Glycomacropeptide: A comprehensive understanding of its major biological characteristics and purification methodologies.

Glycomacropeptide (GMP) is a bioactive peptide derived from whey protein, consisting of 64 amino acids. It is a phenylalanine-free peptide, making it a beneficial dietary option for individuals dealing with phenylketonuria (PKU). PKU is an inherited metabolic disorder characterized by high levels of phenylalanine in the bloodstream, resulting from a deficiency of phenylalanine dehydrogenase in affected individuals. Consequently, patients with PKU require lifelong adherence to a low-phenylalanine diet, wherein a significant portion of their protein intake is typically sourced from a phenylalanine-free amino acid formula. GMP has several nutritional values, numerous bioactivity properties, and therapeutic effects in various inflammatory disorders. Despite all these features, the purification of GMP is an imperative requirement; however, there are no unique methods for achieving this goal. Traditionally, several methods have been used for GMP purification, such as thermal or acid treatment, alcoholic precipitation, ultrafiltration (UF), gel filtration, and membrane separation techniques. However, these methods have poor specificity, and the presence of large amounts of impurities can interfere with the analysis of GMP. More efficient and highly specific GMP purification methods need to be developed. In this review, we have highlighted and summarized the current research progress on the major biological features and purification methodologies associated with GMP, as well as providing an extensive overview of the recent developments in using charged UF membranes for GMP purification and the influential factors.

Dual Heterogeneous Structures Promote Electrochemical Properties and Photocatalytic Hydrogen Evolution for Inverse Opal ZnO/ZnS/Co3O4 Crystals.

Potocatalytic hydrogen evolution represnets a promising way to achieve renewable energy sources. Dual heterojunctions with an inverse opal structure are proposed for addressing fundamental challenges (low surface area, inefficient light absorption, and poor charge separation) in photocatalytic water splitting. Inverse opal structure and Co3O4 were introduced to design and synthesize a ZnO/ZnS/Co3O4 (IO-ZnO/ZnS/Co3O4) photocatalyst. Morphology characterizations and photoelectric measurements reveal that the introduction of three-dimensional (3D) structures and dual heterojunctions improves light utilization efficiency and accelerates charge separation, greatly promoting photoelectric performance. The as-prepared IO-ZnO/ZnS/Co3O4 manifests superior photocurrent density (0.49 mA/cm2), which is 4 times higher than that of IO-ZnO/ZnS due to the existence of dual heterojunctions. The result is further confirmed by an enhanced H2 production rate (153.01 µmol/g/h) in pure water. Notably, excellent cycling stability is achieved in pure water because Co3O4 can rapidly capture photogenerated holes to inhibit severe photocorrosion of ZnO/ZnS. Therefore, this work presents a new insight into inhibiting photocorrosion of metal sulfides and promoting their photoelectric performance by combining 3D structures and dual heterojunctions.

Metabolic Comparison and Molecular Networking of Antimicrobials in Streptomyces Species.

Streptomyces are well-known for producing bioactive secondary metabolites, with numerous antimicrobials essential to fight against infectious diseases. Globally, multidrug-resistant (MDR) microorganisms significantly challenge human and veterinary diseases. To tackle this issue, there is an urgent need for alternative antimicrobials. In the search for potent agents, we have isolated four Streptomyces species PC1, BT1, BT2, and BT3 from soils collected from various geographical regions of the Himalayan country Nepal, which were then identified based on morphology and 16S rRNA gene sequencing. The relationship of soil microbes with different Streptomyces species has been shown in phylogenetic trees. Antimicrobial potency of isolates was carried out against Staphylococcus aureus American Type Culture Collection (ATCC) 43300, Shigella sonnei ATCC 25931, Salmonella typhi ATCC 14028, Klebsiella pneumoniae ATCC 700603, and Escherichia coli ATCC 25922. Among them, Streptomyces species PC1 showed the highest zone of inhibition against tested pathogens. Furthermore, ethyl acetate extracts of shake flask fermentation of these Streptomyces strains were subjected to liquid chromatography-tandem mass spectrometric (LC-MS/MS) analysis for their metabolic comparison and Global Natural Products Social Molecular Networking (GNPS) web-based molecular networking. We found very similar metabolite composition in four strains, despite their geographical variation. In addition, we have identified thirty-seven metabolites using LC-MS/MS analysis, with the majority belonging to the diketopiperazine class. Among these, to the best of our knowledge, four metabolites, namely cyclo-(Ile-Ser), 2-n-hexyl-5-n-propylresorcinol, 3-[(6-methylpyrazin-2-yl) methyl]-1H-indole, and cyclo-(d-Leu-l-Trp), were detected for the first time in Streptomyces species. Besides these, other 23 metabolites including surfactin B, surfactin C, surfactin D, and valinomycin were identified with the help of GNPS-based molecular networking.

Global Natural Products Social (GNPS)-Based Molecular-Networking-Guided Isolation of Phenolic Compounds from Ginkgo biloba Fruits and the Identification of Estrogenic Phenolic Glycosides.

Ginkgo biloba L. stands as one of the oldest living tree species, exhibiting a diverse range of biological activities, including antioxidant, neuroprotective, anti-inflammatory, and cardiovascular activities. As part of our ongoing discovery of novel bioactive components from natural sources, we directed our focus toward the investigation of potential bioactive compounds from G. biloba fruit. The profiles of its chemical compounds were examined using a Global Natural Products Social (GNPS)-based molecular networking analysis. Guided by this, we successfully isolated and characterized 11 compounds from G. biloba fruit, including (E)-coniferin (1), syringin (2), 4-hydroxybenzoic acid 4-O-ß-D-glucopyranoside (3), vanillic acid 4-O-ß-D-glucopyranoside (4), syringic acid 4-O-ß-D-glucopyranoside (5), (E)-ferulic acid 4-O-ß-D-glucoside (6), (E)-sinapic acid 4-O-ß-D-glucopyranoside (7), (1'R,2'S,5'R,8'S,2'Z,4'E)-dihydrophaseic acid 3'-O-ß-D-glucopyranoside (8), eucomic acid (9), rutin (10), and laricitrin 3-rutinoside (11). The structural identification was validated through a comprehensive analysis involving nuclear magnetic resonance (NMR) spectroscopic data and LC/MS analyses. All isolated compounds were evaluated using an E-screen assay for their estrogen-like effects in MCF-7 cells. As a result, compounds 2, 3, 4, 8, and 9 promoted cell proliferation in MCF-7 cells, and these effects were mitigated by the ER antagonist, ICI 182,780. In particular, cell proliferation increased most significantly to 140.9 ± 6.5% after treatment with 100 µM of compound 2. The mechanism underlying the estrogen-like effect of syringin (2) was evaluated using a Western blot analysis to determine the expression of estrogen receptor α (ERα). We found that syringin (2) induced an increase in the phosphorylation of ERα. Overall, these experimental results suggest that syringin (2) can potentially aid the control of estrogenic activity during menopause.

Metabolomics and molecular networking approach for exploring the anti-diabetic activity of medicinal plants.

Metabolomics and molecular networking approaches have expanded rapidly in the field of biological sciences and involve the systematic identification, visualization, and high-throughput characterization of bioactive metabolites in natural products using sophisticated mass spectrometry-based techniques. The popularity of natural products in pharmaceutical therapies has been influenced by medicinal plants with a long history of ethnobotany and a vast collection of bioactive compounds. Here, we selected four medicinal plants Cleistocalyx operculatus, Terminalia chebula, Ficus lacor, and Ficus semicordata, the biochemical characteristics of which remain unclear owing to the inherent complexity of their plant metabolites. In this study, we aimed to evaluate the potential of these aforementioned plant extracts in inhibiting the enzymatic activity of α-amylase and α-glucosidase, respectively, followed by the annotation of secondary metabolites. The methanol extract of Ficus semicordata exhibited the highest α-amylase inhibition with an IC50 of 46.8 ± 1.8 µg mL-1, whereas the water fraction of Terminalia chebula fruits demonstrated the most significant α-glucosidase inhibition with an IC50 value of 1.07 ± 0.01 µg mL-1. The metabolic profiling of plant extracts was analyzed through Liquid Chromatography-Mass Spectrometry (LC-HRMS) of the active fractions, resulting in the annotation of 32 secondary metabolites. Furthermore, we applied the Global Natural Product Social Molecular Networking (GNPS) platform to evaluate the MS/MS data of Terminalia chebula (bark), revealing that there were 205 and 160 individual ion species observed as nodes in the methanol and ethyl acetate fractions, respectively. Twenty-two metabolites were tentatively identified from the network map, of which 11 compounds were unidentified during manual annotation.

Au-Catalyzed Asymmetric Polyene Cyclization and Its Application in the Total Synthesis of (+)-2-Ketoferruginol, (+)-Fleuryinol B, (+)-Salviol, and (-)-Erythroxylisin A.

A catalytic asymmetric 1,3-acyloxy shift/polyene cyclization cascade has been achieved with good enantioselectivities under the catalysis of the chiral Au(I) reagent. The synthetic utility of this method has been showcased by the catalytic asymmetric total syntheses of (+)-2-ketoferruginol, (+)-fleuryinol B, and (+)-salviol. Notably, the first enantioselective total synthesis of (-)-erythroxylisin A has also been realized in 15 steps.

Laricitrin 3-Rutinoside from Ginkgo biloba Fruits Prevents Damage in TNF-α-Stimulated Normal Human Dermal Fibroblasts.

Human skin comprises the epidermis and dermis, which perform interactive functional activities with each other in order to maintain the skin's tensile strength. In particular, the dermal layer is crucial for skin protection. However, skin aging destroys collagen and elastin fibers, causing wrinkles, pigments, and sagging. Skin aging-related factors, such as tumor necrosis factor-α (TNF-α), promote the generation of intercellular reactive oxygen species (ROS). These are known to stimulate the hypersecretion of matrix metalloproteinase-1 (MMP-1), which degrades collagen and inhibits collagen synthesis. In this study, as part of our ongoing discovery of natural products, we investigated potential natural products derived from ginkgo fruit (Ginkgo biloba fruit) with protective effects against TNF-α-induced skin aging. Phytochemical investigation of the MeOH extract of G. biloba fruits, aided by liquid chromatography-mass spectrometry, led to the isolation of 14 compounds (1-14) from the n-butanol-soluble fraction. These were structurally determined to be: (E)-coniferin (1), syringin (2), 4-hydroxybenzoic acid 4-O-ß-D-glucopyranoside (3), vanillic acid 4-O-ß-D-glucopyranoside (4), glucosyringic acid (5), (E)-ferulic acid 4-O-ß-D-glucoside (6), (E)-sinapic acid 4-O-ß-D-glucopyranoside (7), ginkgotoxin-5-glucoside (8), ginkgopanoside (9), (Z)-4-coumaric acid 4-O-ß-D-glucopyranoside (10), (1'R,2'S,5'R,8'S,2'Z,4'E)-dihydrophaseic acid 3'-O-ß-D-glucopyranoside (11), eucomic acid (12), rutin (13), and laricitrin 3-rutinoside (L3R) (14). Biological evaluation of the isolated compounds for their effects on intracellular ROS generation showed that, of these 14 compounds, L3R (14) inhibited TNF-α-stimulated ROS generation (p < 0.001 at 100 µM). Inhibition of ROS generation by L3R led to the suppression of MMP-1 secretion and protection against collagen degradation. The inhibitory effect of L3R was mediated by the inhibition of extracellular signal regulated kinase (ERK) phosphorylation. Furthermore, L3R diminished the secretion of pro-inflammatory cytokines interleukin 6 (IL-6) and interleukin 8 (IL-8). Based on these experimental results, L3R is a potential bioactive natural product that can be used to protect against skin damage, including aging, in cosmetics and pharmaceuticals.

Methoxyflavones from Black Ginger (Kaempferia parviflora Wall. ex Baker) and their Inhibitory Effect on Melanogenesis in B16F10 Mouse Melanoma Cells.

Kaempferia parviflora Wall. ex Baker (Zingiberaceae), commonly known as Thai ginseng or black ginger, is a tropical medicinal plant in many regions. It has been traditionally used to treat various ailments, including ulcers, dysentery, gout, allergies, abscesses, and osteoarthritis. As part of our ongoing phytochemical study aimed at discovering bioactive natural products, we investigated potential bioactive methoxyflavones from K. parviflora rhizomes. Phytochemical analysis aided by liquid chromatography-mass spectrometry (LC-MS) led to the isolation of six methoxyflavones (1-6) from the n-hexane fraction of the methanolic extract of K. parviflora rhizomes. The isolated compounds were structurally determined to be 3,7-dimethoxy-5-hydroxyflavone (1), 5-hydroxy-7-methoxyflavone (2), 7,4'-dimethylapigenin (3), 3,5,7-trimethoxyflavone (4), 3,7,4'-trimethylkaempferol (5), and 5-hydroxy-3,7,3',4'-tetramethoxyflavone (6), based on NMR data and LC-MS analysis. All of the isolated compounds were evaluated for their anti-melanogenic activities. In the activity assay, 7,4'-dimethylapigenin (3) and 3,5,7-trimethoxyflavone (4) significantly inhibited tyrosinase activity and melanin content in IBMX-stimulated B16F10 cells. In addition, structure-activity relationship analysis revealed that the methoxy group at C-5 in methoxyflavones is key to their anti-melanogenic activity. This study experimentally demonstrated that K. parviflora rhizomes are rich in methoxyflavones and can be a valuable natural resource for anti-melanogenic compounds.

InI3-catalyzed polyene cyclization of allenes and its application in the total synthesis of seven abietane-type diterpenoids.

A novel polyene cyclization using the allene group as the initiator has been successfully developed. This methodology provides an efficient strategy for the construction of an abietane-type tricyclic skeleton with a functionalizable C2-C3 double bond and features a wide substrate scope and excellent stereoselectivities. Potential utility of this approach has been well demonstrated by the collective total synthesis of seven abietane-type diterpenoids. Specifically, (±)-2,3-dihydroxyferruginol and (±)-2,3-dihydroxy-15,16-dinor-ent-pimar-8,11,13-triene were synthesized for the first time.

Microbial Transformation of Yakuchinone A and Cytotoxicity Evaluation of Its Metabolites.

Yakuchinone A (1) is a bioactive diarylheptanoid isolated from the dried fruits of Alpinia oxyphylla. Microbial transformation has been recognized as an efficient method to produce new biologically active derivatives from natural products. In the present study, microbial transformation of yakuchinone A was performed with the fungus Mucor hiemalis KCTC 26779, which led to the isolation of nine new metabolites (2, 3a, 3b, and 4-9). Their structures were elucidated as (3S)-oxyphyllacinol (2), (3S,7R)- and (3S,7S)-7-hydroxyoxyphyllacinol (3a and 3b), (3S)-oxyphyllacinol-4'-O-ß-d-glucopyranoside (4), (3S)-4″-hydroxyoxyphyllacinol (5), (3S)-3″-hydroxyoxyphyllacinol (6), (3S)-2″-hydroxyoxyphyllacinol (7), (3S)-2″-hydroxyoxyphyllacinol-2″-O-ß-d-glucopyranoside (8), and (3S)-oxyphyllacinol-3-O-ß-d-glucopyranoside (9) based on the comprehensive spectroscopic analyses and the application of modified Mosher's method. All compounds were evaluated for their cytotoxic activities against melanoma, as well as breast, lung, and colorectal cancer cell lines. Compound 9, which was O-glucosylated on the diarylheptanoid alkyl chain, exhibited the most selective cytotoxic activities against melanoma cell lines with the IC50 values ranging from 6.09 to 9.74 µM, indicating that it might be considered as a possible anti-cancer lead compound.

Prognostic Value of Genomic Instability of m6A-Related lncRNAs in Lung Adenocarcinoma.

Background: Genomic instability of N6-methyladenosine (m6A)-related long noncoding RNAs (lncRNAs) plays a pivotal role in the tumorigenesis of lung adenocarcinoma (LUAD). Our study identified a signature of genomic instability of m6A-associated lncRNA signature and revealed its prognostic role in LUAD. Methods: We downloaded RNA-sequencing data and somatic mutation data for LUAD from The Cancer Genome Atlas (TCGA) and the GSE102287 dataset from the Gene Expression Omnibus (GEO) database. The "Limma" R package was used to identify a network of regulatory m6A-related lncRNAs. We used the Wilcoxon test method to identify genomic-instability-derived m6A-related lncRNAs. A competing endogenous RNA (ceRNA) network was constructed to identify the mechanism of the genomic instability of m6A-related lncRNAs. Univariate and multivariate Cox regression analyses were performed to construct a prognostic model for internal testing and validation of the prognostic m6A-related lncRNAs using the GEO dataset. Performance analysis was conducted to compare our prognostic model with the previously published lncRNA models. The CIBERSORT algorithm was used to explore the relationship of m6A-related lncRNAs and the immune microenvironment. Prognostic m6A-related lncRNAs in prognosis, the tumor microenvironment, stemness scores, and anticancer drug sensitivity were analyzed to explore the role of prognostic m6A-related lncRNAs in LUAD. Results: A total of 42 genomic instability-derived m6A-related lncRNAs were differentially expressed between the GS (genomic stable) and GU (genomic unstable) groups of LUAD patients. Four differentially expressed lncRNAs, 17 differentially expressed microRNAs, and 75 differentially expressed mRNAs were involved in the genomic-instability-derived m6A-related lncRNA-mediated ceRNA network. A prediction model based on 17 prognostic m6A-associated lncRNAs was constructed based on three TCGA datasets (all, training, and testing) and validated in the GSE102287 dataset. Performance comparison analysis showed that our prediction model (area under the curve [AUC] = 0.746) could better predict the survival of LUAD patients than the previously published lncRNA models (AUC = 0.577, AUC = 0.681). Prognostic m6A-related-lncRNAs have pivotal roles in the tumor microenvironment, stemness scores, and anticancer drug sensitivity of LUAD. Conclusion: A signature of genomic instability of m6A-associated lncRNAs to predict the survival of LUAD patients was validated. The prognostic, immune microenvironment and anticancer drug sensitivity analysis shed new light on the potential novel therapeutic targets in LUAD.

Identification of a Five Autophagy Subtype-Related Gene Expression Pattern for Improving the Prognosis of Lung Adenocarcinoma.

Background: Autophagy plays an important role in lung adenocarcinoma (LUAD). In this study, we aimed to explore the autophagy-related gene (ARG) expression pattern and to identify promising autophagy-related biomarkers to improve the prognosis of LUAD. Methods: The gene expression profiles and clinical information of LUAD patients were downloaded from the Cancer Genome Atlas (TCGA), and validation cohort information was extracted from the Gene Expression Omnibus database. The Human Autophagy Database (HADb) was used to extract ARGs. Gene expression data were analyzed using the limma package and visualized using the ggplot2 package as well as the pheatmap package in R software. Functional enrichment analysis was also performed for the differentially expressed ARGs (DEARGs). Then, consensus clustering revealed autophagy-related tumor subtypes, and differentially expressed genes (DEGs) were screened according to the subtypes. Next, the univariate Cox and multivariate Cox regression analyses were used to identify independent prognostic ARGs. After overlapping DEGs and the independent prognostic ARGs, the predictive risk model was established and validated. Correlation analyses between ARGs and clinicopathological variables were also explored. Finally, the TIMER and TISIDB databases were used to further explore the correlation analysis between immune cell infiltration levels and the risk score as well as clinicopathological variables in the predictive risk model. Results: A total of 222 genes from the HADb were identified as ARGs, and 28 of the 222 genes were pooled as DEARGs. The most significant GO term was autophagy (p = 3.05E-07), and KEGG analysis results indicated that 28 DEARGs were significantly enriched in the ErbB signaling pathway (p < 0.001). Then, consensus clustering analysis divided the LUAD into two clusters, and a total of 168 DEGs were identified according to cluster subtypes. Then univariate and multivariate Cox regression analyses were used to identify 12 genes that could serve as independent prognostic indicators. After overlapping 168 DEGs and 12 genes, 10 genes (ATG4A, BAK1, CAPNS1, CCR2, CTSD, EIF2AK3, ITGB1, MBTPS2, SPHK1, ST13) were selected for the further exploration of the prognostic pattern. Survival analysis results indicated that this risk model identified the prognosis (p = 4.379E-10). Combined with the correlation analysis results between ARGs and clinicopathological variables, five ARGs were screened as prognostic genes. Among them, SPHK1 expression levels were positively correlated with CD4+ T cells and dendritic cell infiltration levels. Conclusions: In this study, we constructed a predictive risk model and identified a five autophagy subtype-related gene expression pattern to improve the prognosis of LUAD. Understanding the subtypes of LUAD is helpful to accurately characterize the LUAD and develop personalized treatment.

Comprehensive Bioinformatics Analysis of Lipopolysaccharide-Induced Altered Autophagy in Acute Lung Injury and Construction of Underlying Competing Endogenous RNA Regulatory Mechanism.

BACKGROUND: Acute lung injury (ALI) is a fatal syndrome frequently induced by lipopolysaccharide (LPS) released from the bacterial cell wall. LPS could also trigger autophagy of lung bronchial epithelial cell to relieve the inflammation, while the overwhelming LPS would impair the balance of autophagy consequently inducing serious lung injury. METHODS: We observed the autophagy variation of 16HBE, human bronchial epithelial cell, under exposure to different concentrations of LPS through western blot, immunofluorescence staining, and electron microscopy. Eight strands of 16HBE were divided into two groups upon 1000 ng/ml LPS stimulation or not, which were sent to be sequenced at whole transcriptome. Subsequently, we analyzed the sequencing data in functional enrichment, pathway analysis, and candidate gene selection and constructed a hsa-miR-663b-related competing endogenous RNA (ceRNA) network. RESULTS: We set a series of concentrations of LPS to stimulate 16HBE and observed the variation of autophagy in related protein expression and autophagosome count. We found that the effective concentration of LPS was 1000 ng/ml at 12 hours of exposure and sequenced the 1000 ng/ml LPS-stimulated 16HBE. As a result, a total of 750 differentially expressed genes (DEGs), 449 differentially expressed lncRNAs (DElncRNAs), 76 differentially expressed circRNAs (DEcircRNAs), and 127 differentially expressed miRNAs (DEmiRNAs) were identified. We constructed the protein-protein interaction (PPI) network to visualize the interaction between DEGs and located 36 genes to comprehend the core discrepancy between LPS-stimulated 16HBE and the negative control group. In combined analysis of differentially expressed RNAs (DERNAs), we analyzed all the targeted relationships of ceRNA in DERNAs and figured hsa-miR-663b as a central mediator in the ceRNA network to play when LPS induced the variation of autophagy in 16HBE. CONCLUSION: Our research indicated that the hsa-miR-663b-related ceRNA network may contribute to the key regulatory mechanism in LPS-induced changes of autophagy and ALI.

Identification of CDK2-Related Immune Forecast Model and ceRNA in Lung Adenocarcinoma, a Pan-Cancer Analysis.

BACKGROUND: Tumor microenvironment (TME) plays important roles in different cancers. Our study aimed to identify molecules with significant prognostic values and construct a relevant Nomogram, immune model, competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD). METHODS: "GEO2R," "limma" R packages were used to identify all differentially expressed mRNAs from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Genes with P-value <0.01, LogFC>2 or <-2 were included for further analyses. The function analysis of 250 overlapping mRNAs was shown by DAVID and Metascape software. By UALCAN, Oncomine and R packages, we explored the expression levels, survival analyses of CDK2 in 33 cancers. "Survival," "survminer," "rms" R packages were used to construct a Nomogram model of age, gender, stage, T, M, N. Univariate and multivariate Cox regression were used to establish prognosis-related immune forecast model in LUAD. CeRNA network was constructed by various online databases. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore correlations between CDK2 expression and IC50 of anti-tumor drugs. RESULTS: A total of 250 differentially expressed genes (DEGs) were identified to participate in many cancer-related pathways, such as activation of immune response, cell adhesion, migration, P13K-AKT signaling pathway. The target molecule CDK2 had prognostic value for the survival of patients in LUAD (P = 5.8e-15). Through Oncomine, TIMER, UALCAN, PrognoScan databases, the expression level of CDK2 in LUAD was higher than normal tissues. Pan-cancer analysis revealed that the expression, stage and survival of CDK2 in 33 cancers, which were statistically significant. Through TISIDB database, we selected 13 immunodepressants, 21 immunostimulants associated with CDK2 and explored 48 genes related to these 34 immunomodulators in cBioProtal database (P < 0.05). Gene Set Enrichment Analysis (GSEA) and Metascape indicated that 49 mRNAs were involved in PUJANA ATM PCC NETWORK (ES = 0.557, P = 0, FDR = 0), SIGNAL TRANSDUCTION (ES = -0.459, P = 0, FDR = 0), immune system process, cell proliferation. Forest map and Nomogram model showed the prognosis of patients with LUAD (Log-Rank = 1.399e-08, Concordance Index = 0.7). Cox regression showed that four mRNAs (SIT1, SNAI3, ASB2, and CDK2) were used to construct the forecast model to predict the prognosis of patients (P < 0.05). LUAD patients were divided into two different risk groups (low and high) had a statistical significance (P = 6.223e-04). By "survival ROC" R package, the total risk score of this prognostic model was AUC = 0.729 (SIT1 = 0.484, SNAI3 = 0.485, ASB2 = 0.267, CDK2 = 0.579). CytoHubba selected ceRNA mechanism medicated by potential biomarkers, 6 lncRNAs-7miRNAs-CDK2. The expression of CDK2 was associated with IC50 of 89 antitumor drugs, and we showed the top 20 drugs with P < 0.05. CONCLUSION: In conclusion, our study identified CDK2 related immune forecast model, Nomogram model, forest map, ceRNA network, IC50 of anti-tumor drugs, to predict the prognosis and guide targeted therapy for LUAD patients.

Glycolysis Define Two Prognostic Subgroups of Lung Adenocarcinoma With Different Mutation Characteristics and Immune Infiltration Signatures.

Increasing studies have proved that malignant tumors are associated with energy metabolism. This study was aimed to explore biological variables that impact the prognosis of patients in the glycolysis-related subgroups of lung adenocarcinoma (LUAD). The mRNA expression profiling and mutation data in large LUAD samples were collected from the Cancer Genome Atlas (TCGA) database. Then, we identified the expression level and prognostic value of glycolysis-related genes, as well as the fractions of 22 immune cells in the tumor microenvironment. The differences between glycolysis activity, mutation, and immune infiltrates were discussed in these groups, respectively. Two hundred fifty-five glycolysis-related genes were identified from gene set enrichment analysis (GSEA), of which 43 genes had prognostic values (p < 0.05). Next, we constructed a glycolysis-related competing endogenous RNA (ceRNA) network which related to the survival of LUAD. Then, two subgroups of LUAD (clusters 1 and 2) were identified by applying unsupervised consensus clustering to 43 glycolysis-related genes. The survival analysis showed that the cluster 1 patients had a worse prognosis (p < 0.001), and upregulated differentially expressed genes (DEGs) are interestingly enriched in malignancy-related biological processes. The differences between the two subgroups are SPTA1, KEAP1, USH2A, and KRAS among top 10 mutated signatures, which may be the underlying mechanism of grouping. Combined high tumor mutational burden (TMB) with tumor subgroups preferably predicts the prognosis of LUAD patients. The CIBERSORT algorithm results revealed that low TMB samples were concerned with increased infiltration level of memory resting CD4+ T cell (p = 0.03), resting mast cells (p = 0.044), and neutrophils (p = 0.002) in cluster 1 and high TMB samples were concerned with increased infiltration level of memory B cells, plasma cells, CD4 memory-activated T cells, macrophages M1, and activated mast cells in cluster 2, while reduced infiltration of monocytes, resting dendritic cells, and resting mast cells was captured in cluster 2. In conclusion, significant different gene expression characteristics were pooled according to the two subgroups of LUAD. The combination of subgroups, TMB and tumor-infiltrating immune cell signature, might be a novel prognostic biomarker in LUAD.

Long non-coding RNA Rian protects against experimental bronchopulmonary dysplasia by sponging miR-421.

Bronchopulmonary dysplasia (BPD) is a frequent complication characterized by accelerated lung alveolarization in newborns. Long non-coding RNAs (lncRNAs) and microRNAs (miRs) are regarded as essential regulators in various diseases, including BPD. However, the detailed mechanism of the functions of RNA imprinted and accumulated in nucleus (Rian) lncRNA in the progression of BPD have remained elusive. The aim of the present study was to illustrate the interaction between miR-421 and Rian in BPD models and MLE-12 cells. The ability of Rian to protect neonatal lungs from hyperoxia-induced lung damage was examined. A mouse model of BPD and a hyperoxia-stimulated MLE-12 cell damage model were generated and treated with specific plasmid/mimics for the overexpression of Rian/miR-421. The interaction between miR-421 and Rian was predicted and verified using StarBase and a dual-luciferase reporter assay, respectively. The expression levels of miR-421 or Rian in both tissues and the MLE-12 alveolar epithelial cell line were assessed using reverse transcription-quantitative (RT-q)PCR. As parameters of alveolarization, the mean linear intercept (MLI), radial alveolar count (RAC) and the lung weight/body weight (LW/BW) ratio were measured. Furthermore, RT-qPCR was used to measure mRNA levels of pro-inflammatory cytokines (TNF-α, IL-6 and IL-1ß) in the lung tissue of mice, and ELISAs were performed to determine the levels of pro-inflammatory cytokines (TNF-α, IL-6 and IL-1ß) in the supernatant of MLE-12 cells. Cell growth and apoptosis were evaluated using an MTT assay and flow cytometry, respectively. Furthermore, caspase-3 activity was assessed using a caspase-3 activity detection kit. Prediction with StarBase and the dual-luciferase reporter assay revealed that miR-421 directly targeted Rian. RT-qPCR analysis confirmed that Rian was downregulated and miR-421 was upregulated in lung tissues of the mouse model of BPD and in hyperoxia-induced MLE-12 cells. However, the expression of miR-421 was decreased by Rian-overexpression, an effect that was reversed by miR-421 mimics. In addition, BPD was alleviated by Rian-plasmid, as confirmed by the enhanced RAC and reduced MLI and LW/BW ratio. The present results also indicated that Rian-plasmid inhibited the secretion of pro-inflammatory cytokines (TNF-α, IL-6 and IL-1ß) in BPD mouse serum and hyperoxia-induced MLE-12 cells. In addition, Rian-plasmid eliminated the effect of hyperoxia to inhibit cell viability and induce apoptosis in MLE-12 cells. However, all of these effects of Rian were markedly reversed by miR-421 mimics. The present results indicated that Rian may attenuate hyperoxic damage in neonatal lungs and may serve as a novel molecular target for BPD treatment.

AURKA and FAM83A are prognostic biomarkers and correlated with Tumor-infiltrating Lymphocytes in smoking related Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) has become the main histologic type, which account for nearly 40% of lung cancer. The present study aimed to investigate the gene expression signature in smoking related LUAD. A total of 45 smoking related DEGs in LUAD were identified and functional enrichment analysis was also performed. Then Cox's regression model and Kaplan-Meier analysis were used to screen potential prognostic genes. Finally, AURKA and FAM83A were left for further immune-related mechanism exploration. Kaplan-Meier analysis indicated survival rates are related to different immune cell (B cell and Dendritic cell) infiltration levels. Mechanistically, we further explore the correlation between AURKA and FAM83A gene expression levels and tumor-infiltrating lymphocytes (TILs) level as well as their response to immunomodulators. The results suggested that AURKA and FAM83A are highly expressed in smoking related LUAD, and negatively correlated to B cell and Dendritic cell infiltration levels. At the same time, B cell and Dendritic cell infiltration levels also related to the prognosis of LUAD. We further revealed AURKA and FAM83A could be novel targets to improve the prognosis of LUAD through regulated the response to immunomodulators.

Cigarette smoke extract induces pyroptosis in human bronchial epithelial cells through the ROS/NLRP3/caspase-1 pathway.

AIMS: Pyroptosis and inflammation are involved in the development of chronic obstructive pulmonary disease (COPD). However, the cigarette smoke-mediated mechanism of COPD remains unclear. In this study, we aimed to investigate the role of nucleotide-binding domain-like receptor protein-3 (NLRP3) inflammasome-mediated pyroptosis in the death of human bronchial epithelial (HBE) cells after cigarette smoke extract (CSE) exposure. MAIN METHODS: The protein level of NLRP3 in lung tissue was measured after cigarette smoke exposure in vivo. In vitro, HBE cells were treated with CSE. Subsequently, the activity of caspase-1, lactate dehydrogenase (LDH) release, release of interleukin (IL)-1ß and NLRP3 expression levels were measured. The involvement of reactive oxygen species (ROS) was also explored. KEY FINDINGS: After exposure to CSE, increased release of LDH, the transcriptional and translational upregulation of NLRP3, the caspase-1 activity levels, and enhanced IL-1ß and IL-18 release were observed in 16HBE cells. In addition, NLRP3 was required to activate the caspase-1. Our results suggested that pre-stimulated of 16HBE with a caspase-1 inhibitor, or using NLRP3 siRNA to silence NLRP3 expression, also caused the decrease of IL-1ß release and pyroptosis. SIGNIFICANCES: CSE induced inflammation and contributed to pyroptosis through the ROS/NLRP3/caspase-1 pathway in 16HBE cells. The NLRP3 inflammasome participates in CSE-induced HBE cell damage and pyroptosis, which could provide new insights into COPD.

Prognostic implication of glycolysis related gene signature in non-small cell lung cancer.

Abnormal glycolysis is one of the hallmarks of cancer and plays an important role in its development. This study was devoted to identify glycolysis related genes as prognostic biomarkers for non-small cell lung cancer (NSCLC). The mRNA expression profile and clinical follow-up data were obtained using The Cancer Genome Atlas (TCGA) database. The validation set was obtained by bootstrap method of random repeated sampling. A total of 200 glycolysis-related genes were obtained from Gene Set Enrichment Analysis (GSEA) and 46 genes were significantly associated with overall survival (OS). Five genes (PKP2, LDHA, HMMR, COL5A1 and B3GNT3) were eventually identified to calculate risk score of NSCLC patients. The univariate and multivariate Cox regression analysis indicated that the risk score was an independent prognostic factor (training set: HR=2.126, 95% CI [1.605, 2.815], p<0.001; validation set: HR=2.298, 95%CI [1.450, 3.640], p<0.001). Patients assigned to the high-risk group were associated with poor OS compared with patients in the low-risk group (training set: P=7.946e-06; validation set: P=6.368e-07). Receiver operating characteristic (ROC) curve and stratification analysis also demonstrated the potential prognostic performance. In conclusion, we constructed a novel glycolysis related risk signature which might contribute to predicting the prognosis of NSCLC.

LncRNA XIST acts as a MicroRNA-520 sponge to regulate the Cisplatin resistance in NSCLC cells by mediating BAX through CeRNA network.

Background: In recent years, LncRNA acts as a member of competing endogenous RNA (ceRNA), playing an important role in drug resistance of lung cancer. The aim of this study was to identify potential biomarkers about cisplatin resistant lung cancer cells using a comprehensive ceRNA network. Methods: GSE6410 (GPL-201) analyzed gene expression changes about cisplatin resistance in A549 NSCLC cells. GSE43249 (GPL-14613) included noncoding RNA expression profiling derived from the cisplatin resistant A549 lung cells. GEO2R, an online analysis tool, analyzed the differentially expressed mRNAs and miRNAs (DEmRNAs and DEmiRNAs). To explore the functional enrichment implication of differentially expressed mRNAs, we used the GO (Gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis. Through miRDB, Targetscan, Starbase and miRWalk, we found targeted miRNAs. The Kaplan-Meier curve method was used to show clinical survival analysis of targeted RNAs (P<0.05). The Starbase database predicted potential lncRNAs mediated targeted miRNAs. Eventually, the novel ceRNA network of lncRNAs, miRNAs, mRNA was constructed by cytoscape3.7.2. Results: 118 differentially expressed mRNAs were the basis of the mediated ceRNA network. DAVID and Kaplan-Meier picked out BAX, an apoptosis regulator. Venn diagram demonstrated 8 miRNAs commonly regulating BAX. Starbase predicted lncRNA XIST mediated miRNAs. Finally, lncRNA XIST may be a useful biomarker regulating cisplatin resistance in lung cancer cells and further, we explored the BAX may effect tumor-infiltrating immune cells. Conclusions: LncRNA XIST competitively bound to miRNA 520 in the regulation of cisplatin resistance by BAX, participating apoptosis in the p53 signaling pathway.