Myasthenia gravis (MG) is a complex neurological autoimmune disease with a pathogenetic mechanism that has yet to be elucidated. Emerging evidence has revealed that genes, non-coding RNAs and genetic ...variants play significant roles in the pathogenesis of MG. However, the molecular mechanisms of single nucleotide polymorphisms (SNPs) located on lncRNAs could disturb lncRNA-mediated ceRNA regulatory functions still unclear in MG. In this study, we collated 276 experimentally confirmed MG risk genes and 192 MG risk miRNAs. We then constructed a lncRNA-mediated ceRNA network for MG based on multi-step computational strategies. Next, we systematically integrated risk pathways and identified candidate SNPs in lncRNAs for MG based on data acquired from public databases. In addition, we constructed a pathway-based lncRNA-SNP mediated network (LSPN) that contained 128 lncRNAs targeting 8 MG risk pathways. By analyzing network, we propose a latent mechanism for how the "lncRNA-SNP-mRNA-pathway" axis affects the pathogenesis of MG. Moreover, 25 lncRNAs and 51 SNPs on lncRNAs were extracted from the "lncRNA-SNP-mRNA-pathway" axis. Finally, functional analyses demonstrated lncRNA-SNPs mediated ceRNA regulation pairs associated with MG participated in the MAPK signaling pathway. In summary, we constructed MG-specific lncRNA-SNPs mediated ceRNA regulatory networks based on pathway in the present study, which was helpful to elucidate the roles of lncRNA-SNPs in the pathogenesis of MG and provide novel insights into mechanism of lncRNA-SNPs as potential genetic risk biomarkers of MG.
Temporal lobe epilepsy (TLE) is the most common form of adult epilepsy and frequently evolving drug resistance. Although there is growing consensus that noncoding ribonucleic acids (ncRNAs) are ...modulators of TLE, the knowledge about the deoxyribonucleic acid (DNA) methylation patterns of ncRNAs in TLE remains limited. In the current study, we constructed DNA methylation profiles from 30 TLE patients and 30 healthy controls for ncRNAs, primarily focusing on long ncRNAs (lncRNAs) and microRNAs (miRNAs), by reannotating data of DNA methylation BeadChip. Statistics analyses have revealed a global hypermethylation pattern in miRNA and lncRNA gene in TLE patients. Bioinformatic analyses have found aberrantly methylated miRNAs and lncRNAs are related to ion channel activity, drug metabolism, mitogen-activated protein kinase (MAPK) signaling pathway, and neurotrophin signaling pathway. Aberrantly methylated ncRNA and pathway target might be involved in TLE development and progression. The methylated and demethylated ncRNAs identified in this study provide novel insights for developing TLE biomarkers and potential therapeutic targets.
Accurate classification of gliomas is critical to the selection of immunotherapy, and MRI contains a large number of radiomic features that may suggest some prognostic relevant signals. We aim to ...predict new subtypes of gliomas using radiomic features and characterize their survival, immune, genomic profiles and drug response.
We initially obtained 341 images of 36 patients from the CPTAC dataset for the development of deep learning models. Further 1812 images of 111 patients from TCGA_GBM and 152 images of 53 patients from TCGA_LGG were collected for testing and validation. A deep learning method based on Mask R–CNN was developed to identify new subtypes of glioma patients and compared the survival status, immune infiltration patterns, genomic signatures, specific drugs, and predictive models of different subtypes.
200 glioma patients (mean age, 33 years ± 19 standard deviation) were enrolled. The accuracy of the deep learning model for identifying tumor regions achieved 88.3 % (98/111) in the test set and 83 % (44/53) in the validation set. The sample was divided into two subtypes based on radiomic features showed different prognostic outcomes (hazard ratio, 2.70). According to the results of the immune infiltration analysis, the subtype with a poorer prognosis was defined as the immunosilencing radiomic (ISR) subtype (n = 43), and the other subtype was the immunoactivated radiomic (IAR) subtype (n = 53). Subtype-specific genomic signatures distinguished celllines into ISR celllines (n = 9) and control celllines (n = 13), and identified eight ISR-specific drugs, four of which were validated by the OCTAD database. Three machine learning-based classifiers showed that radiomic and genomic co-features better predicted the radiomic subtypes of gliomas.
These findings provide insights into how radiogenomic could identify specific subtypes that predict prognosis, immune and drug sensitivity in a non-invasive manner.
•Deep learning extracts radiomic features are complementary to clinical features.•Genomic signatures in radiomic subtypes are associated with immunity.•Radiogenomics machine learning models can predict radiomic subtypes.
Idiopathic pulmonary fibrosis (IPF) is one of interstitial lung diseases (ILDs) with poor prognosis. S100 calcium binding protein A12 (S100A12) has been reported as a prognostic serum biomarker in ...the IPF, but its correlation with IPF remains unclear in the lung tissue and bronchoalveolar lavage fluids (BALF).
Datasets were collected from the Gene Expression Omnibus (GEO) database. Person correlation coefficient, Kaplan-Meier analysis, Cox regression analysis, functional enrichment analysis and so on were used. And single cell RNA-sequencing (scRNA-seq) analysis was also used to explore the role of S100A12 and related genes in the IPF.
S100A12 was mainly and highly expressed in the monocytes, and its expression was downregulated in the lung of patients with IPF according to scRNA-seq and the transcriptome analysis. However, S100A12 expression was upregulated both in blood and BALF of patients with IPF. In addition, 10 genes were found to interact with S100A12 according to protein-protein interaction (PPI) network, and the first four transcription factors (TF) targeted these genes were found according to hTFtarget database. Two most significant co-expression genes of S100A12 were S100A8 and S100A9. The 3 genes were significantly negatively associated with lung function and positively associated with the St. George's Respiratory Questionnaire (SGRQ) scores in the lung of patients with IPF. And, high expression of the 3 genes was associated with higher mortality in the BALF, and shorter transplant-free survival (TFS) and progression-free survival (PFS) time in the blood. Prognostic predictive value of S100A12 was more superior to S100A8 and S100A9 in patients with IPF, and the composited variable S100A12 + GAP index (gender, age, and physiological index) may be a more effective predictive index.
These results imply that S100A12 might be an efficient disease severity and prognostic biomarker in patients with IPF.
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.
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.
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.
CRS can be utilized as a clinical indicator to predict patient prognosis and responsiveness to therapy, and identify potential "clock-drugs".
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.
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.
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).
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.
Gliomas are malignant tumours of the human nervous system with different World Health Organization (WHO) classifications, glioblastoma (GBM) with higher grade and are more malignant than lower-grade ...glioma (LGG). To dissect how the DNA methylation heterogeneity in gliomas is influenced by the complex cellular composition of the tumour immune microenvironment, we first compared the DNA methylation profiles of purified human immune cells and bulk glioma tissue, stratifying three tumour immune microenvironmental subtypes for GBM and LGG samples from The Cancer Genome Atlas (TCGA). We found that more intermediate methylation sites were enriched in glioma tumour tissues, and used the Proportion of sites with Intermediate Methylation (PIM) to compare intertumoral DNA methylation heterogeneity. A larger PIM score reflected stronger DNA methylation heterogeneity. Enhanced DNA methylation heterogeneity was associated with stronger immune cell infiltration, better survival rates, and slower tumour progression in glioma patients. We then created a Cell-type-associated DNA Methylation Heterogeneity Contribution (CMHC) score to explore the impact of different immune cell types on heterogeneous CpG site (
) in glioma tissues. We identified eight prognosis-related
to construct a risk score: the Cell-type-associated DNA Methylation Heterogeneity Risk (CMHR) score. CMHR was positively correlated with cytotoxic T-lymphocyte infiltration (CTL), and showed better predictive performance for IDH status (AUC = 0.96) and glioma histological phenotype (AUC = 0.81). Furthermore, DNA methylation alterations of eight
might be related to drug treatments of gliomas. In conclusion, we indicated that DNA methylation heterogeneity is associated with a complex tumour immune microenvironment, glioma phenotype, and patient's prognosis.
Idiopathic pulmonary fibrosis (IPF) has high mortality worldwide. The CD247 molecule (CD247, as known as T-cell surface glycoprotein CD3 zeta chain) has been reported as a susceptibility locus in ...systemic sclerosis, but its correlation with IPF remains unclear.
Datasets were acquired by researching the Gene Expression Omnibus (GEO). CD247 was identified as the hub gene associated with percent predicted diffusion capacity of the lung for carbon monoxide (Dlco% predicted) and prognosis according to Pearson correlation, logistic regression, and survival analysis.
CD247 is significantly downregulated in patients with IPF compared with controls in both blood and lung tissue samples. Moreover, CD247 is significantly positively associated with Dlco% predicted in blood and lung tissue samples. Patients with low-expression CD247 had shorter transplant-free survival (TFS) time and more composite end-point events (CEP, death, or decline in FVC >10% over a 6-month period) compared with patients with high-expression CD247 (blood). Moreover, in the follow-up 1st, 3rd, 6th, and 12th months, low expression of CD247 was still the risk factor of CEP in the GSE93606 dataset (blood). Thirteen genes were found to interact with CD247 according to the protein-protein interaction network, and the 14 genes including CD247 were associated with the functions of T cells and natural killer (NK) cells such as PD-L1 expression and PD-1 checkpoint pathway and NK cell-mediated cytotoxicity. Furthermore, we also found that a low expression of CD247 might be associated with a lower activity of TIL (tumor-infiltrating lymphocytes), checkpoint, and cytolytic activity and a higher activity of macrophages and neutrophils.
These results imply that CD247 may be a potential T cell-derived disease severity and prognostic biomarker for IPF.
Abstract
The nervous system is one of the most complex biological systems, and nervous system disease (NSD) is a major cause of disability and mortality. Extensive evidence indicates that numerous ...dysregulated microRNAs (miRNAs) are involved in a broad spectrum of NSDs. A comprehensive review of miRNA-mediated regulatory will facilitate our understanding of miRNA dysregulation mechanisms in NSDs. In this work, we summarized currently available databases on miRNAs and NSDs, star NSD miRNAs, NSD spectrum width, miRNA spectrum width and the distribution of miRNAs in NSD sub-categories by reviewing approximately 1000 studies. In addition, we characterized miRNA–miRNA and NSD–NSD interactions from a network perspective based on miRNA–NSD benchmarking data sets. Furthermore, we summarized the regulatory principles of miRNAs in NSDs, including miRNA synergistic regulation in NSDs, miRNA modules and NSD modules. We also discussed computational challenges for identifying novel miRNAs in NSDs. Elucidating the roles of miRNAs in NSDs from a network perspective would not only improve our understanding of the precise mechanism underlying these complex diseases, but also provide novel insight into the development, diagnosis and treatment of NSDs.
Abstract
Differences in genetic molecular features including mutation, copy number alterations and DNA methylation, can explain interindividual variability in response to anti-cancer drugs in cancer ...patients. However, identifying genetic alteration-driven genes and characterizing their functional mechanisms in different cancer types are still major challenges for cancer studies. Here, we systematically identified functional regulations between genetic alteration-driven genes and drug target genes and their potential prognostic roles in breast cancer. We identified two mutation and copy number-driven gene pairs (
PARP1-ACSL1
and
PARP1-SRD5A3
), three DNA methylation-driven gene pairs (
PRLR-CDKN1C
,
PRLR
-
PODXL2
and
PRLR
-
SRD5A3
), six gene pairs between mutation-driven genes and drug target genes (
SLC19A1
-
SLC47A2
,
SLC19A1
-
SRD5A3
,
AKR1C3
-
SLC19A1
,
ABCB1
-
SRD5A3
,
NR3C2
-
SRD5A3
and
AKR1C3
-
SRD5A3
), and four copy number-driven gene pairs (
ADIPOR2
-
SRD5A3
,
CASP12-SRD5A3
,
SLC39A11
-
SRD5A3
and
GALNT2
-
SRD5A3
) that all served as prognostic biomarkers of breast cancer. In particular,
RARP1
was found to be upregulated by simultaneous copy number amplification and gene mutation. Copy number deletion and downregulated expression of
ACSL1
and upregulation of
SRD5A3
both were observed in breast cancers. Moreover, copy number deletion of
ACSL1
was associated with increased resistance to PARP inhibitors.
PARP1
-
ACSL1
pair significantly correlated with poor overall survival in breast cancer owing to the suppression of the MAPK, mTOR and NF-kB signaling pathways, which induces apoptosis, autophagy and prevents inflammatory processes. Loss of
SRD5A3
expression was also associated with increased sensitivity to PARP inhibitors. The
PARP1
-
SRD5A3
pair significantly correlated with poor overall survival in breast cancer through regulating androgen receptors to induce cell proliferation. These results demonstrate that genetic alteration-driven gene pairs might serve as potential biomarkers for the prognosis of breast cancer and facilitate the identification of combination therapeutic targets for breast cancers.
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