GRPR down-regulation inhibits spermatogenesis through Ca2+ mediated by PLCß/IP3R signaling pathway in long-term formaldehyde-exposed rats.

Formaldehyde (FA), which is known as an air pollutant, has been proven to induce male infertility. However, the underlying mechanism of FA-induced male infertility remains elusive. In this study, 24 male SD rats were exposed to different levels of FA (0, 0.5, 2.46, and 5 mg/m3) for eight consecutive weeks. Through HE staining and sperm smear, we observed that FA exposure resulted in spermatogenic injury and the sperm quality decreased in rats. The qRT-PCR and Western blot analysis further revealed that GRPR was down-regulated in testicular tissues of FA-exposed rats as well as primary spermatogenic cells. Meanwhile, ZDOCK uncovered an interaction between GRPR and PLCß. In addition, the CCK8, Fluo 3-AM and Flow cytometry results showed that FA exposure suppressed the expression of GRPR, PLCß and IP3R, consequently reducing the Ca2+ concentration in spermatogenic cells, inducing apoptosis and inhibiting proliferation of spermatogenic cells. Moreover, rescue experiments confirmed that promoting GRPR could improve intracellular Ca2+ concentration by upregulating PLCß and IP3R, partially reducing the apoptosis and promoting the proliferation of FA-treated spermatogenic cells. These findings revealed that GRPR participates in spermatogenesis through Ca2+ mediated by the PLCß/IP3R signaling pathway in FA-exposed rats.

A Comprehensive Review of Pea (Pisum sativum L.): Chemical Composition, Processing, Health Benefits, and Food Applications.

Pisum sativum L., commonly referred to as dry, green, or field pea, is one of the most common legumes that is popular and economically important. Due to its richness in a variety of nutritional and bioactive ingredients, the consumption of pea has been suggested to be associated with a wide range of health benefits, and there has been increasing focus on its potential as a functional food. However, there have been limited literature reviews concerning the bioactive compounds, health-promoting effects, and potential applications of pea up to now. This review, therefore, summarizes the literature from the last ten years regarding the chemical composition, physicochemical properties, processing, health benefits, and potential applications of pea. Whole peas are rich in macronutrients, including proteins, starches, dietary fiber, and non-starch polysaccharides. In addition, polyphenols, especially flavonoids and phenolic acids, are important bioactive ingredients that are mainly distributed in the pea coats. Anti-nutritional factors, such as phytic acid, lectin, and trypsin inhibitors, may hinder nutrient absorption. Whole pea seeds can be processed by different techniques such as drying, milling, soaking, and cooking to improve their functional properties. In addition, physicochemical and functional properties of pea starches and pea proteins can be improved by chemical, physical, enzymatic, and combined modification methods. Owing to the multiple bioactive ingredients in peas, the pea and its products exhibit various health benefits, such as antioxidant, anti-inflammatory, antimicrobial, anti-renal fibrosis, and regulation of metabolic syndrome effects. Peas have been processed into various products such as pea beverages, germinated pea products, pea flour-incorporated products, pea-based meat alternatives, and encapsulation and packing materials. Furthermore, recommendations are also provided on how to better utilize peas to promote their development as a sustainable and functional grain. Pea and its components can be further developed into more valuable and nutritious products.

Facile synthesis of chitosan-based nanogels through photo-crosslinking for doxorubicin delivery.

Chitosan-based nanogels are effective carriers for drug delivery due to their biocompatibility and biodegradability. However, the chemically cross-linked nanogels usually require complicated procedures or tough conditions. Herein, we report a simple approach to generate chitosan-based nanogels by photo-crosslinking of poor solvent-induced nanoaggregates without requiring any emulsifying agent, catalyst, or external crosslinker. O-nitrobenzyl alcohol-modified carboxymethyl chitosan was synthesized and self-crosslinked into the nanogels in a mixed solution of ethanol and water under 365 nm light irradiation due to UV-induced primary amine and o-nitrobenzyl alcohol cyclization. The nanogels (CMC-NBA NPs) and lactobionic acid-decorated nanogels (LACMC-NBA NPs) displayed a uniform diameter (~200 nm) and excellent stability under physiological conditions. Notably, the nanogels exhibited a high loading content (~28 %) due to π-π stacking and electrostatic interactions between doxorubicin (DOX) and the carriers. These DOX-loaded nanogels showed rapid drug release under slightly acidic conditions. The cell and animal experiments confirmed that LACMC-NBA NPs increased cellular uptake, improved cytotoxicity in tumor cells, and enhanced growth inhibition in vivo than CMC-NBA NPs. Thus, these photo-crosslinked nanogels possess great potential for DOX delivery.

Integrated analysis of 14 lymphoma datasets revealed high expression of CXCL14 promotes cell migration in mantle cell lymphoma.

Lymphoma is accompanied by the impairment of multiple immune functions. Cytokines play an important role in a variety of immune-related functions and affect the tumor microenvironment. However, the exact regulatory mechanisms between them remain unclear. This study aimed to explore the cytokines expression and function in Hodgkin's lymphoma (HL), diffuse large B-cell lymphoma (DLBCL), and mantle cell lymphoma (MCL). We performed a transcriptome integration analysis of 14 lymphoma datasets including 240 Hodgkin's lymphoma, 891 diffuse large B-cell lymphoma, 216 mantle cell lymphoma, and 64 health samples. The results showed that multiple immune functions and signal pathway damage were shared by all three types of lymphoma, and these functions were related to cytokines. Furthermore, through co-expression network and functional interaction network analysis, we identified CXCL14 as a key regulator and it affects cell chemotaxis and migration functions. The functional experiment showed that CXCL14 knockdown inhibited cell migration in MCL cell lines. This study suggested that high expression of CXCL14 may aggravate MCL via promoting cell migration. Our findings provide novel insights into the biology of this disease and would be helpful for the pathogenesis study and drug discovery of lymphomas.

System-level metabolic modeling facilitates unveiling metabolic signature in exceptional longevity.

Although it is well known that metabolic control plays a crucial role in regulating the health span and life span of various organisms, little is known for the systems metabolic profile of centenarians, the paradigm of human healthy aging and longevity. Meanwhile, how to well characterize the system-level metabolic states in an organism of interest remains to be a major challenge in systems metabolism research. To address this challenge and better understand the metabolic mechanisms of healthy aging, we developed a method of genome-wide precision metabolic modeling (GPMM) which is able to quantitatively integrate transcriptome, proteome and kinetome data in predictive modeling of metabolic networks. Benchmarking analysis showed that GPMM successfully characterized metabolic reprogramming in the NCI-60 cancer cell lines; it dramatically improved the performance of the modeling with an R2 of 0.86 between the predicted and experimental measurements over the performance of existing methods. Using this approach, we examined the metabolic networks of a Chinese centenarian cohort and identified the elevated fatty acid oxidation (FAO) as the most significant metabolic feature in these long-lived individuals. Evidence from serum metabolomics supports this observation. Given that FAO declines with normal aging and is impaired in many age-related diseases, our study suggests that the elevated FAO has potential to be a novel signature of healthy aging of humans.

Screening of antibacterial compounds with novel structure from the FDA approved drugs using machine learning methods.

Bacterial infection is one of the most important factors affecting the human life span. Elderly people are more harmed by bacterial infections due to their deficits in immunity. Because of the lack of new antibiotics in recent years, bacterial resistance has increasingly become a serious problem globally. In this study, an antibacterial compound predictor was constructed using the support vector machines and random forest methods and the data of the active and inactive antibacterial compounds from the ChEMBL database. The results showed that both models have excellent prediction performance (mean accuracy >0.9 and mean AUC >0.9 for the two models). We used the predictor to screen potential antibacterial compounds from FDA-approved drugs in the DrugBank database. The screening results showed that 1087 small-molecule drugs have potential antibacterial activity and 154 of them are FDA-approved antibacterial drugs, which accounts for 76.2% of the approved antibacterial drugs collected in this study. Through molecular fingerprint similarity analysis and common substructure analysis, we screened 8 predicted antibacterial small-molecule compounds with novel structures compared with known antibacterial drugs, and 5 of them are widely used in the treatment of various tumors. This study provides a new insight for predicting antibacterial compounds by using approved drugs, the predicted compounds might be used to treat bacterial infections and extend lifespan.

Transcriptome integration analysis and specific diagnosis model construction for Hodgkin's lymphoma, diffuse large B-cell lymphoma, and mantle cell lymphoma.

Transcriptome differences between Hodgkin's lymphoma (HL), diffuse large B-cell lymphoma (DLBCL), and mantle cell lymphoma (MCL), which are all derived from B cell, remained unclear. This study aimed to construct lymphoma-specific diagnostic models by screening lymphoma marker genes. Transcriptome data of HL, DLBCL, and MCL were obtained from public databases. Lymphoma marker genes were screened by comparing cases and controls as well as the intergroup differences among lymphomas. A total of 9 HL marker genes, 7 DLBCL marker genes, and 4 MCL marker genes were screened in this study. Most HL marker genes were upregulated, whereas DLBCL and MCL marker genes were downregulated compared to controls. The optimal HL-specific diagnostic model contains one marker gene (MYH2) with an AUC of 0.901. The optimal DLBCL-specific diagnostic model contains 7 marker genes (LIPF, CCDC144B, PRO2964, PHF1, SFTPA2, NTS, and HP) with an AUC of 0.951. The optimal MCL-specific diagnostic model contains 3 marker genes (IGLV3-19, IGKV4-1, and PRB3) with an AUC of 0.843. The present study reveals the transcriptome data-based differences between HL, DLBCL, and MCL, when combined with other clinical markers, may help the clinical diagnosis and prognosis.

Low microRNA150 expression is associated with activated carcinogenic pathways and a poor prognosis in patients with breast cancer.

Breast cancer is the most common type of cancer amongst women worldwide, and numerous microRNAs (miRNAs/miRs) are involved in the initiation and progression of breast cancer. The aim of the present study was to identify hub miRNAs and determine the underlying mechanisms regulated by these miRNAs in breast cancer. Breast invasive carcinoma transcriptome data (including mRNAs and miRNAs), and clinical data were acquired from The Cancer Genome Atlas database. Differential gene expression analysis, co­expression network analysis, gene set enrichment analysis (GSEA) and prognosis analysis were used to screen the hub miRNAs and explore their functions. Functional experiments were used to determine the underlying mechanisms of the hub miRNAs in breast cancer cells. The results revealed that low miR150 expression predicted a more advanced disease stage, and was associated with a less favorable prognosis. Through the combined use of five miRNA­target gene prediction tools, 31 potential miR150 target genes were identified. GSEA revealed that low miR150 expression was associated with the upregulation of several cancer­associated signaling pathways, and the downregulation of several tumor suppressor genes. Furthermore, miR150 independently affected overall survival in patients, and interacted with its target genes to indirectly affect overall and disease­free survival. Functional experiments demonstrated that miR150 positively regulated B and T lymphocyte attenuator (BTLA), and the downregulation of miR150 and BTLA combined promoted cell migration. In conclusion, the present study revealed that low miR150 expression was associated with less favorable clinical features, upregulation of several carcinogenic signaling pathways, and poor patient survival. Additionally, a miR150­BTLA axis was suggested to regulate cell viability and migration.

Integrated Analysis of lncRNAs and mRNAs Identifies a Potential Driver lncRNA FENDRR in Lung Cancer in Xuanwei, China.

This study was to screen out potential driver long non-coding RNAs (lncRNAs) in lung cancer in Xuanwei (LCXW) differently expressed mRNAs and lncRNAs were detected by gene expression microarrays in 23 paired lung adenocarcinoma and adjacent tissues. Combined bioinformatics analysis was performed to identify potential driver lncRNAs and their potential regulatory relationships. Transcriptome and clinical data in TCGA-LUAD were used as comparison and validation dataset. The comparison of LCXW and TCGA-LUAD revealed significant differences in expression of some genes, signaling pathways affected by differentially expressed genes, and the 5-year survival rate of patients. We identified 14 consistently deregulated mRNAs and 5 lncRNAs as candidate genes, which affected multiple cancer-related pathways and influenced patients' overall survival. By combined bioinformatics analysis, we further identified a potential driver lncRNA fetal-lethal non-coding developmental regulatory RNA (FENDRR) and proposed its possible regulation mechanism. The low expression of FENDRR was positively correlated with Krüppel-like factor4 (KLF4), KLF4 down-regulation may loss the activation function of cyclin-dependent kinase inhibitor 1A (CDKN1A) and cyclin-dependent kinase inhibitor 1C (CDKN1C) and the inhibition function of CyclinB1 (CCNB1), eventually cause excessive cell cycle activation and lead to lung cancer. This study revealed a potential FENDRR-KLF4-cell cycle regulation axis. These results lay an important foundation for further research on the pathogenesis of LCXW and identification of potential novel biomarkers or therapeutic targets.

Novel Long Non-coding RNA Markers for Prognostic Prediction of Patients with Bladder Cancer.

Objective To explore novel long non-coding RNA (lncRNA) molecular markers related to bladder cancer prognosis and to construct a prognostic prediction model for bladder cancer patients. Methods LncRNA expression data of patients with bladder cancer were downloaded from TCGA database. Univariate Cox regression and likelihood-based survival analysis were used to discover prognosis related lncRNAs. Functional studies of prognosis related lncRNAs were conducted by co-expression analysis and pathway enrichment analysis. Multivariate Cox regression analysis was used to establish risk score model, and Receiver Operating Characteristic analysis was used to determine the optimal cut-off point of the model. The risk score model was validated through Kaplan Meier estimation method and log-rank test. Results Seven prognosis related lncRNAs (OCIAD1-AS1, RP11-111J6.2, AC079354.3, RP11-553A21.3, RP11-598F7.3, CYP4F35P and RP11-113K21.4) which can predict survival of bladder cancer patient were discovered. Co-expression analysis and pathway analysis of these novel lncRNA signature and their target genes further revealed that these lncRNAs play important roles in the occurrence and development of bladder cancer. Additionally, a seven-lncRNA signature based risk score model for prognostic prediction of bladder cancer patients was established and validated. Notably, we identified the potential significance of two tumor-related antisense lncRNAs (OCIAD1-AS1 and RP11-553A21.3) in the prognosis of bladder cancer. Conclusion Our results suggest that these lncRNA markers may serve as potential prognosis predictors for bladder cancer and deserve further functional verification studies.

Regulatory function of praja ring finger ubiquitin ligase 2 mediated by the P2rx3/P2rx7 axis in mouse hippocampal neuronal cells.

Praja2 (Pja2), a member of the growing family of mammalian RING E3 ubiquitin ligases, is reportedly involved in not only several types of cancer but also neurological diseases and disorders, but the genetic mechanism underlying the regulation of Pja2 in the nervous system remains unclear. To study the cellular and molecular functions of Pja2 in mouse hippocampal neuronal cells (MHNCs), we used gain- and loss-of-function manipulations of Pja2 in HT-22 cells and tested their regulatory effects on three Alzheimer's disease (AD) genes and cell proliferation. The results revealed that the expression of AD markers, including amyloid beta precursor protein (App), microtubule-associated protein tau (Mapt), and gamma-secretase activating protein (Gsap), could be inhibited by Pja2 overexpression and activated by Pja2 knockdown. In addition, HT-22 cell proliferation was enhanced by Pja2 upregulation and suppressed by its downregulation. We also evaluated and quantified the targets that responded to the enforced expression of Pja2 by RNA-Seq, and the results showed that purinergic receptor P2X, ligand-gated ion channel 3 and 7 (P2rx3 and P2rx7), which show different expression patterns in the critical calcium signaling pathway, mediated the regulatory effect of Pja2 in HT-22 cells. Functional studies indicated that Pja2 regulated HT-22 cells development and AD marker genes by inhibiting P2rx3 but promoting P2rx7, a gene downstream of P2rx3. In conclusion, our results provide new insights into the regulatory function of the Pja2 gene in MHNCs and thus underscore the potential relevance of this molecule to the pathophysiology of AD.

Transcriptome analysis reveals gender-specific differences in overall metabolic response of male and female patients in lung adenocarcinoma.

BACKGROUND: Evidence from multiple studies suggests metabolic abnormalities play an important role in lung cancer. Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. The present study aimed to explore differences in the global metabolic response between male and female patients in LUAD and to identify the metabolic genes associated with lung cancer susceptibility. METHODS: Transcriptome and clinical LUAD data were acquired from The Cancer Genome Atlas (TCGA) database. Information on metabolic genes and metabolic subsystems were collected from the Recon3D human metabolic model. Two validation datasets (GSE68465 and GSE72094) were downloaded from the Gene Expression Omnibus (GEO) database. Differential expression analysis, gene set enrichment analysis and protein-protein interaction networks were used to identified key metabolic pathways and genes. Functional experiments were used to verify the effects of genes on proliferation, migration, and invasion in lung cancer cells in vitro. RESULTS: Samples of tumors and adjacent non-tumor tissue from both male and female patients exhibited distinct global patterns of gene expression. In addition, we found large differences in methionine and cysteine metabolism, pyruvate metabolism, cholesterol metabolism, nicotinamide adenine dinucleotide (NAD) metabolism, and nuclear transport between male and female LUAD patients. We identified 34 metabolic genes associated with lung cancer susceptibility in males and 15 in females. Most of the metabolic cancer-susceptibility genes had high prediction accuracy for lung cancer (AUC > 0.9). Furthermore, both bioinformatics analysis and experimental results showed that TAOK2 was down-regulated and ASAH1 was up-regulated in male tumor tissue and female tumor tissue in LUAD. Functional experiments showed that inhibiting ASAH1 suppressed the proliferation, migration, and invasion of lung cancer cells. CONCLUSIONS: Metabolic cancer-susceptibility genes may be used alone or in combination as diagnostic markers for LUAD. Further studies are required to elucidate the functions of these genes in LUAD.

Novel pathways of HIV latency reactivation revealed by integrated analysis of transcriptome and target profile of bryostatin.

The reactivation of HIV latency cell will be necessary to curing HIV infection. Although many latency-reversal agents (LRAs) have proven effective to reactivate the latency cell, there is a lack of any systematic analysis of the molecular targets of these LRAs and related pathways in the context of transcriptome. In this study, we performed an integrated analysis of the target profile of bryostatin and transcriptome of the reactivated CD4+ T cells after exposing to bryostatin. The result showed a distinct gene expression profile between latency cells and bryostatin reactivated cells. We found bryostatin can target multiple types of protein other than only protein kinase C. Functional network analysis of the target profile and differential expressed genes suggested that bryostatin may activate a few novel pathways such as pyrimidine metabolism, purine metabolism and p53 signaling pathway, besides commonly known pathways DNA replication, cell cycle and so on. The results suggest that bryostatin may reactivate the HIV-latent cells through up-regulation of pyrimidine and purine metabolism or through starting the cell-cycle arrest and apoptosis induced by up-regulation of p53 signaling pathway. Our study provides some novel insights into the role of bryostatin and its affected pathways in controlling HIV latency and reactivation.

[Effect of irisin on hypoxic-ischemic brain damage in neonatal rats].

OBJECTIVE: To study the effect and mechanism of action of irisin on hypoxic-ischemic brain damage in neonatal rats. METHODS: A total of 248 7-day-old Sprague-Dawley rats were randomly divided into a sham-operation group, a model group, and low- and high-dose irisin intervention groups (n=62 each). The rats in the model and irisin intervention groups were given hypoxic treatment after right common carotid artery ligation to establish a model of hypoxic-ischemic brain damage. Those in the sham-operation group were given the separation of the right common carotid artery without ligation or hypoxic treatment. The rats in the high- and low-dose irisin intervention groups were given intracerebroventricular injection of recombinant irisin polypeptide at a dose of 0.30 µg and 0.15 µg respectively. Those in the model and sham-operation groups were given the injection of an equal volume of PBS. The water maze test was used to compare neurological behaviors between groups. TTC staining, hematoxylin-eosin staining and TUNEL staining were used to observe histopathological changes of the brain. Western blot was used to measure the expression of the apoptosis-related molecules cleaved-caspase-3 (CC3), BCL-2 and BAX. RESULTS: Compared with the sham-operation group, the model group had a significant increase in latency time and a significant reduction in the number of platform crossings (P<0.05). Compared with the model group, the high-dose irisin intervention group had a significant reduction in latency time and a significant increase in the number of platform crossings (P<0.05). Compared with the sham-operation group, the model group had massive infarction in the right hemisphere, with significant increases in karyopyknosis and karyorrhexis. Compared with the model group, the high-dose irisin intervention group had a smaller infarct area of the right hemisphere, with reductions in karyopyknosis and karyorrhexis. The model group had a significantly higher apoptosis rate of cells in the right cerebral cortex and the hippocampus than the sham-operation group. The high-dose irisin intervention group had a significantly lower apoptosis rate than the model group (P<0.05). At 24 and 48 hours after modeling, the sham-operation group had a significantly lower level of CC3 than the model group (P<0.05). Compared with the model group, the high-dose irisin intervention group had a significantly lower level of CC3 and a significantly higher BCL-2/BAX ratio (P<0.05). The low-dose irisin intervention group had similar laboratory markers and histopathological changes of the brain to the model group. CONCLUSIONS: Irisin can alleviate hypoxic-ischemic brain damage in neonatal rats in a dose-dependent manner, possibly by reducing cell apoptosis in the cerebral cortex and the hippocampus.

High infiltration of CD20+ B lymphocytes in extranodal natural killer/T-cell lymphoma is associated with better prognosis.

Immune cells have an uncertain function during the progression of extranodal natural killer/T-cell lymphoma (ENKTL). The present study determined the distribution, phenotype, and clinical significance of B lymphocytes in ENKTL. Immunohistochemistry indicated high infiltration of CD20+ B lymphocytes in the tumour tissues of 40% of the patients, and that a high infiltration correlated with better overall survival. Moreover, B lymphocytes had an active mature phenotype in situ and suppressed the proliferation of ENKTL cells in vitro. These results suggest that tumour infiltration of CD20+ B lymphocytes may be a new prognostic indicator for patients with ENKTL.

Bioinformatics Analysis Identifies Protein Tyrosine Kinase 7 (PTK7) as a Potential Prognostic and Therapeutic Biomarker in Stages I to IV Hepatocellular Carcinoma.

BACKGROUND Worldwide, hepatocellular carcinoma (HCC) accounts for 80-90% of all cases of primary liver cancer, and is one of the ten most common malignancies. This study used bioinformatics analysis to identify genes associated with patient outcome in stages I-IV HCC and the gene pathways that distinguished between normal liver and liver cells and HCC and human HCC cell lines. MATERIAL AND METHODS Target genes were defined as those that had marketed drugs or drugs under development targeting a specific gene and acquired from the Clarivate Analytics Integrity Database. Differential expression gene analysis, co-expression network analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, survival analysis and receiver operating characteristic (ROC) curve analysis were used to explore the similarities and differences in gene expression profiles, functional associations, and survival in stage I-IV HCC. Normal liver cells (HL-7702) and HCC cell lines (HepaRG, HepG2, SK-Hep1, and Huh7) were studied using Western blot and quantitative reverse transcription PCR (RT-qPCR). RESULTS Hierarchical gene clustering identified target genes that distinguished between HCC and normal liver tissue. For stages I-IV HCC, there were seven commonly upregulated target genes EPHB1, LTK, NTRK2, PTK7, TBK1, TIE1, and TLR3, which were mainly involved in immune and signaling transduction pathways. PTK7 was highly expressed in stage I-IV HCC and was an independent prognostic marker for reduced overall survival (OS). CONCLUSIONS Bioinformatics analysis, combined with patient survival analysis, identified PTK7 gene expression as a potential therapeutic target and prognostic biomarker for all stages of HCC.

Integrated analysis of 10 lymphoma datasets identifies E2F8 as a key regulator in Burkitt's lymphoma and mantle cell lymphoma.

Burkitt's lymphoma (BURK), diffuse large B-cell lymphoma (DLBCL) and mantle cell lymphoma (MCL) are three main types of B-cell lymphomas. This study aimed to compare the differences of affected biological functions and pathways, as well as to explore the possible regulatory mechanisms and the potential therapeutic targets in BURK, DLBCL and MCL. We performed an integrated analysis of 10 lymphoma datasets including 352 BURK patients, 880 DLBCL patients, 216 MCL patients, and 33 controls. Our results showed that signaling pathways, amino acid metabolism and several lipid metabolism pathways varies considerably among these three types of lymphoma. Furthermore, we identified several key transcription factors (TFs) and their target genes that may promote these diseases by influencing multiple carcinogenic pathways. Among these TFs, we reported first that E2F8 displayed the most significant effects in BURK and MCL. Our results demonstrate that over-expression of E2F8 activates target genes that may promote cell cycle, mitosis, immune and other cancer related functions in BURK and MCL. Therefore, we suggest that E2F8 could be used as a biomarker and potential therapeutic target for BURK and MCL. These findings would be helpful in the study of pathogenesis, and drug discovery and also in the prognosis of B cell lymphomas.

Identification of metabolism-associated pathways and genes involved in male and female liver cancer patients.

Hepatocellular carcinoma (HCC) is a major type of primary liver cancer. HCC is influenced by sex and multiple metabolic abnormalities. The present study aimed to compare the overall metabolic changes between male and female HCC patients and identify key metabolic genes. Metabolic genes and pathways were identified based on analyses of publicly available data. Differential expression analysis, gene set enrichment analysis, survival analysis and transcriptional regulation analysis were employed to explore sex differences and identify key metabolic genes in HCC. The results suggested that female patients had more severe metabolic gene expression abnormalities and pathway deregulation than male patients. This study identified 9 key metabolic genes, and only upregulated ALDH1A2 independently increased overall survival risk in patients. Bioinformatic analyses suggest that upregulated GATA3 and TAL1 activate ALDH1A2 and then disrupt amino acid and carbohydrate metabolism, which may increase the risk of HCC. This study identified a novel contribution of upregulated ALDH1A2 to HCC. Future studies are needed to elucidate the potential metabolic mechanism of the role of ALDH1A2 in HCC.

Soluble CXCL16 promotes TNF-α-induced apoptosis in DLBCL via the AMAD10-NF-κB regulatory feedback loop.

We had previously identified that the co-expression of transmembrane CXCL16 (TM-CXCL16) and its receptor CXCR6 is an independent risk factor for poor survival in patients with diffuse large B-cell lymphoma (DLBCL). However, the impact of the soluble form of CXCL16 (sCXCL16) on the pathogenesis of DLBCL remains unknown. In the present study, the synergistic effect of sCXCL16 and tumor necrosis factor α (TNF-α) on apoptosis in DLBCL cell lines (OCI-LY8 and OCI-LY10) was investigated in vitro. sCXCL16 reinforced TNF-α-mediated inhibition of DLBCL cell proliferation, as determined by the cell counting kit-8 assay. The results of annexin V staining showed that sCXCL16 enhanced TNF-α-induced apoptosis in OCI-LY8 and OCI-LY10 cells through a death receptor-caspase signaling pathway. The results of gene microarray suggested a significant upregulation of differentially expressed genes in the TNF signaling pathway. sCXCL16 increased the concentration of extracellular TNF-α by binding to CXCR6 to activate the nuclear factor-κB (NF-κB) signaling pathway. TNF-α also induced the secretion of sCXCL16 by increasing the expression of ADAM10, which is known to cleave TM-CXCL16 to yield sCXCL16. Moreover, bioinformatics analysis revealed that elevated TNF-α and ADAM10 expression levels in tumor tissues predicted better survival in patients with DLBCL. Thus, our study suggests that sCXCL16 enhances TNF-α-induced apoptosis of DLBCL cells, which may involve a positive feedback loop consisting of TNF-α, ADAM10, sCXCL16, and members of the NF-κB pathway. sCXCL16 and TNF-α may be used as prognostic markers in the clinic, and their combinational use is a promising approach in the context of DLBCL therapy.

Regulatory network reconstruction of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets.

Although many of the genetic loci associated with breast cancer risk have been reported, there is a lack of systematic analysis of regulatory networks composed of different miRNAs and mRNAs on survival analysis in breast cancer. To reconstruct the microRNAs-genes regulatory network in breast cancer, we employed the expression data from The Cancer Genome Atlas (TCGA) related to five essential miRNAs including miR-21, miR-22, miR-210, miR-221, and miR-222, and their associated functional genomics data from the GEO database. Then, we performed an integration analysis to identify the essential target factors and interactions for the next survival analysis in breast cancer. Based on the results of our integrated analysis, we have identified significant common regulatory signatures including differentially expressed genes, enriched pathways, and transcriptional regulation such as interferon regulatory factors (IRFs) and signal transducer and activator of transcription 1 (STAT1). Finally, a reconstructed regulatory network of five miRNAs and 34 target factors was established and then applied to survival analysis in breast cancer. When we used expression data for individual miRNAs, only miR-21 and miR-22 were significantly associated with a survival change. However, we identified 45 significant miRNA-gene pairs that predict overall survival in breast cancer out of 170 one-on-one interactions in our reconstructed network covering all of five miRNAs, and several essential factors such as PSMB9, HLA-C, RARRES3, UBE2L6, and NMI. In our study, we reconstructed regulatory network of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets. These results may provide new insights into regulatory network-based precision medicine for breast cancer.