Cuproptosis-related DNA methylation signature predict prognosis and immune microenvironment in cutaneous melanoma.

The prognosis for Cutaneous Melanoma (CM), a skin malignant tumor that is extremely aggressive, is not good. A recently identified type of controlled cell death that is intimately related to immunotherapy and the development of cancer is called cuproptosis. Using The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, we developed and validated a DNA-methylation located in cuproptosis death-related gene prognostic signature (CRG-located DNA-methylation prognostic signature) to predict CM's prognosis. Kaplan-Meier analysis of our TCGA and GEO cohorts showed that high-risk patients had a shorter overall survival. The area under the curve (AUC) for the TCGA cohort was 0.742, while for the GEO cohort it was 0.733, according to the receiver operating characteristic (ROC) analysis. Furthermore, this signature was discovered as an independent prognostic indicator over CM patients based on Cox-regression analysis. Immunogenomic profiling indicated that majority immune-checkpoints got an opposite relationship with the signature, and patients in the group at low risk got higher immunophenoscore. Several immune pathways were enriched, according to functional enrichment analysis. In conclusion, a prognostic methylation signature for CM patients was established and confirmed. Because of its close relationship to the immune landscape, this signature may help clinicians make more accurate and individualized choices regarding therapy.

Theoretical Study of the Decomposition Reactions of 2-Vinylfuran.

With the development of new synthetic methods, 2-vinylfuran (V2F) has become a potential renewable biofuel. In this work, the potential energy surfaces for the V2F unimolecular dissociation reaction, the H-addition reaction, and the H-abstraction reaction were constructed at the G4 level. The temperature- and pressure-dependent rate constants for the relevant reactions on the potential energy surfaces were calculated by solving the master equation based on the transition state theory and Rice-Ramsperger-Kassel-Marcus theory. The results show that the rate constant for the intramolecular H-transfer reaction of V2F with H atoms from the C(5) site to the C(4) site to form 2-vinylfuran-3(2H)-carbene, followed by the decomposition to form h145te3o, is the highest. The rate constants for the H-abstraction reaction of V2F with H atoms were the largest at C(6) on the branched chain, followed by C(7), and the rate constants for the H-abstraction reaction at C(3), C(4), and C(5) on the furan ring were not competitive. Negative temperature coefficient effects are observed for the rate constants of the addition reactions of V2F with H atoms at low pressures, with the H-addition rate constant at the C(5) site being the largest. This work not only provides the necessary rate constants for the reaction mechanism of V2F combustion but also provides theoretical guidance for the practical application of furan-based fuels.

Cuproptosis-related gene-located DNA methylation in lower-grade glioma: Prognosis and tumor microenvironment.

Cuproptosis a novel copper-dependent cell death modality, plays a crucial part in the oncogenesis, progression and prognosis of tumors. However, the relationships among DNA-methylation located in cuproptosis-related genes (CRGs), overall survival (OS) and the tumor microenvironment remain undefined. In this study, we systematically assessed the prognostic value of CRG-located DNA-methylation for lower-grade glioma (LGG). Clinical and molecular data were sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We employed Cox hazard regression to examine the associations between CRG-located DNA-methylation and OS, leading to the development of a prognostic signature. Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) analyses were utilized to gauge the accuracy of the signature. Gene Set Enrichment Analysis (GSEA) was applied to uncover potential biological functions of differentially expressed genes between high- and low-risk groups. A three CRG-located DNA-methylation prognostic signature was established based on TCGA database and validated in GEO dataset. The 1-year, 3-year, and 5-year area under the curve (AUC) of ROC curves in the TCGA dataset were 0.884, 0.888, and 0.859 while those in the GEO dataset were 0.943, 0.761 and 0.725, respectively. Cox-regression-analyses revealed the risk signature as an independent risk factor for LGG patients. Immunogenomic profiling suggested that the signature was associated with immune infiltration level and immune checkpoints. Functional enrichment analysis indicated differential enrichment in cell differentiation in the hindbrain, ECM receptor interactions, glycolysis and reactive oxygen species pathway across different groups. We developed and verified a novel CRG-located DNA-methylation signature to predict the prognosis in LGG patients. Our findings emphasize the potential clinical implications of CRG-located DNA-methylation indicating that it may serve as a promising therapeutic target for LGG patients.

Exploring the Role of DNA Methylation Located in Cuproptosis-Related Genes: Implications for Prognosis and Immune Landscape in Hepatocellular Carcinoma.

BACKGROUND: Copper dysregulation has been linked to liver disease, cardiac dysfunction, neuropathy, and anemia. Previous investigations have been undertaken to demonstrate the impact of cuproptosis-related genes (CRGs) on the poor prognosis of hepatocellular carcinoma (HCC), while the prognostic significance and beneath molecular basis of DNA-methylation sites located in CRGs remain unknown. This study aims to identify CRG-located DNA-methylation sites linked to patient prognosis and establish a novel prognostic biomarkers combination for CRG-located DNA-methylation signature. METHODS: The prognostic biomarkers combination was established through multivariate-Cox-regression after CRG-located DNA-methylation sites tied to the outcome of patients emerged by univariate-Cox-regression. The correlation between signature and immune cell infiltration levels, immune-checkpoint-associated genes was analyzed using spearman correlation and the difference was contrasted between different groups utilizing the Mann-Whitney-U test. Real-time quantitative methylation-specific polymerase chain reaction (RT-qMSP) was used to identify gene methylation. RESULTS: A novel prognostic biomarkers combination for CRG-located DNA-methylation signature was established. Subsequently, the independence of this methylation signature from clinical features and its correlation with immune infiltrative and immune checkpoints in HCC were also investigated. DNA methylation alterations can influence the onset, development, and treatment of various tumors by regulating the transcription of corresponding genes. Our analysis found that cg05706061 contained in prognosis signature was located in the promoter region of the cuproptosis-related gene SLC31A2. The DNA-methylation level of cg05706061 demonstrated significantly different between tumor and normal tissue, and significantly correlated with the expression of SLC31A2. We further investigated the promoter methylation status of SLC31A2 by qMSP, the result showed that the DNA-methylation level of SLC31A2 in HCC cell lines were significantly decreased compared with normal liver cells. CONCLUSIONS: Our findings reveal possible mechanisms of CRG-located DNA-methylation on the advancement of HCC and offers new perspectives for prognostic assessment and treatment options.

Theoretical and Modeling Study about the Low-Temperature Reaction Mechanism Between Oxymethylene Ether-2 (OME2) Radicals and O2.

Oxymethylene ether-2 (CH3-O-CH2-O-CH2-O-CH3, OME2), a carbon-neutral fuel, was hydrogenated from CO2 captured in air or exhaust gases and reused for synthesis with renewable electricity. In the current work, two different potential energy surfaces (PESs) for the reaction of OME2 radicals with O2 were constructed at the CCSD(T)/CBS//M062X/6-311++G(d,p) level. Based on the Rice-Ramsperger-Kassel-Marcus (RRKM) theory and transition state theory, the temperature- and pressure-dependent rate constants for the relevant reactions on the PES were calculated by solving the master equation. The Arrhenius equation has been used to fit the temperature- and pressure-dependent reaction rate constants. The main reaction channels on the PES are discussed, showing that initial adduct generation and intramolecular H-transfer reactions are the key reaction channels for low-temperature combustion. Among them, the HO2 concerted elimination reaction channel needs to overcome higher energy barriers leading to uncompetitive HO2 concerted elimination reactions. The calculated rate constants were updated to the OME2 combustion model, and the updated model is in considerable agreement with experimentally measured data on the ignition delay time in the shock tube. The present work provides support for further studies on the oxidation reaction of long-chain OME..

Theoretical Studies on the Reaction Kinetic of 2-Acetylfuran with Hydroxyl Radicals.

With the development of synthetic methods, 2-acetylfuran (AF2) has become a potential biomass fuel. The potential energy surfaces of AF2 and OH including OH-addition reactions and H-abstraction reactions were constructed by theoretical calculations at the CCSDT/CBS/M06-2x/cc-pVTZ level. The temperature- and pressure-dependent rate constants of the relevant reaction pathways were solved based on transition state theory and Rice-Ramsperger-Kassel-Marcus theory, as well as Eckart tunneling effect correction. The results showed that the H-abstraction reaction on CH3 on the branched chain and the OH-addition reaction at the C (2) and C (5) sites on the furan ring were the main reaction channels in the reaction system. At low temperatures, the AF2 and OH-addition reactions dominate, and the percentage decreases gradually to zero with increasing temperature, and at high temperatures, the H-abstraction reactions on the branched chains become the most dominant reaction channel. The rate coefficients calculated in the current work improve the combustion mechanism of AF2 and provide theoretical guidance for the practical application of AF2.

CircRNA Galntl6 sponges miR-335 to ameliorate stress-induced hypertension through upregulating Lig3 in rostral ventrolateral medulla.

Rostral ventrolateral medulla (RVLM) is thought to serve as a major vasomotor center that participates in controlling the progression of stress-induced hypertension (SIH). Circular RNAs (circRNAs) perform important functions in the regulation of diverse physiological and pathological processes. However, information concerning the functions of RVLM circRNAs on SIH remains limited. RNA sequencing was performed to profile circRNA expression in RVLMs from SIH rats, which were induced by electric foot shocks and noises. The functions of circRNA Galntl6 in reducing blood pressure (BP) and its potential molecular mechanisms on SIH were investigated via various experiments, such as Western blot and intra-RVLM microinjection. A total of 12,242 circRNA transcripts were identified, among which circRNA Galntl6 was dramatically downregulated in SIH rats. The upregulation of circRNA Galntl6 in RVLM effectively decreased the BP, sympathetic outflow, and neuronal excitability in SIH rats. Mechanistically, circRNA Galntl6 directly sponged microRNA-335 (miR-335) and restrained it to reduce oxidative stress. Reintroduction of miR-335 observably reversed the circRNA Galntl6-induced attenuation of oxidative stress. Furthermore, Lig3 can be a direct target of miR-335. MiR-335 inhibition substantially increased the expression of Lig3 and suppressed oxidative stress, and these favorable effects were blocked by Lig3 knockdown. CircRNA Galntl6 is a novel factor that impedes SIH development, and the circRNA Galntl6/miR-335/Lig3 axis represents one of the possible mechanisms. These findings demonstrated circRNA Galntl6 as a possibly useful target for the prevention of SIH.

A systems biology-based approach to screen key splicing factors in hepatocellular carcinoma.

A splicing factor is as an important upstream regulator of the alternative splicing process. Hence, it is considered to be a therapeutic target for hepatocellular carcinoma (HCC) tissues. In this study, a systems biology-based methodology was used to screen the essential splicing factors precisely and efficiently. A more comprehensive set of alternative splicing events, which were linked to patient survival, was constructed by performing the bivariate Cox regression and receiver operating characteristic (ROC) analyses. Then, the expression data was obtained from The Cancer Genome Altas (TCGA) data set and the three Gene Expression Omnibus (GEO) datasets. It was used to obtain the survival-related splicing factors, which showed a significantly differential expression in the tumor and normal tissues. Using the topological properties of the bipartite graph association network of the alternative splicing events and the splicing factors, we identified the five key splicing factors. Among them, four factors were found to play a prominent role in the development of HCC. The remaining factor was Survival Motor Neuron Domain Containing 1(SMNDC1), which showed a positive correlation with the immune cell infiltration, the biomarkers of immune cells, and the immune checkpoint genes. By performing quantitative real-time polymerase chain reaction analyses, we proved that SMNDC1 was overexpressed in tumor cells. Following the knockdown of its expression, the proliferation and the migration of HCC cells could be suppressed. These results confirmed that the screening method of this study was reliable and accurate. It provided new insights into the mechanism through which splicing factors elicit tumor development.

LncRNA INPP5F ameliorates stress-induced hypertension via the miR-335/Cttn axis in rostral ventrolateral medulla.

AIMS: The rostral ventrolateral medulla (RVLM) is an essential vasomotor center responsible for regulating the development of stress-induced hypertension (SIH). Long non-coding RNAs (lncRNAs) play critical roles in various physiopathology processes, but existing research on the functions of RVLM lncRNAs on SIH has been lacking. In this study, we investigated the roles of RVLM lncRNAs in SIH. METHODS: Genome-wide lncRNA profiles in RVLM were determined by RNA sequencing in a SIH rat model established using electric foot shocks plus noises. The hypotensive effect of lncRNA INPP5F and the underlying mechanisms of lncRNA INPP5F on SIH were explored through in vivo and in vitro experiments, such as intra-RVLM microinjection and immunofluorescence. RESULTS: We discovered 10,179 lncRNA transcripts, among which the lncRNA INPP5F expression level was significantly decreased in SIH rats. Overexpression of lncRNA INPP5F in RVLM dramatically reduced the blood pressure, sympathetic nerve activity, and neuronal excitability of SIH rats. LncRNA INPP5F overexpression markedly increased Cttn expression and reduced neural apoptosis by activating the PI3K-AKT pathway, and its inhibition had opposite effects. Mechanistically, lncRNA INPP5F acted as a sponge of miR-335, which further regulated the Cttn expression. CONCLUSION: LncRNA INPP5F was a key factor that inhibited SIH progression, and the identified lncRNA INPP5F/miR-335/Cttn/PI3K-AKT/apoptosis axis represented one of the possible mechanisms. LncRNA INPP5F could serve as a therapeutic target for SIH.

SLAM Back-End Optimization Algorithm Based on Vision Fusion IPS.

SLAM (Simultaneous Localization and Mapping) is mainly composed of five parts: sensor data reading, front-end visual odometry, back-end optimization, loopback detection, and map building. And when visual SLAM is estimated by visual odometry only, cumulative drift will inevitably occur. Loopback detection is used in classical visual SLAM, and if loopback is not detected during operation, it is not possible to correct the positional trajectory using loopback. Therefore, to address the cumulative drift problem of visual SLAM, this paper adds Indoor Positioning System (IPS) to the back-end optimization of visual SLAM, and uses the two-label orientation method to estimate the heading angle of the mobile robot as the pose information, and outputs the pose information with position and heading angle. It is also added to the optimization as an absolute constraint. Global constraints are provided for the optimization of the positional trajectory. We conducted experiments on the AUTOLABOR mobile robot, and the experimental results show that the localization accuracy of the SLAM back-end optimization algorithm with fused IPS can be maintained between 0.02 m and 0.03 m, which meets the requirements of indoor localization, and there is no cumulative drift problem when there is no loopback detection, which solves the problem of cumulative drift of the visual SLAM system to some extent.

Identification and Validation of Ferroptosis-Related DNA Methylation Signature for Predicting the Prognosis and Guiding the Treatment in Cutaneous Melanoma.

Cutaneous melanoma (CM) is one of the most aggressive skin tumors with a poor prognosis. Ferroptosis is a newly discovered form of regulated cell death that is closely associated with cancer development and immunotherapy. The aim of this study was to establish and validate a ferroptosis-related gene (FRG) DNA methylation signature to predict the prognosis of CM patients using data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. A reliable four-FRG DNA methylation prognostic signature was constructed via Cox regression analysis based on TCGA database. Kaplan-Meier analysis showed that patients in the high-risk group tended to have a shorter overall survival (OS) than the low-risk group in both training TCGA and validation GEO cohorts. Time-dependent receiver operating characteristic (ROC) analysis showed the areas under the curve (AUC) at 1, 3, and 5 years were 0.738, 0.730, and 0.770 in TCGA cohort and 0.773, 0.775, and 0.905 in the validation cohort, respectively. Univariate and multivariate Cox regression analyses indicated that the signature was an independent prognostic indicator of OS in patients with CM. Immunogenomic profiling showed the low-risk group of patients had a higher immunophenoscore, and most immune checkpoints were negatively associated with the risk signature. Functional enrichment analysis revealed that immune response and immune-related pathways were enriched in the low-risk group. In conclusion, we established and validated a four-FRG DNA methylation signature that independently predicts prognosis in CM patients. This signature was strongly correlated with the immune landscape, and may serve as a biomarker to guide clinicians in making more precise and personalized treatment decisions for CM patients.

Computer-Aided Design of DNA Self-Limited Assembly for Relative Quantification of Membrane Proteins.

Immunofluorescence imaging of cells plays a vital role in biomedical research and clinical diagnosis. However, when it is applied to relative quantification of proteins, it suffers from insufficient fluorescence intensity or partial overexposure, resulting in inaccurate relative quantification. Herein, we report a computer-aided design of DNA self-limited assembly (CAD-SLA) technology and apply it for relative quantification of membrane proteins, a concept proposed for the first time. CAD-SLA can achieve exponential cascade signal amplification in one pot and terminate at any desired level. By conjugating CAD-SLA with immunofluorescence, in situ imaging of cell membrane proteins is achieved with a controllable amplification level. Besides, comprehensive fluorescence intensity information from fluorescent images can be obtained, accurately showing relative quantitative information. Slight protein expression differences previously indistinguishable by immunofluorescence or Western blotting can now be discriminated, making fluorescence imaging-based relative quantification a promising tool for membrane protein analysis. From the perspectives of both DNA self-assembly technology and immunofluorescence technology, this work has solved difficult problems and provided important reference for future development.

Computer-aided design of reversible hybridization chain reaction (CAD-HCR) enables multiplexed single-cell spatial proteomics imaging.

In situ spatial proteomics analysis of a single cell has not been achieved yet, mainly because of insufficient throughput and sensitivity of current techniques. Recent progress on immuno-nucleic acid amplification technology presents tremendous opportunities to address this issue. Here, we report an innovative hybridization chain reaction (HCR) technique that involves computer-aided design (CAD) and reversible assembly. CAD enables highly multiplexed HCR with a sequence database that can work in parallel, while reversible assembly enables the switching of HCR between a working state and a resting state. Thus, CAD-HCR has been successfully adopted for single-cell spatial proteomics analysis. The fluorescence signal of CAD-HCR is comparable with conventional immunofluorescence, and it is positively correlated with the abundance of target proteins, which is beneficial for the visualization of proteins. The method developed here expands the toolbox of single-cell analysis and proteomics studies, as well as the performance and application of HCR.

Identifying Tumor-Associated Genes from Bilayer Networks of DNA Methylation Sites and RNAs.

Network theory has attracted much attention from the biological community because of its high efficacy in identifying tumor-associated genes. However, most researchers have focused on single networks of single omics, which have less predictive power. With the available multiomics data, multilayer networks can now be used in molecular research. In this study, we achieved this with the construction of a bilayer network of DNA methylation sites and RNAs. We applied the network model to five types of tumor data to identify key genes associated with tumors. Compared with the single network, the proposed bilayer network resulted in more tumor-associated DNA methylation sites and genes, which we verified with prognostic and KEGG enrichment analyses.

Screening and Identification of Survival-Associated Splicing Factors in Lung Squamous Cell Carcinoma.

Lung squamous cell carcinoma (LUSC) is a disease with high morbidity and mortality. Many studies have shown that aberrant alternative splicing (AS) can lead to tumorigenesis, and splicing factors (SFs) serve as an important function during AS. In this research, we propose an analysis method based on synergy to screen key factors that regulate the initiation and progression of LUSC. We first screened alternative splicing events (ASEs) associated with survival in LUSC patients by bivariate Cox regression analysis. Then an association network consisting of OS-ASEs, SFs, and their targeting relationship was constructed to identify key SFs. Finally, 10 key SFs were selected in terms of degree centrality. The validation on TCGA and cross-platform GEO datasets showed that some SFs were significantly differentially expressed in cancer and paracancer tissues, and some of them were associated with prognosis, indicating that our method is valid and accurate. It is expected that our method would be applied to a wide range of research fields and provide new insights in the future.

An Integrating Immune-Related Signature to Improve Prognosis of Hepatocellular Carcinoma.

Growing evidence suggests that the superiority of long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) could act as biomarkers for cancer prognosis. However, the prognostic marker for hepatocellular carcinoma with high accuracy and sensitivity is still lacking. In this research, a retrospective, cohort-based study of genome-wide RNA-seq data of patients with hepatocellular carcinoma was carried out, and two protein-coding genes (GTPBP4, TREM-1) and one lncRNA (LINC00426) were sorted out to construct an integrative signature to predict the prognosis of patients. The results show that both the AUC and the C-index of this model perform well in TCGA validation dataset, cross-platform GEO validation dataset, and different subsets divided by gender, stage, and grade. The expression pattern and functional analysis show that all three genes contained in the model are associated with immune infiltration, cell proliferation, invasion, and metastasis, providing further confirmation of this model. In summary, the proposed model can effectively distinguish the high- and low-risk groups of hepatocellular carcinoma patients and is expected to shed light on the treatment of hepatocellular carcinoma and greatly improve the patients' prognosis.

Prognostic Value of a Three-DNA Methylation Biomarker in Patients with Soft Tissue Sarcoma.

Soft tissue sarcomas (STS) are a highly aggressive and heterogeneous group of malignant mesenchymal tumors. The prognosis of patients with advanced or metastatic STS remains poor, and the main therapy of STS patients combines primary surgery, radiotherapy, and chemotherapy. Aberrant DNA methylation shows close association with the pathogenesis and tumor progression. Therefore, DNA methylation biomarkers might have the potential in accurately predicting the survival of STS patients. In order to identify a prognostic biomarker based on DNA methylation sites, a comprehensive analysis of the DNA methylation profile of STS patients in the Cancer Genome Atlas (TCGA) database was performed. All samples were randomly divided into training and testing datasets. Cox proportional hazards regression analysis was performed to identify a prognostic biomarker that contains three DNA methylation sites. The Kaplan-Meier analysis demonstrated that the 3-DNA methylation biomarker discriminated patients into high-risk and low-risk groups, both in the training and in the testing datasets, and the area under the receiver operating characteristic curve values (AUCs) were 0.844 (P < 0.001, 95% CI: 0.740-0.948) and 0.710 (P = 0.002, 95% CI: 0.595-0.823), respectively. Besides, this biomarker presented superior prognostic performance in STS patients with different age, sex, tissue of origin, therapy, and histologic subtypes. Compared with other prognostic biomarkers, this biomarker tended to be a more precise prognostic factor in STS patients. Moreover, methylation sites in this biomarker might provide a new way for clinicians to make decisions regarding the intervention and assess the effectiveness of an individual therapeutic strategy.

Identifying Discriminative Biological Function Features and Rules for Cancer-Related Long Non-coding RNAs.

Cancer has been a major public health problem worldwide for many centuries. Cancer is a complex disease associated with accumulative genetic mutations, epigenetic aberrations, chromosomal instability, and expression alteration. Increasing lines of evidence suggest that many non-coding transcripts, which are termed as non-coding RNAs, have important regulatory roles in cancer. In particular, long non-coding RNAs (lncRNAs) play crucial roles in tumorigenesis. Cancer-related lncRNAs serve as oncogenic factors or tumor suppressors. Although many lncRNAs are identified as potential regulators in tumorigenesis by using traditional experimental methods, they are time consuming and expensive considering the tremendous amount of lncRNAs needed. Thus, effective and fast approaches to recognize tumor-related lncRNAs should be developed. The proposed approach should help us understand not only the mechanisms of lncRNAs that participate in tumorigenesis but also their satisfactory performance in distinguishing cancer-related lncRNAs. In this study, we utilized a decision tree (DT), a type of rule learning algorithm, to investigate cancer-related lncRNAs with functional annotation contents [gene ontology (GO) terms and KEGG pathways] of their co-expressed genes. Cancer-related and other lncRNAs encoded by the key enrichment features of GO and KEGG filtered by feature selection methods were used to build an informative DT, which further induced several decision rules. The rules provided not only a new tool for identifying cancer-related lncRNAs but also connected the lncRNAs and cancers with the combinations of GO terms. Results provided new directions for understanding cancer-related lncRNAs.

Screening of Methylation Signature and Gene Functions Associated With the Subtypes of Isocitrate Dehydrogenase-Mutation Gliomas.

Isocitrate dehydrogenase (IDH) is an oncogene, and the expression of a mutated IDH promotes cell proliferation and inhibits cell differentiation. IDH exists in three different isoforms, whose mutation can cause many solid tumors, especially gliomas in adults. No effective method for classifying gliomas on genetic signatures is currently available. DNA methylation may be applied to distinguish cancer cells from normal tissues. In this study, we focused on three subtypes of IDH-mutation gliomas by examining methylation data. Several advanced computational methods were used, such as Monte Carlo feature selection (MCFS), incremental feature selection (IFS), support machine vector (SVM), etc. The MCFS method was adopted to analyze methylation features, resulting in a feature list. Then, the IFS method incorporating SVM was applied to the list to extract important methylation features and construct an optimal SVM classifier. As a result, several methylation features (sites) were found to relate to glioma subclasses, which are annotated onto multiple genes, such as FLJ37543, LCE3D, FAM89A, ADCY5, ESR1, C2orf67, REST, EPHA7, etc. These genes are enriched in biological functions, including cellular developmental process, neuron differentiation, cellular component morphogenesis, and G-protein-coupled receptor signaling pathway. Our results, which are supported by literature reports and independent dataset validation, showed that our identified genes and functions contributed to the detailed glioma subtypes. This study provided a basic research on IDH-mutation gliomas.

An eight-mRNA signature predicts the prognosis of patients with bladder urothelial carcinoma.

BACKGROUND: Bladder cancer is one of the most common cancers, and its histopathological type is mainly bladder urothelial carcinoma, accounting for about 90%. The prognostic biomarkers of bladder cancer are classified into clinical features biomarkers and molecular biomarkers. Nevertheless, due to the existence of individual specificity, patients with similar pathological characteristics still have great differences in the risk of disease recurrence. Therefore, it is often inaccurate to predict the survival status of patients based on clinical characteristic biomarkers, and a prognostic molecular biomarker that can grade the risk of bladder cancer patients is needed. METHODS: A total of three bladder urothelial carcinoma datasets were used in this study from the Cancer Genome Atlas database and Gene Expression Omnibus database. In order to avoid overfitting, all samples were randomly divided into one training set and three validation sets, which were used to construct and test the prognostic biomarker model of bladder urothelial carcinoma. Univariate and multivariate Cox regression were used to screen candidate mRNAs and construct prognostic biomarkers model. Kaplan-Meier survival analysis and the receiver operating characteristic (ROC) curve were used to evaluate the predictive performance of the model. RESULTS: A prognostic biomarker model of bladder urothelial carcinoma combining with eight mRNA was constructed. Kaplan-Meier analyses indicated that a significant difference in the survival time of patients between the high-risk and the low-risk group. The area under the ROC curve were 0.632 (95% confidence interval (CI) [0.541-0.723]), 0.693 (95% CI [0.601-0.784]) and 0.686 (95% CI [0.540-0.831]) when the model was used to predict the patient's survival time in three validation datasets. The model showed high accuracy and applicability.