P-type nitrogen-doped ß-Ga2O3: the role of stable shallow acceptor NO-VGa complexes.

In-depth understanding of the acceptor states and origins of p-type conductivity is essential and critical to overcome the great challenge for the p-type doping of ultrawide-bandgap oxide semiconductors. In this study we find that stable NO-VGa complexes can be formed with ε(0/-) transition levels significantly smaller than those of the isolated NO and VGa defects using N2 as the dopant source. Due to the defect-induced crystal-field splitting of the p orbitals of Ga, O and N atoms, and the Coulomb binding between NO(II) and VGa(I), an a' doublet state at 1.43 eV and an a'' singlet state at 0.22 eV above the valence band maximum (VBM) are formed for the ß-Ga2O3:NO(II)-VGa(I) complexes with an activated hole concentration of 8.5 × 1017 cm-3 at the VBM, indicating the formation of a shallow acceptor level and the feasibility to obtain p-type conductivity in ß-Ga2O3 even when using N2 as the dopant source. Considering the transition from NO(II)-V0Ga(I) + e to NO(II)-V-Ga(I), an emission peak at 385 nm with a Franck-Condon shift of 1.08 eV is predicted. These findings are of general scientific significance as well as technological application significance for p-type doping of ultrawide-bandgap oxide semiconductors.

Lateralized differences for verbal learning across trials in temporal lobe epilepsy are not affected by surgical intervention.

This research aimed to broaden understanding of learning verbal material in participants with left- and right-sided mesial temporal lobe epilepsy (MTLE). We modeled word list-learning to determine how anterior temporal lobe resection affects verbal learning. Verbal learning (across trials) was assessed using the first five trials of the Rey Auditory Verbal Learning Test (RAVLT) in 128 participants with MTLE. Mixedeffects modeling was used to determine whether learning curves differed between participants with left- and right-sided MTLE pre- and post- anterior temporal lobe resection. Laterality of MTLE had a significant effect on both the model intercept and the linear slope, whereby participants with left-sided MTLE retained fewer words on both the first trial and on each subsequent trial than participants with right-sided MTLE; and this held regardless of anterior temporal lobe resection status (t(117) = -3.516, p < .001; t(120.50) = -2.049, p = .042, for intercept and linear slope, respectively). There were no significant differences in the learning curves after anterior temporal lobe resection surgery in either left- or right-sided MTLE. Our findings suggest that acquisition of verbal information may be especially impaired in patients with left-sided MTLE. Further, we show that verbal learning across trials was not affected by surgical intervention. This finding contributes to the broader understanding of the impacts of anterior temporal lobe resection on verbal memory function, and has important implications for the clinical management and surgical planning for patients with temporal lobe epilepsy.

Activation of autophagy contributes to the protective effects of lycopene against oxidative stress-induced apoptosis in rat chondrocytes.

Oxidative stress is commonly associated with osteoarthritis (OA). Lycopene (LYC), a natural carotenoid compound, is an effective antioxidant with potential cartilage-protecting actions. However, how it affects hydrogen peroxide (H2 O2 )-induced damage to the cartilage is unclear. In this study, an in vitro oxidative stress model was developed via treating primary chondrocytes with H2 O2 . Western blot, immunohistochemistry, and quantitative RT-PCR (qRT-PCR) were used to assess the levels of related factors. Reactive oxygen species (ROS) and apoptosis levels were analyzed by the use of appropriate probes and flow cytometry. The expression and activity of stress-specific enzymes (malondialdehyde, superoxide dismutase, and catalase) were also assessed. The role of autophagy was explored by using the inhibitor, 3-methyladenine (3-MA), as well as monodansylcadaverine staining, western blotting, and red fluorescent protein-green fluorescent protein-light chain 3 lentivirus infection. The result showed LYC exerted significant chondrocyte-protective effects, including reduced inflammation and chondrocyte degradation, increased chondrocyte proliferation, apoptosis inhibition, and reduced ROS production. LYC could effectively induce autophagy in the H2 O2 treatment group, and this effect could be attenuated by 3-MA. In terms of mechanism, LYC played a role in inhibiting MAPK and PI3K/Akt/NF-κB axis, which down-regulates levels of mTOR and had a potential therapeutic significance for cartilage degeneration.

GluN2B-BDNF pathway in the cerebrospinal fluid-contacting nucleus mediates nerve injury-induced neuropathic pain in rats.

The present study was aimed to investigate the role of GluN2B-BDNF pathway in the cerebrospinal fluid-contacting nucleus (CSF-CN) in neuropathic pain. Intra-lateral ventricle injection of cholera toxin subunit B conjugated with horseradish peroxidase (CBHRP) was used to label the CSF-CN. Double-labeled immunofluorescent staining and Western blot were used to observe the expression of GluN2B and BDNF in the CSF-CN. Chronic constriction injury of sciatic nerve (CCI) rat model was used to duplicate the neuropathic pain. Pain behavior was scored to determine the analgesic effects of GluN2B antagonist Ro 25-6981 and BDNF neutralizing antibody on CCI rats. GluN2B and BDNF were expressed in the CSF-CN and their expression was up-regulated in CCI rats. Intra-lateral ventricle injection of GluN2B antagonist Ro 25-6981 or BDNF neutralizing antibody notably alleviated thermal hyperalgesia and mechanical allodynia in CCI rats. Moreover, the increased expression of BDNF protein in CCI rats was reversed by intra-lateral ventricle injection of Ro 25-6981. These results suggest that GluN2B and BDNF are expressed in the CSF-CN and alteration of GluN2B-BDNF pathway in the CSF-CN is involved in the modulation of the peripheral neuropathic pain.

The therapeutic effects of edaravone on collagen-induced arthritis in rats.

Current research suggests that synovial phagocytic cells remove excessive amounts of free oxygen radicals (reactive oxygen species [ROS]), thereby preventing damage to synovial tissues. Moreover, ROS may affect the expression of growth arrest and DNA damage inducible α (GADD45A), thus further promoting the activation of synovial fibroblasts. Male adult rats were assessed for progression of collagen-induced arthritis (CIA) using a macroscopic arthritis scoring system of the hind paws and by measuring the changes in the rat's body weight, and activity level before and after diagnosis of CIA. Rats were intraperitoneally injected twice daily with edaravone at doses of 3, 6, and 9 mL/kg. Samples were taken at 2, 4, and 6 weeks, respectively. Edaravone was found to significantly reduce macroscopic arthritis and microscopic pathology scores in CIA rats. The concentration of endothelial nitric oxide synthase-6, glutathione, and heme oxygenase-1 in the serum of rats decreased, as was the production of ROS around the synovium and inflammatory factors. Moreover, ROS-1 increased the expression of the nuclear factor-κB (NF-κB) p65 protein by altering the expression level of GADD45A, causing aggravation of tissue damage. Edaravone also significantly improved the physiological condition of CIA rats, including appetite, weight changes, and loss of fur, as well as limb mobility. We believe that edaravone acts to reduce the expression of NF-ĸB p65 by clearing ROS, which causes reduced expression of GADD45A, and subsequently reduces the level of apoptosis and inflammatory response proteins, thereby reducing the symptoms of CIA. We, therefore, propose that edaravone is an effective option for clinical treatment of rheumatic arthritis.

Gö6983 attenuates breast cancer-induced osteolysis by the apoptotic pathway.

Bone metastasis caused by breast cancer leads to significant complications in treatment, and the resulting osteolysis considerably affects patients' overall survival and quality of life. Gö6983 is a broad spectrum protein kinase C inhibitor. In this study, based on our finding that the Gö6983 inhibits osteolysis, we applied Gö6983 to the MDA-MB-231 breast cancer-induced mouse bone metastasis model. And we found that Gö6983 has a strong inhibitory effect on the tumorigenic model of breast cancer by promoting the mitochondrial apoptosis pathway. Our study, therefore, demonstrates that Gö6983 has a potential inhibitory effect on breast cancer-induced osteoclast activation and provides mechanistic insight that may prove useful for designing future treatments.

GABARAP promotes bone marrow mesenchymal stem cells-based the osteoarthritis cartilage regeneration through the inhibition of PI3K/AKT/mTOR signaling pathway.

Osteoarthritis (OA) is a degenerative disease of the cartilage prevalent in the middle-aged and elderly demographic. Direct transplantation of bone marrow mesenchymal stem cells (BMSCs) or stem cell-derived chondrocytes into the damaged cartilage is a promising therapeutic strategy for OA, but is limited by the poor survival and in situ stability of the chondrocytes. Autophagy is a unique catabolic pathway conserved across eukaryotes that maintains cellular homeostasis, recycles damaged proteins and organelles, and promotes survival. The aim of this study was to determine the role of the proautophagic γ-aminobutyric acid receptor-associated protein (GABARAP) on the therapeutic effects of BMSCs-derived chondrocytes in a rat model of OA, and elucidate the underlying mechanisms. Anterior cruciate ligament transection (ACLT) was performed in Sprague-Dawley rats to simulate OA, and the animals were injected weekly with recombinant human His6-GABARAP protein, BMSCs-derived differentiated chondrocytes (DCs) or their combination directly into the knee cartilage. The regenerative effects of GABARAP and/or DCs were determined in term of International Cartilage Repair Society scores and cartilage thickness. The combination treatment of DCs and GABARAP significantly increased the levels of the ECM proteins Col II and SOX9, indicating formation of hyaline-like cartilage, and decreased chondrocyte apoptosis and inflammation. DCs + GABARAP treatment also upregulated the mediators of the autophagy pathway and suppressed the PI3K/AKT/mTOR pathway, indicating a mechanistic basis of its therapeutic action.

Nanowire-Seeded Growth of Single-Crystalline (010) ß-Ga2 O3 Nanosheets with High Field-Effect Electron Mobility and On/Off Current Ratio.

2D ß-Ga2 O3 nanosheets, as fundamental materials, have great potential in next generations of ultraviolet transparent electrodes, high-temperature gas sensors, solar-blind photodetectors, and power devices, while their synthesis and growth with high crystalline quality and well-controlled orientation have not been reported yet. The present study demonstrates how to grow single-crystalline ultrathin quasi-hexagonal ß-Ga2 O3 nanosheets with nanowire seeds and proposes a hierarchy-oriented growth mechanism. The hierarchy-oriented growth is initiated by epitaxial growth of a single-crystalline ( 2 - 01 ) ß-Ga2 O3 nanowire on a GaN nanocrystal and followed by homoepitaxial growth of quasi-hexagonal (010) ß-Ga2 O3 nanosheets. The undoped 2D (010) ß-Ga2 O3 nanosheet field effect transistor has a field-effect electron mobility of 38 cm2 V-1 s-1 and an on/off current ratio of 107 with an average subthreshold swing of 150 mV dec-1 . The from-nanowires-to-nanosheets technique paves a novel way to fabricate nanosheets, which has great impact on the field of nanomaterial synthesis and growth and the area of nanoelectronics as well.

Experiments on Temperature Changes of Microbolometer under Blackbody Radiation and Predictions Using Thermal Modeling by COMSOL Multiphysics Simulator.

In this study, we study a heat transfer model, with the surface of the microbolometer device receiving radiation from blackbody constructed using a COMSOL Multiphysics simulator. We have proposed three kinds of L-type 2-leg and 4-leg with the pixel pitch of 35 µm based on vanadium oxide absorbent membrane sandwiched with top passivated and bottom Si3N4 supporting films, respectively. Under the blackbody radiation, the surface temperature changes and distributions of these samples are simulated and analyzed in detail. The trend of change of the temperature dependent resistance of the four kinds of bolometer devices using the proposed heat transfer model is consistent with the actual results of the change of resistance of 4 samples irradiated with 325 K blackbody located in the front distance of 5 cm. In this paper, ΔT indicates the averaged differences of the top temperature on the suspended membrane and the lowest temperature on the post of legs of the microbolometers. It is shown that ΔT ≈ 17 mK is larger in nominal 2-leg microbolometer device than that of 4-leg one and of 2-leg with 2 µm × 2 µm central square hole and two 7.5 µm × 2 µm slits in suspended films. Additionally, only ΔT ≈ 5 mK with 4-leg microbolometer device under the same radiated energy of 325 K blackbody results from the larger total thermal conductance.

Identification and validation of oxeiptosis-associated lncRNAs and prognosis-related signature genes to predict the immune status in uterine corpus endometrial carcinoma.

As a novel cell death modality, oxeiptosis is mainly caused by oxidative stress. However, the associations of uterine corpus endometrial carcinoma (UCEC) with oxeiptosis-associated long non-coding RNAs (lncRNAs) are unknown. Here, to identify hub oxeiptosis-associated lncRNAs in UCEC, we collected the data for lncRNAs and gene expression in UCEC from The Cancer Genome Atlas (TCGA) database. Then, a lncRNA risk signature was constructed, and its prognostic value was further evaluated. Finally, the expression levels of hub lncRNA HOXB-AS3 were validated by quantitative RT-PCR analysis. MTT and wounding analyses were also applied to confirm the role of HOXB-AS3 knockdown on UCEC cells. Five lncRNAs associated with oxeiptosis and connected to the prognosis of UCEC were identified, and a risk signature was constructed based on these identified lncRNAs. Our clinical value analyses suggested that the risk signature was closely connected to the overall survival, TNM stage, and grade of UCEC patients. Meanwhile, compared to the conventional clinicopathological characteristics, this risk signature exhibited significantly higher diagnostic accuracy. Moreover, the potential mechanism analysis indicated a close connection of this risk signature to tumor stemness, m6A-related genes, immune cell infiltration, and immune subtypes. Based on the risk scores, we constructed a nomogram. In vitro experiments found that HOXB-AS3 was significantly higher expressed in UCEC cells, and the silence of HOXB-AS3 inhibited the proliferation and migration of UCEC cells. In conclusion, using five hub lncRNAs associated with oxeiptosis, we generated a risk signature, which could be applied in the novel therapeutic strategies of UCEC development.

Identification and validation of anoikis-associated gene SNCG as a prognostic biomarker in gastric cancer.

As a type of cell apoptosis, anoikis is caused by cells detachment from the extracellular matrix and anoikis resistance is central to cancer metastasis. Here, SNCG was identified as hub anoikis-associated gene in GC and associated with prognosis of patients with GC. To screen the hub anoikis-associated genes connected to GC, the database of Cancer Genome Atlas (TCGA) was employed. For further validating these identified genes, the Gene Expression Omnibus (GEO) dataset was applied, and Western blotting and quantitative Real-Time PCR were carried out. To Identify hub genes, we conducted the analyses of univariate Cox regression, differential expression, and weighted gene co-expression network analysis (WGCNA). According to the identified hub genes, we constructed a model of prognosis. Following complex analysis, SNCG was finally identified as hub anoikis-associated gene in GC. Indeed, K-M and receiver operating characteristic analyses suggested that the expression patterns of SNCG can be used as prognostic factors for GC survival. The expression and survival trends of SNCG were verified in the validation cohort and in vitro experimental analyses. The analysis of immune cell infiltration showed that the infiltrated immune cells varied among patients with GC and gene SNCG. Furthermore, due to the significant association of the constructed risk signature with patient age and survival, this risk signature can be used to predict the prognosis of GC. We suggest that SNCG was served as hub anoikis-associated gene in GC. Meanwhile, SNCG may have prognostic potential for overall patient survival.

Chemical screening links disulfiram with cardiac protection after ischemic injury.

Ischemia-reperfusion injury occurs after reperfusion treatment for patients suffering myocardial infarction, however the underlying mechanisms are incompletely understood and effective pharmacological interventions are limited. Here, we report the identification and characterization of the FDA-approved drug disulfiram (DSF) as a cardioprotective compound. By applying high-throughput chemical screening, we found that DSF decreased H2O2-induced cardiomyocyte death by inhibiting Gasdermin D, but not ALDH1, in cardiomyocytes. Oral gavage of DSF decreased myocardial infarct size and improved heart function after myocardial ischemia-reperfusion injury in rats. Therefore, this work reveals DSF as a potential therapeutic compound for the treatment of ischemic heart disease.

Identification of a predictive gene signature related to pyroptosis for the prognosis of cutaneous melanoma.

Pyroptosis is a form of inflammatory programmed cell death. However, because of no specific molecular biomarker, pyroptosis has not been considered as a novel therapeutic method to treat cutaneous melanoma (CM). Here, we identified pyroptosis genes that associate with the prognosis of CM patients and constructed an effective model for the prognostic prediction of CM patients. To identify genes related to pyroptosis that are differentially expressed in CM, we obtained gene expression data of CM patients and normal skin tissues from the Cancer Genome Atlas and the Genotype-Tissue Expression databases, and used another cohort obtained from Gene Expression Omnibus database for validation. Three genes (BST2, GBP5, and AIM2) that were associated with prognosis were found and incorporated into our prognostic model. Furthermore, we divided the patients into 2 groups: a high-risk group and a low-risk group. Functional analyses indicated that our model was correlated with patient survival and cancer growth. Multivariate and univariate Cox regressions revealed that the constructed model could serve as an independent prognostic factor for CM patients. Meanwhile, compared with other clinical characteristics, our model significantly improved the diagnostic accuracy. Gene function analysis revealed that pyroptosis genes BST2, GBP5, and AIM2 were differentially expressed in CM patients and positively associated with patient prognosis. Finally, a risk score was used to generate nomograms that displayed favorable discriminatory abilities for CM. In summary, our model could significantly predict the prognosis of CM patients and be used for the development of CM therapy.

Cuproptosis-associated genes and immune microenvironment characterization in breast cancer.

Excess Cu can cause cell death as a cofactor for essential enzymes. The relationship between cuproptosis-associated genes (CAGs) and breast cancer (BR) is not completely investigated. Here, the transcriptome expression and mutation profile data of BR samples from the Cancer Genome Atlas database were retrieved to identify CAGs. Patients with BR were clustered using consensus clustering. A least absolute shrinkage and selection operator analysis was then performed to construct a CAGs risk signature. As a result, all 13 cuproptosis regulators were significantly differentially expressed between BR and normal samples; among them, 9 cuproptosis genes were correlated with prognoses. Patients with BR were separated into 2 clusters that were associated with patient survival, clinical phenotypes, and immune infiltration, Based on the components of cuproptosis. Subsequently, genes differentially expressed between clusters were obtained, and 11 CAGs were ultimately incorporated into the risk signature. Functional analyses revealed that the risk signature correlated with patient outcomes, ER, PR, HER2 expression, and BR IHC subtypes. Additionally, immune microenvironment analyses showed that CAGs-high-risk patients exhibited lower immune cell infiltration and immune functions. Furthermore, high-risk BR patients had higher TMB, lower immune checkpoint expression, higher m6A gene expression, and higher tumor stemness. Finally, the immunophenoscore analysis revealed that the risk signature could potentially predict the immune response in BR and help guide the application of various immunotherapeutic drugs. Overall, the newly constructed CAGs risk signature presented a predictive value for the prognosis and tumor microenvironment of BR patients and can be further used in the guidance of immunotherapy for BR.

Identification of m7G-associated lncRNA prognostic signature for predicting the immune status in cutaneous melanoma.

RNA modifications, including RNA methylation, are widely existed in cutaneous melanoma (CM). Among epigenetic modifications, N7-methylguanosine (m7G) is a kind of modification at 5' cap of RNA which participate in maintaining the stability of mRNA and various cell biological processes. However, there is still no study concerning the relationship between CM and m7G methylation complexes, METTL1 and WDR4. Here, long non-coding RNA (lncRNAs) and gene expression data of CM from the Cancer Genome Atlas (TCGA) database were retrieved to identify differentially expressed m7G-related lncRNAs connected with overall survival of CM. Then, Cox regression analyses was applied to construct a lncRNA risk signature, the prognostic value of identified signature was further evaluated. As a result, 6 m7G-associated lncRNAs that were significantly related to CM prognosis were incorporated into our prognostic signature. The functional analyses indicated that the prognostic model was correlated with patient survival, cancer metastasis, and growth. Meanwhile, its diagnostic accuracy was better than conventional clinicopathological characteristics. The pathway enrichment analysis showed that the risk model was enriched in several immunity-associated pathways. Moreover, the signature model was significantly connected with the immune subtypes, infiltration of immune cells, immune microenvironment, as well as several m6A-related genes and tumor stem cells. Finally, a nomogram based on the calculated risk score was established. Overall, a risk signature based on 6 m7G-associated lncRNAs was generated which presented predictive value for the prognosis of CM patients and can be further used in the development of novel therapeutic strategies for CM.

Identifying the hub genes and immune infiltration related to pyroptosis in rheumatoid arthritis.

ABSTRACT: Rheumatoid arthritis (RA) is one of the most common autoimmune joint disorders globally, but its pathophysiological mechanisms have not been thoroughly investigated. Pyroptosis significantly correlates with programmed cell death. However, targeting pyroptosis has not been considered as a therapeutic strategy in RA due to a lack of systematic studies on validated biomarkers. The present study aimed to identify hub pyroptosis biomarkers and immune infiltration in RA. The gene expression profiles of synovial tissues were obtained from the Gene Expression Omnibus (GEO) database to identify differentially expressed pyroptosis genes (DEPGs). Meanwhile, the CIBERSORT algorithm was used to explore the association between immune infiltration and RA. Consequently, two hub DEPGs (EGFR and JUN) were identified as critical genes in RA. Through gene ontology and pathway enrichment analysis. EGFR and JUN were found to be primarily involved in the ErbB signaling pathway, PD-1 checkpoint pathway, GnRH signaling pathway, etc. Furthermore, for immune infiltration analysis, the pyroptosis genes EGFR and JUN were closely connected with four and one immune cell types, respectively. Overall, this study presents a novel method to identify hub DEPGs and their correlation with immune infiltration, which may provide novel perspectives into the diagnosis and treatment of patients with RA.

Identifying hub genes and immune infiltration of osteoarthritis using comprehensive bioinformatics analysis.

BACKGROUND: Osteoarthritis (OA) is the most common chronic degenerative joint disorder globally that is characterized by synovitis, cartilage degeneration, joint space stenosis, and sub-cartilage bone hyperplasia. However, the pathophysiologic mechanisms of OA have not been thoroughly investigated. METHODS: In this study, we conducted various bioinformatics analyses to identify hub biomarkers and immune infiltration in OA. The gene expression profiles of synovial tissues from 29 healthy controls and 36 OA samples were obtained from the gene expression omnibus database to identify differentially expressed genes (DEGs). The CIBERSORT algorithm was used to explore the association between immune infiltration and arthritis. RESULTS: Eighteen hub DEGs were identified as critical biomarkers for OA. Through gene ontology and pathway enrichment analyses, it was found that these DEGs were primarily involved in PI3K-Akt signaling pathway and Rap1 signaling pathway. Furthermore, immune infiltration analysis revealed differences in immune infiltration between patients with OA and healthy controls. The hub gene ZNF160 was closely related to immune cells, especially mast cell activation in OA. CONCLUSION: Overall, this study presented a novel method to identify hub DEGs and their correlation with immune infiltration, which may provide novel insights into the diagnosis and treatment of patients with OA.

Integrated analysis identifies oxidative stress genes associated with progression and prognosis in gastric cancer.

Oxidative stress (OS) reactions are reported to be associated with oncogenesis and tumor progression. However, little is known about the potential diagnostic value of OS in gastric cancer (GC). This study identified hub OS genes associated with the prognosis and progression of GC and illustrated the underlying mechanisms. The transcriptome data and corresponding GC clinical information were collected from The Cancer Genome Atlas (TCGA) database. Aberrantly expressed OS genes between tumors and adjacent normal tissues were screened, and 11 prognosis-associated genes were identified with a series of bioinformatic analyses and used to construct a prognostic model. These genes were validated in the Gene Expression Omnibus (GEO) database. Furthermore, weighted gene co-expression network analysis (WGCNA) was subsequently conducted to identify the most significant hub genes for the prediction of GC progression. Analysis revealed that a good prognostic model was constructed with a better diagnostic accuracy than other clinicopathological characteristics in both TCGA and GEO cohorts. The model was also significantly associated with the overall survival of patients with GC. Meanwhile, a nomogram based on the risk score was established, which displayed a favorable discriminating ability for GC. In the WGCNA analysis, 13 progression-associated hub OS genes were identified that were also significantly associated with the progression of GC. Furthermore, functional and gene ontology (GO) analyses were performed to reveal potential pathways enriched with these genes. These results provide novel insights into the potential applications of OS-associated genes in patients with GC.

Identification and prognostic value of a glycolysis-related gene signature in patients with bladder cancer.

ABSTRACT: Bladder cancer (BC) is one of the most common malignancies worldwide. Several biomarkers related to the prognosis of patients with BC have previously been identified. However, these prognostic models use only one gene and are thus not reliable or accurate enough. The purpose of our study was to develop an innovative gene signature that has greater prognostic value in BC. So, in this study, we performed mRNA expression profiling of glycolysis-related genes in BC (n = 407) cohorts by mining data from The Cancer Genome Atlas (TCGA) database. The glycolysis-related gene sets were confirmed using the Gene Set Enrichment Analysis (GSEA). Using Cox regression analysis, a risk score staging model was built based on the genes that were determined to be significantly associated with BC outcome. Eventually, the system of risk score was structured to predict a patient's survival, and we identified four genes (CHPF, AK3, GALK1, and NUP188) that were associated with the outcomes of BC patients. According to the above-mentioned gene signature, patients were divided into two risk subgroups. The analysis showed that our constructed risk model was independent of clinical features and that the risk score was a highly powerful tool for predicting the overall survival (OS) of BC patients. Taking together, we identified a gene signature associated with glycolysis that could effectively predict the prognosis of BC patients. Our findings offer a new perspective for the clinical research and treatment of BC.

DNA methylation patterns-based subtype distinction and identification of soft tissue sarcoma prognosis.

ABSTRACT: Soft tissue sarcomas (STSs) are heterogeneous at the clinical with a variable tendency of aggressive behavior. In this study, we constructed a specific DNA methylation-based classification to identify the distinct prognosis-subtypes of STSs based on the DNA methylation spectrum from the TCGA database. Eventually, samples were clustered into 4 subgroups, and their survival curves were distinct from each other. Meanwhile, the samples in each subgroup reflected differentially in several clinical features. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was also conducted on the genes of the corresponding promoter regions of the above-described specific methylation sites, revealing that these genes were mainly concentrated in certain cancer-associated biological functions and pathways. In addition, we calculated the differences among clustered methylation sites and performed the specific methylation sites with LASSO algorithm. The selection operator algorithm was employed to derive a risk signature model, and a prognostic signature based on these methylation sites performed well for risk stratification in STSs patients. At last, a nomogram consisted of clinical features and risk score was developed for the survival prediction. This study declares that DNA methylation-based STSs subtype classification is highly relevant for future development of personalized therapy as it identifies the prediction value of patient prognosis.