Embryonic stem cell extracellular vesicles reverse the senescence of retinal pigment epithelial cells by the p38MAPK pathway.

Retinal pigment epithelial (RPE) cellular senescence is regarded as an initiator for age-related macular degeneration (AMD). We previously demonstrated that by the coculture way, embryonic stem cells (ESCs) can reverse the senescence of RPE cells, but xenograft cells can cause a plethora of adverse effects. Extracellular vesicles (EVs) derived from ESCs can act as messengers to mediate nearby cell activities and have the same potential as ESCs to reverse RPE senescence. Furthermore, ESC-EVs have achieved preliminary efficacy while treating many age-related diseases. The present study aimed to test the effect of ESC-EVs on the replicative senescence model of RPE cells as well as its mechanism. The results showed that ESC-EVs enhanced the proliferative ability and cell cycle transition of senescent RPE cells, whereas reduced the senescence-associated galactosidase (SA-ß-gal) staining rate, as well as the levels of mitochondrial membrane potential (MMP) and reactive oxygen species (ROS). Moreover, classical markers of cellular senescence p21WAF1/CIP1 (p21) and p16INK4a (p16) were downregulated. The bioinformatic analysis and further study showed that the inhibition of the p38MAPK pathway by ESC-EVs played a pivotal role in RPE cellular senescence-reversing effect, which was ameliorated or even abolished when dehydrocorydaline were administrated simultaneously, demonstrating that ESC-EVs can effectively reverse RPE cellular senesence by inhibiting the p38MAPK pathway, thus highlights the potential of ESC-derived EVs as biomaterials for preventative and protective therapy in AMD.

A survey on identification and quantification of alternative polyadenylation sites from RNA-seq data.

Alternative polyadenylation (APA) has been implicated to play an important role in post-transcriptional regulation by regulating mRNA abundance, stability, localization and translation, which contributes considerably to transcriptome diversity and gene expression regulation. RNA-seq has become a routine approach for transcriptome profiling, generating unprecedented data that could be used to identify and quantify APA site usage. A number of computational approaches for identifying APA sites and/or dynamic APA events from RNA-seq data have emerged in the literature, which provide valuable yet preliminary results that should be refined to yield credible guidelines for the scientific community. In this review, we provided a comprehensive overview of the status of currently available computational approaches. We also conducted objective benchmarking analysis using RNA-seq data sets from different species (human, mouse and Arabidopsis) and simulated data sets to present a systematic evaluation of 11 representative methods. Our benchmarking study showed that the overall performance of all tools investigated is moderate, reflecting that there is still lot of scope to improve the prediction of APA site or dynamic APA events from RNA-seq data. Particularly, prediction results from individual tools differ considerably, and only a limited number of predicted APA sites or genes are common among different tools. Accordingly, we attempted to give some advice on how to assess the reliability of the obtained results. We also proposed practical recommendations on the appropriate method applicable to diverse scenarios and discussed implications and future directions relevant to profiling APA from RNA-seq data.

A Type IX Secretion System Substrate Involved in Crystalline Cellulose Degradation by Affecting Crucial Cellulose Binding Proteins in Cytophaga hutchinsonii.

Cytophaga hutchinsonii is an abundant soil cellulolytic bacterium that uses a unique cellulose degradation mechanism different from those that involve free cellulases or cellulosomes. Though several proteins have been identified as important for cellulose degradation, the mechanism used by C. hutchinsonii to digest crystalline cellulose remains a mystery. In this study, chu_0922 was identified by insertional mutation and gene deletion as an important gene locus indispensable for crystalline cellulose utilization. Deletion of chu_0922 resulted in defects in crystalline cellulose utilization. The Δ0922 mutant completely lost the ability to grow on crystalline cellulose, even with extended incubation, and selectively utilized the amorphous region of cellulose, leading to increased crystallinity. As a protein secreted by the type IX secretion system (T9SS), CHU_0922 was found to be located on the outer membrane, and the outer membrane localization of CHU_0922 relied on the T9SS. Comparative analysis of the outer membrane proteins revealed that the abundance of several cellulose-binding proteins, including CHU_1276, CHU_1277, and CHU_1279, was reduced in the Δ0922 mutant. Further study showed that CHU_0922 is crucial for the full expression of the gene cluster containing chu_1276, chu_1277, chu_1278, chu_1279, and chu_1280 (cel9C), which is essential for cellulose utilization. Moreover, CHU_0922 is required for the cell surface localization of CHU_3220, a cellulose-binding protein that is essential for crystalline cellulose utilization. Our study provides insights into the complex system that C. hutchinsonii uses to degrade crystalline cellulose. IMPORTANCE The widespread aerobic cellulolytic bacterium Cytophaga hutchinsonii, belonging to the phylum Bacteroidetes, utilizes a novel mechanism to degrade crystalline cellulose. No genes encoding proteins specialized in loosening or disruption the crystalline structure of cellulose were identified in the genome of C. hutchinsonii, except for chu_3220 and chu_1557. The crystalline cellulose degradation mechanism remains enigmatic. This study identified a new gene locus, chu_0922, encoding a typical T9SS substrate that is essential for crystalline cellulose degradation. Notably, CHU_0922 is crucial for the normal transcription of chu_1276, chu_1277, chu_1278, chu_1279, and chu_1280 (cel9C), which play important roles in the degradation of cellulose. Moreover, CHU_0922 participates in the cell surface localization of CHU_3220. These results demonstrated that CHU_0922 plays a key role in the crystalline cellulose degradation network. Our study will promote the uncovering of the novel cellulose utilization mechanism of C. hutchinsonii.

Tear film cytokines as prognostic indicators for predicting early recurrent pterygium.

Cytokine profiles in tears have become a noninvasive biomarker for various ocular surface diseases. Therefore, the preoperative profile of cytokines in tear samples of 89 primary pterygium patients were obtained from Zhongshan Ophthalmic Center during 2015-2017. Compared to the tear cytokines in primary groups, the concentrations of IL-8, MMP-1, MMP-9, bFGF and VEGF were generally higher in recurrent pterygium group. The five cytokines were used to build diagnostic models by multiple machine learning algorithms, which can accurately distinguish non-recurrent and recurrent samples of primary pterygium patients. Besides, these cytokines were significantly associated with Recurrent-free survival (RFS) time in pterygium patients and further applied to develop a prognostic model which can estimate the prognosis of pterygium after resection. Afterward, a novel nomogram combined risk score of cytokines related biomarker and clinical characteristics was constructed, which manifested ideal accuracies to predict the 1 and 2 years' probability of pterygium recurrent events. Thus, our finding provides a more simple and accurate prediction for early pterygium recurrence after resection. It also affords a useful tool for ophthalmologists to choose the optimal treatment strategies for pterygium patients.

Therapeutic effects and perspective of stem cell extracellular vesicles in aging and cancer.

Senescent cells can secrete a plethora of cytokines which induce senescent phenotype of neighboring cells and was called senescence-associated secretory phenotype. Previously, it was believed that cancer was caused by the infinite division and uncontrolled proliferation of cells. Based on this, anticancer treatments were all aimed at killing cancer cells. Cancer is now considered an age-related disease. Cancer cells are not exogenous, but one of the worst results of injuries which initially induce cell senescence. Therefore, reversing cell senescence can fundamentally prevent and treat cancer. Though current anticancer treatments induce the cancer cells apoptosis, they induce senescence of normal cells at the same time, thus promoting the occurrence and development of cancer and forming a vicious circle. Extracellular vesicles (EVs) are nano-sized vesicles which partially mirror their parent cells. In the tumor microenvironment, EVs of senescent cells can change the expression profile of cancer cells, contributing to their resistance to chemotherapy. There is growing evidence indicates that stem cell EVs exert effective antiaging and anticancer actions by transferring functional microRNAs and proteins. This review will summarize the therapeutic role of stem cell EVs in reversing aging and cancer, which suggests the broad clinical application perspective.

AStrap: identification of alternative splicing from transcript sequences without a reference genome.

SUMMARY: Alternative splicing (AS) is a well-established mechanism for increasing transcriptome and proteome diversity, however, detecting AS events and distinguishing among AS types in organisms without available reference genomes remains challenging. We developed a de novo approach called AStrap for AS analysis without using a reference genome. AStrap identifies AS events by extensive pair-wise alignments of transcript sequences and predicts AS types by a machine-learning model integrating more than 500 assembled features. We evaluated AStrap using collected AS events from reference genomes of rice and human as well as single-molecule real-time sequencing data from Amborella trichopoda. Results show that AStrap can identify much more AS events with comparable or higher accuracy than the competing method. AStrap also possesses a unique feature of predicting AS types, which achieves an overall accuracy of ∼0.87 for different species. Extensive evaluation of AStrap using different parameters, sample sizes and machine-learning models on different species also demonstrates the robustness and flexibility of AStrap. AStrap could be a valuable addition to the community for the study of AS in non-model organisms with limited genetic resources. AVAILABILITY AND IMPLEMENTATION: AStrap is available for download at https://github.com/BMILAB/AStrap. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Development and validation of autophagy-related-gene biomarker and nomogram for predicting the survival of cutaneous melanoma.

Autophagy plays a critical role in cutaneous melanoma, but the prognostic research of differentially expressed autophagy-related genes (DEARGs) in melanoma is lacking. Therefore, autophagy-related gene expression data of 630 melanoma patients were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas database. The DEARGs were identified by "limma" package in R software. Best survival analysis and the least absolute shrinkage and selection operator method were performed to identify a robust 7-DEARG signature as well as construct nomogram associated with the clinical characteristics and validation in internal and external sets. This 7-DEARG signature could be regarded as an independent prognostic signature in clinical setting, and nomogram may supply a more simple and accurate prediction for the prognosis of melanoma. Moreover, 5 cancer hallmarks and 18 potential compounds are commonly enriched in high-risk expression phenotype. Thus, our finding provides new clinical evidences for the accurate diagnosis and identifies a potential prognostic autophagy-related marker for the treatment of melanoma.

Cluster analysis of replicated alternative polyadenylation data using canonical correlation analysis.

BACKGROUND: Alternative polyadenylation (APA) has emerged as a pervasive mechanism that contributes to the transcriptome complexity and dynamics of gene regulation. The current tsunami of whole genome poly(A) site data from various conditions generated by 3' end sequencing provides a valuable data source for the study of APA-related gene expression. Cluster analysis is a powerful technique for investigating the association structure among genes, however, conventional gene clustering methods are not suitable for APA-related data as they fail to consider the information of poly(A) sites (e.g., location, abundance, number, etc.) within each gene or measure the association among poly(A) sites between two genes. RESULTS: Here we proposed a computational framework, named PASCCA, for clustering genes from replicated or unreplicated poly(A) site data using canonical correlation analysis (CCA). PASCCA incorporates multiple layers of gene expression data from both the poly(A) site level and gene level and takes into account the number of replicates and the variability within each experimental group. Moreover, PASCCA characterizes poly(A) sites in various ways including the abundance and relative usage, which can exploit the advantages of 3' end deep sequencing in quantifying APA sites. Using both real and synthetic poly(A) site data sets, the cluster analysis demonstrates that PASCCA outperforms other widely-used distance measures under five performance metrics including connectivity, the Dunn index, average distance, average distance between means, and the biological homogeneity index. We also used PASCCA to infer APA-specific gene modules from recently published poly(A) site data of rice and discovered some distinct functional gene modules. We have made PASCCA an easy-to-use R package for APA-related gene expression analyses, including the characterization of poly(A) sites, quantification of association between genes, and clustering of genes. CONCLUSIONS: By providing a better treatment of the noise inherent in repeated measurements and taking into account multiple layers of poly(A) site data, PASCCA could be a general tool for clustering and analyzing APA-specific gene expression data. PASCCA could be used to elucidate the dynamic interplay of genes and their APA sites among various biological conditions from emerging 3' end sequencing data to address the complex biological phenomenon.

scNPF: an integrative framework assisted by network propagation and network fusion for preprocessing of single-cell RNA-seq data.

BACKGROUND: Single-cell RNA-sequencing (scRNA-seq) is fast becoming a powerful tool for profiling genome-scale transcriptomes of individual cells and capturing transcriptome-wide cell-to-cell variability. However, scRNA-seq technologies suffer from high levels of technical noise and variability, hindering reliable quantification of lowly and moderately expressed genes. Since most downstream analyses on scRNA-seq, such as cell type clustering and differential expression analysis, rely on the gene-cell expression matrix, preprocessing of scRNA-seq data is a critical preliminary step in the analysis of scRNA-seq data. RESULTS: We presented scNPF, an integrative scRNA-seq preprocessing framework assisted by network propagation and network fusion, for recovering gene expression loss, correcting gene expression measurements, and learning similarities between cells. scNPF leverages the context-specific topology inherent in the given data and the priori knowledge derived from publicly available molecular gene-gene interaction networks to augment gene-gene relationships in a data driven manner. We have demonstrated the great potential of scNPF in scRNA-seq preprocessing for accurately recovering gene expression values and learning cell similarity networks. Comprehensive evaluation of scNPF across a wide spectrum of scRNA-seq data sets showed that scNPF achieved comparable or higher performance than the competing approaches according to various metrics of internal validation and clustering accuracy. We have made scNPF an easy-to-use R package, which can be used as a versatile preprocessing plug-in for most existing scRNA-seq analysis pipelines or tools. CONCLUSIONS: scNPF is a universal tool for preprocessing of scRNA-seq data, which jointly incorporates the global topology of priori interaction networks and the context-specific information encapsulated in the scRNA-seq data to capture both shared and complementary knowledge from diverse data sources. scNPF could be used to recover gene signatures and learn cell-to-cell similarities from emerging scRNA-seq data to facilitate downstream analyses such as dimension reduction, cell type clustering, and visualization.

TSAPA: identification of tissue-specific alternative polyadenylation sites in plants.

Summary: Alternative polyadenylation (APA) is now emerging as a widespread mechanism modulated tissue-specifically, which highlights the need to define tissue-specific poly(A) sites for profiling APA dynamics across tissues. We have developed an R package called TSAPA based on the machine learning model for identifying tissue-specific poly(A) sites in plants. A feature space including more than 200 features was assembled to specifically characterize poly(A) sites in plants. The classification model in TSAPA can be customized by selecting desirable features or classifiers. TSAPA is also capable of predicting tissue-specific poly(A) sites in unannotated intergenic regions. TSAPA will be a valuable addition to the community for studying dynamics of APA in plants. Availability and implementation: https://github.com/BMILAB/TSAPA. Supplementary information: Supplementary data are available at Bioinformatics online.

Benchmarking Algorithms for Gene Set Scoring of Single-cell ATAC-seq Data.

Gene set scoring (GSS) has been routinely conducted for gene expression analysis of bulk or single-cell RNA sequencing (RNA-seq) data, which helps to decipher single-cell heterogeneity and cell type-specific variability by incorporating prior knowledge from functional gene sets. Single-cell assay for transposase accessible chromatin using sequencing (scATAC-seq) is a powerful technique for interrogating single-cell chromatin-based gene regulation, and genes or gene sets with dynamic regulatory potentials can be regarded as cell type-specific markers as if in single-cell RNA-seq (scRNA-seq). However, there are few GSS tools specifically designed for scATAC-seq, and the applicability and performance of RNA-seq GSS tools on scATAC-seq data remain to be investigated. Here, we systematically benchmarked ten GSS tools, including four bulk RNA-seq tools, five scRNA-seq tools, and one scATAC-seq method. First, using matched scATAC-seq and scRNA-seq datasets, we found that the performance of GSS tools on scATAC-seq data was comparable to that on scRNA-seq, suggesting their applicability to scATAC-seq. Then, the performance of different GSS tools was extensively evaluated using up to ten scATAC-seq datasets. Moreover, we evaluated the impact of gene activity conversion, dropout imputation, and gene set collections on the results of GSS. Results show that dropout imputation can significantly promote the performance of almost all GSS tools, while the impact of gene activity conversion methods or gene set collections on GSS performance is more dependent on GSS tools or datasets. Finally, we provided practical guidelines for choosing appropriate preprocessing methods and GSS tools in different application scenarios.

Sulphate-reducing bacteria-mediated pyrite formation in the Dachang Tongkeng tin polymetallic deposit, Guangxi, China.

Mediation by sulphate-reducing bacteria (SRB) is responsible for pyrite (FeS2) formation. The origin of the Dachang tin polymetallic ore field is related to the mineralisation of submarine hydrothermal vent sediments. Here, we investigated SRB in these ores via morphological, chemical, and isotopic analyses. Polarised and scanning electron microscopy indicated that trace SRB fossils in the metal sulphide ore were present in the form of tubular, beaded, and coccoidal bodies comprising FeS2 and were enclosed within a pyrrhotite (FeS) matrix in the vicinity of micro-hydrothermal vents. The carbon (C), nitrogen (N), and oxygen (O) contents in the FeS2 synthesised by SRB were high, and a clear biological Raman signal was detected. No such signals were discerned in the peripheral FeS. This co-occurrence of FeS, FeS2, and the remains of bacteria (probably chemoautotrophic bacteria) was interpreted as the coprecipitation process of SRB-mediated FeS2 formation, which has, to the best of our knowledge, not been reported before. Our study also illustrates that combined energy-dispersive X-ray spectroscopy, Raman spectroscopy, and isotopic analysis can be used as a novel methodology to document microbial-mediated processes of mineral deposition in submarine hydrothermal vent ecology on geological time scales.

PINK1/Parkin-mediated mitophagy inhibits osteoblast apoptosis induced by advanced oxidation protein products.

Osteoblast apoptosis plays an important role in age-related bone loss and osteoporosis. Our previous study revealed that advanced oxidation protein products (AOPPs) could induce nicotinamide adenine dinucleotide phosphate oxidase (NOX)-derived reactive oxygen species (ROS) production, cause mitochondrial membrane potential (ΔΨm) depolarization, trigger the mitochondria-dependent intrinsic apoptosis pathway, and lead to osteoblast apoptosis and ultimately osteopenia and bone microstructural destruction. In this study, we found that AOPPs also induced mitochondrial ROS (mtROS) generation in osteoblastic MC3T3-E1 cells, which was closely related to NOX-derived ROS, and aggravated the oxidative stress condition, thereby further promoting apoptosis. Removing excessive ROS and damaged mitochondria is the key factor in reversing AOPP-induced apoptosis. Here, by in vitro studies, we showed that rapamycin further activated PINK1/Parkin-mediated mitophagy in AOPP-stimulated MC3T3-E1 cells and significantly alleviated AOPP-induced cell apoptosis by eliminating ROS and damaged mitochondria. Our in vivo studies revealed that PINK1/Parkin-mediated mitophagy could decrease the plasma AOPP concentration and inhibit AOPP-induced osteoblast apoptosis, thus ameliorating AOPP accumulation-related bone loss, bone microstructural destruction and bone mineral density (BMD) loss. Together, our study indicated that therapeutic strategies aimed at upregulating osteoblast mitophagy and preserving mitochondrial function might have potential for treating age-related osteoporosis.

Common Genes Involved in Autophagy, Cellular Senescence and the Inflammatory Response in AMD and Drug Discovery Identified via Biomedical Databases.

Purpose: Retinal pigment epithelial cell autophagy dysfunction, cellular senescence, and the retinal inflammatory response are key pathogenic factors in age-related macular degeneration (AMD), which has been reviewed in our previously work in 2019. This study aims to identify genes collectively involved in these three biological processes and target drugs in AMD. Methods: The pubmed2ensembl database was used to perform text mining. The GeneCodis database was applied to analyze gene ontology biological process and the KEGG pathway. The STRING database was used to analyze protein-protein interaction analysis and hub genes were identified by the Cytoscape software. The Drug Gene Interaction Database was used to perform drug-gene interactions. Results: We identified 62 genes collectively involved in AMD, autophagy, cellular senescence, and inflammatory response, 19 biological processes including 42 genes, 11 enriched KEGG pathways including 37 genes, and 12 hub genes step by step via the above biomedical databases. Finally, five hub genes (IL-6, VEGF-A, TP53, IL-1ß, and transforming growth factor [TGF]-ß1) and their specific interaction modes were identified, corresponding with 24 target drugs with therapeutic potential for AMD. Conclusions: IL-6, VEGF-A, TP53, IL-1ß, and TGF-ß1 are pivotal in autophagy, cellular senescence, and the inflammatory response in AMD, corresponding with 24 drugs with therapeutic potential for AMD, providing definite molecular mechanisms for further research and new possibilities for AMD treatment in the future. Translational Relevance: IL-6, VEGF-A, TP53, IL-1ß, and TGF-ß1 may be new targets for AMD gene therapy and drug development.

Tumor Microenvironmental Competitive Endogenous RNA Network and Immune Cells Act as Robust Prognostic Predictor of Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is malignant hematologic tumors with frequent recurrence and cause high mortality. Its fate is determined by abnormal intracellular competitive endogenous RNA (ceRNA) network and extracellular tumor microenvironment (TME). This study aims to build a ceRNA network related to AML TME to explore new prognostic and therapeutic targets. The RNA expression data of AML were obtained from The Cancer Genome Atlas (TCGA) database. First, we used the ESTIMATE algorithm to calculate the immune cells and stromal cells infiltration scores in the TME and found that all scores were highly correlated with AML's prognostic characteristics. Subsequently, differentially expressed mRNAs and lncRNAs between high and low score groups were identified to construct a TME-related ceRNA network. Further, the Cox-lasso survival model was employed to screen out the hub prognostic ceRNA network composed of two mRNAs (EPB41L3, COL2A1), three miRNAs (hsa-mir-26a-5p, hsa-mir-148b-3p, hsa-mir-148a-3p), and two lncRNAs (CYP1B1-AS1, C9orf106), and construct nomograms. Finally, we used CIBERSORT algorithm and Kaplan-Meier survival analysis to identify the prognostic TME immune cells and found that naive B cells, M2-type macrophages, and helper follicular T cells were related to prognosis, and the hub ceRNAs were highly correlated with immune cell infiltration. This study provided a new perspective to elucidate how TME regulates AML process and put forward the new therapy strategies combining targeting tumor cells with disintegrating TME.

Intrastriatal transplantation of GDNF-engineered BMSCs and its neuroprotection in lactacystin-induced Parkinsonian rat model.

The potential value of glial cell line-derived neurotrophic factor (GDNF) in treating Parkinson's disease (PD) remains controversial. In order to evaluate the therapeutic effect of GDNF-engineered bone marrow stromal cells (BMSCs) in parkinsonian rat model, GDNF-BMSCs and LacZ-BMSCs were transplanted into striatum and followed by Lactacystin lesioning at median forebrain bundles 1 week later. We observed that the intrastriatal transplantation of GDNF-BMSCs could significantly rescue the dopaminergic neurons from lactacystin-induced neurotoxicity with regard to behavioral recovery, tyrosine hydroxylase level in nigra and striatum, and striatal dopamine level. We interpret the outcomes that intrastriatal transplantation of GDNF-BMSCs might be beneficial in the treatment of PD.

Endogenous Toll-like Receptor 2 Modulates Th1/Treg-Promoting Dendritic Cells in Mice Corneal Transplantation Model.

PURPOSE: Endogenous toll-like receptor (TLR) 2 is linked to allograft rejection in corneal transplantation. TLR2 also could modulate dendritic cell (DC) phenotype, resulting in T cell polarization. Thus, we investigated the role of endogenous TLR2 on DC development and T cell polarization during corneal rejection. MATERIALS AND METHODS: Corneas of BALB/c mice were transplanted into the eyes of C57BL/6 wild-type (WT) recipients and TLR2-/- (KO) recipients. Graft survival and TLR2 mRNA expression were assessed. At day 14 after transplantation, to study endogenous TLR2 effects on DC development and function, surface expression of MHC classⅡ (MHCⅡ), CD86, CD80 and CD40 in ipsilateral cervical draining lymph nodes (DLNs) is measured by flow cytometry, and DC phenotype in corneas is detected by immunofluorescence. The levels of IL-12, IL-10 and IL-4 in corneas were measured by real time-qPCR (RT-qPCR). The ability of DCs to stimulate T cell polarization was assessed by IFN-γ expressions via RT-qPCR and immunohistochemistry. RESULTS: TLR2 mRNA expression in corneas was peaked at day 14 post-transplantation in WT group. KO group improved corneal allograft survival compared to the WT group. In addition, the KO group decreased expression of CD86, CD80 and CD40 on DCs compared to the WT group. There was no difference in MHCⅡ expression in two groups. The CD11c+MHCⅡ+CD40high DCs could not be detected in corneas of the KO group. Moreover, the KO group decreased IL-12 (Th1-promoting cytokines) mRNA expression and increasing IL-10 (Treg-promoting cytokines) mRNA expression compared to the WT group. IL-4 (Th2-promoting cytokines) mRNA expression gained no difference between the two groups. The IFN-γ (Th1 cytokines) expression was significantly decreased in the KO group compared to the WT group. CONCLUSIONS: Endogenous TLR2 may contribute to allogeneic corneal rejection via Th1 immunity by activating Th1-promoting DCs and suppressing Treg-promoting DCs.

Six-gene-based prognostic model predicts overall survival in patients with uveal melanoma.

BACKGROUND: Uveal melanoma (UM) is the most common primary intraocular tumor in adults, which has a high mortality rate and worse prognosis. Therefore, early potential molecular detection and prognostic evaluation seem more important for early diagnosis and treatment. METHODS: Gene expression data were obtained from The Cancer Genome Atlas-Uveal melanomas database. Survival genes were identified by univariate analysis and were regarded to be associated with the overall survival of UM patients. Then, pathway enrichment analysis of these survival genes was performed. Robust likelihood-based survival model and multivariate survival analysis were conducted to identify more reliable genes and the prognostic signature for UM survival prediction. Two internal datasets and another two UM datasets from Gene Expression Omnibus (GEO) were used for the validation of prognostic signature. RESULTS: Firstly, 2,010 survival genes were screened by univariate survival analysis. GO and KEGG analysis revealed that these genes were mainly involved in pathways such as mRNA processing, RNA splicing, spliceosome and ubiquitin mediated proteolysis. Secondly, a six-gene signature was identified by Robust likelihood-based survival model approach. The gene expression of the six genes can successfully divide UM samples into high- and low-risk groups and have strong survival prediction ability. What's more, the expression of six genes was compared in 80 healthy adipose tissue samples obtained from GTEx (Genotype-Tissue Expression) database and further validated in internal datasets and GEO datasets, which also can predict UM patient survival. CONCLUSIONS: The six genes (SH2D3A, TMEM201, LZTS1, CREG1, NIPA1 and HIST1H4E) model might play a vital role in prognosis of UM, which should be helpful for further insight into the treatment of uveal melanoma.

Identification of circRNA-lncRNA-miRNA-mRNA Competitive Endogenous RNA Network as Novel Prognostic Markers for Acute Myeloid Leukemia.

BACKGROUND: Acute myeloid leukemia (AML) is one of the most common malignant and aggressive hematologic tumors, and its pathogenesis is associated with abnormal post-transcriptional regulation. Unbalanced competitive endogenous RNA (ceRNA) promotes tumorigenesis and progression, and greatly contributes to tumor risk classification and prognosis. However, the comprehensive analysis of the circular RNA (circRNA)-long non-coding RNA (lncRNA)-miRNA-mRNA ceRNA network in the prognosis of AML is still rarely reported. METHOD: We obtained transcriptome data of AML and normal samples from The Cancer Genome Atlas (TCGA), Genotype-tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases, and identified differentially expressed (DE) mRNAs, lncRNAs, and circRNAs. Then, the targeting relationships among lncRNA-miRNA, circRNA-miRNA, and miRNA-mRNA were predicted, and the survival related hub mRNAs were further screened by univariate and multivariate Cox proportional hazard regression. Finally, the AML prognostic circRNA-lncRNA-miRNA-mRNA ceRNA regulatory network was established. RESULTS: We identified prognostic 6 hub mRNAs (TM6SF1, ZMAT1, MANSC1, PYCARD, SLC38A1, and LRRC4) through Cox regression model, and divided the AML samples into high and low risk groups according to the risk score obtained by multivariate Cox regression. Survival analysis verified that the survival rate of the high-risk group was significantly reduced (p < 0.0001). The prognostic ceRNA network of 6 circRNAs, 32 lncRNAs, 8 miRNAs, and 6 mRNAs was established according to the targeting relationship between 6 hub mRNAs and other RNAs. CONCLUSION: In this study, ceRNA network jointly participated by circRNAs and lncRNAs was established for the first time. It comprehensively elucidated the post-transcriptional regulatory mechanism of AML, and identified novel AML prognostic biomarkers, which has important guiding significance for the clinical diagnosis, treatment, and further scientific research of AML.

Reversed Senescence of Retinal Pigment Epithelial Cell by Coculture With Embryonic Stem Cell via the TGFß and PI3K Pathways.

Retinal pigment epithelium (RPE) cellular senescence is an important etiology of age-related macular degeneration (AMD). Aging interventions based on the application of stem cells to delay cellular senescence have shown good prospects in the treatment of age-related diseases. This study aimed to investigate the potential of the embryonic stem cells (ESCs) to reverse the senescence of RPE cells and to elucidate its regulatory mechanism. The hydrogen peroxide (H2O2)-mediated premature and natural passage-mediated replicative senescent RPE cells were directly cocultured with ESCs. The results showed that the proliferative capacity of premature and replicative senescent RPE cells was increased, while the positive rate of senescence-associated galactosidase (SA-ß-GAL) staining and levels of reactive oxygen species (ROS) and mitochondrial membrane potential (MMP) were decreased. The positive regulatory factors of cellular senescence (p53, p21WAF1/CIP1, p16INK4a) were downregulated, while the negative regulatory factors of cellular senescence (Cyclin A2, Cyclin B1, Cyclin D1) were upregulated. Furthermore, replicative senescent RPE cells entered the S and G2/M phases from the G0/G1 phase. TGFß (TGFB1, SMAD3, ID1, ID3) and PI3K (PIK3CG, PDK1, PLK1) pathway-related genes were upregulated in premature and replicative senescent RPE cells after ESCs application, respectively. We further treated ESCs-cocultured premature and replicative senescent RPE cells with SB531542 and LY294002 to inhibit the TGFß and PI3K pathways, respectively, and found that p53, p21WAF1/CIP1 and p16INK4a were upregulated, while Cyclin A2, Cyclin B1, Cyclin D1, TGFß, and PI3K pathway-related genes were downregulated, accompanied by decreased proliferation and cell cycle transition and increased positive rates of SA-ß-GAL staining and levels of ROS and MMP. In conclusion, we demonstrated that ESCs can effectively reverse the senescence of premature and replicative senescent RPE cells by a direct coculture way, which may be achieved by upregulating the TGFß and PI3K pathways, respectively, providing a basis for establishing a new therapeutic option for AMD.