BUB1 Promotes Gemcitabine Resistance in Pancreatic Cancer Cells by Inhibiting Ferroptosis.

The development of chemotherapy resistance severely limits the therapeutic efficacy of gemcitabine (GEM) in pancreatic cancer (PC), and the dysregulation of ferroptosis is a crucial factor in the development of chemotherapy resistance. BUB1 Mitotic Checkpoint Serine/Threonine Kinase (BUB1) is highly overexpressed in PC patients and is closely associated with patient prognosis. However, none of the literature reports the connection between BUB1 and ferroptosis. The molecular mechanisms underlying GEM resistance are also not well understood. Therefore, this study first established the high expression levels of BUB1 in PC patients, then explored the role of BUB1 in the process of ferroptosis, and finally investigated the mechanisms by which BUB1 regulates ferroptosis and contributes to GEM resistance in PC cells. In this study, downregulation of BUB1 enhanced the sensitivity of PC cells to Erastin, and inhibited cell proliferation and migration. Mechanistically, BUB1 could inhibit the expression levels of Neurofibromin 2 (NF2) and MOB kinase activator 1 (MOB1), and promote Yes-associated protein (YAP) expression, thereby inhibiting ferroptosis and promoting GEM resistance in PC cells. Furthermore, the combination of BUB1 inhibition with GEM exhibited a synergistic therapeutic effect. These findings reveal the mechanisms underlying the development of GEM chemotherapy resistance based on ferroptosis and suggest that the combined use of BUB1 inhibitors may be an effective approach to enhance GEM efficacy.

KAN0438757, a novel PFKFB3 inhibitor, prevent the progression of severe acute pancreatitis via the Nrf2/HO-1 pathway in infiltrated macrophage.

Acute pancreatitis (AP) is a non-infectious pancreatic enzyme-induced disorder, a life-threatening inflammatory condition that can cause multi-organ dysfunction, characterized by high morbidity and mortality. Several therapies have been employed to target this disorder; however, few happen to be effectively employable even in the early phase. PFKFB3(6-phosphofructo-2-kinase/fructose-2,6-biphosphatase-3) is a critical regulator of glycolysis and is upregulated under inflammatory, mitogenic, and hypoxia conditions. Essential information on the targeting of the inflammatory pathway will present the termination of the disorder and recovery. Herein we investigated the protective function of KAN0438757, a potent inhibitor of PFKFB3, and its mechanism of impeding AP induced in mice. KAN0438757 was confirmed to activate the Nrf2/HO-1 inflammatory signaling pathways in response to caerulein induced acute pancreatitis (CAE-AP) and fatty acid ethyl ester induced severe acute pancreatitis (FAEE-SAP). Additionally, KAN0438757 alleviated the inflammatory process in infiltrated macrophage via the Nrf2/HO-1 inflammatory signaling pathway and demonstrated a significant effect on the growth of mice with induced AP. And more importantly, KAN0438757 displayed negligible toxicity in vivo. Taken together our data suggest KAN0438757 directly suppresses the inflammatory role of PFKFB3 and induces a protective role via the Nrf2/HO-1 pathway, which could prove as an excellent therapeutic platform for SAP amelioration.

MaxCLK: discovery of cancer driver genes via maximal clique and information entropy of modules.

MOTIVATION: Cancer is caused by the accumulation of somatic mutations in multiple pathways, in which driver mutations are typically of the properties of high coverage and high exclusivity in patients. Identifying cancer driver genes has a pivotal role in understanding the mechanisms of oncogenesis and treatment. RESULTS: Here, we introduced MaxCLK, an algorithm for identifying cancer driver genes, which was developed by an integrated analysis of somatic mutation data and protein-protein interaction (PPI) networks and further improved by an information entropy index. Tested on pancancer and single cancers, MaxCLK outperformed other existing methods with higher accuracy. About pancancer, we predicted 154 driver genes and 787 driver modules. The analysis of co-occurrence and exclusivity between modules and pathways reveals the correlation of their combinations. Overall, our study has deepened the understanding of driver mechanism in PPI topology and found novel driver genes. AVAILABILITY AND IMPLEMENTATION: The source codes for MaxCLK are freely available at https://github.com/ShandongUniversityMasterMa/MaxCLK-main.

Histone lysine methyltransferase SMYD3 promotes oral squamous cell carcinoma tumorigenesis via H3K4me3-mediated HMGA2 transcription.

BACKGROUND: Epigenetic dysregulation is essential to the tumorigenesis of oral squamous cell carcinoma (OSCC). SET and MYND domain-containing protein 3 (SMYD3), a histone lysine methyltransferase, is implicated in gene transcription regulation and tumor development. However, the roles of SMYD3 in OSCC initiation are not fully understood. The present study investigated the biological functions and mechanisms involved in the SMYD3-mediated tumorigenesis of OSCC utilizing bioinformatic approaches and validation assays with the aim of informing the development of targeted therapies for OSCC. RESULTS: 429 chromatin regulators were screened by a machine learning approach and aberrant expression of SMYD3 was found to be closely associated with OSCC formation and poor prognosis. Data profiling of single-cell and tissue demonstrated that upregulated SMYD3 significantly correlated with aggressive clinicopathological features of OSCC. Alterations in copy number and DNA methylation patterns may contribute to SMYD3 overexpression. Functional experimental results suggested that SMYD3 enhanced cancer cell stemness and proliferation in vitro and tumor growth in vivo. SMYD3 was observed to bind to the High Mobility Group AT-Hook 2 (HMGA2) promoter and elevated tri-methylation of histone H3 lysine 4 at the corresponding site was responsible for transactivating HMGA2. SMYD3 also was positively linked to HMGA2 expression in OSCC samples. Furthermore, treatment with the SMYD3 chemical inhibitor BCI-121 exerted anti-tumor effects. CONCLUSIONS: Histone methyltransferase activity and transcription-potentiating function of SMYD3 were found to be essential for tumorigenesis and the SMYD3-HMGA2 is a potential therapeutic target in OSCC.

Design and synthesis of boron-containing ALK inhibitor with favorable in vivo efficacy.

ALK is an attractive therapeutic target for the treatment of non-small cell lung cancer. As an emerging element in medicinal chemistry, boron has achieved great success in the discovery of antitumor drugs and antibacterial agents. Through construction of a BCC (boron-containing compound) compound library and broad kinase screening, we found the ALK inhibitor hit compound 10a. Structural optimization by CADD and isosterism revealed that lead compound 10k has improved activity (ALKL1196M IC50 = 8.4 nM, NCI-H2228 cells IC50 = 520 nM) and better in vitro metabolic stability (human liver microsomes, T1/2 = 238 min). Compound 10k showed good in vivo efficacy in a nude mouse NCI-H2228 lung cancer xenograft model with a TGI of 52 %. Molecular simulation analysis results show that the hydroxyl group on the oxaborole forms a key hydrogen bond with Asn1254 or Asp1270, and this binding site provides a new idea for drug design. This is the first publicly reported lead compound for a boron-containing ALK inhibitor.

Identification of Prognosis-Related Molecular Subgroups and Construction of a Prognostic Prediction Model Using Immune-Related Genes in Pancreatic Cancer.

Background: Pancreatic cancer patients with similar clinicopathological status exhibit substantially different therapeutic responses, which might be caused by the vast molecular heterogeneity of tumors. In this study, we attempted to identify specific molecular subgroups and construct a prognostic prediction model based on the expression level of immune-related genes in pancreatic cancer. The transcriptome profiling, single nucleotide variation, copy number variation, clinicopathological information, and follow-up data of pancreatic cancer patients were obtained from The Cancer Genome Atlas database. Thereafter, the immune-related genes with prognostic significance were identified for further consensus cluster analysis. The molecular characteristics and clinicopathological information were compared between the identified subgroups, and a weighted correlation network analysis was performed to identify the hub genes associated with the subgroups. Finally, the prognostic prediction model based on immune-related genes was established using the least absolute shrinkage and selection operator (LASSO) analysis. Results: A total of 67 immune-relevant genes with prognostic significance were selected and used for the consensus cluster analysis. The total samples were divided into two groups, C1 and C2. The subgroup C1 had a significantly worse prognosis than C2, as well as lower levels of immune cell infiltration, which indicate an immunosuppressed state. The mutational rate of the cancer-related genes including KRAS, TP53, and RNF43 was higher in the C1 subgroup. The C1 subgroup was associated with more advanced tumor grade and T stage and with higher mortality. Using LASSO regression, we developed a prognostic prediction model based on the expression levels of 19 immune-related genes, which we validated in three external data sets. In addition, we identified four potential therapeutic and prognostic biomarkers (TNNT1, KCNN4, SH2D3A, and PHLDA2). Conclusion: We identified two novel molecular subgroups of pancreatic cancer and developed a prognostic prediction model based on the expression levels of immune-related genes, which could be used in a clinical setting and could aid in unraveling the molecular processes leading to the development of pancreatic cancer.

Role of ferroptosis in gastrointestinal tumors: From mechanisms to therapies.

Ferroptosis is an iron-dependent nonapoptotic regulated cell death, which is mainly caused by an abnormal increase in lipid oxygen free radicals and an imbalance in redox homeostasis. Recently, ferroptosis has been shown to have implications in various gastrointestinal cancers, such as gastric carcinoma, hepatocellular carcinoma, and pancreatic cancer. This review summarises the latest research on ferroptosis, its mechanism of action, and its role in the progression of different gastrointestinal tumors to provide more information regarding the prevention and treatment of these tumors.

Identification of Novel Metabolism-Associated Subtypes for Pancreatic Cancer to Establish an Eighteen-Gene Risk Prediction Model.

Pancreatic cancer (PanC) is an intractable malignancy with a high mortality. Metabolic processes contribute to cancer progression and therapeutic responses, and histopathological subtypes are insufficient for determining prognosis and treatment strategies. In this study, PanC subtypes based on metabolism-related genes were identified and further utilized to construct a prognostic model. Using a cohort of 171 patients from The Cancer Genome Atlas (TCGA) database, transcriptome data, simple nucleotide variants (SNV), and clinical information were analyzed. We divided patients with PanC into metabolic gene-enriched and metabolic gene-desert subtypes. The metabolic gene-enriched subgroup is a high-risk subtype with worse outcomes and a higher frequency of SNVs, especially in KRAS. After further characterizing the subtypes, we constructed a risk score algorithm involving multiple genes (i.e., NEU2, GMPS, PRIM2, PNPT1, LDHA, INPP4B, DPYD, PYGL, CA12, DHRS9, SULT1E1, ENPP2, PDE1C, TPH1, CHST12, POLR3GL, DNMT3A, and PGS1). We verified the reproducibility and reliability of the risk score using three validation cohorts (i.e., independent datasets from TCGA, Gene Expression Omnibus, and Ensemble databases). Finally, drug prediction was completed using a ridge regression model, yielding nine candidate drugs for high-risk patients. These findings support the classification of PanC into two metabolic subtypes and further suggest that the metabolic gene-enriched subgroup is associated with worse outcomes. The newly established risk model for prognosis and therapeutic responses may improve outcomes in patients with PanC.

Identification of prognosis-related molecular subgroups based on DNA methylation in pancreatic cancer.

BACKGROUND: Pancreatic cancer (PC) is one of the most lethal and aggressive cancer malignancies. The lethality of PC is associated with delayed diagnosis, presence of distant metastasis, and its easy relapse. It is known that clinical treatment decisions are still mainly based on the clinical stage and pathological grade, which are insufficient to determine an appropriate treatment. Considering the significant heterogeneity of PC biological characteristics, the current clinical classificatory pattern relying solely on classical clinicopathological features identification needs to be urgently improved. In this study, we conducted in-depth analyses to establish prognosis-related molecular subgroups based on DNA methylation signature. RESULTS: DNA methylation, RNA sequencing, somatic mutation, copy number variation, and clinicopathological data of PC patients were obtained from The Cancer Genome Atlas (TCGA) dataset. A total of 178 PC samples were used to develop distinct molecular subgroups based on the 4227 prognosis-related CpG sites. By using consensus clustering analysis, four prognosis-related molecular subgroups were identified based on DNA methylation. The molecular characteristics and clinical features analyses based on the subgroups offered novel insights into the development of PC. Furthermore, we built a risk score model based on the expression data of five CpG sites to predict the prognosis of PC patients by using Lasso regression. Finally, the risk score model and other independent prognostic clinicopathological information were integrative utilised to construct a nomogram model. CONCLUSION: Novel prognosis-related molecular subgroups based on the DNA methylation signature were established. The specific five CpG sites model for PC prognostic prediction and the derived nomogram model are effective and intuitive tools. Moreover, the construction of molecular subgroups based on the DNA methylation data is an innovative complement to the traditional classification of PC and may contribute to precision medicine development, therapeutic efficacy prediction, and clinical decision guidance.

A Prognostic Prediction Model Developed Based on Four CpG Sites and Weighted Correlation Network Analysis Identified DNAJB1 as a Novel Biomarker for Pancreatic Cancer.

BACKGROUND: The prognosis of pancreatic cancer, which is among the solid tumors associated with high mortality, is poor. There is a need to improve the overall survival rate of patients with pancreatic cancer. MATERIALS AND METHODS: The Cancer Genome Atlas (TCGA) dataset with 153 samples and the International Cancer Genome Consortium (ICGC) dataset with 235 samples were used as the discovery and validation cohorts, respectively. The least absolute shrinkage and selection operator regression was used to construct the prognostic prediction model based on the DNA methylation markers. The predictive efficiency of the model was evaluated based on the calibration curve, concordance index, receiver operating characteristic curve, area under the curve, and decision curve. The xenograft model and cellular functional experiments were used to investigate the potential role of DNAJB1 in pancreatic cancer. RESULTS: A prognostic prediction model based on four CpG sites (cg00609645, cg13512069, cg23811464, and cg03502002) was developed using TCGA dataset. The model effectively predicted the overall survival rate of patients with pancreatic cancer, which was verified in the ICGC dataset. Next, a nomogram model based on the independent prognostic factors was constructed to predict the overall survival rate of patients with pancreatic cancer. The nomogram model had a higher predictive value than TCGA or ICGC datasets. The low-risk group with improved prognosis exhibited less mutational frequency and high immune infiltration. The brown module with 247 genes derived from the WGCNA analysis was significantly correlated with the prognostic prediction model, tumor grade, clinical stage, and T stage. The bioinformatic analysis indicated that DNAJB1 can serve as a novel biomarker for pancreatic cancer. DNAJB1 knockdown significantly inhibited the proliferation, migration, and invasion of pancreatic cancer cells in vivo and in vitro. CONCLUSION: The prognostic prediction model based on four CpG sites is a new method for predicting the prognosis of patients with pancreatic cancer. The molecular characteristic analyses, including Gene Ontology, Gene Set Enrichment Analysis, mutation spectrum, and immune infiltration of the subgroups, stratified by the model provided novel insights into the initiation and development of pancreatic cancer. DNAJB1 may serve as diagnostic and prognostic biomarkers for pancreatic cancer.

A hypoxia-related signature for clinically predicting diagnosis, prognosis and immune microenvironment of hepatocellular carcinoma patients.

BACKGROUND: Hypoxia plays an indispensable role in the development of hepatocellular carcinoma (HCC). However, there are few studies on the application of hypoxia molecules in the prognosis predicting of HCC. We aim to identify the hypoxia-related genes in HCC and construct reliable models for diagnosis, prognosis and recurrence of HCC patients as well as exploring the potential mechanism. METHODS: Differentially expressed genes (DEGs) analysis was performed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database and four clusters were determined by a consistent clustering analysis. Three DEGs closely related to overall survival (OS) were identified using Cox regression and LASSO analysis. Then the hypoxia-related signature was developed and validated in TCGA and International Cancer Genome Consortium (ICGC) database. The Gene Set Enrichment Analysis (GSEA) was performed to explore signaling pathways regulated by the signature. CIBERSORT was used for estimating the fractions of immune cell types. RESULTS: A total of 397 hypoxia-related DEGs in HCC were detected and three genes (PDSS1, CDCA8 and SLC7A11) among them were selected to construct a prognosis, recurrence and diagnosis model. Then patients were divided into high- and low-risk groups. Our hypoxia-related signature was significantly associated with worse prognosis and higher recurrence rate. The diagnostic model also accurately distinguished HCC from normal samples and nodules. Furthermore, the hypoxia-related signature could positively regulate immune response. Meanwhile, the high-risk group had higher fractions of macrophages, B memory cells and follicle-helper T cells, and exhibited higher expression of immunocheckpoints such as PD1and PDL1. CONCLUSIONS: Altogether, our study showed that hypoxia-related signature is a potential biomarker for diagnosis, prognosis and recurrence of HCC, and it provided an immunological perspective for developing personalized therapies.

HOXB5 promotes proliferation, migration, and invasion of pancreatic cancer cell through the activation of the GSK3ß/ß-catenin pathway.

Many homeobox (HOX) genes have been shown to be related to cancer progression. HOXB5, a member of the HOX genes, is overexpressed in retinoblastoma cancer and positively regulates the breast cancer cell proliferation as well as invasion. However, the role and underlying mechanism of HOXB5 in pancreatic cancer cells are still unclear. HOXB5 expression was measured in four pancreatic cancer cell lines, including PANC-1, ASPC-1, MIA-PaCa-2, and CFPAC-1. PANC-1 and ASPC-1 cells were selected for cell transfection experiments. Cell proliferation, migration, and invasion were measured by Cell Counting Kit-8 (CCK-8) assay, wound healing assay, and transwell assay. Expressions of epithelial-to-mesenchymal transition (EMT) markers were determined by western blotting. Immunofluorescence staining and cellular morphology were used to confirm the effect of HOXB5 dysregulation on pancreatic cancer cells. We found that HOXB5 was markedly expressed in pancreatic cancer cell lines. HOXB5 overexpression contributed to proliferation, migration, and invasion in ASPC-1 cells, whereas HOXB5 knockdown decreased proliferation, migration, and invasion of PANC-1 cells. Western blotting confirmed that overexpression of HOXB5 promoted the EMT process. Conversely, knockdown of HOXB5 alleviated EMT. Furthermore, knockdown of HOXB5 suppressed proliferation, migration, and invasion of pancreatic cancer cells via the Glycogen synthase kinase 3ß (GSK3ß)/ß-catenin pathway. Our study demonstrates that HOXB5 is a tumor promoter in pancreatic cancer, and the GSK3ß/ß-catenin pathway is important in HOXB5-induced proliferation, migration, and invasion in pancreatic cancer cells.

The miR-1224-5p/ELF3 Axis Regulates Malignant Behaviors of Pancreatic Cancer via PI3K/AKT/Notch Signaling Pathways.

PURPOSE: Aberrant expression of microRNAs contributes to the progression of pancreatic cancer by targeting downstream genes. A novel regulatory axis, miR-1224-5p/ELF3, was identified by bioinformatic analysis and experimental verification. Studies of the underlying molecular mechanisms behind this axis lead to a better understanding of the development of pancreatic cancer. MATERIALS AND METHODS: The differential expression of miR-1224-5p and ELF3 was verified based on Gene Expression Omnibus (GEO) datasets and clinical samples. The relationship between miR-1224-5p and ELF3 was demonstrated by luciferase assay and Western blot. The related signaling pathways of the miR-1224-5p/ELF3 axis in pancreatic cancer were investigated by gene set enrichment analysis (GSEA) and verified by Western blot. An analysis between ELF3 expression and immune infiltration was performed. Cellular and animal experiments were utilized to explore the effects of miR-1224-5p and ELF3 in pancreatic cancer. RESULTS: Suppressed expression of miR-1224-5p in pancreatic tumor tissues and cancer cells was identified first. Furthermore, miR-1224-5p is correlated with clinicopathological features, and decreased expression of miR-1224-5p indicates poor prognosis. miR-1224-5p serves as a tumor suppressor and inhibits malignant behaviors of pancreatic cancer based on in vivo and in vitro assays. The putative target gene ELF3 was predicted by bioinformatic analysis and confirmed by dual-luciferase reporter assay. Overexpression of ELF3 can improve the malignant behaviors of pancreatic cancer and demonstrates poor prognosis and advanced clinical stage. The inhibitory role of miR-1224-5p in pancreatic cancer is manifested by its direct targeting of ELF3. A negative correlation between ELF3 expression and immune cell infiltration was identified, suggesting an immunosuppressive state resulting from ELF3 overexpression. The PI3K/AKT/Notch signaling pathways and epithelial-to-mesenchymal transition (EMT) are important underlying mechanisms. CONCLUSION: The miR-1224-5p/ELF3 axis may serve as a new diagnostic, therapeutic, and prognostic biomarker in pancreatic cancer. The related PI3K/AKT/Notch/EMT signaling pathways greatly promote the elucidation of the progression of pancreatic cancer.

Multi-omics analysis based on integrated genomics, epigenomics and transcriptomics in pancreatic cancer.

Aim: Integrated analysis of genomics, epigenomics, transcriptomics and clinical information contributes to identify specific molecular subgroups and find novel biomarkers for pancreatic cancer. Materials & methods: The DNA copy number variation, the simple nucleotide variation, methylation and mRNA data of pancreatic cancer patients were obtained from The Cancer Genome Atlas. Four molecular subgroups (iC1, iC2, iC3 and iC4) of pancreatic cancer were identified by integrating analysis. Results: The iC1 subgroup harbors better prognosis, higher immune score, lesser DNA copy number variation mutations and better genomic stability compared with iC2, iC3 and iC4 subgroups. Three new genes (GRAP2, ICAM3 and A2ML1) correlated with prognosis were identified. Conclusion: Integrated multi-omics analysis provides fresh insight into molecular classification of pancreatic cancer, which may help discover new prognostic biomarkers and reveal the underlying mechanism of pancreatic cancer.

Identification of dissociation factors in pancreatic Cancer using a mass spectrometry-based proteomic approach.

BACKGROUD: Pancreatic cancer is a highly malignant tumor of the digestive system. This secretome of pancreatic cancer is key to its progression and metastasis. But different methods of protein extraction affect the final results. In other words, the real secretion of proteins in cancer cells has been changed. Based on mass spectrometry, we analyze the secretome from the serum-containing and serum-free medium, using different protein pretreatment methods. This study aims to identify dissociation factors in pancreatic cancer. METHODS: In this study, pancreatic cancer cells were cultured in serum-containing or serum-free medium, and the corresponding supernatants were extracted as samples. Subsequently, the above samples were separated by size exclusion chromatography (SEC), and peptide segments were identified by LC-MS/MS. The final results were identified via the hamster secreted protein database and a public database. RESULTS: Although the number of identified proteins in the serum-free medium group was high, the real secretion of proteins in pancreatic cancer cells was changed. There were six significant secreted proteins in the serum-containing medium group. Survival analysis via the TCGA database suggested that patients with higher expression levels of YWHAG showed a worse overall survival rate than those with lower YWHAG expression. CONCLUSIONS: Our study demonstrated the results in the serum-containing medium group were more similar to the real secretome of pancreatic cancer cells. YWHAG could be used as a prognostic indicator for pancreatic cancer.

Differential secretome of pancreatic cancer cells in serum-containing conditioned medium reveals CCT8 as a new biomarker of pancreatic cancer invasion and metastasis.

BACKGROUND: Pancreatic cancer is a malignancy with a very poor prognosis. The emergence of liquid biopsy is expected to achieve accurate early diagnosis through detection of tumor-derived secreted proteins in the blood. Early diagnosis and treatment of pancreatic cancer could help to improve prognosis. METHODS: The pretreatment approach of samples can have a major effect on downstream analysis. In this study, we used a pair of homologous pancreatic cancer cell supernatants with different capacities for invasion and metastasis to examine secreted proteins in the conditioned media without the removal of fetal bovine serum, namely through size exclusion chromatography combined with high-abundance protein affinity chromatography to enrich low-concentration protein, followed by mass spectrometry using triple dimethyl labeling. Identification of proteins was performed using an online public database and western blot. RESULTS: Mass spectrometry data revealed 77 proteins with quantitative properties, of which 12 proteins had over a 1.5-fold difference (in the supernatant of the highly invasive pancreatic cancer cell line PC-1.0, the expression of 8 proteins were increased and the expression of 4 proteins were decreased). Bioinformatics analysis results showed that CCT8, CTSL, SAA1, IGF2 are secreted via the exosome pathway. According to the literature, with the exception of CCT8, the other three proteins can be detected in blood samples of pancreatic cancer patients, and they can be used as prognostic markers. Western blot results were used to validate consistency with MS results. CONCLUSION: This study found that CCT8 can be used as a liquid biopsy marker to assess the prognosis of pancreatic cancer patients.

Regulatory Role of lncRNA NONHSAT089447 in the Dopamine Signaling Pathway in Schizophrenic Patients.

BACKGROUND We previously discovered that 3 long non-coding RNAs (lncRNAs) NONHSAT089447, NONHSAT021545, and NONHSAT041499 were differentially expressed in the peripheral blood of patients with schizophrenia, in comparison to those in normal healthy controls. In this study, we conducted bioinformatic analysis of these 3 lncRNAs and the regulatory role of lncRNA NONHSAT089447 in the dopamine signaling pathway in patients with schizophrenia. MATERIAL AND METHODS There lncRNAs in peripheral blood mononuclear cells (PBMCs) were screened using microarray analysis. Pearson's correlation analysis was performed to assess the levels of co-expressed mRNAs of respective lncRNAs. The Database for Annotation, Visualization and Integrated Discovery (DAVID) software was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes or Genomes (KEGG) enrichment analysis for these lncRNAs. Human neuroblastoma cell lines (SK-N-SH) were cultured and treated with dopamine or olanzapine (OLP), or transfected with siRNA targeting NONHSAT089447 or plasmid expressing NONHSAT089447. Levels of lncRNAs were detected by quantitative real-time reverse transcription polymerase chain reaction (RT-PCR). Then, mRNA and protein expression of the dopamine receptors DRD1, DRD2, DRD3, DRD4, and DRD5 were measured by RT-PCR and western blot analysis, respectively. RESULTS OLP treatment significantly inhibited the expression of NONHSAT089447. Knockdown of NONHSAT089447 by siRNA decreased DRD3 and DRD5 expression, while overexpression of NONHSAT089447 significantly upregulated expression of DRD3 and DRD5. Western blot analysis confirmed that levels of NONHSAT089447 regulated downstream DRD signaling. CONCLUSIONS Our results revealed that the lncRNA NONHSAT089447 participated in the dopamine signaling pathway via upregulation of DRDs.

Identification of RE1-Silencing Transcription Factor as a Promoter of Metastasis in Pancreatic Cancer.

Pancreatic cancer is characterized by its rapid progression and early metastasis. This requires further elucidation of the key promoters for its progression and metastasis. In this study, we identified REST as the hub gene of a gene module which is closely associated with cancer stage by weighted gene correlation network analysis. Validation with the TCGA database, western blot analysis of human pancreatic cancer cell lines (AsPC-1, Capan-2, SW-1990, and PANC-1) and immunohistochemical analysis of paraffin-embedded pancreatic cancer tissue sections showed that REST was enriched in tissue samples of advanced stage and metastatic phenotype cell lines. Survival analysis with the TCGA database and our own follow-up data suggested that patients with higher expression level of REST showed worse overall survival rate. In vitro functional experiments suggested that knockdown of REST suppressed proliferation, migration, invasion and epithelial-mesenchymal transition of AsPC-1 and PANC-1 cells. In vivo experiments (a subcutaneous BALB/c nude mouse model and a superior mesenteric vein injection BALB/c nude mouse model) suggested that knockdown of REST suppressed growth and metastasis of xenograft tumor. Finally, we investigated the underlying molecular mechanism of REST and identified REST as a potential downstream target of MAPK signaling pathway. In conclusion, our results of bioinformatic analysis, in vitro and in vivo functional analysis suggested that REST may serve as a promoter of metastasis in pancreatic cancer.

Storage quality of walnut oil containing lycopene during accelerated oxidation.

The purpose of investigation was to assess the effect of lycopene on the peroxide value, acid value, fatty acids, total phenolic content and ferric-reducing antioxidant power of walnut oil. Walnut oil was extracted from Xinjiang walnut variety using cold pressing method. Our study reported that after 45 days of accelerated oxidation at 60 °C (Schaal oven test), 0.005% lycopene exhibited the greatest antioxidant effect than other addition levels of lycopene. Therefore, under ambient storage conditions, the shelf-life of walnut oil could be extended up to 16 months by 0.005% lycopene. Moreover, 0.005% lycopene added to walnut oil had a significantly higher content of saturated fatty acid, unsaturated fatty acid, total phenol, reducing ability of the polar and non-polar components than the blank sample (walnut oil without any addition of lycopene). In conclusion, lycopene improved the quality of walnut oil because of its antioxidant effect against lipid oxidation.