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.

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.

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.

Tuning Tumor Targeting and Ratiometric Photoacoustic Imaging by Fine-Tuning Torsion Angle for Colorectal Liver Metastasis Diagnosis.

Photoacoustic (PA) tomography is an emerging biomedical imaging technology for precision cancer medicine. Conventional small-molecule PA probes usually exhibit a single PA signal and poor tumor targeting that lack the imaging reliability. Here, we introduce a series of cyanine/hemicyanine interconversion dyes (denoted Cy-HCy) for PA/fluorescent dual-mode probe development that features optimized ratiometric PA imaging and tunable tumor-targeting ability for precise diagnosis and resection of colorectal cancer (CRC). Importantly, Cy-HCy can be presented in cyanine (inherent tumor targeting and long NIR PA wavelength) and hemicyanine (poor tumor targeting and short NIR PA wavelength) by fine-tuning torsion angle and the ingenious transformation between cyanine and hemicyanine through regulation optically tunable group endows the NIR ratiometric PA and tunable tumor-targeting properties. To demonstrate the applicability of Cy-HCy dyes, we designed the first small-molecule tumor-targeting and NIR ratiometric PA probe Cy-HCy-H2S for precise CRC liver metastasis diagnosis, activated by H2S (a CRC biomarker). Using this probe, we not only visualized the subcutaneous tumor and liver metastatic cancers in CRC mouse models but also realized PA and fluorescence image-guided tumor excision. We expect that Cy-HCy will be generalized for creating a wide variety of inherently tumor-targeting NIR ratiometric PA probes in oncological research and practice.

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.

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.

Breast cancer prognosis signature: linking risk stratification to disease subtypes.

Breast cancer is a very complex and heterogeneous disease with variable molecular mechanisms of carcinogenesis and clinical behaviors. The identification of prognostic risk factors may enable effective diagnosis and treatment of breast cancer. In particular, numerous gene-expression-based prognostic signatures were developed and some of them have already been applied into clinical trials and practice. In this study, we summarized several representative gene-expression-based signatures with significant prognostic value and separately assessed their ability of prognosis prediction in their originally targeted populations of breast cancer. Notably, many of the collected signatures were originally designed to predict the outcomes of estrogen receptor positive (ER+) patients or the whole breast cancer cohort; there are no typical signatures used for the prognostic prediction in a specific population of patients with the intrinsic subtype. We thus attempted to identify subtype-specific prognostic signatures via a computational framework for analyzing multi-omics profiles and patient survival. For both the discovery and an independent data set, we confirmed that subtype-specific signature is a strong and significant independent prognostic factor in the corresponding cohort. These results indicate that the subtype-specific prognostic signature has a much higher resolution in the risk stratification, which may lead to improved therapies and precision medicine for patients with breast cancer.

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.

CellMarker: a manually curated resource of cell markers in human and mouse.

One of the most fundamental questions in biology is what types of cells form different tissues and organs in a functionally coordinated fashion. Larger-scale single-cell sequencing and biology experiment studies are now rapidly opening up new ways to track this question by revealing substantial cell markers for distinguishing different cell types in tissues. Here, we developed the CellMarker database (http://biocc.hrbmu.edu.cn/CellMarker/ or http://bio-bigdata.hrbmu.edu.cn/CellMarker/), aiming to provide a comprehensive and accurate resource of cell markers for various cell types in tissues of human and mouse. By manually curating over 100 000 published papers, 4124 entries including the cell marker information, tissue type, cell type, cancer information and source, were recorded. At last, 13 605 cell markers of 467 cell types in 158 human tissues/sub-tissues and 9148 cell makers of 389 cell types in 81 mouse tissues/sub-tissues were collected and deposited in CellMarker. CellMarker provides a user-friendly interface for browsing, searching and downloading markers of diverse cell types of different tissues. Furthermore, a summarized marker prevalence in each cell type is graphically and intuitively presented through a vivid statistical graph. We believe that CellMarker is a comprehensive and valuable resource for cell researches in precisely identifying and characterizing cells, especially at the single-cell level.

Combination of multiple tumor-infiltrating immune cells predicts clinical outcome in colon cancer.

The infiltration of immune cells is highly associated with the development and progression of cancer. Thus, integrating the immune cell infiltrating profile into an immune cell infiltrating score may predict the survival of cancer patients. Here, by combining the infiltration proportion of 22 immune cells inferred from bulk tumor transcriptome of 879 patients, we identified an immune cell infiltrating indicator including five types of immune cells: resting T cells CD4 memory, macrophages M0-M2, and activated mast cells. The signature distinguished patients into two groups (high-risk and low-risk) with significantly different survival in the training cohort (HR = 1.96, 95% CI = 1.29-2.98, P = .0013) and two additional cohorts (HR = 1.78, 95%, CI = 1.16-2.75, P = .0079 and HR = 2.01, 95% CI = 1.28-3.14, P = .0019). The indicator remained as an independent prognostic factor after adjusting for clinicopathological factors by multivariable analysis in all cohorts. Stratification analysis showed that the signature consistently and significantly predicted survival of high-stage colon cancer patients in the training cohort (P = .00053) and validation cohorts (P = .017 and P = .0035). Moreover, we found that the low-risk patients were significantly correlated with deficient mismatch repair and the high-risk patients had a weak ability of trafficking of immune cells to tumors in the cancer immunity cycle. Overall, our results showed that integrating multiple tumor-infiltrating immune cells was an effective strategy for uncovering robust prognostic factor for tumor patients, and potentially was a promising response marker for precision oncology to be explored.

A comprehensive overview of lncRNA annotation resources.

Long noncoding RNAs (lncRNAs) are emerging as a class of important regulators participating in various biological functions and disease processes. With the widespread application of next-generation sequencing technologies, large numbers of lncRNAs have been identified, producing plenty of lncRNA annotation resources in different contexts. However, at present, we lack a comprehensive overview of these lncRNA annotation resources. In this study, we reviewed 24 currently available lncRNA annotation resources referring to > 205 000 lncRNAs in over 50 tissues and cell lines. We characterized these annotation resources from different aspects, including exon structure, expression, histone modification and function. We found many distinct properties among these annotation resources. Especially, these resources showed diverse chromatin signatures, remarkable tissue and cell type dependence and functional specificity. Our results suggested the incompleteness and complementarity of current lncRNA annotations and the necessity of integration of multiple resources to comprehensively characterize lncRNAs. Finally, we developed 'LNCat' (lncRNA atlas, freely available at http://biocc.hrbmu.edu.cn/LNCat/), a user-friendly database that provides a genome browser of lncRNA structures, visualization of different resources from multiple angles and download of different combinations of lncRNA annotations, and supports rapid exploration, comparison and integration of lncRNA annotation resources. Overall, our study provides a comprehensive comparison of numerous lncRNA annotations, and can facilitate understanding of lncRNAs in human disease.

Aberrant Epigenetic Modifications of Non-coding RNAs in Human Disease.

Non-coding RNAs, especially lncRNAs, have emerged as key components in histone modification. The alterations in the epigenetic modifications of lncRNAs underlie some human disorders ranging from neurodegeneration to cancer. To characterize the epigenetic modifications of lncRNAs, we first constructed the histone modification maps of various epigenetic markers across different cell lines. Then, we developed a method to identify epigenetically regulated lncRNAs and their response genes by integrating large scale epigenetic and transcriptional profiles. Our results showed that epigenetic alterations at the promoters of lncRNAs can influence their expression and the negative response genes of most epigenetically regulated lncRNAs were enriched for PRC2-binding genes. At last, we inferred some lncRNAs with aberrant epigenetic modifications in glioblastoma and Alzheimer's disease, and proved that theses lncRNAs may contribute to the initiation of human diseases.

Effect of a Traditional Chinese Medicine combined therapy on adolescent idiopathic scoliosis: a randomized controlled trial.

OBJECTIVE: To evaluate the effectiveness of a combined Traditional Chinese Medicine (TCM) therapy versus conventional treatment on adolescent idiopathic scoliosis. METHODS: One hundred twenty outpatients with mild and moderate adolescent idiopathic scoliosis were randomly divided into a TCM group (TCMG) and a brace group (CG). TCMG patients underwent Daoyin, Tuina, and acupotomology therapies. CG patients were treated with a Milwaukee brace. Each patient's Cobb angle was measured after 12 and 24 months of treatment, and pulmonary function was determined after 12 months of treatment. Average electromyogram (AEMG) ratio of the surface electromyogram was measured after 6 and 12 months of treatment and followed-up after 18 and 24 months. RESULTS: The Cobb angle significantly decreased in both groups after 12 months of treatment compared with before treatment (P< 0.05). The percentages of original Cobb angle in TCMG and CG were 51.4% and 47.8% (P > 0.05) after 12 months and 62.5% and 34.7% (P < 0.05) after 24 months, respectively. Pulmonary function significantly improved after 12 months in TCMG (P < 0.05) but significantly decreased in CG (P < 0.05). The AEMG ratio was significantly lower (P < 0.01) and tended to remain at 1 after stopping treatment in TCMG, but increased in CG (P < 0.05). CONCLUSION: TCM combined therapy can prevent the progression of scoliosis. The AEMG ratio is a promising index that could replace radiography in the evaluation of treatment effect and progression in scoliosis.

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.

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.

High expression levels of centromere protein O participates in cell proliferation of human ovarian cancer.

Ovarian cancer is a common malignant tumor in women, with a high mortality rate ranking first among gynecological tumors. Currently, there is insufficient understanding of the causes, pathogenesis, recurrence and metastasis of ovarian cancer, and early diagnosis and treatment still face great challenges. The sensitivity and specificity of existing ovarian cancer screening methods are still unsatisfactory. Centromere protein O (CENP-O) is a recently discovered structural centromere protein that is involved in cell death and is essential for spindle assembly, chromosome separation, and checkpoint signaling during mitosis. The abnormal high expression of CENP-O was detected in various tumors such as bladder cancer and gastric cancer, and it participates in the regulation of tumor cell proliferation. In this study, we detect the expression abundance of CENP-O mRNA in different ovarian cancer cells ( ES-2, A2780, Caov-3, OVCAR-3 and SK-OV-3). The biological function changes of cell proliferation and apoptosis were detected and the role of CENP-O in ovarian cancer cell proliferation and apoptosis was explored by knocking down the expression of CENP-O gene. The results showed that CENP-O gene was significantly expressed in 5 types of ovarian cancer cell lines. After knocking down the CENP-O gene, the proliferation and cloning ability of ovarian cancer cells decreased, and the apoptosis increased. This study indicates that CENP-O has the potential to be a molecular therapeutic target, and downregulating the expression of CENP-O gene can break the unlimited proliferation ability of cancer cells and promote their apoptosis, providing a foundation and new ideas for subsequent molecular mechanism research and targeted therapy.

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.

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.