As of April 1, 2021, more than 2.8 million people have died of SARS-CoV-2 infection. In addition, the mutation of virus strains that have accompanied the pandemic has brought more severe challenges to pandemic control. Host microRNAs (miRNAs) are widely involved in a variety of biological processes of coronavirus infection, including autophagy in SARS-CoV-2 infection. However, the mechanisms underlying miRNAs involved in autophagy in SARS-CoV-2 infection have not been fully elucidated. In this study, the miRNA and messenger RNA (mRNA) expression profiles of patients with SARS-CoV-2 infection were investigated based on raw data from Gene Expression Omnibus (GEO) datasets, and potential novel biomarkers of autophagy were revealed by bioinformatics analyses. We identified 32 differentially expressed miRNAs and 332 differentially expressed mRNAs in patients with SARS-CoV-2 infection. Cytokine receptor related pathways were the most enriched pathways for differentially expressed miRNAs identified by pathway analysis. Most importantly, an autophagy interaction network, which was associated with the pathological processes of SARS-CoV-2 infection, especially with the cytokine storm, was constructed. In this network, hsa-miR-340–3p, hsa-miR-652–3p, hsa-miR-4772–5p, hsa-miR-192–5p, TP53INP2, and CCR2 may be biomarkers that predict changes in mild SARS-CoV-2 infection. Some molecules, including hsa-miR-1291 and CXCR4, were considered potential targets to predict the emergence of severe symptoms in SARS-CoV-2 infection. To our knowledge, this study provided the first profile analysis of an autophagy interaction network in SARS-CoV-2 infection and revealed several novel autophagy-related biomarkers for understanding the pathogenesis of SARS-CoV-2 infection in vivo.

Background Because its metastasis to the lymph nodes are closely related to poor prognosis, miRNAs and mRNAs can serve as biomarkers for the diagnosis, prognosis, and therapy of colorectal cancer (CRC). This study aimed to identify novel gene signatures in the lymph node metastasis of CRC. Methods GSE56350, GSE70574, and GSE95109 datasets were downloaded from the Gene Expression Omnibus (GEO) database, while data from 569 colorectal cancer cases were also downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs (DE-miRNAs) were calculated using R programming language (Version 3.6.3), while gene ontology and enrichment analysis of target mRNAs were performed using FunRich (http://www.funrich.org). Furthermore, the mRNA–miRNA network was constructed using Cytoscape software (Version 3.8.0). Gene expression levels were verified using the GEO datasets. Similarly, quantitative real-time PCR (qPCR) was used to examine expression profiles from 20 paired non-metastatic and metastatic lymph node tissue samples obtained from patients with CRC. Results In total, five DE-miRNAs were selected, and 34 mRNAs were identified after filtering the results. Moreover, two key miRNAs (hsa-miR-99a, hsa-miR-100) and one gene (heparan sulfate-glucosamine 3-sulfotransferase 2 [HS3ST2]) were identified. The GEO datasets analysis and qPCR results showed that the expression of key miRNA and genes were consistent with that obtained from the bioinformatic analysis. A novel miRNA–mRNA network capable of predicting the prognosis and confirmed experimentally, hsa-miR-99a-HS3ST2-hsa-miR-100, was found after expression analysis in metastasized lymph node tissue from CRC samples. Conclusion In summary, miRNAs and genes with potential as biomarkers were found and a novel miRNA–mRNA network was established for CRC lymph node metastasis by systematic bioinformatic analysis and experimental validation. This network may be used as a potential biomarker in the development of lymph node metastatic CRC.

Background The role of circular RNAs (circRNAs) and microRNAs (miRNAs) in osteosarcoma (OS) development has not been fully elucidated. Further, the contribution of the immune response to OS progression is not well defined. However, it is known that circRNAs and miRNAs can serve as biomarkers for the diagnosis, prognosis, and therapy of many cancers. Thus, the aim of this study was to identify novel key serum biomarkers for the diagnosis and metastatic prediction of OS by analysis of immune cell infiltration and associated RNA molecules. Methods Human OS differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were identified by analysis of microarray data downloaded from Gene Expression Omnibus (GEO) datasets. Further, characteristic patterns of OS-infiltrating immune cells were analyzed. On this basis, we identified statistically significant transcription factors. Moreover we performed pathway enrichment analysis, constructed protein–protein interaction networks, and devised competitive endogenous RNA (ceRNA) networks. Biological targets of the ceRNA networks were evaluated and potential OS biomarkers confirmed by RT-qPCR analysis of the patients’ serum. Results Seven differentially expressed circRNAs, 166 differentially expressed miRNAs, and 175 differentially expressed mRNAs were identified. An evaluation of cellular OS infiltration identified the highest level of infiltration by M0 macrophages, M2 macrophages, and CD8+ T cells, with M0 macrophages and CD8+ T cells as the most prominent. Significant patterns of tumor-infiltrating immune cells were identified by principal component analysis. Moreover, 185 statistically significant transcription factors were associated with OS. Further, in association with immune cell infiltration, hsa-circ-0010220, hsa-miR-326, hsa-miR-338-3p, and FAM98A were identified as potential novel biomarkers for OS diagnosis. Of these, FAM98A had the most promise as a diagnostic marker for OS and OS metastasis. Most importantly, a novel diagnostic model consisting of these four biomarkers (hsa-circ-0010220, hsa-miR-326, hsa-miR-338-3p, and FAM98A) was established with a 0.928 AUC value. Conclusions In summary, potential serum biomarkers for OS diagnosis and metastatic prediction were identified based on an analysis of immune cell infiltration. A novel diagnostic model consisting of these four promising serum biomarkers was established. Taken together, the results of this study provide a new perspective by which to understand immunotherapy of OS.

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Background: miRNAs and mRNAs can serve as biomarkers for the diagnosis, prognosis and therapy of colorectal cancer (CRC), whose metastasis to lymph node is closely related to the poor prognosis. The current study aimed to identify the novel gene signatures in the lymph node metastasis of CRC.Methods: GSE56350, GSE70574 and GSE95109 were downloaded from the Gene Expression Omnibus (GEO) database and 569 colorectal cancer statistics were also downloaded from the The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs (DE-miRNAs) were calculated by using R software. Besides, gene ontology and Enriched pathway analysis of target mRNAs were analyzed by using FunRich. Furthermore, the mRNA-miRNA network was constructed using Cytoscape software. Gene expression level was verified by GEO datasets and forty paired lymph node non-metastasis CRC tissues and lymph node metastatic CRC tissues obtained from patients with CRC using quantitative real-time PCR (qPCR) .Results: In total, five DE-miRNAs were selected, and 34 mRNAs were identified after filtering. Moreover, 2 key miRNAs and one gene were identified including hsa-miR-99a, has-miR-100 and heparan sulfate-glucosamine 3-sulfotransferase 2 (HS3ST2). The GEO datasets analysis and qPCR results showed the expression of key miRNA and genes were consistent with that in the bioinformatic analysis. A novel miRNA-mRNA network, hsa-miR-99a-HS3ST2-has-miR-100 was found in lymph node metastasis of CRC after expression analysis, prognostic prediction and experiments confirmation.Conclusions: In summary, the potential miRNAs and genes were found and a novel miRNA-mRNA network was established in CRC lymph node metastasis by systematic bioinformatic analysis and experiments validation, which may be used as potential biomarkers in the development of lymph node metastatic CRC.