Prioritizing human cancer microRNAs based on genes’ functional consistency between microRNA and cancer

The identification of human cancer-related microRNAs (miRNAs) is important for cancer biology research. Although several identification methods have achieved remarkable success, they have overlooked the functional information associated with miRNAs. We present a computational framework that can be used to prioritize human cancer miRNAs by measuring the association between cancer and miRNAs based on the functional consistency score (FCS) of the miRNA target genes and the cancer-related genes. This approach proved successful in identifying the validated cancer miRNAs for 11 common human cancers with area under ROC curve (AUC) ranging from 71.15% to 96.36%. The FCS method had a significant advantage over miRNA differential expression analysis when identifying cancer-related miRNAs with a fine regulatory mechanism, such as miR-27a in colorectal cancer. Furthermore, a case study examining thyroid cancer showed that the FCS method can uncover novel cancer-related miRNAs such as miR-27a/b, which were showed significantly upregulated in thyroid cancer samples by qRT-PCR analysis. Our method can be used on a web-based server, CMP (cancer miRNA prioritization) and is freely accessible at http://bioinfo.hrbmu.edu.cn/CMP. This time- and cost-effective computational framework can be a valuable complement to experimental studies and can assist with future studies of miRNA involvement in the pathogenesis of cancers

Inferring SARS-CoV-2 functional genomics from viral transcriptome with identification of potential antiviral drugs and therapeutic targets

AbstractCoronavirus disease 2019 (COVID-19) is an emerging infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and has posed a serious threat to global health. Here, we systematically characterized the transcription levels of the SARS-CoV-2 genes and identified the responsive human genes associated with virus infection. We inferred the possible biological functions of each viral gene and depicted the functional landscape based on guilt-by-association and functional enrichment analyses. Subsequently, the transcription factor regulatory network, protein–protein interaction network, and non-coding RNA regulatory network were constructed to discover more potential antiviral targets. In addition, several potential drugs for COVID-19 treatment and prevention were recognized, including known cell proliferation-related, immune-related, and antiviral drugs, in which proteasome inhibitors (bortezomib, carfilzomib, and ixazomib citrate) may play an important role in the treatment of COVID-19. These results provided novel insights into the understanding of SARS-CoV-2 functional genomics and host-targeting antiviral strategies for SARS-CoV-2 infection.</jats:p

A Ferroptosis-Related Gene Signature for Lung Function and Quality of Life in Patients with Idiopathic Pulmonary Fibrosis

Abstract Background: Rapid advances in genetic and genomic technologies have begun to reshape our understanding of idiopathic pulmonary fibrosis (IPF). Ferroptosis, an iron-dependent form of regulated cell death, play an important role in the development of IPF. Therefore, our study aimed to explore the role of ferroptosis-related genes (FRGs) and their correlation with lung dysfunction and quality of life in patients with IPF. Methods: Datasets were acquired by researching the Gene Expression Omnibus. FRGs were acquired by researching GeneCard database and PubMed. Ferroptosis-related differentially expressed genes (FRDEGs) were identified according to integrating FRGs and the DEGs identified in the GSE110147 dataset. Candidate key genes were identified from the miRNA-target FRDEGs network and protein-protein interactions (PPI) network. The relationship between key genes and lung function or quality of life was calculated using the GSE32537 datasets.Results: 293 FRGs were obtained, and 71 FRDEGs were identified. According to enrichment analysis, cell growth and death and pathways associated cancer were the important pathways, and significant biological processes were mainly consisted of cellular responses to stimulus and various situations. In addition, this study constructed an PPI network and a miRNA-target network based on the 71 FRDEGs, determined 19 candidate key genes. Furthermore, acyl-CoA synthetase long chain family member 1 (ACSL1), integrin subunit beta 8 (ITGB8) and ceruloplasmin (CP) were identified as the key genes. The expression level of ACSL1 was the strongest predictor for lung function (negatively) including percent predicted forced vital capacity (FVC% predicted) and percent predicted diffusion capacity of the lung for carbon monoxide (Dlco% predicted) and quality of life (negatively). In addition, ITGB8 and CP were negatively associated with FVC% predicted. According to DrugBank and PubMed, 4 drugs and 16 drugs have been found to act on ACSL1 and CP, respectively. Conclusion: These results imply that FRGs may shed new understanding on disease mechanism and provide potential biomarkers and therapy target to predict IPF progression.</jats:p

Self-organizing gelatin–polycaprplactone materials with good fluid transmission can promote full-thickness skin regeneration

Gt–PCL composite materials, synthesized with polycaprplactone, gelatin and collagen, showed an improved epidermal healing rate and were able to respond and repair in advance.</jats:p

Ethylene-orchestrated circuitry coordinates a seedling’s response to soil cover and etiolated growth

Significance Seedlings’ ability to both adapt to their soil environment and acquire photoautotrophic capacity under various buried conditions is a life-or-death issue for terrestrial flowering plants. By designing and utilizing a standardized real-soil assay, we identify the key features of germinating seedlings’ soil response and deduce that the gaseous phytohormone ethylene acts as the primary regulator of soil-induced plant morphogenetic changes. Moreover, our study illustrates that an EIN3/EIL1-conducted PIF3–ERF1 molecular circuitry enables seedlings to synchronize the rate of protochlorophyllide biosynthesis with upward growth, a mechanism critical to the prevention of photooxidative damage during seedlings’ initial transition from dark to light in natural conditions.</jats:p

Additional file 2 of Inferring SARS-CoV-2 functional genomics from viral transcriptome with identification of potential antiviral drugs and therapeutic targets

Additional file 2: Table S1. The differentially expressed human genes and SR genes in SARS-CoV-2-infected human cells. Table S2. TFs that significantly associated with viral genes. Table S3. The co-expression relationships between ncRNAs and SR genes in COVID-19. Table S4. Potential host-targeted antiviral drugs associated with SR genes

Construction of asthma related competing endogenous RNA network revealed novel long non-coding RNAs and potential new drugs

Abstract Background Asthma is a heterogeneous disease characterized by chronic airway inflammation. Long non-coding RNA can act as competing endogenous RNA to mRNA, and play significant role in many diseases. However, there is little known about the profiles of long non-coding RNA and the long non-coding RNA related competing endogenous RNA network in asthma. In current study, we aimed to explore the long non-coding RNA-microRNA-mRNA competing endogenous RNA network in asthma and their potential implications for therapy and prognosis. Methods Asthma-related gene expression profiles were downloaded from the Gene Expression Omnibus database, re-annotated with these genes and identified for asthma-associated differentially expressed mRNAs and long non-coding RNAs. The long non-coding RNA-miRNA interaction data and mRNA-miRNA interaction data were downloaded using the starBase database to construct a long non-coding RNA-miRNA-mRNA global competing endogenous RNA network and extract asthma-related differentially expressed competing endogenous RNA network. Finally, functional enrichment analysis and drug repositioning of asthma-associated differentially expressed competing endogenous RNA networks were performed to further identify key long non-coding RNAs and potential therapeutics associated with asthma. Results This study constructed an asthma-associated competing endogenous RNA network, determined 5 key long non-coding RNAs (MALAT1, MIR17HG, CASC2, MAGI2-AS3, DAPK1-IT1) and identified 8 potential new drugs (Tamoxifen, Ruxolitinib, Tretinoin, Quercetin, Dasatinib, Levocarnitine, Niflumic Acid, Glyburide). Conclusions The results suggested that long non-coding RNA played an important role in asthma, and these novel long non-coding RNAs could be potential therapeutic target and prognostic biomarkers. At the same time, potential new drugs for asthma treatment have been discovered through drug repositioning techniques, providing a new direction for the treatment of asthma. </jats:sec

A ferroptosis-related gene signature for lung function and quality of life in patients with idiopathic pulmonary fibrosis

Abstract Background: Rapid advances in genetic and genomic technologies have begun to reshape our understanding of idiopathic pulmonary fibrosis (IPF). Ferroptosis, an iron-dependent form of regulated cell death, play an important role in the development of IPF. Therefore, our study aimed to explore the role of ferroptosis-related genes (FRGs) and their correlation with lung dysfunction and quality of life in patients with IPF. Methods: Datasets were acquired by researching the Gene Expression Omnibus. FRGs were acquired by researching GeneCard database and PubMed. Ferroptosis-related differentially expressed genes (FRDEGs) were identified according to integrating FRGs and the DEGs identified in the GSE110147 dataset. Candidate key genes were identified from the miRNA-target FRDEGs network and protein-protein interactions (PPI) network. The relationship between key genes and lung function or quality of life was calculated using the GSE32537 datasets.Results: 293 FRGs were obtained, and 71 FRDEGs were identified. According to enrichment analysis, cell growth and death and pathways associated cancer were the important pathways, and significant biological processes were mainly consisted of cellular responses to stimulus and various situations. In addition, this study constructed an PPI network and a miRNA-target network based on the 71 FRDEGs, determined 19 candidate key genes. Furthermore, acyl-CoA synthetase long chain family member 1 (ACSL1), integrin subunit beta 8 (ITGB8) and ceruloplasmin (CP) were identified as the key genes. The expression level of ACSL1 was the strongest predictor for lung function (negatively) including percent predicted forced vital capacity (FVC% predicted) and percent predicted diffusion capacity of the lung for carbon monoxide (Dlco% predicted) and quality of life (negatively). In addition, ITGB8 and CP were negatively associated with FVC% predicted. According to DrugBank and PubMed, 4 drugs and 16 drugs have been found to act on ACSL1 and CP, respectively. Conclusion: These results imply that FRGs may shed new understanding on disease mechanism and provide potential biomarkers and therapy target to predict IPF progression.</jats:p

Additional file 1 of Inferring SARS-CoV-2 functional genomics from viral transcriptome with identification of potential antiviral drugs and therapeutic targets

Additional file 1: Supplementary Methods

CRS: a circadian rhythm score model for predicting prognosis and treatment response in cancer patients

Abstract Background Circadian rhythm regulates complex physiological activities in organisms. A strong link between circadian dysfunction and cancer has been identified. However, the factors of dysregulation and functional significance of circadian rhythm genes in cancer have received little attention. Methods In 18 cancer types from The Cancer Genome Atlas (TCGA), the differential expression and genetic variation of 48 circadian rhythm genes (CRGs) were examined. The circadian rhythm score (CRS) model was created using the ssGSEA method, and patients were divided into high and low groups based on the CRS. The Kaplan–Meier curve was created to assess the patient survival rate. Cibersort and estimate methods were used to identify the infiltration characteristics of immune cells between different CRS subgroups. Gene Expression Omnibus (GEO) dataset is used as verification queue and model stability evaluation queue. The CRS model's ability to predict chemotherapy and immunotherapy was assessed. Wilcoxon rank-sum test was used to compare the differences of CRS among different patients. We use CRS to identify potential "clock-drugs" by the connective map method. Results Transcriptomic and genomic analyses of 48 CRGs revealed that most core clock genes are up-regulated, while clock control genes are down-regulated. Furthermore, we show that copy number variation may affect CRGs aberrations. Based on CRS, patients can be classified into two groups with significant differences in survival and immune cell infiltration. Further studies showed that patients with low CRS were more sensitive to chemotherapy and immunotherapy. Additionally, we identified 10 compounds (e.g. flubendazole, MLN-4924, ingenol) that are positively associated with CRS, and have the potential to modulate circadian rhythms. Conclusions CRS can be utilized as a clinical indicator to predict patient prognosis and responsiveness to therapy, and identify potential "clock-drugs". </jats:sec