The identification of a novel shared therapeutic target and drug across all insulin-sensitive tissues under insulin resistance.

Background: To identify key and shared insulin resistance (IR) molecular signatures across all insulin-sensitive tissues (ISTs), and their potential targeted drugs. Methods: Three datasets from Gene Expression Omnibus (GEO) were acquired, in which the ISTs (fat, muscle, and liver) were from the same individual with obese mice. Integrated bioinformatics analysis was performed to obtain the differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) was carried out to determine the "most significant trait-related genes" (MSTRGs). Enrichment analysis and PPI network were performed to find common features and novel hub genes in ISTs. The shared genes of DEGs and genes between DEGs and MSTRGs across four ISTs were identified as key IR therapeutic target. The Attie Lab diabetes database and obese rats were used to verify candidate genes. A medical drug-gene interaction network was conducted by using the Comparative Toxicogenomics Database (CTD) to find potential targeted drugs. The candidate drug was validated in Hepa1-6 cells. Results: Lipid metabolic process, mitochondrion, and oxidoreductase activity as common features were enriched from ISTs under an obese context. Thirteen shared genes (Ubd, Lbp, Hp, Arntl, Cfd, Npas2, Thrsp., Tpx2, Pkp1, Sftpd, Mthfd2, Tnfaip2, and Vnn3) of DEGs across ISTs were obtained and confirmed. Among them, Ubd was the only shared gene between DEGs and MSTRGs across four ISTs. The expression of Ubd was significantly upregulated across four ISTs in obese rats, especially in the liver. The IR Hepa1-6 cell models treated with dexamethasone (Dex), palmitic acid (PA), and 2-deoxy-D-ribose (dRib) had elevated expression of Ubd. Knockdown of Ubd increased the level of p-Akt. A lowing Ubd expression drug, promethazine (PMZ) from CTD analysis rescued the decreased p-Akt level in IR Hepa1-6 cells. Conclusion: This study revealed Ubd, a novel and shared IR molecular signature across four ISTs, as an effective biomarker and provided new insight into the mechanisms of IR. PMZ was a candidate drug for IR which increased p-Akt level and thus improved IR by targeting Ubd and downregulation of Ubd expression. Both Ubd and PMZ merit further clinical translational investigation to improve IR.

Preliminary Mechanism of Glial Maturation Factor ß on Pulmonary Vascular Remodeling in Pulmonary Arterial Hypertension.

Recent evidence suggests that glia maturation factor ß (GMFß) is important in the pathogenesis of pulmonary arterial hpertension (PAH), but the underlying mechanism is unknown. To clarify whether GMFß can be involved in pulmonary vascular remodeling and to explore the role of the IL-6-STAT3 pathway in this process, the expression of GMFß in PAH rats is examined and the expression of downstream molecules including periostin (POSTN) and interleukin-6 (IL-6) is measured using real-time quantitative polymerase chain reaction (RT-qPCR) and western blot analysis. The location and expression of POSTN is also tested in PAH rats using immunofluorescence. It is proved that GMFß is upregulated in the lungs of PAH rats. Knockout GMFß alleviated the MCT-PAH by reducing right ventricular systolic pressure (RVSP), mean pulmonary arterial pressure (mPAP), and pulmonary vascular remodeling. Moreover, the inflammation of the pulmonary vasculature is ameliorated in PAH rats with GMFß absent. In addition, the IL-6-STAT3 signaling pathway is activated in PAH; knockout GMFß reduced POSTN and IL-6 production by inhibiting the IL-6-STAT3 signaling pathway. Taken together, these findings suggest that knockout GMFß ameliorates PAH in rats by inhibiting the IL-6-STAT3 signaling pathway.

GMFB/AKT/TGF-ß3 in Müller cells mediated early retinal degeneration in a streptozotocin-induced rat diabetes model.

Retinal degeneration, characterized by Müller cell gliosis and photoreceptor apoptosis, is considered an early event in diabetic retinopathy (DR). Our previous study proposed that GMFB may mediate diabetic retinal degeneration. This study identified GMFB as a sensitive and functional gliosis marker for DR. Compared to the wild type (WT) group, Gmfb knockout (KO) significantly improved visual function, attenuated gliosis, reduced the apoptosis of neurons, and decreased the mRNA levels of tumor necrosis factor α (Tnf-α) and interleukin-1ß (Il-1ß) in diabetic retinas. Tgf-ß3 was enriched by hub genes using RNA sequencing in primary WT and KO Müller cells. Gmfb KO significantly upregulated the transforming growth factor (TGF)-ß3 protein level via the AKT pathway. The protective effect of TGF-ß3 in the vitreous resulted in significantly improved visual function and decreased the number of apoptotic cells in the diabetic retina. The protection of Gmfb KO in primary Müller cells against high glucose (HG)-induced photoreceptor apoptosis was partially counteracted by TGF-ß3 antibody and administration of TGFBR1/2 inhibitors. Nuclear receptor subfamily 3 group C member 1 (NR3C1) binds to the promoter region of Gmfb and regulates Gmfb mRNA at the transcriptional level. NR3C1 was increased in the retinas of early diabetic rats but decreased in the retinas of late diabetic rats. N'-[(1E)-(3-Methoxyphenyl)Methylene]-3-Methyl-1H-Pyrazole-5-Carbohydrazide (DS-5) was identified as an inhibitor of GMFB, having a protective role in DR. We demonstrated that GMFB/AKT/TGF-ß3 mediated early diabetic retinal degeneration in diabetic rats. This study provides a novel therapeutic strategy for treating retinal degeneration in patients with DR.

Biaxial strain modulated electronic structures of layered two-dimensional MoSiGeN4 Rashba systems.

The two-dimensional (2D) MA2Z4 family has received extensive attention in manipulating its electronic structure and achieving intriguing physical properties. However, engineering the electronic properties remains a challenge. Herein, based on first-principles calculations, we systematically investigate the effect of biaxial strains on the electronic structure of 2D Rashba MoSiGeN4 (MSGN), and further explore how the interlayer interactions affect the Rashba spin splitting (RSS) in such strained layered MSGN systems. After applying biaxial strains, the band gap decreases monotonically with increasing tensile strains but increases when the compressive strains are applied. An indirect-direct-indirect band gap transition is induced by applying a moderate compressive strain (<5%) in the MSGN systems. Due to the symmetry breaking and moderate spin-orbit coupling (SOC), the monolayer MSGN possesses an isolated RSS near the Fermi level, which could be effectively regulated to the Lifshitz-type spin splitting (LSS) by biaxial strain. For instance, the LSS ← RSS → LSS transformation of the Fermi surface is presented in the monolayer and a more complex and changeable LSS ← RSS → LSS → RSS evolution is observed in bilayer and trilayer MSGN systems as the biaxial strain varies from -8% to 12%, which actually depends on the appearance, variation, and vanish of the Mexican hat band in the absence of SOC under different strains. The contribution of the Mo-dz2 orbital hybridized with the N-pz orbital in the highest valence band plays a dominant role in band evolution under biaxial strains, where the RSS → LSS evolution corresponds to the decreased Mo-dz2 orbital contribution. Our study highlights the biaxial strain controllable RSS, in particular the introduction and even the evolution of LSS near the Fermi surface, which makes the strained MSGN systems promising candidates for future applications in spintronic devices.

Dissecting cellular states of infiltrating microenvironment cells in melanoma by integrating single-cell and bulk transcriptome analysis.

BACKGROUND: Cellular states of different immune cells can affect the activity of the whole immune microenvironment. METHODS: Here, leveraging reference profiles of microenvironment cell states that were constructed based on single-cell RNA-seq data of melanoma, we dissected the composition of microenvironment cell states across 463 skin cutaneous melanoma (SKCM) bulk samples through CIBERSORT-based deconvolution of gene expression profiles and revealed high heterogeneity of their distribution. Correspondence analysis on the estimated cellular fractions of melanoma bulk samples was performed to identify immune phenotypes. Based on the publicly available clinical survival and therapy data, we analyzed the relationship between immune phenotypes and clinical outcomes of melanoma. RESULTS: By analysis of the relationships among those cell states, we further identified three distinct tumor microenvironment immune phenotypes: "immune hot/active", "immune cold-suppressive" and "immune cold-exhausted". They were characterized by markedly different patterns of cell states: most notably the CD8 T Cytotoxic state, CD8 T Mixed state, B non-regulatory state and cancer-associated fibroblasts (CAFs), depicting distinct types of antitumor immune response (or immune activity). These phenotypes had prognostic significance for progression-free survival and implications in response to immune therapy in an independent cohort of anti-PD1 treated melanoma patients. CONCLUSIONS: The proposed strategy of leveraging single-cell data to dissect the composition of microenvironment cell states in individual bulk tumors can also extend to other cancer types, and our results highlight the importance of microenvironment cell states for the understanding of tumor immunity.

Alloying Reversed Anisotropy of Thermal Transport in Bulk Al0.5Ga0.5N.

Anisotropic heat transfer is crucial for advanced thermal management in nanoelectronics, optoelectronics, thermoelectrics, etc. Traditional approaches modifying thermal conductivity (κ) mostly adjust the magnitude but disregard anisotropy. Herein, by solving the Boltzmann transport equation from first principles, we report κ anisotropy modulation by alloying gallium nitride (GaN) and aluminum nitride (AlN). The alloyed Al0.5Ga0.5N demonstrates reversed κ anisotropy compared to the parent materials, where the preferred thermal transport direction shifts from cross-plane to in-plane. Moreover, the κ anisotropy (κin-plane/κcross-plane) in the Al0.5Ga0.5N alloy is enhanced to 1.63 and 1.51 times that in bulk GaN and AlN, respectively, which can be further enhanced by increased temperature. Deep analysis attributes the alloying reversed κ anisotropy of Al0.5Ga0.5N to the structure distortion-driven phonon group velocity, as well as phonon anharmonicity. The alloying reversed κ anisotropy as reported in this study sheds light on future studies in advanced heat dissipation and intelligent thermal management.

Identifying the personalized driver gene sets maximally contributing to abnormality of transcriptome phenotype in glioblastoma multiforme individuals.

High heterogeneity in genome and phenotype of cancer populations made it difficult to apply population-based common driver genes to the diagnosis and treatment of cancer individuals. Characterizing and identifying the personalized driver mechanism for glioblastoma multiforme (GBM) individuals were pivotal for the realization of precision medicine. We proposed an integrative method to identify the personalized driver gene sets by integrating the profiles of gene expression and genetic alterations in cancer individuals. This method coupled genetic algorithm and random walk to identify the optimal gene sets that could explain abnormality of transcriptome phenotype to the maximum extent. The personalized driver gene sets were identified for 99 GBM individuals using our method. We found that genomic alterations in between one and seven driver genes could maximally and cumulatively explain the dysfunction of cancer hallmarks across GBM individuals. The driver gene sets were distinct even in GBM individuals with significantly similar transcriptomic phenotypes. Our method identified MCM4 with rare genetic alterations as previously unknown oncogenic genes, the high expression of which were significantly associated with poor GBM prognosis. The functional experiments confirmed that knockdown of MCM4 could significantly inhibit proliferation, invasion, migration, and clone formation of the GBM cell lines U251 and U118MG, and overexpression of MCM4 significantly promoted the proliferation, invasion, migration, and clone formation of the GBM cell line U87MG. Our method could dissect the personalized driver genetic alteration sets that are pivotal for developing targeted therapy strategies and precision medicine. Our method could be extended to identify key drivers from other levels and could be applied to more cancer types.

Glia maturation factor beta deficiency protects against diabetic osteoporosis by suppressing osteoclast hyperactivity.

Excessive osteoclast activation, which depends on dramatic changes in actin dynamics, causes osteoporosis (OP). The molecular mechanism of osteoclast activation in OP related to type 1 diabetes (T1D) remains unclear. Glia maturation factor beta (GMFB) is considered a growth and differentiation factor for both glia and neurons. Here, we demonstrated that Gmfb deficiency effectively ameliorated the phenotype of T1D-OP in rats by inhibiting osteoclast hyperactivity. In vitro assays showed that GMFB participated in osteoclast activation rather than proliferation. Gmfb deficiency did not affect osteoclast sealing zone (SZ) formation but effectively decreased the SZ area by decreasing actin depolymerization. When GMFB was overexpressed in Gmfb-deficient osteoclasts, the size of the SZ area was enlarged in a dose-dependent manner. Moreover, decreased actin depolymerization led to a decrease in nuclear G-actin, which activated MKL1/SRF-dependent gene transcription. We found that pro-osteoclastogenic factors (Mmp9 and Mmp14) were downregulated, while anti-osteoclastogenic factors (Cftr and Fhl2) were upregulated in Gmfb KO osteoclasts. A GMFB inhibitor, DS-30, targeting the binding site of GMFB and Arp2/3, was obtained. Biocore analysis revealed a high affinity between DS-30 and GMFB in a dose-dependent manner. As expected, DS-30 strongly suppressed osteoclast hyperactivity in vivo and in vitro. In conclusion, our work identified a new therapeutic strategy for T1D-OP treatment. The discovery of GMFB inhibitors will contribute to translational research on T1D-OP.

Integrated analysis of ferroptosis-related gene signature for overall survival prediction in Asian patients with hepatocellular carcinoma

Purpose Hepatocellular carcinoma (HCC) is one of the most prevalent types of cancers in Asia. Accumulating evidence suggests that ferroptosis is a non-apoptotic form of cell death, and has played an important role in cancer biology. Methods Based on the manually curated ferroptosis-related gene set and TCGA-LIHC dataset of Asian patients, we used DESeq2, Kaplan–Meier analysis, and univariate Cox regression to identify differentially expressed ferroptosis-related genes with significantly prognostic capacity. A risk signature was constructed based on the selected genes for predicting the survival of HCC patients in Asia. The survival prediction accuracy was confirmed by the time-dependent receiver operating characteristic (ROC) curve analysis. Gene set variation analysis (GSVA) was used to explore the functional associations of the signature. Ferroptosis potential index (FPI) and xCell algorithm was applied to quantify ferroptosis and immune cell infiltration, respectively. Two independent datasets from the GEO and the ICGC database were used for external validation. Results The ferroptosis-related signature could accurately predict the survival outcomes of HCC patients in Asian (p value < 0.0001). We showed that the signature was an independent factor and was beneficial in elevating risk stratification of current clinicopathologic features, such as the amount of alpha-fetoprotein (AFP) and residual tumor classification. Functional characterization showed that critical processes in tumorigenesis belonged to the high-risk groups, for example inflammatory response, which may be the main driver of HCC. The high-risk group had higher FPIs and infiltrations of macrophages and T-helper cells than the low-risk group. Furthermore, two independent cohorts confirmed the prognostic value of our signature (AU)

Integrated analysis of ferroptosis-related gene signature for overall survival prediction in Asian patients with hepatocellular carcinoma.

PURPOSE: Hepatocellular carcinoma (HCC) is one of the most prevalent types of cancers in Asia. Accumulating evidence suggests that ferroptosis is a non-apoptotic form of cell death, and has played an important role in cancer biology. METHODS: Based on the manually curated ferroptosis-related gene set and TCGA-LIHC dataset of Asian patients, we used DESeq2, Kaplan-Meier analysis, and univariate Cox regression to identify differentially expressed ferroptosis-related genes with significantly prognostic capacity. A risk signature was constructed based on the selected genes for predicting the survival of HCC patients in Asia. The survival prediction accuracy was confirmed by the time-dependent receiver operating characteristic (ROC) curve analysis. Gene set variation analysis (GSVA) was used to explore the functional associations of the signature. Ferroptosis potential index (FPI) and xCell algorithm was applied to quantify ferroptosis and immune cell infiltration, respectively. Two independent datasets from the GEO and the ICGC database were used for external validation. RESULTS: The ferroptosis-related signature could accurately predict the survival outcomes of HCC patients in Asian (p value < 0.0001). We showed that the signature was an independent factor and was beneficial in elevating risk stratification of current clinicopathologic features, such as the amount of alpha-fetoprotein (AFP) and residual tumor classification. Functional characterization showed that critical processes in tumorigenesis belonged to the high-risk groups, for example inflammatory response, which may be the main driver of HCC. The high-risk group had higher FPIs and infiltrations of macrophages and T-helper cells than the low-risk group. Furthermore, two independent cohorts confirmed the prognostic value of our signature. CONCLUSION: Overall, our results demonstrated potential application of ferroptosis-related genes as independent biomarkers in Asian HCC patients. Targeting ferroptosis may be clinically useful beyond known clinicopathological factors and provide benefit in immunotherapy.

The Heterogeneous Cellular States of Glioblastoma Stem Cells Revealed by Single Cell Analysis.

Glioblastoma stem cells (GSCs) contributed to the progression, treatment resistance, and relapse of glioblastoma (GBM). However, current researches on GSCs were performed usually outside the human tumor microenvironment, ignoring the importance of the cellular states of primary GSCs. In this study, we leveraged single-cell transcriptome sequencing data of 6 independent GBM cohorts from public databases, and combined lineage and stemness features to identify primary GSCs. We dissected the cell states of GSCs and correlated them with the clinical outcomes of patients. As a result, we constructed a cellular hierarchy where GSCs resided at the center. In addition, we identified and characterized 2 different and recurrent GSCs subpopulations: proliferative GSCs (pGSCs) and quiescent GSCs (qGSCs). The pGSCs showed high cell cycle activity, indicating rapid cell division, while qGSCs showed a quiescent state. Then we traced the processes of tumor development by pseudo-time analysis and tumor phylogeny, and found that GSCs accumulated throughout the whole tumor development period. During the process, pGSCs mainly contributed to the early stage and qGSCs were enriched in the later stage. Finally, we constructed an 8-gene prognostic signature reflecting pGSCs activity and found that patients whose tumors were enriched for the pGSC signature had poor clinical outcomes. Our study highlights the primary GSCs heterogeneity and its correlation to tumor development and clinical outcomes, providing the potential targets for GBM treatment.

Anisotropic Optical, Mechanical, and Thermoelectric Properties of Two-Dimensional Fullerene Networks.

Nanoclusters like fullerenes as the unit to build intriguing two-dimensional (2D) topological structures is of great challenge. Here we propose three bridged fullerene monolayers and comprehensively investigate the novel fullerene monolayer (α-C60-2D) as synthesized experimentally [Hou et al. Nature 2022, 606, 507-510] by state-of-the-art first-principles calculations. Our results show that α-C60-2D has a direct band gap of 1.55 eV close to the experimental value, an optical linear dichroism with strong absorption in the long-wave ultraviolet region, a small anisotropic Young's modulus, a large hole mobility, and an ultrahigh Seebeck coefficient at middle-low temperatures. It is unveiled that the anisotropic optical, mechanical, electrical, and thermoelectric properties of α-C60-2D originate from the asymmetric bridging arrangements between C60 clusters. Our study promises potential applications of monolayer fullerene networks in lots of fields.

The record low thermal conductivity of monolayer cuprous iodide (CuI) with a direct wide bandgap.

Two-dimensional materials have attracted significant research interest due to the fantastic properties that are unique to their bulk counterparts. In this paper, from the state-of-the-art first-principles, we predicted the stable structure of a monolayer counterpart of γ-CuI (cuprous iodide) that is a p-type wide bandgap semiconductor. The monolayer CuI presents multifunctional superiority in terms of electronic, optical, and thermal transport properties. Specifically, the ultralow thermal conductivity of 0.116 W m-1 K-1 is predicted for monolayer CuI, which is much lower than those of γ-CuI (0.997 W m-1 K-1) and other typical semiconductors. Moreover, an ultrawide direct bandgap of 3.57 eV is found in monolayer CuI, which is even larger than that of γ-CuI (2.95-3.1 eV), promising for applications in nano-/optoelectronics with better optical performance. The ultralow thermal conductivity and direct wide bandgap of monolayer CuI as reported in this study would promise its potential applications in transparent and wearable electronics.

Systematic investigation of the prognostic impact of clonal status of somatic mutations across multiple cancer types.

Tumors are genetically heterogeneous and many mutations are actually present in subclonal populations. The clonal status of mutations is valuable for accurate prognosis, clinical management. The aim of this study was to identify the clonal status of somatic mutations and systematically evaluate their prognostic values across various cancer types. We totally identified 227 clonal and 432 subclonal mutations contributed to prognosis and demonstrated the importance of clonal status in improving mutation-related clinical guidance. We further developed a customized multi-step approach to identify gene-specific prognostic patterns of clonal status at pan-cancer level and found some cancer-specific prognostic patterns. The 'subclonal-dependent risk' subpattern was one of the most common subpatterns, it usually accompanied by high genomic in-stability and high extent of intra-tumor heterogeneity and could be used to improve the accuracy of prognostic analysis. Our results revealed the importance of clonal status, especially subclonal mutation in clinical survival.

Identification of Novel Key Molecular Signatures in the Pathogenesis of Experimental Diabetic Kidney Disease.

Diabetic kidney disease (DKD) is a long-term major microvascular complication of uncontrolled hyperglycemia and one of the leading causes of end-stage renal disease (ESDR). The pathogenesis of DKD has not been fully elucidated, and effective therapy to completely halt DKD progression to ESDR is lacking. This study aimed to identify critical molecular signatures and develop novel therapeutic targets for DKD. This study enrolled 10 datasets consisting of 93 renal samples from the National Center of Biotechnology Information (NCBI) Gene Expression Omnibus (GEO). Networkanalyst, Enrichr, STRING, and Cytoscape were used to conduct the differentially expressed genes (DEGs) analysis, pathway enrichment analysis, protein-protein interaction (PPI) network construction, and hub gene screening. The shared DEGs of type 1 diabetic kidney disease (T1DKD) and type 2 diabetic kidney disease (T2DKD) datasets were performed to identify the shared vital pathways and hub genes. Strepotozocin-induced Type 1 diabetes mellitus (T1DM) rat model was prepared, followed by hematoxylin & eosin (HE) staining, and Oil Red O staining to observe the lipid-related morphological changes. The quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was conducted to validate the key DEGs of interest from a meta-analysis in the T1DKD rat. Using meta-analysis, 305 shared DEGs were obtained. Among the top 5 shared DEGs, Tmem43, Mpv17l, and Slco1a1, have not been reported relevant to DKD. Ketone body metabolism ranked in the top 1 in the KEGG enrichment analysis. Coasy, Idi1, Fads2, Acsl3, Oxct1, and Bdh1, as the top 10 down-regulated hub genes, were first identified to be involved in DKD. The qRT-PCR verification results of the novel hub genes were mostly consistent with the meta-analysis. The positive Oil Red O staining showed that the steatosis appeared in tubuloepithelial cells at 6 w after DM onset. Taken together, abnormal ketone body metabolism may be the key factor in the progression of DKD. Targeting metabolic abnormalities of ketone bodies may represent a novel therapeutic strategy for DKD. These identified novel molecular signatures in DKD merit further clinical investigation.

Revealing the contribution of somatic gene mutations to shaping tumor immune microenvironment.

Interaction between tumor cells and immune cells determined highly heterogeneous microenvironments across patients, leading to substantial variation in clinical benefits from immunotherapy. Somatic gene mutations were found not only to elicit adaptive immunity but also to influence the composition of tumor immune microenvironment and various processes of antitumor immunity. However, due to an incomplete view of associations between gene mutations and immunophenotypes, how tumor cells shape the immune microenvironment and further determine the clinical benefit of immunotherapy is still unclear. To address this, we proposed a computational approach, inference of mutation effect on immunophenotype by integrated gene set enrichment analysis (MEIGSEA), for tracing back the genomic factor responsible for differences in immunophenotypes. MEIGSEA was demonstrated to accurately identify the previous confirmed immune-associated gene mutations, and systematic evaluation in simulation data further supported its performance. We used MEIGSEA to investigate the influence of driver gene mutations on the infiltration of 22 immune cell types across 19 cancers from The Cancer Genome Atlas. The top associated gene mutations with infiltration of CD8 T cells, such as CASP8, KRAS and EGFR, also showed extensive impact on other immune components; meanwhile, immune effector cells shared critical gene mutations that collaboratively contribute to shaping distinct tumor immune microenvironment. Furthermore, we highlighted the predictive capacity of gene mutations that are positively associated with CD8 T cells for the clinical benefit of immunotherapy. Taken together, we present a computational framework to help illustrate the potential of somatic gene mutations in shaping the tumor immune microenvironment.

Identifying Key Somatic Copy Number Alterations Driving Dysregulation of Cancer Hallmarks in Lower-Grade Glioma.

Somatic copy-number alterations (SCNAs) are major contributors to cancer development that are pervasive and highly heterogeneous in human cancers. However, the driver roles of SCNAs in cancer are insufficiently characterized. We combined network propagation and linear regression models to design an integrative strategy to identify driver SCNAs and dissect the functional roles of SCNAs by integrating profiles of copy number and gene expression in lower-grade glioma (LGG). We applied our strategy to 511 LGG patients and identified 98 driver genes that dysregulated 29 cancer hallmark signatures, forming 143 active gene-hallmark pairs. We found that these active gene-hallmark pairs could stratify LGG patients into four subtypes with significantly different survival times. The two new subtypes with similar poorest prognoses were driven by two different gene sets (one including EGFR, CDKN2A, CDKN2B, INFA8, and INFA5, and the other including CDK4, AVIL, and DTX3), respectively. The SCNAs of the two gene sets could disorder the same cancer hallmark signature in a mutually exclusive manner (including E2F_TARGETS and G2M_CHECKPOINT). Compared with previous methods, our strategy could not only capture the known cancer genes and directly dissect the functional roles of their SCNAs in LGG, but also discover the functions of new driver genes in LGG, such as IFNA5, IFNA8, and DTX3. Additionally, our method can be applied to a variety of cancer types to explore the pathogenesis of driver SCNAs and improve the treatment and diagnosis of cancer.

Erratum: Telocinobufagin inhibits the epithelial-to-mesenchymal transition of breast cancer cells through the PI3K/Akt/Snail signaling pathway.

[This corrects the article DOI: 10.3892/ol.2018.8349.].

Isolation of evolvulic acids B and C, two new components of crude resin glycoside fraction from Evolvulus alsinoides.

Two new glycosidic acids, evolvulic acids B and C (1 and 2), along with a known one, evolvulic acid A (3), were isolated from the glycosidic acid fraction afforded by alkaline hydrolysis of crude resin glycosides from Evolvulus alsinoides whole plants. Their structures were characterized by the spectroscopic data and chemical evidences. Compounds 1 and 2 are both defined as tetrasaccharides, composed of D-fucose, D-glucose, L-rhamnose or D-galactose units. Their aglycones are identified to be a distinctive 3S,11R,14R-trihydroxyhexadecanoic acid, which is only discovered from E. alsinoides up to now. The cytotoxic and anti-migration activities of compounds 1-3 were also tested.

IDH clonal heterogeneity segregates a subgroup of non-1p/19q codeleted gliomas with unfavourable clinical outcome.

AIMS: Diffuse gliomas (DGs) are classified into three major molecular subgroups following the revised World Health Organisation (WHO) classification criteria based on their IDH mutation and 1p/19q codeletion status. However, substantial biological heterogeneity and differences in the clinical course are apparent within each subgroup, which remain to be resolved. We sought to assess the clonal status of somatic mutations and explore whether additional molecular subgroups exist within DG. METHODS: A computational framework that integrates the variant allele frequency, local copy number and tumour purity was used to infer the clonality of somatic mutations in 876 DGs from The Cancer Genome Atlas (TCGA). We performed an unsupervised cluster analysis to identify molecular subgroups and characterised their clinical and biological significance. RESULTS: DGs showed widespread genetic intratumoural heterogeneity (ITH), with nearly all driver genes harbouring subclonal mutations, even for known glioma initiating event IDH1 (17.1%). Gliomas with subclonal IDH mutation and without 1p/19q codeletion showed shorter overall and disease-specific survival, higher ITH and exhibited differences in genomic patterns, transcript levels and proliferative potential, when compared with IDH clonal mutation and no 1p/19q codeletion gliomas. We defined a refined stratification system based on the current WHO glioma molecular classification, which showed close correlations with patients' clinical outcomes. CONCLUSIONS: For the first time, we integrated the clonal status of somatic mutations into cancer genomic classification and highlighted the necessity of considering IDH clonal architectures in glioma precision stratification.