Association of epilepsy, anti-epileptic drugs (AEDs), and type 2 diabetes mellitus (T2DM): a population-based cohort retrospective study, impact of AEDs on T2DM-related molecular pathway, and via peroxisome proliferator-activated receptor γ transactivation

Introduction

A potential association between epilepsy and subsequent type 2 diabetes mellitus (T2DM) has emerged in recent studies. However, the association between epilepsy, anti-epileptic drugs (AEDs), and the risk of T2DM development remains controversial. We aimed to conduct a nationwide, population-based, retrospective, cohort study to evaluate this relationship.

Methods

We extracted data from the Taiwan Longitudinal Generation Tracking Database of patients with new-onset epilepsy and compared it with that of a comparison cohort of patients without epilepsy. A Cox proportional hazards regression model was used to analyze the difference in the risk of developing T2DM between the two cohorts. Next-generation RNA sequencing was used to characterize T2DM-related molecularchanges induced by AEDs and the T2DM-associated pathways they alter. The potential of AEDs to induce peroxisome proliferator-activated receptor γ (PPARγ) transactivation was also evaluated.

Results

After adjusting for comorbidities and confounding factors, the case group (N = 14,089) had a higher risk for T2DM than the control group (N = 14,089) [adjusted hazards ratio (aHR), 1.27]. Patients with epilepsy not treated with AEDs exhibited a significantly higher risk of T2DM (aHR, 1.70) than non-epileptic controls. In those treated with AEDs, the risk of developing T2DM was significantly lower than in those not treated (all aHR ≤ 0.60). However, an increase in the defined daily dose of phenytoin (PHE), but not of valproate (VPA), increased the risk of T2DM development (aHR, 2.28). Functional enrichment analysis of differentially expressed genes showed that compared to PHE, VPA induced multiple beneficial genes associated with glucose homeostasis. Among AEDs, VPA induced the specific transactivation of PPARγ.

Discussion

Our study shows epilepsy increases the risk of T2DM development, however, some AEDs such as VPA might yield a protective effect against it. Thus, screening blood glucose levels in patients with epilepsy is required to explore the specific role and impact of AEDs in the development of T2DM. Future in depth research on the possibility to repurpose VPA for the treatment of T2DM, will offer valuable insight regarding the relationship between epilepsy and T2DM.

Cardiothoracic ratio values and trajectories are associated with risk of requiring dialysis and mortality in chronic kidney disease

BACKGROUND

The prognostic role of the cardiothoracic ratio (CTR) in chronic kidney disease (CKD) remains undetermined.

METHODS

We conducted a retrospective cohort study of 3117 patients with CKD aged 18-89 years who participated in an Advanced CKD Care Program in Taiwan between 2003 and 2017 with a median follow up of 1.3(0.7-2.5) and 3.3(1.8-5.3) (IQR) years for outcome of end-stage renal disease (ESRD) and overall death, respectively. We developed a machine learning (ML)-based algorithm to calculate the baseline and serial CTRs, which were then used to classify patients into trajectory groups based on latent class mixed modelling. Association and discrimination were evaluated using multivariable Cox proportional hazards regression analyses and C-statistics, respectively.

RESULTS

The median (interquartile range) age of 3117 patients is 69.5 (59.2-77.4) years. We create 3 CTR trajectory groups (low [30.1%], medium [48.1%], and high [21.8%]) for the 2474 patients with at least 2 CTR measurements. The adjusted hazard ratios for ESRD, cardiovascular mortality, and all-cause mortality in patients with baseline CTRs ≥0.57 (vs CTRs <0.47) are 1.35 (95% confidence interval, 1.06-1.72), 2.89 (1.78-4.71), and 1.50 (1.22-1.83), respectively. Similarly, greater effect sizes, particularly for cardiovascular mortality, are observed for high (vs low) CTR trajectories. Compared with a reference model, one with CTR as a continuous variable yields significantly higher C-statistics of 0.719 (vs 0.698, P = 0.04) for cardiovascular mortality and 0.697 (vs 0.693, P < 0.001) for all-cause mortality.

CONCLUSIONS

Our findings support the real-world prognostic value of the CTR, as calculated by a ML annotation tool, in CKD. Our research presents a methodological foundation for using machine learning to improve cardioprotection among patients with CKD.

Cross-Platform in-silico Analyses Exploring Tumor Immune Microenvironment with Prognostic Value in Triple-Negative Breast Cancer

INTRODUCTION

Only a proportion of triple-negative breast cancer (TNBC) is immunotherapy-responsive. We hypothesized that the tumor microenvironment (TME) influences the outcomes of TNBC and investigated the relevant signaling pathways.

MATERIALS AND METHODS

Immune score (IS) and stromal score (SS) were calculated using the ESTIMATE and correlated with the overall survival (OS) in TNBC. RNA-seq data from 115 TNBC samples and 112 normal adjacent tissues were retrieved. Validations in the methylation levels in 10 TNBC and five non-TNBC cell lines were obtained. Cox model overall survival (OS) validated the derived transcription factor (TF) genes in cBioPortal breast cancer patients.

RESULTS

SS-low predicts a higher OS compared with SS-high patients (P = 0.0081 IS-high/SS-low patients had better OS (P = 0.045) than IS-low/SS-high patients. More macrophages were polarized to the M2 state in patients with IS-low/SS-high patients (P < 0.001). Moreover, CIBERSORTx showed more CD8+ cytotoxic T-cells in IS-high/SS-low patients (p = 0.0286) and more resting NK cells in the IS-low/SS-high TME (P = 0.0108). KEGG pathway analysis revealed that overexpressed genes were enriched in the IL-17 and cytokine-cytokine receptor interaction pathways. The lncRNA DRAIC, a tumor suppressor, was consistently deactivated in the 10 TNBC cell lines. On the cBioPortal platform, we validated that 13% of ER-negative, HER2-unamplified BC harbored IL17RA deep deletion and 25% harbored TRAF3IP2 amplification. On cBioPortal datasets, the nine altered TF genes derived from the X2K analysis showed significantly worse relapse-free survival in 2377 patients and OS in 4819 invasive BC patients than in the unaltered cohort.

CONCLUSION

Of note, the results of this integrated in silico study can only be generalized to approximately 17% of patients with TNBC, in which infiltrating stromal cells and immune cells play a determinant prognostic role.

LASSO and Bioinformatics Analysis in the Identification of Key Genes for Prognostic Genes of Gynecologic Cancer

The aim of this study is to identify potential biomarkers for early diagnosis of gynecologic cancer in order to improve survival. Cervical cancer (CC) and endometrial cancer (EC) are the most common malignant tumors of gynecologic cancer among women in the world. As the underlying molecular mechanisms in both cervical and endometrial cancer remain unclear, a comprehensive and systematic bioinformatics analysis is required. In our study, gene expression profiles of GSE9750, GES7803, GES63514, GES17025, GES115810, and GES36389 downloaded from Gene Expression Omnibus (GEO) were utilized to analyze differential gene expression between cancer and normal tissues. A total of 78 differentially expressed genes (DEGs) common to CC and EC were identified to perform the functional enrichment analyses, including gene ontology and pathway analysis. KEGG pathway analysis of 78 DEGs indicated that three main types of pathway participate in the mechanism of gynecologic cancer such as drug metabolism, signal transduction, and tumorigenesis and development. Furthermore, 20 diagnostic signatures were confirmed using the least absolute shrink and selection operator (LASSO) regression with 10-fold cross validation. Finally, we used the GEPIA2 online tool to verify the expression of 20 genes selected by the LASSO regression model. Among them, the expression of PAMR1 and SLC24A3 in tumor tissues was downregulated significantly compared to the normal tissue, and found to be statistically significant in survival rates between the CC and EC of patients (p < 0.05). The two genes have their function: (1.) PAMR1 is a tumor suppressor gene, and many studies have proven that overexpression of the gene markedly suppresses cell growth, especially in breast cancer and polycystic ovary syndrome; (2.) SLC24A3 is a sodium–calcium regulator of cells, and high SLC24A3 levels are associated with poor prognosis. In our study, the gene signatures can be used to predict CC and EC prognosis, which could provide novel clinical evidence to serve as a potential biomarker for future diagnosis and treatment.

Prediction of non-responsiveness to pre-dialysis care program in patients with chronic kidney disease: a retrospective cohort analysis

The responsiveness of patients with chronic kidney disease (CKD) to nephrologists’ care is unpredictable. We defined the longitudinal stages (LSs) 1–5 of estimated glomerular filtration rate (eGFR) by group-based trajectory modeling for repeated eGFR measurements of 7135 patients with CKD aged 20–90 years from a 13-year pre-end-stage renal disease (ESRD) care registry. Patients were considered nonresponsive to the pre-dialysis care if they had a more advanced eGFR LS compared with the baseline. Conversely, those with improved or stable eGFR LS were considered responsive. The proportion of patients with CKD stage progression increased with the increase in the baseline CKD stage (stages 1–2: 29.2%; stage 4: 45.8%). The adjusted times to ESRD and all-cause mortality in patients with eGFR LS-5 were 92% (95% confidence interval [CI] 86–96%) and 57% (95% CI 48–65%) shorter, respectively, than in patients with eGFR LS-3A. Among patients with baseline CKD stages 3 and 4, the adjusted times to ESRD and all-cause death in the nonresponsive patients were 39% (95% CI 33–44%) and 20% (95% CI 14–26%) shorter, respectively, than in the responsive patients. Our proposed Renal Care Responsiveness Prediction (RCRP) model performed significantly better than the conventional Kidney Failure Risk Equation in discrimination, calibration, and net benefit according to decision curve analysis. Non-responsiveness to nephrologists’ care is associated with rapid progression to ESRD and all-cause mortality. The RCRP model improves early identification of responsiveness based on variables collected during enrollment in a pre-ESRD program. Urgent attention should be given to characterize the underlying heterogeneous responsiveness to pre-dialysis care.

Abstract 2719: Interleukin-17 and cytokine-related signalings are determinants for tumor immune microenvironment in triple-negative breast cancer: in silico integrated analysis

Introduction: Programmed death (PD)-1/PD-ligand 1 immunotherapy increases the pathological complete response rate by 13.6 percentage points when added to neoadjuvant chemotherapy for early triple-negative breast cancer (TNBC) (Schmid et al. 2020). This indicates a proportion of TNBC are immune-responsive while many are not. We hypothesized that the tumor immune microenvironment might influence the clinical outcomes of TNBC patients. We wanted to investigate which signaling pathways could determine the TNBC being immune-hot or cold and have prognostication capability.

Methods: Dataset: TCGA-BRCA. Immune score (IS) and stromal score (SS) were calculated from the ESTIMATE and correlated with the documented overall survival. CIBERSORTx and Timer 2.0 were adopted for fractions of immune cell analysis. Differentially expressed genes (DEGs) were identified. Gene Ontology analysis and KEGG were adopted to study the enrichment of the gene sets. We explored and queried the cBioPortal for cancer genomics.

RESULTS: 115 patients with triple-negative breast cancer and 112 normal adjacent tissues were retrieved. The stromal score was high in 12 patients, and the immune score was high in another 12 patients. On Kaplan-Meier analyses, SS-low predicts higher overall survival (OS) vis-à-vis SS-high patients (P = 0.0081), while IS-high predicts higher OS as compared with IS-low patients (P = 0.2, too few cases in the IS-high). When compared with IS-low/SS-high patients, IS-high/SS-low patients had better OS (P = 0.045). In the tumor microenvironment (TME), a higher proportion of macrophages are in the M2 state in patients with IS-low/SS-high patients (P &lt; 0.001). More CD8+ cytotoxic T-cells in IS-high/SS-low patients (14.8% vs. 3.7%, p = 0.0286). More resting NK cells in IS-low/SS-high TME (P = 0.0108). DEGs analysis shows 651 DEGs (284 upregulated, 367 down) in IS-high/SS-low TME, whereas there were 370 DEGs (187 upregulated, 183 down) in IS-low/SS-high patients. The KEGG pathway analysis reveals the DEGs were enriched in the IL-17 signaling pathway and the cytokine-cytokine receptor interaction pathway. IL-17 is a proinflammatory cytokine that signals mainly via TRAF3 Interacting Protein 2 (TRAF3IP2), an inflammatory mediator and upstream regulator of several crucial transcription factors such as AP-1 and NF-κB. On the cBioPortal platform, we discovered that 13% of ER-negative, HER2-FISH-unamplified breast cancers harbor IL17RA deep deletion and 25% with TRAF3IP2 amplification.

Conclusions: The tumor microenvironment with each immune cell component determines the impact on women's survival with TNBC. IS-high/SS-low TME portends a better overall survival. We propose further studies to examine if an immune/stromal state also predicts the response to immunotherapy.

Citation Format: Victor C. Kok, Charles C. N. Wang, Szu-Han Liao, De-Lun Chen. Interleukin-17 and cytokine-related signalings are determinants for tumor immune microenvironment in triple-negative breast cancer: in silico integrated analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2719.

Abstract 2719: Interleukin-17 and cytokine-related signalings are determinants for tumor immune microenvironment in triple-negative breast cancer: in silico integrated analysis

Introduction: Programmed death (PD)-1/PD-ligand 1 immunotherapy increases the pathological complete response rate by 13.6 percentage points when added to neoadjuvant chemotherapy for early triple-negative breast cancer (TNBC) (Schmid et al. 2020). This indicates a proportion of TNBC are immune-responsive while many are not. We hypothesized that the tumor immune microenvironment might influence the clinical outcomes of TNBC patients. We wanted to investigate which signaling pathways could determine the TNBC being immune-hot or cold and have prognostication capability.

Methods: Dataset: TCGA-BRCA. Immune score (IS) and stromal score (SS) were calculated from the ESTIMATE and correlated with the documented overall survival. CIBERSORTx and Timer 2.0 were adopted for fractions of immune cell analysis. Differentially expressed genes (DEGs) were identified. Gene Ontology analysis and KEGG were adopted to study the enrichment of the gene sets. We explored and queried the cBioPortal for cancer genomics.

RESULTS: 115 patients with triple-negative breast cancer and 112 normal adjacent tissues were retrieved. The stromal score was high in 12 patients, and the immune score was high in another 12 patients. On Kaplan-Meier analyses, SS-low predicts higher overall survival (OS) vis-à-vis SS-high patients (P = 0.0081), while IS-high predicts higher OS as compared with IS-low patients (P = 0.2, too few cases in the IS-high). When compared with IS-low/SS-high patients, IS-high/SS-low patients had better OS (P = 0.045). In the tumor microenvironment (TME), a higher proportion of macrophages are in the M2 state in patients with IS-low/SS-high patients (P &lt; 0.001). More CD8+ cytotoxic T-cells in IS-high/SS-low patients (14.8% vs. 3.7%, p = 0.0286). More resting NK cells in IS-low/SS-high TME (P = 0.0108). DEGs analysis shows 651 DEGs (284 upregulated, 367 down) in IS-high/SS-low TME, whereas there were 370 DEGs (187 upregulated, 183 down) in IS-low/SS-high patients. The KEGG pathway analysis reveals the DEGs were enriched in the IL-17 signaling pathway and the cytokine-cytokine receptor interaction pathway. IL-17 is a proinflammatory cytokine that signals mainly via TRAF3 Interacting Protein 2 (TRAF3IP2), an inflammatory mediator and upstream regulator of several crucial transcription factors such as AP-1 and NF-κB. On the cBioPortal platform, we discovered that 13% of ER-negative, HER2-FISH-unamplified breast cancers harbor IL17RA deep deletion and 25% with TRAF3IP2 amplification.

Conclusions: The tumor microenvironment with each immune cell component determines the impact on women's survival with TNBC. IS-high/SS-low TME portends a better overall survival. We propose further studies to examine if an immune/stromal state also predicts the response to immunotherapy.

Citation Format: Victor C. Kok, Charles C. N. Wang, Szu-Han Liao, De-Lun Chen. Interleukin-17 and cytokine-related signalings are determinants for tumor immune microenvironment in triple-negative breast cancer: in silico integrated analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2719.

Abstract 2719: Interleukin-17 and cytokine-related signalings are determinants for tumor immune microenvironment in triple-negative breast cancer: in silico integrated analysis

Introduction: Programmed death (PD)-1/PD-ligand 1 immunotherapy increases the pathological complete response rate by 13.6 percentage points when added to neoadjuvant chemotherapy for early triple-negative breast cancer (TNBC) (Schmid et al. 2020). This indicates a proportion of TNBC are immune-responsive while many are not. We hypothesized that the tumor immune microenvironment might influence the clinical outcomes of TNBC patients. We wanted to investigate which signaling pathways could determine the TNBC being immune-hot or cold and have prognostication capability.

Methods: Dataset: TCGA-BRCA. Immune score (IS) and stromal score (SS) were calculated from the ESTIMATE and correlated with the documented overall survival. CIBERSORTx and Timer 2.0 were adopted for fractions of immune cell analysis. Differentially expressed genes (DEGs) were identified. Gene Ontology analysis and KEGG were adopted to study the enrichment of the gene sets. We explored and queried the cBioPortal for cancer genomics.

RESULTS: 115 patients with triple-negative breast cancer and 112 normal adjacent tissues were retrieved. The stromal score was high in 12 patients, and the immune score was high in another 12 patients. On Kaplan-Meier analyses, SS-low predicts higher overall survival (OS) vis-à-vis SS-high patients (P = 0.0081), while IS-high predicts higher OS as compared with IS-low patients (P = 0.2, too few cases in the IS-high). When compared with IS-low/SS-high patients, IS-high/SS-low patients had better OS (P = 0.045). In the tumor microenvironment (TME), a higher proportion of macrophages are in the M2 state in patients with IS-low/SS-high patients (P &lt; 0.001). More CD8+ cytotoxic T-cells in IS-high/SS-low patients (14.8% vs. 3.7%, p = 0.0286). More resting NK cells in IS-low/SS-high TME (P = 0.0108). DEGs analysis shows 651 DEGs (284 upregulated, 367 down) in IS-high/SS-low TME, whereas there were 370 DEGs (187 upregulated, 183 down) in IS-low/SS-high patients. The KEGG pathway analysis reveals the DEGs were enriched in the IL-17 signaling pathway and the cytokine-cytokine receptor interaction pathway. IL-17 is a proinflammatory cytokine that signals mainly via TRAF3 Interacting Protein 2 (TRAF3IP2), an inflammatory mediator and upstream regulator of several crucial transcription factors such as AP-1 and NF-κB. On the cBioPortal platform, we discovered that 13% of ER-negative, HER2-FISH-unamplified breast cancers harbor IL17RA deep deletion and 25% with TRAF3IP2 amplification.

Conclusions: The tumor microenvironment with each immune cell component determines the impact on women's survival with TNBC. IS-high/SS-low TME portends a better overall survival. We propose further studies to examine if an immune/stromal state also predicts the response to immunotherapy.

Citation Format: Victor C. Kok, Charles C. N. Wang, Szu-Han Liao, De-Lun Chen. Interleukin-17 and cytokine-related signalings are determinants for tumor immune microenvironment in triple-negative breast cancer: in silico integrated analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2719.

Repeated centrifuging and washing concentrates bacterial samples in peritoneal dialysis for optimal culture: an original article

Background

Bacterial cultures allow the identification of infectious disease pathogens. However, obtaining the results of conventional culture methods is time-consuming, taking at least two days. A more efficient alternative is the use of concentrated bacterial samples to accelerate culture growth. Our study focuses on the development of a high-yield sample concentrating technique.

Results

A total of 71 paired samples were obtained from patients on peritoneal dialysis (PD). The peritoneal dialysates were repeat-centrifuged and then washed with saline, namely the centrifuging and washing method (C&W method). The concentrated samples were Gram-stained and inoculated into culture plates. The equivalent unprocessed dialysates were cultured as the reference method. The times until culture results for the two methods were compared. The reference method yielded no positive Gram stain results, but the C&W method immediately gave positive Gram stain results for 28 samples (p < 0.001). The culture-negative rate was lower in the C&W method (5/71) than in the reference method (13/71) (p = 0.044). The average time for bacterial identification achieved with the C&W method (22.0 h) was shorter compared to using the reference method (72.5 h) (p < 0.001).

Conclusions

The C&W method successfully concentrated bacterial samples and superseded blood culture bottles for developing adequate bacterial cultures. The C&W method may decrease the culture report time, thus improving the treatment of infectious diseases.

Association of diabetes, education level, and care dependency with use of temporary vascular access in patients with chronic kidney disease

OBJECTIVE

Temporary vascular access (TVA) is frequently used during the first dialysis in patients with chronic kidney disease (CKD), and it is associated with an increased risk of infection, central vein stenosis, and mortality. Here, factors associated with TVA in patients with CKD were explored.

METHODS

This study included patients in a single-center CKD care program who initiated long-term renal replacement therapy. The primary outcome was TVA use at first dialysis. Factors possibly associated with TVA use were analyzed using Cox regression.

RESULTS

Temporary vascular access was used in 53.2% of the patients at first dialysis. In total, 73.2% (n = 865) and 26.8% (n = 317) of the patients were on hemodialysis and peritoneal dialysis, respectively. Multivariate Cox regression analysis showed that TVA use in patients with CKD was associated with diabetes (hazard ratio [HR] 1.52, 95% confidence interval [CI] 1.28-1.81, p < 0.001), lower albumin (HR 0.82, 95% CI 0.75-0.91, p < 0.001), lower education level (HR 0.75, 95% CI 0.56-1.00, p = 0.055), and total care dependency (HR 1.92, CI 1.44-3.43, p = 0.003).

CONCLUSION

Diabetes, education level, and care dependency are associated with TVA at dialysis initiation in patients with CKD.

Identification of most influential co-occurring gene suites for gastrointestinal cancer using biomedical literature mining and graph-based influence maximization

Background

Gastrointestinal (GI) cancer including colorectal cancer, gastric cancer, pancreatic cancer, etc., are among the most frequent malignancies diagnosed annually and represent a major public health problem worldwide.

Methods

This paper reports an aided curation pipeline to identify potential influential genes for gastrointestinal cancer. The curation pipeline integrates biomedical literature to identify named entities by Bi-LSTM-CNN-CRF methods. The entities and their associations can be used to construct a graph, and from which we can compute the sets of co-occurring genes that are the most influential based on an influence maximization algorithm.

Results

The sets of co-occurring genes that are the most influential that we discover include RARA - CRBP1, CASP3 - BCL2, BCL2 - CASP3 – CRBP1, RARA - CASP3 – CRBP1, FOXJ1 - RASSF3 - ESR1, FOXJ1 - RASSF1A - ESR1, FOXJ1 - RASSF1A - TNFAIP8 - ESR1. With TCGA and functional and pathway enrichment analysis, we prove the proposed approach works well in the context of gastrointestinal cancer.

Conclusions

Our pipeline that uses text mining to identify objects and relationships to construct a graph and uses graph-based influence maximization to discover the most influential co-occurring genes presents a viable direction to assist knowledge discovery for clinical applications.

Wilforine resensitizes multidrug resistant cancer cells via competitive inhibition of P-glycoprotein

BACKGROUND AND PURPOSE

Multidrug resistance (MDR) remains the main obstacle in cancer treatment and overexpression of P-glycoprotein (P-gp) is one of the most common causes of chemoresistance. The development of novel P-gp inhibitors from natural products is a prospective strategy to combat MDR cancers. Among the natural sesquiterpene compounds, sesquiterpene pyridine alkaloids exhibit various biological properties. Therefore, in the present study, we evaluated the modulatory effects of wilforine on P-gp expression and function. The molecular mechanisms and kinetic models of wilforine-mediated P-gp inhibition were further investigated.

METHODS

The human P-gp stable expression cells (ABCB1/Flp-In^TM-293) and human cervical cancer cells (sensitive: HeLaS3; MDR: KBvin) were used. The cell viability was assessed by SRB assay. The inhibitory effect of wilforine on P-gp efflux and the underlying mechanism were evaluated by assays for calcein-AM uptake, rhodamine123 and doxorubicin efflux, ATPase activity, real-time quantitative RT-PCR, apoptosis, and cell cycle analysis. Molecular docking was performed by the docking software CDOCKER with BIOVIA Discovery Studio 4.5 (D.S. 4.5).

RESULTS

We found that wilforine significantly inhibited the efflux activity of P-gp in a concentration-dependent manner. Further kinetic analysis demonstrated that wilforine significantly inhibited P-gp efflux function by competitive inhibition and stimulated the basal P-gp ATPase activity. In addition, wilforine re-sensitized MDR cancer cells to chemotherapeutic drugs. The docking model indicated that wilforine was bound to residues of P-gp such as LEU884, LYS887, THR176 and ASN172.

CONCLUSION

These results suggest a novel future therapeutic strategy for MDR cancer using wilforine as an adjuvant treatment with chemotherapy.

Text mining in a literature review of urothelial cancer using topic model

Background

Urothelial cancer (UC) includes carcinomas of the bladder, ureters, and renal pelvis. New treatments and biomarkers of UC emerged in this decade. To identify the key information in a vast amount of literature can be challenging. In this study, we use text mining to explore UC publications to identify important information that may lead to new research directions.

Method

We used topic modeling to analyze the titles and abstracts of 29,883 articles of UC from Pubmed, Web of Science, and Embase in Mar 2020. We applied latent Dirichlet allocation modeling to extract 15 topics and conducted trend analysis. Gene ontology term enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed to identify UC related pathways.

Results

There was a growing trend regarding UC treatment especially immune checkpoint therapy but not the staging of UC. The risk factors of UC carried in different countries such as cigarette smoking in the United State and aristolochic acid in Taiwan and China. GMCSF, IL-5, Syndecan-1, ErbB receptor, integrin, c-Met, and TRAIL signaling pathways are the most relevant biological pathway associated with UC.

Conclusions

The risk factors of UC may be dependent on the countries and GMCSF, IL-5, Syndecan-1, ErbB receptor, integrin, c-Met, and TRAIL signaling pathways are the most relevant biological pathway associated with UC. These findings may provide further UC research directions.

Identification of Hub Genes Associated With Development of Head and Neck Squamous Cell Carcinoma by Integrated Bioinformatics Analysis

Improved insight into the molecular mechanisms of head and neck squamous cell carcinoma (HNSCC) is required to predict prognosis and develop a new therapeutic strategy for targeted genes. The aim of this study is to identify significant genes associated with HNSCC and to further analyze its prognostic significance. In our study, the cancer genome atlas (TCGA) HNSCC database and the gene expression profiles of GSE6631 from the Gene Expression Omnibus (GEO) were used to explore the differential co-expression genes in HNSCC compared with normal tissues. A total of 29 differential co-expression genes were screened out by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. As suggested in functional annotation analysis using the R clusterProfiler package, these genes were mainly enriched in epidermis development and differentiation (biological process), apical plasma membrane and cell-cell junction (cellular component), and enzyme inhibitor activity (molecular function). Furthermore, in a protein-protein interaction (PPI) network containing 21 nodes and 25 edges, the ten hub genes (S100A8, S100A9, IL1RN, CSTA, ANXA1, KRT4, TGM3, SCEL, PPL, and PSCA) were identified using the CytoHubba plugin of Cytoscape. The expression of the ten hub genes were all downregulated in HNSCC tissues compared with normal tissues. Based on survival analysis, the lower expression of CSTA was associated with worse overall survival (OS) in patients with HNSCC. Finally, the protein level of CSTA, which was validated by the Human Protein Atlas (HPA) database, was down-regulated consistently with mRNA levels in head and neck cancer samples. In summary, our study demonstrated that a survival-related gene is highly correlated with head and neck cancer development. Thus, CSTA may play important roles in the progression of head and neck cancer and serve as a potential biomarker for future diagnosis and treatment.

Identification of Prognostic Candidate Genes in Breast Cancer by Integrated Bioinformatic Analysis

Breast cancer is one of the most common malignancies. However, the molecular mechanisms underlying its pathogenesis remain to be elucidated. The present study aimed to identify the potential prognostic marker genes associated with the progression of breast cancer. Weighted gene coexpression network analysis was used to construct free-scale gene coexpression networks, evaluate the associations between the gene sets and clinical features, and identify candidate biomarkers. The gene expression profiles of GSE48213 were selected from the Gene Expression Omnibus database. RNA-seq data and clinical information on breast cancer from The Cancer Genome Atlas were used for validation. Four modules were identified from the gene coexpression network, one of which was found to be significantly associated with patient survival time. The expression status of 28 genes formed the black module (basal); 18 genes, dark red module (claudin-low); nine genes, brown module (luminal), and seven genes, midnight blue module (nonmalignant). These modules were clustered into two groups according to significant difference in survival time between the groups. Therefore, based on betweenness centrality, we identified TXN and ANXA2 in the nonmalignant module, TPM4 and LOXL2 in the luminal module, TPRN and ADCY6 in the claudin-low module, and TUBA1C and CMIP in the basal module as the genes with the highest betweenness, suggesting that they play a central role in information transfer in the network. In the present study, eight candidate biomarkers were identified for further basic and advanced understanding of the molecular pathogenesis of breast cancer by using co-expression network analysis.

Demethoxycurcumin sensitizes the response of non-small cell lung cancer to cisplatin through downregulation of TP and ERCC1-related pathways

BACKGROUND

Excision repair cross-complementary 1 (ERCC1) overexpression in lung cancer cells is strongly correlated with its resistance to platinum-based chemotherapy. Overexpression of thymidine phosphorylase (TP) reverts platinum-induced cancer cell death.

PURPOSE

Curcumin has been reported to enhance antitumor properties through the suppression of TP and ERCC1 in non-small cell lung carcinoma cells (NSCLC). Nevertheless, whether two other curcuminoids, demethoxycurcumin (DMC) and bisdemethoxycurcumin (BDMC) from Curcuma longa demonstrate antitumor activity like that of curcumin remain unknown.

METHODS

MTT assay was conducted to determine the cell cytotoxicity. Western blotting was used to determine the protein expressions. Docking is the virtual screening of a database of compounds and predicting the strongest binders based on various scoring functions. BIOVIA Discovery Studio 4.5 (D.S. 4.5) were used for docking.

RESULTS

Firstly, when compared with curcumin and BDMC, DMC exhibited the most potent cytotoxic effect on NSCLC, most importantly, MRC-5, a lung fetal fibroblast, was insensitive to DMC (under 30 µM). Secondly, DMC alone significantly inhibited on-target cisplatin (CDDP) resistance protein, ERCC1, via PI3K-Akt-snail pathways, and TP protein expression in A549 cells. Thirdly, DMC treatment markedly increased post-target CDDP resistance pathway including Bax and cytochrome c. DMC significantly decreased Bcl-2 protein expressions. Finally, MTT assay indicated that DMC significantly increased CDDP-induced cytotoxicity and was confirmed with an increased Bax/Bcl-2 ratio, indicating upregulation of caspase-3.

CONCLUSIONS

We concluded that enhancement of the cytotoxicity to CDDP by coadminstration with DMC was mediated by down-regulation of the expression of TP and ERCC1, regulated by PI3K-Akt-Snail pathway inactivation.

Tenulin and isotenulin inhibit P-glycoprotein function and overcome multidrug resistance in cancer cells

BACKGROUND

Multidrug resistance (MDR) in cancer is one of the main obstacles in treatment with chemotherapy. Drug efflux through P-glycoprotein is the major mechanism involved in MDR. A potential strategy to provide the best possible clinical outcomes is to develop P-glycoprotein (P-gp) inhibitors from natural products.

PURPOSE

The present study investigated the effects of the natural sesquiterpene lactone tenulin and its derivative isotenulin on human P-gp; the mechanisms of kinetic interactions were also explored.

METHODS

The human P-gp (ABCB1/Flp-In™-293) stable expression cells were established by using the Flp-In™ system. The effects of tenulin and isotenulin on cell viability were evaluated by SRB assays in established cell lines, sensitive cancer cell line (HeLaS3), and resistant cancer cell line (KB-vin). The transporter inhibition ability was evaluated by calcein-AM uptake assays. The P-gp inhibition kinetics of tenulin and isotenulin were evaluated by rhodamine123 and doxorubicin efflux assays. The ATPase activity was evaluated with the Pgp-Glo™ Assay System.

RESULTS

Tenulin and isotenulin significantly inhibited the P-gp efflux function by stimulating P-gp ATPase activity. Tenulin and isotenulin interacted with the effluxes of rhodamine 123 and doxorubicin through a competitive and noncompetitive mechanism, respectively. The combinations of tenulin and isotenulin with chemotherapeutic drugs significantly resensitized MDR cancer cells.

CONCLUSION

These results suggested that tenulin and isotenulin are potential candidates to be developed for synergistic treatment of MDR cancers.

Taxifolin Resensitizes Multidrug Resistance Cancer Cells via Uncompetitive Inhibition of P-Glycoprotein Function

P-glycoprotein (P-gp) effluxes lots of chemotherapeutic agents and leads to multidrug resistance (MDR) in cancer treatments. The development of P-gp inhibitors from natural products provide a potential strategy for the beneficial clinical outcomes. This study aimed to evaluate the effects of the natural flavonoid taxifolin, luteolin, (-)-gallocatechin, and (-)-catechin on human P-gp activity. The kinetic interactions and underlying mechanisms of taxifolin-mediated transporter inhibition were further investigated. The transporter inhibition ability was evaluated in human P-gp stable expression cells (ABCB1/Flp-InTM-293) by calcein-AM uptake assays. The kinetics study for P-gp inhibition was evaluated by doxorubicin and rhodamine123 efflux assays. The MDR reversal ability of taxifolin were performed by SRB assays to detect the cell viability in sensitive cancer cell line (HeLaS3), and resistant cancer cell line (KB-vin). Cell cycle analysis and ABCB1 real-time RT-PCR were used for mechanical exploration. The results demonstrated that taxifolin decreased ABCB1 expression in a concentration-dependent manner. The function of P-gp was inhibited by taxifolin through uncompetitive inhibition of rhodamine 123 and doxorubicin efflux. The combination of taxifolin significantly resensitized MDR cancer cells to chemotherapeutic agents. These results suggested that taxifolin may be considered as a potential P-gp modulator for synergistic treatment of MDR cancers.

Ursolic Acid, a Novel Liver X Receptor α (LXRα) Antagonist Inhibiting Ligand-Induced Nonalcoholic Fatty Liver and Drug-Induced Lipogenesis

Nonalcoholic fatty liver disease (NAFLD) is a very common liver disease, and its incidence has significantly increased worldwide. The liver X receptor α (LXRα) is a multifunctional nuclear receptor that controls lipid homeostasis. Inhibition of LXRα transactivation may be beneficial for NAFLD and hyperlipidemia treatment. Ursolic acid (UA) is a plant triterpenoid with many beneficial effects; however, the mechanism of its action on LXRα remains elusive. We evaluated the effects of UA on T0901317 (T090)-induced LXRα activation and steatosis. UA significantly decreased the LXR response element and sterol regulatory element-binding protein-1c ( SREBP-1c) gene promoter activities, mRNA, protein expression of LXRα target genes, and hepatic cellular lipid content in a T090-induced mouse model. A molecular docking study indicated that UA bound competitively with T090 at the LXRα ligand binding domain. UA stimulated AMP-activated protein kinase (AMPK) phosphorylation in hepatic cells and increased corepressor, small heterodimer partner-interacting leucine zipper protein (SMILE) but decreased coactivator, steroid receptor coactivator-1 (SRC-1) recruitment to the SREBP-1c promoter region. In contrast, UA induced SRC-1 binding but decreased SMILE binding to reverse cholesterol transport-related gene promoters in intestinal cells, increasing lipid excretion from intestinal cells. Additionally, UA reduced valproate-induced LXRα mediated and rifampin-induced pregnane X receptor mediated lipogenesis, offering potential treatments for drug-induced hepatic steatosis. Thus, UA displays liver specificity and can be selectively repressed while RCT stimulation by LXRα is preserved and enhanced. This is a novel therapeutic option to treat NAFLD and may be helpful in developing LXR agonists to prevent atherosclerosis.

Oleanolic Acid Inhibits Liver X Receptor Alpha and Pregnane X Receptor to Attenuate Ligand-Induced Lipogenesis

Liver X receptor α (LXRα) controls important biological and pathophysiological processes such as lipid homeostasis. Inhibiting LXRα transactivation may beneficial in the treatment of nonalcoholic fatty liver disease (NAFLD), which is one of the main causes of liver diseases and hyperlipidemia. Oleanolic acid (OA) is a naturally occurring triterpenoid found in many plants. It has several beneficial effects on biological pathways; however, the mechanisms underlying its effects on LXRα are unclear. Therefore, we evaluated the effects of OA on T0901317-induced LXRα activation and explored whether OA can attenuate hepatic lipogenesis. The results showed that OA significantly decreased the promoter activities of LXR response element and sterol regulatory element binding protein-1c (SREBP-1c). It also decreased the mRNA and protein expression of LXRα target genes. These resulted in reduced hepatocellular lipid content. Our results also revealed that the overall binding pose of OA is similar to the X-ray pose of T0901317. Furthermore, OA stimulated AMP-activated protein kinase phosphorylation in hepatic cells. Additionally, it increased small heterodimer partner-interacting leucine zipper protein (SMILE) but decreased steroid receptor coactivator-1 (SRC-1) recruitment to the SREBP-1c promoter region. OA also enhanced LXRα-mediated induction of reverse cholesterol transport (RCT)-related gene, ATP-binding cassette transporter (ABC) A1, and ABCG1 expression in intestinal cells. It was found that OA increased the binding of SRC-1 but decreased SMILE recruitment to the ABCG1 gene promoter region. Furthermore, it reduced valproate- and rifampin-induced LXRα- and pregnane X receptor-mediated lipogenesis, respectively, which indicates its potential benefit in treating drug-induced hepatic steatosis. The results also show that OA is liver-specific and can be selectively repressed of lipogenesis. Moreover, it preserves and enhances LXRα-induced RCT stimulation. The results show that OA may be a promising treatment for NAFLD. Additionally, it can be used in the development of LXRα agonists to prevent atherosclerosis.

Towards Semantic Biomedical Problem Solving

Biological and medical intelligence (BMI) has been studied in solos, lacking a systematic methodology. In this paper, we describe how Semantic Computing can enhance biological and medical intelligence. Specifically, we show how Structured Natural Language (SNL) can express many problems in BMI with a finite number of sentence patterns, and show how biological tools, OLAP, data mining tools and statistical analysis tools may be linked to solve problems related to biomedical data.

A model comparison study of the flowering time regulatory network in Arabidopsis

Background

Several dynamic models of a gene regulatory network of the light-induced floral transition process in Arabidopsis have been developed to capture the behavior of gene transcription and infer predictions based on experimental observations. It has been proven that the models can make accurate and novel predictions, which generate testable hypotheses.

Two major issues were addressed in this study. First, construction of dynamic models for gene regulatory networks requires the use of mathematic modeling that comprises equations of a large number of parameters. Second, the binding mechanism of the transcription factor with DNA is another factor that requires detailed modeling. The first issue was tackled by adopting an optimization algorithm, and the second was addressed by comparing the performance of three alternative modeling approaches, namely the S-system, the Michaelis-Menten model and the Mass-action model. The efficiencies of parameter estimation and modeling performance were calculated based on least square error (O(p)), mean relative error (MRE) and Akaike Information Criterion (AIC).

Results

We compared three models to describe gene regulation of the flowering transition process in Arabidopsis. The Mass-action model is the simplest and has the least parameters. It is therefore less computation-intensive with the smallest AIC value. The disadvantage, however, is that it assumes the system is simply a second order reaction which is not the case in our study. The Michaelis-Menten model also assumes the system is homogeneous and ignores the intracellular protein transport process. The S-system model has the best performance and it does describe the diffusion effects. A disadvantage of the S-system is that it involves the most parameters. The largest AIC value also implies an over-fitting may occur in parameter estimation.

Conclusions

Three dynamic models were adopted to describe the dynamics of the gene regulatory network of the flowering transition process in Arabidopsis. Based on MRE, the least square error and global sensitivity analysis, the S-system has the best performance. However, the fact that it has the highest AIC suggests an over-fitting may occur in parameter estimation. The result of this study may need to be applied carefully when modeling complex gene regulatory networks.