Dynamic m6 A profiles reveal the role of YTHDC2-TLR2 signaling axis in Talaromyces marneffei infection.

Talaromyces marneffei (TM) immune evasion is an important factor leading to the high mortality rate of Penicilliosis marneffei. N6 -methyladenosine (m6 A) plays important roles in host immune response to various pathogen infections, yet its role in TM and HIV/TM coinfection remains largely unexplored. Here we reported genome-wide transcriptional m6 A profiles of TM mono-infection and HIV/TM coinfection. Our finding revealed dynamic alterations in global m6 A levels and upregulation of the m6 A reader YTH N6 -methyladenosine RNA binding protein C2 (YTHDC2) in TM-infected macrophages. Knockdown of YTHDC2 in TM-infected cells showed an elevated expression of TLR2 through m6 A-dependence, along with upregulation of TNF-α and IL1-ß. Overall, we characterized the m6 A profiles of the host and fungus before and after TM infection, and demonstrated that YTHDC2 mediates the key m6 A site of TLR2 to exert its function. These findings provide new insights into the underlying mechanisms and novel therapeutic approaches for TM diseases.

Integrative epigenomic profiling reveal AP-1 is a key regulator in intrahepatich cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (ICC) is a malignant tumor with poor prognosis while its mechanisms of pathogenesis remain elusive. In this study, we performed systemic epigenomic and transcriptomic profiling via MNase-seq, ChIP-seq and RNA-seq in normal cholangiocyte and ICC cell lines. We showed that active histone modifications (H3K4me3, H3K4me1 and H3K27ac) were less enriched on cancer-related genes in ICC cell lines compared to control. The region of different histone modification patterns is enrichment in sites of AP-1 motif. Subsequent analysis showed that ICC had different nucleosome occupancy in differentially expressed genes compared to a normal cell line. Furthermore, we found that AP-1 plays a key role in ICC and regulates ICC-related genes through its AP-1 binding site. This study is the first report showing the global features of histone modification, transcript, and nucleosome profiles in ICC; we also show that the transcription factor AP-1 might be a key target gene in ICC.

Potential Inhibitors of Monkeypox Virus Revealed by Molecular Modeling Approach to Viral DNA Topoisomerase I.

The monkeypox outbreak has become a global public health emergency. The lack of valid and safe medicine is a crucial obstacle hindering the extermination of orthopoxvirus infections. The identification of potential inhibitors from natural products, including Traditional Chinese Medicine (TCM), by molecular modeling could expand the arsenal of antiviral chemotherapeutic agents. Monkeypox DNA topoisomerase I (TOP1) is a highly conserved viral DNA repair enzyme with a small size and low homology to human proteins. The protein model of viral DNA TOP1 was obtained by homology modeling. The reliability of the TOP1 model was validated by analyzing its Ramachandran plot and by determining the compatibility of the 3D model with its sequence using the Verify 3D and PROCHECK services. In order to identify potential inhibitors of TOP1, an integrated library of 4103 natural products was screened via Glide docking. Surface Plasmon Resonance (SPR) was further implemented to assay the complex binding affinity. Molecular dynamics simulations (100 ns) were combined with molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) computations to reveal the binding mechanisms of the complex. As a result, three natural compounds were highlighted as potential inhibitors via docking-based virtual screening. Rosmarinic acid, myricitrin, quercitrin, and ofloxacin can bind TOP1 with KD values of 2.16 µM, 3.54 µM, 4.77 µM, and 5.46 µM, respectively, indicating a good inhibitory effect against MPXV. The MM/PBSA calculations revealed that rosmarinic acid had the lowest binding free energy at -16.18 kcal/mol. Myricitrin had a binding free energy of -13.87 kcal/mol, quercitrin had a binding free energy of -9.40 kcal/mol, and ofloxacin had a binding free energy of -9.64 kcal/mol. The outputs (RMSD/RMSF/Rg/SASA) also indicated that the systems were well-behaved towards the complex. The selected compounds formed several key hydrogen bonds with TOP1 residues (TYR274, LYS167, GLY132, LYS133, etc.) via the binding mode analysis. TYR274 was predicted to be a pivotal residue for compound interactions in the binding pocket of TOP1. The results of the enrichment analyses illustrated the potential pharmacological networks of rosmarinic acid. The molecular modeling approach may be acceptable for the identification and design of novel poxvirus inhibitors; however, further studies are warranted to evaluate their therapeutic potential.

CASA: a comprehensive database resource for the COVID-19 Alternative Splicing Atlas.

BACKGROUND: As a key process in transcriptional regulatory mechanisms, alternative splicing (AS) plays a crucial role in maintaining the diversity of RNA and protein expression, and mediates the immune response in infectious diseases, especially for the COVID-19. Therefore, urgent data gathering and more research of AS profiles in microbe-infected human cells are needed to improve understanding of COVID-19 and related infectious diseases. Herein, we have created CASA, the COVID-19 Alternative Splicing Atlas to provide a convenient computing platform for studies of AS in COVID-19 and COVID-19-related infectious diseases. METHODS: In CASA, we reanalyzed thousands of RNA-seq datasets generated from 65 different tissues, organoids and cell lines to systematically obtain quantitative data on AS events under different conditions. A total of 262,994 AS events from various infectious diseases with differing severity were detected and visualized in this database. In order to explore the potential function of dynamics AS events, we performed analysis of functional annotations and drug-target interactions affected by AS in each dataset. RNA-binding proteins (RBPs), which may regulate these dynamic AS events are also provided for users in this database. RESULTS: CASA displays microbe-induced alterations of the host cell splicing landscape across different virus families and helps users identify condition-specific splicing patterns, as well as their potential regulators. CASA may greatly facilitate the exploration of AS profiles and novel mechanisms of host cell splicing by viral manipulation. CASA is freely available at http://www.splicedb.net/casa/ .

Integrative network analysis identifies cell-specific trans regulators of m6A.

N6-methyladenosine (m6A) is a reversible and dynamic RNA modification in eukaryotes. However, how cells establish cell-specific m6A methylomes is still poorly understood. Here, we developed a computational framework to systematically identify cell-specific trans regulators of m6A through integrating gene expressions, binding targets and binding motifs of large number of RNA binding proteins (RBPs) with a co-methylation network constructed using large-scale m6A methylomes across diverse cell states. We applied the framework and successfully identified 32 high-confidence m6A regulators that modulated the variable m6A sites away from stop codons in a cell-specific manner. To validate them, we knocked down three regulators respectively and found two of them (TRA2A and CAPRIN1) selectively promoted the methylations of the m6A sites co-localized with their binding targets on RNAs through physical interactions with the m6A writers. Knockdown of TRA2A increased the stabilities of the RNAs with TRA2A bound near the m6A sites and decreased the viability of cells. The successful identification of m6A regulators demonstrates a powerful and widely applicable strategy to elucidate the cell-specific m6A regulators. Additionally, our discovery of pervasive trans-acting regulating of m6A provides novel insights into the mechanisms by which spatial and temporal dynamics of m6A methylomes are established.

Comprehensive machine learning-based integration develops a novel prognostic model for glioblastoma.

In this study, we developed a new prognostic model for glioblastoma (GBM) based on an integrated machine learning algorithm. We used univariate Cox regression analysis to identify prognostic genes by combining six GBM cohorts. Based on the prognostic genes, 10 machine learning algorithms were integrated into 117 algorithm combinations, and the artificial intelligence prognostic signature (AIPS) with the greatest average C-index was chosen. The AIPS was compared with 10 previously published models by univariate Cox analysis and the C-index. We compared the differences in prognosis, tumor immune microenvironment (TIME), and immunotherapy sensitivity between the high and low AIPS score groups. The AIPS based on the random survival forest algorithm with the highest average C-index (0.868) was selected. Compared with the previous 10 prognostic models, our AIPS has the highest C-index. The AIPS was closely linked to the clinical features of GBM. We discovered that patients in the low score group had improved prognoses, a more active TIME, and were more sensitive to immunotherapy. Finally, we verified the expression of several key genes by western blotting and immunohistochemistry. We identified an ideal prognostic signature for GBM, which might provide new insights into stratified treatment approaches for GBM patients.

Pan-cancer Analysis Reveals m6A Variation and Cell-specific Regulatory Network in Different Cancer Types.

As the most abundant messenger RNA (mRNA) modification in mRNA, N  6-methyladenosine (m6A) plays a crucial role in RNA fate, impacting cellular and physiological processes in various tumor types. However, our understanding of the function and role of the m6A methylome in tumor heterogeneity remains limited. Herein, we collected and analyzed m6A methylomes across nine human tissues from 97 m6A sequencing (m6A-seq) and RNA sequencing samples. Our findings demonstrate that m6A exhibits different heterogeneity in most tumor tissues compared to normal tissues, which contributes to the diverse clinical outcomes in different cancer types. We also found that the cancer type-specific m6A level regulated the expression of different cancer-related genes in distinct cancer types. Utilizing a novel and reliable method called "m6A-express", we predicted m6A-regulated genes and revealed that cancer type-specific m6A-regulated genes contributed to the prognosis, tumor origin, and infiltration level of immune cells in diverse patient populations. Furthermore, we identified cell-specific m6A regulators that regulate cancer-specific m6A and constructed a regulatory network. Experimental validation was performed, confirming that the cell-specific m6A regulator CAPRIN1 controls the m6A level of TP53. Overall, our work reveals the clinical relevance of m6A in various tumor tissues and explains how such heterogeneity is established. These results further suggest the potential of m6A for cancer precision medicine for patients with different cancer types.

Willingness to accept monkeypox vaccine and its correlates among men who have sex with men in Southern China: a web-based online cross-sectional study.

Background: The May 2022 global outbreak of monkeypox (MPX) poses a threat to the health of men who have sex with men. However, there is limited data on the willingness of MSM to receive monkeypox vaccination in Southern China. This study aimed to assess the knowledge of MPX, concerns regarding MPX, and willingness to receive monkeypox vaccination, as well as their correlates, among MSM in China. Methods: We conducted a Web-based online survey of MSM in Southern China from August to September 2022. Data were collected on the socio-demographic characteristics, knowledge, worries, concerns regarding MPX and willingness to receive monkeypox vaccination. Multivariate logistic regression was employed to explore the factors associated with willingness to receive monkeypox vaccination. Results: A total of 1903 participants completed the survey. Among them, approximately 69.9% reported being aware of MPX awareness, 94.1% of the participants supported the promotion of monkeypox vaccination. The majority of participants (91.4%) expressed their willingness to receive monkeypox vaccination. Participants who considered monkeypox vaccination safe [adjusted odds ratio (aOR) = 4.82, 95% CI: 1.35-17.18], agreed on the necessity of government promotion of monkeypox vaccination in China (aOR = 6.03, 95% CI: 1.07-33.93), believed in prioritizing monkeypox vaccination for MSM (aOR = 5.01, 95% CI: 1.10-22.71), and had friends or sexual partners who had already received the monkeypox or smallpox vaccination (aOR = 10.37, 95% CI: 2.11-50.99) are more likely to be vaccinated. Conversely, married individuals (aOR = 0.13, 95% CI: 0.03-0.47), those engaging in anal sex 4-6 times per week in the past 3 months (aOR = 0.26, 95% CI: 0.09-0.77) expressed hesitancy toward monkeypox vaccination. Conclusion: There was a high willingness to receive monkeypox vaccination among MSM in China. The hesitancy toward the monkeypox vaccine can be effectively mitigated by addressing concerns about its safety and potential adverse reactions. Moreover, increasing acceptance of the monkeypox vaccination among MSM and their peers is crucial, as social influence significantly impacts vaccine attitudes and behaviors.

GutUDB: A comprehensive multiomics database for intestinal diseases.

Gut Universe Database (GutUDB) provides a comprehensive, systematic, and practical platform for researchers, and is dedicated to the management, analysis, and visualization of knowledge related to intestinal diseases. Based on this database, eight major categories of omics data analyses are carried out to explore the genotype-phenotype characteristics of a certain intestinal disease. The first tool for comprehensive omics data research on intestinal diseases will help each researcher better understand intestinal diseases.

Integrative analysis of multi-omics data reveals inhibition of RB1 signaling promotes apatinib resistance of hepatocellular carcinoma.

Although apatinib is a promising drug for the treatment of liver cancer, the underlying drug resistance mechanism is still unclear. Here, we constructed apatinib-resistant HepG2 cells. We then characterized the epigenomic, transcriptomic, and proteomic landscapes both in apatinib-resistant and non-resistant HepG2 cells. Differential expression, ATAC-seq, and proteomic data analyses were performed. We found that the cell cycle related protein RB1 may play an essential role in the process of apatinib resistant to hepatocarcinoma. Moreover, there were extensive variations at the transcriptome, epigenetic, and proteomic level. Finally, quantitative PCR (qPCR) and western blot analysis showed that expression level of RB1 in apatinib-resistant cell as well as the samples of patients in progressive disease were significantly lower than that in controls. Those results also showed that the RB1 pathway inhibitors CDK2-IN-73 and Palbociclib could relieve the resistance of apatinib resistant cells. Our results further enhance our understanding of the anti-tumorigenic and anti-angiogenic efficacy of apatinib in liver cancer and provide a novel perspective regarding apatinib resistance. Furthermore, we proved that CDKN2B inhibition of RB1 signaling promoted apatinib resistance in hepatocellular carcinoma. Those findings have greatly important biological significance for the resistance of apatinib and the treatment of liver cancer.

Weighted gene co-expression network analysis revealed T cell differentiation associated with the age-related phenotypes in COVID-19 patients.

The risk of severe condition caused by Corona Virus Disease 2019 (COVID-19) increases with age. However, the underlying mechanisms have not been clearly understood. The dataset GSE157103 was used to perform weighted gene co-expression network analysis on 100 COVID-19 patients in our analysis. Through weighted gene co-expression network analysis, we identified a key module which was significantly related with age. This age-related module could predict Intensive Care Unit status and mechanical-ventilation usage, and enriched with positive regulation of T cell receptor signaling pathway biological progress. Moreover, 10 hub genes were identified as crucial gene of the age-related module. Protein-protein interaction network and transcription factors-gene interactions were established. Lastly, independent data sets and RT-qPCR were used to validate the key module and hub genes. Our conclusion revealed that key genes were associated with the age-related phenotypes in COVID-19 patients, and it would be beneficial for clinical doctors to develop reasonable therapeutic strategies in elderly COVID-19 patients.

Talaromyces marneffei suppresses macrophage inflammation by regulating host alternative splicing.

Talaromyces marneffei (T. marneffei) immune escape is essential in the pathogenesis of talaromycosis. It is currently known that T. marneffei achieves immune escape through various strategies. However, the role of cellular alternative splicing (AS) in immune escape remains unclear. Here, we depict the AS landscape in macrophages upon T. marneffei infection via high-throughput RNA sequencing and detect a truncated protein of NCOR2 / SMRT, named NCOR2-013, which is significantly upregulated after T. marneffei infection. Mechanistic analysis indicates that NCOR2-013 forms a co-repression complex with TBL1XR1 / TBLR1 and HDAC3, thereby inhibiting JunB-mediated transcriptional activation of pro-inflammatory cytokines via the inhibition of histone acetylation. Furthermore, we identify TUT1 as the AS regulator that regulates NCOR2-013 production and promotes T. marneffei immune evasion. Collectively, these findings indicate that T. marneffei escapes macrophage killing through TUT1-mediated alternative splicing of NCOR2 / SMRT, providing insight into the molecular mechanisms of T. marneffei immune evasion and potential targets for talaromycosis therapy.

Identification and analysis of lncRNA, microRNA and mRNA expression profiles and construction of ceRNA network in Talaromyces marneffei-infected THP-1 macrophage.

BACKGROUND: Competitive endogenous RNA (ceRNA) reveals new mechanisms for interactions between RNAs, which have been considered to play a significant role in pathogen-host innate immune response. However, knowledge of ceRNA regulatory networks in Talaromyces marneffei (TM)-macrophages is still limited. METHODS: Next-generation sequencing technology (NGS) was used to obtain mRNA, miRNA and lncRNA expression profiles in TM-infected macrophages. The R package DESeq2 was used to identify differentially expressed lncRNA, miRNA and mRNA. The R package GOseq was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and the ceRNA network of lncRNA-miRNA-mRNA interaction was constructed in Cytoscape. Similarly, functional enrichment analysis on mRNA in the ceRNA network. Finally, two mRNAs and four lncRNAs in the ceRNA network were randomly selected to verify the expression using qRT-PCR. RESULTS: In total, 119 lncRNAs, 28 miRNAs and 208 mRNAs were identified as differentially expressed RNAs in TM-infected macrophages. The constructed ceRNA network contains 38 lncRNAs, 10 miRNAs and 45 mRNAs. GO and KEGG analysis of mRNA in the ceRNA network indicated that activated pathways in TM-infected macrophages were related to immunity, inflammation and metabolism. The quantitative validation of the expression of four randomly selected differentially expressed lncRNAs, AC006252.1, AC090197.1, IL6R-AS1, LINC02009 and two mRNAs, CSF1, NR4A3 showed that the expression levels were consistent with those in the RNA-sequencing. CONCLUSIONS: The ceRNA network related to immunity, inflammation and metabolism plays an important role in TM-macrophage interaction. This study may provide effective and novel insights for further understanding the underlying mechanism of TM infection.

Genome-Wide Profiling Reveals Alternative Polyadenylation of Innate Immune-Related mRNA in Patients With COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic has caused many deaths worldwide. To date, the mechanism of viral immune escape remains unclear, which is a great obstacle to developing effective clinical treatment. RNA processing mechanisms, including alternative polyadenylation (APA) and alternative splicing (AS), are crucial in the regulation of most human genes in many types of infectious diseases. Because the role of APA and AS in response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remains unknown, we performed de novo identification of dynamic APA sites using a public dataset of human peripheral blood mononuclear cell (PBMC) RNA-Seq data in COVID-19 patients. We found that genes with APA were enriched in innate immunity -related gene ontology categories such as neutrophil activation, regulation of the MAPK cascade and cytokine production, response to interferon-gamma and the innate immune response. We also reported genome-wide AS events and enriched viral transcription-related categories upon SARS-CoV-2 infection. Interestingly, we found that APA events may give better predictions than AS in COVID-19 patients, suggesting that APA could act as a potential therapeutic target and novel biomarker in those patients. Our study is the first to annotate genes with APA and AS in COVID-19 patients and highlights the roles of APA variation in SARS-CoV-2 infection.

Transcriptome integration analysis and specific diagnosis model construction for Hodgkin's lymphoma, diffuse large B-cell lymphoma, and mantle cell lymphoma.

Transcriptome differences between Hodgkin's lymphoma (HL), diffuse large B-cell lymphoma (DLBCL), and mantle cell lymphoma (MCL), which are all derived from B cell, remained unclear. This study aimed to construct lymphoma-specific diagnostic models by screening lymphoma marker genes. Transcriptome data of HL, DLBCL, and MCL were obtained from public databases. Lymphoma marker genes were screened by comparing cases and controls as well as the intergroup differences among lymphomas. A total of 9 HL marker genes, 7 DLBCL marker genes, and 4 MCL marker genes were screened in this study. Most HL marker genes were upregulated, whereas DLBCL and MCL marker genes were downregulated compared to controls. The optimal HL-specific diagnostic model contains one marker gene (MYH2) with an AUC of 0.901. The optimal DLBCL-specific diagnostic model contains 7 marker genes (LIPF, CCDC144B, PRO2964, PHF1, SFTPA2, NTS, and HP) with an AUC of 0.951. The optimal MCL-specific diagnostic model contains 3 marker genes (IGLV3-19, IGKV4-1, and PRB3) with an AUC of 0.843. The present study reveals the transcriptome data-based differences between HL, DLBCL, and MCL, when combined with other clinical markers, may help the clinical diagnosis and prognosis.

Low microRNA150 expression is associated with activated carcinogenic pathways and a poor prognosis in patients with breast cancer.

Breast cancer is the most common type of cancer amongst women worldwide, and numerous microRNAs (miRNAs/miRs) are involved in the initiation and progression of breast cancer. The aim of the present study was to identify hub miRNAs and determine the underlying mechanisms regulated by these miRNAs in breast cancer. Breast invasive carcinoma transcriptome data (including mRNAs and miRNAs), and clinical data were acquired from The Cancer Genome Atlas database. Differential gene expression analysis, co­expression network analysis, gene set enrichment analysis (GSEA) and prognosis analysis were used to screen the hub miRNAs and explore their functions. Functional experiments were used to determine the underlying mechanisms of the hub miRNAs in breast cancer cells. The results revealed that low miR150 expression predicted a more advanced disease stage, and was associated with a less favorable prognosis. Through the combined use of five miRNA­target gene prediction tools, 31 potential miR150 target genes were identified. GSEA revealed that low miR150 expression was associated with the upregulation of several cancer­associated signaling pathways, and the downregulation of several tumor suppressor genes. Furthermore, miR150 independently affected overall survival in patients, and interacted with its target genes to indirectly affect overall and disease­free survival. Functional experiments demonstrated that miR150 positively regulated B and T lymphocyte attenuator (BTLA), and the downregulation of miR150 and BTLA combined promoted cell migration. In conclusion, the present study revealed that low miR150 expression was associated with less favorable clinical features, upregulation of several carcinogenic signaling pathways, and poor patient survival. Additionally, a miR150­BTLA axis was suggested to regulate cell viability and migration.

Specific Regulation of m6A by SRSF7 Promotes the Progression of Glioblastoma.

Serine/arginine-rich splicing factor 7 (SRSF7), a known splicing factor, has been revealed to play oncogenic roles in multiple cancers. However, the mechanisms underlying its oncogenic roles have not been well addressed. Here, based on N6-methyladenosine (m6A) co-methylation network analysis across diverse cell lines, we find that the gene expression of SRSF7 is positively correlated with glioblastoma (GBM) cell-specific m6A methylation. We then indicate that SRSF7 is a novel m6A regulator, which specifically facilitates the m6A methylation near its binding sites on the mRNAs involved in cell proliferation and migration, through recruiting the methyltransferase complex. Moreover, SRSF7 promotes the proliferation and migration of GBM cells largely dependent on the presence of the m6A methyltransferase. The two m6A sites on PDZ-binding kinase (PBK) are regulated by SRSF7 and partially mediate the effects of SRSF7 in GBM cells through recognition by insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2). Together, our discovery reveals a novel role of SRSF7 in regulating m6A and validates the presence and functional importance of temporal- and spatial-specific regulation of m6A mediated by RNA-binding proteins (RBPs).

A novel pancreatic cancer model originated from transformation of acinar cells in adult tree shrew, a primate-like animal.

Pancreatic cancer is one of the most lethal common cancers. The cell of origin of pancreatic ductal adenocarcinoma (PDAC) has been controversial, and recent evidence suggested acinar cells as the most probable candidate. However, the genetic alterations driving the transformation of pancreatic acinar cells in fully mature animals remain to be deciphered. In this study, lentivirus was used as a tool to introduce genetic engineering in tree shrew pancreatic acinar cells to explore the driver mutation essential for malignant transformation, establishing a novel tree shrew PDAC model, because we found that lentivirus could selectively infect acinar cells in tree shrew pancreas. Combination of oncogenic KRASG12D expression and inactivation of tumor suppressor genes Tp53, Cdkn2a and Cdkn2b could induce pancreatic cancer with full penetrance. Silencing of Cdkn2b is indispensable for Rb1 phosphorylation and tumor induction. Tree shrew PDAC possesses the main histological and molecular features of human PDAC. The gene expression profile of tree shrew PDAC was more similar to human disease than a mouse model. In conclusion, we established a novel pancreatic cancer model in tree shrew and identified driver mutations indispensable for PDAC induction from acinar cells in mature adults, demonstrating the essential roles of Cdkn2b in the induction of PDAC originating from adult acinar cells. Tree shrew could thus provide a better choice than mouse for a PDAC model derived from acinar cells in fully mature animals.

Co-expression analysis and ceRNA network reveal eight novel potential lncRNA biomarkers in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common primary liver cancer in the world, with a high degree of malignancy and recurrence. The influence of the ceRNA network in tumor on the biological function of liver cancer is very important, It has been reported that many lncRNA play a key role in liver cancer development. In our study, integrated data analysis revealed potential eight novel lncRNA biomarkers in hepatocellular carcinoma. METHODS: Transcriptome data and clinical data were downloaded from the The Cancer Genome Atlas (TCGA) data portal. Weighted gene co-expression network analysis was performed to identify the expression pattern of genes in liver cancer. Then, the ceRNA network was constructed using transcriptome data. RESULTS: The integrated analysis of miRNA and RNAseq in the database show eight novel lncRNAs that may be involved in important biological pathways, including TNM and disease development in liver cancer. We performed function enrichment analysis of mRNAs affected by these lncRNAs. CONCLUSIONS: By identifying the ceRNA network and the lncRNAs that affect liver cancer, we showed that eight novel lncRNAs play an important role in the development and progress of liver cancer.

A new method of identifying glioblastoma subtypes and creation of corresponding animal models.

Glioblastoma (GBM) accounts for up to 50% of brain parenchymal tumors. It is the most malignant type of brain cancer with very poor survival and limited remedies. Cancer subtyping is important for cancer research and therapy. Here, we report a new subtyping method for GBM based on the genetic alterations of CDKN2A and TP53 genes. CDKN2A and TP53 are the most frequently mutated genes with mutation rates of 60 and 30%, respectively. We found that patients with deletion of CDKN2A possess worse survival than those with TP53 mutation. Interestingly, survival of patients with both TP53 mutation and CDKN2A deletion is no worse than for those with only one of these genetic alterations, but similar to those with TP53 mutation alone. Next, we investigated differences in the gene expression profile between TP53 and CDKN2A samples. Consistent with the survival data, the samples with both TP53 mutation and CDKN2A deletion showed a gene expression profile similar to those samples with TP53 mutation alone. Finally, we found that activation of RAS pathway plus Cdkn2a/b silencing can induce GBM, in a similar way to tumor induction by RAS activation plus TP53 silencing. In conclusion, we show that the genetic alterations of CDKN2A and TP53 may be used to stratify GBM, and the new animal models matching this stratification method were generated.