The Mining And Validation Of MiRNA Biomakers In Diffuse Large B Cell Lymphoma

Diffuse large B-cell lymphoma(DLBCL) is the most common form of non-Hodgkin’s lymphoma. In clinical, the diagnosis and classification of DLBCL is based on morphology, histology as well as on immune phenotyping, which is invasive. The acquisition difficultly of pathological specimen or the infection and necrosis of lesion tissue will improve the difficulty of diagnosis. Needle puncture will overcome the limitation of tissue biopsy, as long as it obtains enough lymph samples and combines reliable biomarkers. Micro RNAs(miRNAs) is endogenous small non-coding RNA with regulatory function. They are deregulated in many types of disorders. Furthermore, they are relatively stable both in vitro and vivo; and can be detected in many tissues including blood and solid tissues. It is suggested that they can be candidate biomarkers.With the development of next-generation sequencing(NGS), RNA-seq has become important tool to analyze transcriptome. MiRNA-seq based on NGS technology can provide millions even billions of sequence information, and quickly distinguish miRNAs and their different expression in various tissues, developmental stage and disease status. It provides a powerful tool to study the biological effect of mi RNAs in development and complex diseases. In clinical, the lack of reliable and sensitive miRNA detection method hinders the application of miRNA. MicroRNA-derived fragment length polymorphism assay(miRFLP) is an absolute quantification method based on the miRNA length polymorphism fluorescent quantitative analysis to measure the content of miRNA, can detect miRNA of clinical specimens miRNA quickly and precisely.In this research, we obtain miRNA sequence datasets associated with B cell lymphoma from the NGS database. In order to pick out candidate miRNA biomarkers, some processing and analysis will be done on human miRNAs. After excavating the miRNA biomaker, formalin-fixed, paraffin-embedded(FFPE) tissues about lymphoma will be obtained and these selected candidate miRNAs will be detected using faithful miRNA detection method. The result will be preprocessed and the classifier will be constructed using support vector machine to assess the diagnosis capacity of candidate miRNA biomarkers for DLBCL.So in sum, we acquired 31 miRNA-seq datasets related to B cell lymphoma from the SRA database. These datasets were processed by an independently developed software-mi Ray. In total, eleven miRNAs(miR-378 a, miR-21, mi R-146 a, miR-25, miR-146 b, miR-155, miR-181 a, miR-16, miR-17, mi R-150, miR-222) were recognized based on the result of miRay and the literature. Subsequently these miRNAs were detected in 138 paraffin section samples about B cell lymphoma using mi RFLP. Based on the assay result, we constructed SVM classifiers and found two classifiers only with miR-155 and miR-150 can distinguish reactive hyperplasia and lymphoma, reactive hyperplasia and DLBCL, and the accuracy was 94.89% and 96.49%, respectively. It indicates that miR-150 and miR-155 could be the effective biomarkers of DLBCL in clinical. The combination of the two miRNA biomarkers and needle puncture could be a fast, specific, precise, minimally noninvasive method for diagnosis of DLBCL.