MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression via recognition of cognate sequences and interference of transcriptional, translational or epigenetic processes. Bioinformatics tools developed for miRNA study include those for miRNA prediction and discovery, structure, analysis and target prediction. We manually curated 95 review papers and ∼1000 miRNA bioinformatics tools published since 2003. We classified and ranked them based on citation number or PageRank score, and then performed network analysis and text mining (TM) to study the miRNA tools development trends. Five key trends were observed: (1) miRNA identification and target prediction have been hot spots in the past decade; (2) manual curation and TM are the main methods for collecting miRNA knowledge from literature; (3) most early tools are well maintained and widely used; (4) classic machine learning methods retain their utility; however, novel ones have begun to emerge; (5) disease-associated miRNA tools are emerging. Our analysis yields significant insight into the past development and future directions of miRNA tools.

/pdf/trends-in-the-development-of-mirna-bioinformatics-tools-k68bndifyi.pdf

Trends in the development of miRNA bioinformatics tools.

Emerging concepts of miRNA therapeutics: from cells to clinic.

Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence

The molecular mechanism of intervertebral disc degeneration (IVDD) remains unclear. This study aimed to investigate the role of circular RNAs (circRNAs) in the pathogenesis of IVDD. We sued nucleus pulposus (NP) tissues of patients, tert-butyl hydroperoxide (TBHP) stimulated NP cells (NPCs), and IVDD rat model to explore the interaction between circERCC2 and miR-182-5p/SIRT1 axis. The results showed that downregulation of circERCC2 increased the level of miR-182-5p and decreased the level of SIRT1 in degenerative NP tissues in vivo as well as in TBHP-stimulated NPCs in vitro. Treatment of SIRT1-si activated apoptosis and inhibited mitophagy. Moreover, miR-182-5p-si could regulate the mitophagy and the apoptosis of NPCs by targeting SIRT1. The effects of circERCC2 on NPCs and IVDD rat model were mediated by miR-182-5p/SIRT1 axis. In conclusion, this study provides the first evidence that circERCC2 could ameliorate IVDD through miR-182-5p/SIRT1 axis by activating mitophagy and inhibiting apoptosis, and suggests that circERCC2 is a potentially effective therapeutic target for IVDD.

/pdf/circercc2-ameliorated-intervertebral-disc-degeneration-by-4dsvwtpvqz.pdf

CircERCC2 ameliorated intervertebral disc degeneration by regulating mitophagy and apoptosis through miR-182-5p/SIRT1 axis

COVID-19 shares the feature of autoantibody production with systemic autoimmune diseases. In order to understand the role of these immune globulins in the pathogenesis of the disease, it is important to explore the autoantibody spectra. Here we show, by a cross-sectional study of 246 individuals, that autoantibodies targeting G protein-coupled receptors (GPCR) and RAS-related molecules associate with the clinical severity of COVID-19. Patients with moderate and severe disease are characterized by higher autoantibody levels than healthy controls and those with mild COVID-19 disease. Among the anti-GPCR autoantibodies, machine learning classification identifies the chemokine receptor CXCR3 and the RAS-related molecule AGTR1 as targets for antibodies with the strongest association to disease severity. Besides antibody levels, autoantibody network signatures are also changing in patients with intermediate or high disease severity. Although our current and previous studies identify anti-GPCR antibodies as natural components of human biology, their production is deregulated in COVID-19 and their level and pattern alterations might predict COVID-19 disease severity. 

https://www.nature.com/articles/s41467-022-28905-5.pdf

Autoantibodies targeting GPCRs and RAS-related molecules associate with COVID-19 severity

MicroRNAs are important regulators of gene expression, achieved by binding to the gene to be regulated. Even with modern high-throughput technologies, it is laborious and expensive to detect all possible microRNA targets. For this reason, several computational microRNA-target prediction tools have been developed, each with its own strengths and limitations. Integration of different tools has been a successful approach to minimize the shortcomings of individual databases. Here, we present mirDIP v4.1, providing nearly 152 million human microRNA-target predictions, which were collected across 30 different resources. We also introduce an integrative score, which was statistically inferred from the obtained predictions, and was assigned to each unique microRNA-target interaction to provide a unified measure of confidence. We demonstrate that integrating predictions across multiple resources does not cumulate prediction bias toward biological processes or pathways. mirDIP v4.1 is freely available at http://ophid.utoronto.ca/mirDIP/.

mirDIP 4.1-integrative database of human microRNA target predictions

The pathological changes in epigenetics and gene regulation that accompany the progression of low-grade to high-grade gliomas are under-studied. The authors use a large set of paired atac-seq and RNA-seq data from surgically resected glioma specimens to infer gene regulatory relationships in glioma. Thirty-eight glioma patient samples underwent atac-seq sequencing and 16 samples underwent additional RNA-seq analysis. Using an atac-seq/RNA-seq correlation matrix, atac-seq peaks were paired with genes based on high correlation values (|r2| > 0.6). Samples clustered by IDH1 status but not by grade. Surprisingly there was a trend for IDH1 mutant samples to have more peaks. The majority of peaks are positively correlated with survival and positively correlated with gene expression. Constructing a model of the top six atac-seq peaks created a highly accurate survival prediction model (r2 = 0.68). Four of these peaks were still significant after controlling for age, grade, pathology, IDH1 status and gender. Grade II, III, and IV (primary) samples have similar transcription factors and gene modules. However, grade IV (recurrent) samples have strikingly few peaks. Patient-derived glioma cultures showed decreased peak counts following radiation indicating that this may be radiation-induced. This study supports the notion that IDH1 mutant and IDH1 wildtype gliomas have different epigenetic landscapes and that accessible chromatin sites mapped by atac-seq peaks tend to be positively correlated with expression. The data in this study leads to a new model of treatment response wherein glioma cells respond to radiation therapy by closing open regions of DNA. 

/pdf/chromatin-structure-predicts-survival-in-glioma-patients-2wjjncnq.pdf

Chromatin structure predicts survival in glioma patients

/pdf/chromatin-structure-predicts-survival-in-glioma-patients-2xm63znx.pdf


 Medulloblastomas (MBs) are the most common malignant childhood brain tumors, yet the origin of the most aggressive subgroup-3 form remains elusive, impeding development of effective targeted treatment strategies. Previous cell-type analyses of mouse cerebella or human counterparts from frozen tissue nuclei have not fully defined the compositional heterogeneity of MBs. Here, we undertook an unprecedented single-cell profiling of freshly-isolated human fetal cerebella at different developmental stages to establish a reference map for delineating the hierarchical cellular states in MBs. We identified a unique transitional cerebellar progenitor connecting neural stem cells to neuronal lineages in human fetal cerebella. Intersectional analysis revealed that the transitional progenitors were enriched in aggressive MB subgroups, including group-3 and metastatic tumors. Integrated single-cell multi-omic profiling revealed unique regulatory networks in the transitional progenitor populations, including transcriptional determinants HNRNPH1 and SOX11, which are correlated with clinical prognosis in aggressive group-3 MBs. Genomic profiling and Hi-C analyses identified de novo long-range chromatin loops juxtaposing HNRNPH1/SOX11-targeted super-enhancers to cis-regulatory elements of MYC, an oncogenic driver for group-3 MBs. Targeting the transitional progenitor regulators inhibited MYC expression and MYC-driven group-3 MB growth. Together, our integrated single-cell atlases of human fetal cerebella and MBs reveal important cell populations predisposed to transformation and regulatory circuitries underlying tumor cell state evolution and oncogenesis, highlighting hitherto unrecognized transitional progenitor intermediates predictive of disease prognosis and potential therapeutic vulnerabilities.

/pdf/stem-24-single-cell-atlas-of-human-fetal-cerebellum-decoding-2c8punwg.pdf

Stem-24. single-cell atlas of human fetal cerebellum decoding medulloblastoma origin and oncogenesis


 Proton therapy is an innovative radiation therapy modality that has been shown to induce higher cytotoxicity to tumor cells compared to standard x-ray therapy while sparing normal tissue. However, the impact of proton radiotherapy on the growth and progression of glioblastoma (GBM) has not been defined. We hypothesize that understanding tumor evolution and micro environmental responses to radiotherapy is critical for developing and targeting interventions. In this study, we investigate the effect of proton versus standard photon radiotherapy on tumor growth and the microenvironment in an orthotopic syngeneic GBM model over the course of treatment. We characterized tumor tissues at early, progressing, and terminal phases post irradiation by single cell transcriptomics, bulk RNA sequencing, and histology. We find that proton irradiation led to a drastic reduction in tumor volume at early stages before eventual recurrence. Proton treatment exhibits equivalent if not superior, tumor control when compared to normal photon radiation. Single cell transcriptomics analyses show a dramatic increase in immune cell populations including T cell and macrophage populations which peak shortly before tumor recurrence. In addition, we identify an increase in exhausted T cell markers such as PD1, Tim-3, and Lag-3 in T cells post irradiation. Treatment with therapeutic agents that reprogram microglia/macrophages to an anti-tumor phenotype and activate T cell effector functions effectively eradicate GBM recurrence post irradiation. Thus, our study demonstrates a powerful combined treatment strategy with radiation against GBM and provides valuable information about how tumor growth and microenvironment respond to proton therapies, as well as potential mechanisms of tumor response and recurrence in GBM.

/pdf/tmic-47-single-cell-transcriptomics-reveals-antitumor-immune-2fe2o32o.pdf

Tmic-47. single-cell transcriptomics reveals antitumor immune responses of proton treatment in glioblastoma

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Papers

mirDIP 4.1-integrative database of human microRNA target predictions

Chromatin structure predicts survival in glioma patients

Chromatin structure predicts survival in glioma patients

Stem-24. single-cell atlas of human fetal cerebellum decoding medulloblastoma origin and oncogenesis

Tmic-47. single-cell transcriptomics reveals antitumor immune responses of proton treatment in glioblastoma