Background: Although immunoglobulin A nephropathy (IgAN) is one of the foremost primary glomerular disease, treatment of IgAN is still in infancy. Non-invasive biomarkers are urgently needed for IgAN diagnosis. We investigate the difference in expression profiles of exosomal long non-coding-RNAs (lncRNAs) in plasma from IgAN patients compared with their healthy first-degree relatives, which may reveal novel non-invasive IgAN biomarkers. Methods: We isolated exosomes from the plasma of both IgAN patients and their healthy first-degree relatives. High-throughput RNA sequencing and real-time quantitative polymerase chain reaction (qRT-PCR) was used to validate lncRNA expression profiles. Pathway enrichment analysis was used to predict their nearest protein-coding genes. Results: lncRNA-G21551 was significantly down-regulated in IgAN patients. Interestingly, the nearest protein-coding gene of lncRNA-G21551 was found to be encoding the low affinity receptor of the Fc segment of immunoglobulin G (FCGR3B). Conclusions: Exosomal lncRNA-G21551, with FCGR3B as the nearest protein-coding gene, was down-regulated in IgAN patients, indicating its potential to serve as a non-invasive biomarker for IgAN.
The accumulating evidence demonstrates that the apolipoprotein B mRNA editing enzyme catalytic polypeptide-like (APOBEC), DNA-editing protein plays an important role in the molecular pathogenesis of cancer. In particular, the APOBEC3 family was shown to induce tumor mutations by an aberrant DNA editing mechanism. However, knowledge regarding the reconstitution of the APOBEC family genes across cancer types is still lacking. Here, we systematically analyzed the molecular alterations, immuno-oncological features, and clinical relevance of the APOBEC family in pan-cancer. We found that APOBEC genes were widely and significantly differentially expressed between normal and cancer samples in 16 cancer types, and that their expression levels are significantly correlated with the prognostic value in 17 cancer types. Moreover, two patterns of APOBEC-mediated stratification with distinct immune characteristics were identified in different cancer types, respectively. In ACC, for example, the first pattern of APOBEC-mediated stratification was closely correlated with the phenotype of immune activation, which was characterized by a high immune score, increased infiltration of CD8 T cells, and higher survival. The other pattern of APOBEC-mediated stratification was closely correlated with the low-infiltration immune phenotype, which was characterized by a low immune score, lack of effective immune infiltration, and poorer survival. Further, we found the APOBEC-mediated pattern with low-infiltration immune was also highly associated with the advanced tumor subtype and the CIMP-high tumor subtype (CpG island hypermethylation). Patients with the APOBEC-mediated pattern with immune activation were more likely to have therapeutic advantages in ICB (immunological checkpoint blockade) treatment. Overall, our results provide a valuable resource that will be useful in guiding oncologic and therapeutic analyses of the role of APOBEC family in cancer.
As one of the hallmarks of cancer, gene fusions play an important role in tumorigenesis, and have been established as biomarkers and therapeutic targets. Although recent years have witnessed the development of gene fusion databases, a tool with interactive analytic functions remains lacking. Here, we introduce fusion profiling interactive analysis (FPIA), a web server to perform interactive and customizable analysis on fusion genes. With this platform, researchers can easily explore fusion‐associated biological and molecular differences including gene expression, tumor purity and ploidy, mutation, copy number variations, protein expression, immune cell infiltration, stemness, telomere length, microsatellite instability, survival and novel peptides based on 33 cancer types from The Cancer Genome Atlas (TCGA) data. Currently, it contains 31 633 fusion events from 6910 patients. FPIA complements the existing gene fusion annotation databases with its multiomics analytic capacity, integrated analysis features, customized analysis selection and user‐friendly design. The comprehensive data analyses by FPIA will greatly facilitate data mining, hypothesis generation and therapeutic target discovery. FPIA is available at http://bioinfo-sysu.com/fpia.
The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 system has been widely used for genome engineering and transcriptional regulation in many different organisms. Current CRISPR-activation (CRISPRa) platforms often require multiple components because of inefficient transcriptional activation. Here, we fused different phase-separation proteins to dCas9-VPR (dCas9-VP64-P65-RTA) and observed robust increases in transcriptional activation efficiency. Notably, human NUP98 (nucleoporin 98) and FUS (fused in sarcoma) IDR domains were best at enhancing dCas9-VPR activity, with dCas9-VPR-FUS IDR (VPRF) outperforming the other CRISPRa systems tested in this study in both activation efficiency and system simplicity. dCas9-VPRF overcomes the target strand bias and widens gRNA designing windows without affecting the off-target effect of dCas9-VPR. These findings demonstrate the feasibility of using phase-separation proteins to assist in the regulation of gene expression and support the broad appeal of the dCas9-VPRF system in basic and clinical applications.
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