五个来源:干扰素和硼替佐米的黑色素瘤临床试验(12份)、购买的正常供体血浆样本(4份)、胃肠道肿瘤库(9份)、黑色素瘤肿瘤库(10份)或与肿瘤库样本年龄匹配的正常供体(8份)。对血浆样本进行miRNA纯化,并使用NanoString阵列或Exiqon公司的方法进行定量。采用标准的生物统计学阵列方法进行数据分析,并与基于秩次的分析方法进行比较。

结果

对于前瞻性收集的样本,由于更加注意消除诸如静脉穿刺时压力增加、小口径针头和多次穿刺等因素,较少的血浆样本出现明显溶血。在基于秩次的分析方法和标准生物统计学阵列方法中,参与黑色素瘤临床研究的癌症患者与正常供体相比,表现出最清晰的miRNA表达模式。对于来自肿瘤库的患者,发现差异表达的miRNA较少(<5个),且假阳性率相对较高。

结论

为了使NanoString miRNA阵列获得一致的结果,患者队列必须具有相似的临床特征和统一的样本制备程序。已优化临床工作流程以收集患者样本,用于研究血浆miRNA。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b09/5047719/1c7579c458f0/ott-9-5931Fig1.jpg

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