Conventional tumor markers for non-invasive diagnosis of gastric cancer (GC) exhibit insufficient sensitivity and specificity to facilitate detection of early gastric cancer (EGC). We aimed to identify EGC-specific exosomal lncRNA biomarkers that are highly sensitive and stable for the non-invasive diagnosis of EGC. Hence, in the present study, exosomes from the plasma of five healthy individuals and ten stage I GC patients and from culture media of four human primary stomach epithelial cells and four gastric cancer cells (GCCs) were isolated. Exosomal RNA profiling was performed using RNA sequencing to identify EGC-specific exosomal lncRNAs. A total of 79 and 285 exosomal RNAs were expressed at significantly higher levels in stage I GC patients and GCCs, respectively, than that in normal controls. Through combinational analysis of the RNA sequencing results, we found two EGC-specific exosomal lncRNAs, lncUEGC1 and lncUEGC2, which were further confirmed to be remarkably up-regulated in exosomes derived from EGC patients and GCCs. Furthermore, stability testing demonstrates that almost all the plasma lncUEGC1 was encapsulated within exosomes and thus protected from RNase degradation. The diagnostic accuracy of exosomal lncUEGC1 was evaluated, and lncUEGC1 exhibited AUC values of 0.8760 and 0.8406 in discriminating EGC patients from healthy individuals and those with premalignant chronic atrophic gastritis, respectively, which was higher than the diagnostic accuracy of carcinoembryonic antigen. Consequently, exosomal lncUEGC1 may be promising in the development of highly sensitive, stable, and non-invasive biomarkers for EGC diagnosis.Electronic supplementary materialThe online version of this article (10.1186/s12943-018-0834-9) contains supplementary material, which is available to authorized users.

Outbreaks of both influenza virus and the novel coronavirus SARS-CoV-2 are serious threats to human health and life. It is very important to establish a rapid, accurate test with large-scale detection potential to prevent the further spread of the epidemic. An optimized RPA-Cas12a-based platform combined with digital microfluidics (DMF), the RCD platform, was established to achieve the automated, rapid detection of influenza viruses and SARS-CoV-2. The probe in the RPA-Cas12a system was optimized to produce maximal fluorescence to increase the amplification signal. The reaction droplets in the platform were all at the microliter level and the detection could be accomplished within 30 min due to the effective mixing of droplets by digital microfluidic technology. The whole process from amplification to recognition is completed in the chip, which reduces the risk of aerosol contamination. One chip can contain multiple detection reaction areas, offering the potential for customized detection. The RCD platform demonstrated a high level of sensitivity, specificity (no false positives or negatives), speed (≤30 min), automation and multiplexing. We also used the RCD platform to detect nucleic acids from influenza patients and COVID-19 patients. The results were consistent with the findings of qPCR. The RCD platform is a one-step, rapid, highly sensitive and specific method with the advantages of digital microfluidic technology, which circumvents the shortcomings of manual operation. The development of the RCD platform provides potential for the isothermal automatic detection of nucleic acids during epidemics. Electronic Supplementary Material Supplementary material is available in the online version of this article at 10.1007/s11426-021-1169-1.

Increased expression of RanBPM associates with postponed disease progression and better prognosis. RanBPM plays an inhibitory role in regulating proliferation and invasion of lung cancer cells.

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