[Analysis of the methods and quality assurance of metagenomic next-generation sequencing to detect the microbial cfDNA from blood samples in China].

Objective: To investigate the methods and quality assurance of metagenomic next-generation sequencing (mNGS) to detect the microbial cfDNA (mcfDNA) from blood samples in different laboratories across China. Methods: In October 2020, questionnaires about detecting mcfDNA in blood samples with mNGS were distributed to 80 laboratories across the country. The questionnaire included four parts: pre-analysis, during analysis, post-analysis, and carrying out of performance validation for mNGS. (1) Pre-analysis: the requirements for samples quality, such as collection, storage, the transportation conditions of samples; (2) During analysis: the extraction workflows of mcfDNA, the quality requirements of the library, the application of the sequencing platforms and the bioinformatics analysis pipelines; (3) Post-analysis: the standard of interpretation results for mNGS; (4) Carrying out of performance validation: the minimum detection limit for various pathogens. All laboratories are required to fill in the questionnaire according to the actual situation. The feedback data were summarized and analyzed. Results: The 80 laboratories included 20 medical centers and 60 independent medical laboratories. There were 80.0% (64/80) of laboratories indicated that both plasma and serum samples were used to detect mcfDNA in blood, and the rest of the laboratories (16/80, 20.0%) only used plasma samples. The sequencing platforms used by mNGS laboratories involved in the survey included illumina (49), Beijing Genomics Institute (16), Ion Torrent (13) and Nanopore sequencing (2). There were 87.5% (70/80) of laboratories used the integrated analysis tools built by the third-party laboratories, and other laboratories (12.5%, 10/80) independently built the analysis platform by open-source software. The interpretation criteria of mNGS results varied between laboratories, among which the normalized number of pathogen-specific sequences, relative abundance, genome coverage rate, and the detection of the microorganism in the negative control were the main factors considered by laboratories. Most laboratories (76.3%, 61/80) had carried out the performance validation for the mcfDNA mNGS workflows. The limit of detection of the laboratories-developed mNGS workflows for Gram-positive bacteria, Gram-negative bacteria, fungi, parasites, and other pathogens were mainly distributed at 10-100 copies/ml, DNA virus was mainly distributed at 500-1 000 copies/ml. Conclusions: The mNGS workflows of various laboratories are very different. In order to ensure timely and accurate testing results, every laboratory needs to actively optimize the mNGS testing procedures, improve quality assurance measures, and carry out performance validation before mNGS is widely used in clinical settings.

LncRNA RP11-567G11.1 accelerates the proliferation and invasion of renal cell carcinoma through activating the Notch pathway.

OBJECTIVE: In recent years, the death number of renal cell carcinoma (RCC) has been enhanced annually. The crucial function of long non-coding RNA (lncRNA) in the occurrence and progression of cancer is of great significance. However, the specific role of lncRNAs in the pathogenesis and prognosis of RCC has not been fully elucidated. Therefore, the aim of this study was to uncover the role of lncRNA RP11-567G11.1 in regulating the progression of RCC. PATIENTS AND METHODS: Relative expression level of RP11-567G11.1 in RCC tissues and cells was determined by quantitative Real Time-Polymerase Chain Reaction (qRT-PCR). The influences of RP11-567G11.1 on proliferative and invasive abilities of RCC cells were assessed. Subsequently, regulatory effects of RP11-567G11.1 on the viability and apoptosis of DDP-induced RCC cells were examined. Furthermore, the mRNA and protein levels of Notch pathway-related genes Jagged1/HES5/HEY1 in RCC were detected by qRT-PCR and Western blot, respectively. RESULTS: RP11-567G11.1 expression was significantly up-regulated in RCC tissues and cells. Meanwhile, RP11-567G11.1 was highly expressed in RCC patients with advanced stage. Knockdown of RP11-567G11.1 significantly attenuated proliferative and invasive abilities of 786-O and 769-P cells. Silence of RP11-567G11.1 attenuated viability, while it induced apoptosis in DDP-induced RCC cells. In addition, knockdown of RP11-567G11.1 remarkably down-regulated both mRNA and protein levels of Jagged1, HES5, and HEY1 in RCC. CONCLUSIONS: RP11-567G11.1 accelerates the proliferative and invasive abilities of RCC through activating the Notch pathway. Our findings suggest that it may be a new therapeutic target for RCC.