Tumor heterogeneity is jointly determined by the components of the tumor ecosystem (TES) including tumor cells, immune cells, stromal cells, and non-cellular components. We aimed to identify subtypes ...using TES-related genes and determine subtype specific drivers and treatments for hepatocellular carcinoma (HCC).
We collected 68 genesets depicting tumor biology, immune infiltration, and liver function, totaling 2831 genes, and collected mRNA profiles and clinical data for over 6000 tumors from 65 datasets in the GEO, TCGA, ICGC, and several other databases. We designed a three-step clustering pipeline to identify subtypes. The microenvironment, genomic alteration, and drug response differences were systematically compared among subtypes.
Seven subtypes (TES-1/2/3/4/5/6/7) were revealed in 159 tumors from the CHCC-HBV cohort. We constructed a single sample classifier using paired genes (sscpgsTES). TES subtypes were significantly associated with multiple clinical variables including etiology, and survival in 14 of 17 cohorts and the meta-cohort. TES-1 had the poorest prognosis and highest proliferation level. Both TES-2 and TES-7 were immune-enriched, however, TES-2 had a significantly worse prognosis, and hypoxic and immunosuppressive microenvironment. TES-4 had activated Wnt pathway, driven by CTNNB1 mutation. Good prognosis TES-6 exhibited the best differentiation. TES-5 and TES-3 were considered as novel subclasses by comparing with ten previous subtyping systems. TES-5 tumors had high AFP but good overall survival, and ∼45% of them harbored AXIN1 mutation. TES-3 was immune and stromal desert, may be driven by high copy number alteration burden, and had the poorest response to immune checkpoint inhibitor. TES-1 and TES-2 had significantly lower response to transarterial chemoembolization, but they showed significantly higher sensitivity to compound YM-155.
Tumor ecosystem subtypes expand existing HCC subtyping systems, have distinct drivers, prognosis, and treatment vulnerabilities.
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•Subtype TES-1 of HCC were enriched in HBV infection and had the worst prognosis.•TES-2 had a hypoxic and immunosuppressive microenvironment, and poor prognosis.•TES-3 were immune and stromal desert, and had the poorest response to ICI.•TES-5 had high AFP but good OS, and ∼45% of them harbored AXIN1 mutation.•The single sample classifier, sscpgsTES, can be easily translated into clinic.
Abstract
The MiRNA SNP Disease Database (MSDD, http://www.bio-bigdata.com/msdd/) is a manually curated database that provides comprehensive experimentally supported associations among microRNAs ...(miRNAs), single nucleotide polymorphisms (SNPs) and human diseases. SNPs in miRNA-related functional regions such as mature miRNAs, promoter regions, pri-miRNAs, pre-miRNAs and target gene 3′-UTRs, collectively called 'miRSNPs', represent a novel category of functional molecules. miRSNPs can lead to miRNA and its target gene dysregulation, and resulting in susceptibility to or onset of human diseases. A curated collection and summary of miRSNP-associated diseases is essential for a thorough understanding of the mechanisms and functions of miRSNPs. Here, we describe MSDD, which currently documents 525 associations among 182 human miRNAs, 197 SNPs, 153 genes and 164 human diseases through a review of more than 2000 published papers. Each association incorporates information on the miRNAs, SNPs, miRNA target genes and disease names, SNP locations and alleles, the miRNA dysfunctional pattern, experimental techniques, a brief functional description, the original reference and additional annotation. MSDD provides a user-friendly interface to conveniently browse, retrieve, download and submit novel data. MSDD will significantly improve our understanding of miRNA dysfunction in disease, and thus, MSDD has the potential to serve as a timely and valuable resource.
Despite growing consensus that long intergenic non-coding ribonucleic acids (lincRNAs) are modulators of cancer, the knowledge about the deoxyribonucleic acid (DNA) methylation patterns of lincRNAs ...in cancers remains limited. In this study, we constructed DNA methylation profiles for 4629 tumors and 705 normal tissue samples from 20 different types of human cancer by reannotating data of DNA methylation arrays. We found that lincRNAs had different promoter methylation patterns in cancers. We classified 2461 lincRNAs into two categories and three subcategories, according to their promoter methylation patterns in tumors. LincRNAs with resistant methylation patterns in tumors had conserved transcriptional regulation regions and were ubiquitously expressed across normal tissues. By integrating cancer subtype data and patient clinical information, we identified lincRNAs with promoter methylation patterns that were associated with cancer status, subtype or prognosis for several cancers. Network analysis of aberrantly methylated lincRNAs in cancers showed that lincRNAs with aberrant methylation patterns might be involved in cancer development and progression. The methylated and demethylated lincRNAs identified in this study provide novel insights for developing cancer biomarkers and potential therapeutic targets.
Temporal lobe epilepsy (TLE) is a complex disease with its pathogenetic mechanism still unclear. Single-nucleotide polymorphisms (SNPs) of miRNA (miRSNPs) are SNPs located on miRNA genes or target ...sites of miRNAs, which have been proved to be associated with neuropsychic disease development by interfering with miRNA-mediated regulatory function. In this study, we integrated TLE–related risk genes and risk pathways multi-dimensionally based on public data resources. Furthermore, we systematically screened candidate functional miRSNPs for TLE and constructed a TLE-associated pathway-based miRSNP switching network, which included 92 miRNAs that target 12 TLE risk pathways. Moreover, we dissected thoroughly the correlation between 5 risk genes of 4 risk pathways and TLE development. Additionally, the biological function of several candidate miRSNPs were validated by luciferase reporter assay. In silico approach facilitates to select potential “miRSNP-miRNA-risk gene-pathway” axis for experimental validation, which provided new insights into the mechanism of miRSNPs as potential genetic risk factors of TLE.
With the rapid advances of genetic and genomic technologies, the pathophysiological mechanisms of idiopathic pulmonary fibrosis (IPF) were gradually becoming clear, however, the prognosis of IPF was ...still poor. This study aimed to systematically explore the ferroptosis-related genes model associated with prognosis in IPF patients.
Datasets were collected from the Gene Expression Omnibus (GEO). The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to create a multi-gene predicted model from patients with IPF in the Freiburg cohort of the GSE70866 dataset. The Siena cohort and the Leuven cohort were used for validation.
Nineteen differentially expressed genes (DEGs) between the patients with IPF and control were associated with poor prognosis based on the univariate Cox regression analysis (all P < 0.05). According to the median value of the risk score derived from an 8-ferroptosis-related genes signature, the three cohorts' patients were stratified into two risk groups. Prognosis of high-risk group (high risk score) was significantly poorer compared with low-risk group in the three cohorts. According to multivariate Cox regression analyses, the risk score was an independently predictor for poor prognosis in the three cohorts. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) confirmed the signature's predictive value in the three cohorts. According to functional analysis, inflammation- and immune-related pathways and biological process could participate in the progression of IPF.
These results imply that the 8-ferroptosis-related genes signature in the bronchoalveolar lavage samples might be an effective model to predict the poor prognosis of IPF.
Human epidermal growth factor receptor 2 (HER2) overexpressed associated with poor prognosis in breast cancer and HER2 has been defined as a therapeutic target for breast cancer treatment. We aimed ...to explore the molecular biological information in ultrasound radiomic features (URFs) of HER2-positive breast cancer using radiogenomic analysis. Moreover, a radiomics model was developed to predict the status of HER2 in breast cancer.
This retrospective study included 489 patients who were diagnosed with breast cancer. URFs were extracted from a radiomics analysis set using PyRadiomics. The correlations between differential URFs and HER2-related genes were calculated using Pearson correlation analysis. Functional enrichment of the identified URFs-correlated HER2 positive-specific genes was performed. Lastly, the radiomics model was developed based on the URF-module mined from auxiliary differential URFs to assess the HER2 status of breast cancer.
Eight differential URFs (p < 0.05) were identified among the 86 URFs extracted by Pyradiomics. 25 genes that were found to be the most closely associated with URFs. Then, the relevant biological functions of each differential URF were obtained through functional enrichment analysis. Among them, Zone Entropy is related to immune cell activity, which regulate the generation of calcification in breast cancer. The radiomics model based on the Logistic classifier and URF-module showed good discriminative ability (AUC = 0.80, 95% CI).
We searched for the URFs of HER2-positive breast cancer, and explored the underlying genes and biological functions of these URFs. Furthermore, the radiomics model based on the Logistic classifier and URF-module relatively accurately predicted the HER2 status in breast cancer.
In this study, we describe miRSponge, a manually curated database, which aims at providing an experimentally supported resource for microRNA (miRNA) sponges. Recent evidence suggests that miRNAs are ...themselves regulated by competing endogenous RNAs (ceRNAs) or 'miRNA sponges' that contain miRNA binding sites. These competitive molecules can sequester miRNAs to prevent them interacting with their natural targets to play critical roles in various biological and pathological processes. It has become increasingly important to develop a high quality database to record and store ceRNA data to support future studies. To this end, we have established the experimentally supported miRSponge database that contains data on 599 miRNA-sponge interactions and 463 ceRNA relationships from 11 species following manual curating from nearly 1200 published articles. Database classes include endogenously generated molecules including coding genes, pseudogenes, long non-coding RNAs and circular RNAs, along with exogenously introduced molecules including viral RNAs and artificial engineered sponges. Approximately 70% of the interactions were identified experimentally in disease states. miRSponge provides a user-friendly interface for convenient browsing, retrieval and downloading of dataset. A submission page is also included to allow researchers to submit newly validated miRNA sponge data. Database URL: http://www.bio-bigdata.net/miRSponge.
Long non-coding RNAs (lncRNAs), functioning as competing endogenous RNAs (ceRNAs), have been reported to play important roles in the pathogenesis of autoimmune diseases. However, little is known ...about the regulatory roles of lncRNAs underlying the mechanism of myasthenia gravis (MG). The aim of the present study was to explore the roles of lncRNAs as ceRNAs associated with the progression of MG.
MG risk genes and miRNAs were obtained from public databases. Protein-protein interaction (PPI) network analysis and module analysis were performed. A lncRNA-mediated module-associated ceRNA (LMMAC) network, which integrated risk genes in modules, risk miRNAs and predicted lncRNAs, was constructed to systematically explore the regulatory roles of lncRNAs in MG. Through performing random walk with restart on the network, HCG18/miR-145-5p/CD28 ceRNA axis was found to play important roles in MG, potentially. The expression of HCG18 in MG patients was detected using RT-PCR. The effects of HCG18 knockdown on cell proliferation and apoptosis were determined by CCK-8 assay and flow cytometry. The interactions among HCG18, miR-145-5p and CD28 were explored by luciferase assay, RT-PCR and western blot assay.
Based on PPI network, we identified 9 modules. Functional enrichment analyses revealed these modules were enriched in immune-related signaling pathways. We then constructed LMMAC network, containing 25 genes, 50 miRNAs, and 64 lncRNAs. Through bioinformatics algorithm, we found lncRNA HCG18 as a ceRNA, might play important roles in MG. Further experiments indicated that HCG18 was overexpressed in MG patients and was a target of miR-145-5p. Functional assays illustrated that HCG18 suppressed Jurkat cell apoptosis and promoted cell proliferation. Mechanistically, knockdown of HCG18 inhibited the CD28 mRNA and protein expression levels in Jurkat cells, while miR-145-5p inhibitor blocked the reduction of CD28 expression induced by HCG18 suppression.
We have reported a novel HCG18/miR-145-5p/CD28 ceRNA axis in MG. Our findings will contribute to a deeper understanding of the molecular mechanism of and provide a novel potential therapeutic target for MG.
Abstract
Coronavirus 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.
Abstract
Background
Genomic studies of colorectal cancer have revealed the complex genomic heterogeneity of the tumor. The acquisition and selection of genomic alterations may be critical to ...understanding the initiation and progression of this disease.
Methods
In this study, we have systematically characterized the clonal architecture of 97 driver genes in 536 colorectal cancer patients from TCGA.
Results
A high proportion of clonal mutations in 93 driver genes were observed. 40 genes showed significant associations between their clonality and multiple clinicopathologic factors. Kaplan–Meier analysis suggested that the mutation clonality of
ANK1
,
CASP8
,
SMAD2,
and
ARID1A
had a significant impact on the CRC patients' outcomes. Multivariable analysis revealed that subclonal
ANK1
mutations, clonal
CASP8
mutations, and clonal
SMAD2
mutations independently predicted for shorter overall survival after adjusting for clinicopathological factors. The poor outcome of the subclonal
ANK1
mutation may be caused by upregulation of IL4I1, IDO1, IFNG and MAPK12 which showed potential roles in tumor immune evasion through accumulation of immunosuppressive cells such as regulatory T cells and myeloid derived suppressor cells.
Conclusion
These results suggested that the clonality of driver genes could act as prognostic markers and potential therapeutic targets in human colorectal cancer.
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