Establishment of preanalytical conditions for microRNA profile analysis of clinical plasma samples.

The relationship between the expression of microRNAs (miRNAs) in blood and a variety of diseases has been investigated. MiRNA-based liquid biopsy has attracted much attention, and cancer-specific miRNAs have been reported. However, the results of analyses of the expression of these miRNAs vary among studies. The reproduction of results regarding miRNA expression levels could be difficult if there are differences in the data acquisition process. Previous studies have shown that the anticoagulant type used during plasma preparation and sample storage conditions could contribute to differences in measured miRNA levels. Thus, the impact of these preanalytical conditions on comprehensive miRNA expression profiles was examined. First, the miRNA expression profiles of samples obtained from healthy volunteers were analyzed using next-generation sequencing. Based on an analysis of the library concentration, human genome identification rate, ratio of unique sequences and expression profiles, the optimal preanalytical conditions for obtaining highly reproducible miRNA expression profiles were established. The optimal preanalytical conditions were as follows: ethylenediaminetetraacetic acid (EDTA) as the anticoagulant, whole-blood storage at room temperature within 6 hours, and plasma storage at 4°C or -20°C within 30 days. Next, plasma samples were collected from 60 cancer patients (3 facilities × 20 patients/facility), and miRNA expression profiles were analyzed. There were no significant differences in measurements except in the expression of erythrocyte-derived hsa-miR-451a. However, the variation in hsa-miR-451a levels was smaller among facilities than among individuals. This finding suggests that samples obtained from the same facility could show significantly different degrees of hemolysis across individuals. We found that the standardization of anticoagulant use and storage conditions contributed to reducing the variation in sample quality across facilities. The findings from this study could be useful in developing protocols for collecting samples from multiple facilities for cancer screening tests.

Multiple cancer type classification by small RNA expression profiles with plasma samples from multiple facilities.

Liquid biopsy is expected to be a promising cancer screening method because of its low invasiveness and the possibility of detecting multiple types in a single test. In the last decade, many studies on cancer detection using small RNAs in blood have been reported. To put small RNA tests into practical use as a multiple cancer type screening test, it is necessary to develop a method that can be applied to multiple facilities. We collected samples of eight cancer types and healthy controls from 20 facilities to evaluate the performance of cancer type classification. A total of 2,475 cancer samples and 496 healthy control samples were collected using a standardized protocol. After obtaining a small RNA expression profile, we constructed a classification model and evaluated its performance. First, we investigated the classification performance using samples from five single facilities. Each model showed areas under the receiver curve (AUC) ranging from 0.67 to 0.89. Second, we performed principal component analysis (PCA) to examine the characteristics of the facilities. The degree of hemolysis and the data acquisition period affected the expression profiles. Finally, we constructed the classification model by reducing the influence of these factors, and its performance had an AUC of 0.76. The results reveal that small RNA can be used for the classification of cancer types in samples from a single facility. However, interfacility biases will affect the classification of samples from multiple facilities. These findings will provide important insights to improve the performance of multiple cancer type classifications using small RNA expression profiles acquired from multiple facilities.