A novel nomogram and survival analysis for different lymph node status in breast cancer based on the SEER database.

INTRODUCTION: The axillary lymph node status (ALNS) and internal mammary lymph nodes (IMLN) expression associated with breast cancer are closely linked to prognosis. This study aimed to establish a nomogram to predict survival at 3, 5, and 10 years in patients with various lymph node statuses. METHODS: We obtained data from patients with breast cancer between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER database). Chi-square analysis was performed to test for differences in the pathological characteristics of the groups, and Kaplan-Meier analysis and the log-rank test were used to plot and compare the correlation between overall survival (OS) and breast cancer specific survival (BCSS). The log-rank test was used for the univariate analysis, and statistically significant characteristics were included in the multivariate and Cox regression analyses. Finally, Independent factor identification was included in constructing the nomogram using R studio 4.2.0; area under curve (AUC) values were calculated, and receiver operating characteristic (ROC) curve, calibration, and decision curve analysis (DCA) curves were plotted for evaluation. RESULTS: A total of 279,078 patients were enrolled and analysed, demonstrating that the isolated tumour cells (ITC) group had clinicopathological characteristics similar to those of micrometastases (Mic). Multivariate analysis was performed to identify each subgroup's independent risk factors and construct a nomogram. The AUC values were 74.7 (95% CI 73.6-75.8), 72.8 (95% CI 71.9-73.8), and 71.2 (95% CI 70.2-72.2) for 3-, 5-, and 10-year OS, respectively, and 82.2 (95% CI 80.9-83.6), 80.1 (95% CI 79.0-81.2), and 75.5 (95% CI 74.3-76.8) for BCSS in overall breast cancer cases, respectively. AUC values for 3-, 5-, and 10-year OS in the ITC group were 64.8 (95% CI 56.5-73.2), 67.7 (95% CI 62.0-73.4), and 65.4 (95% CI 60.0-70.7), respectively. For those in the Mic group, AUC values for 3-, 5-, and 10-year OS were 72.9 (95% CI 70.7-75.1), 72.4 (95% CI 70.6-74.1), and 71.3 (95% CI 69.6-73.1), respectively, and AUC values for BCSS were 77.8 (95% CI 74.9-80.7), 75.7 (95% CI 73.5-77.9), and 70.3 (95% CI 68.0-72.6), respectively. In the IMLN group, AUC values for 3-, 5-, and 10-year OS were 75.2 (95% CI 71.7-78.7), 73.4 (95% CI 70.0-76.8), and 74.0 (95% CI 69.6-78.5), respectively, and AUC values for BCSS were 76.6 (95% CI 73.0-80.3), 74.1 (95% CI 70.5-77.7), and 74.7 (95% CI 69.8-79.5), respectively. The ROC, calibration, and DCA curves verified that the nomogram had better predictability and benefits. CONCLUSION: This study is the first to investigate the predictive value of different axillary lymph node statuses and internal mammary lymph node metastases in breast cancer, providing clinicians with additional aid in treatment decisions.

Long non­coding RNA DANCR aggravates breast cancer through the miR­34c/E2F1 feedback loop.

Emerging scientific evidence has suggested that the long non­coding (lnc)RNA differentiation antagonizing non­protein coding RNA (DANCR) serves a significant role in human tumorigenesis and cancer progression; however, the precise mechanism of its function in breast cancer remains to be fully understood. Therefore, the objective of the present study was to manipulate DANCR expression in MCF7 and MDA­MB­231 cells using lentiviral vectors to knock down or overexpress DANCR. This manipulation, alongside the analysis of bioinformatics data, was performed to investigate the potential mechanism underlying the role of DANCR in cancer. The mRNA and/or protein expression levels of DANCR, miR­34c­5p and E2F transcription factor 1 (E2F1) were assessed using reverse transcription­quantitative PCR and western blotting, respectively. The interactions between these molecules were validated using chromatin immunoprecipitation and dual­luciferase reporter assays. Additionally, fluorescence in situ hybridization was used to confirm the subcellular localization of DANCR. Cell proliferation, migration and invasion were determined using 5­ethynyl­2'­deoxyuridine, wound healing and Transwell assays, respectively. The results of the present study demonstrated that DANCR had a regulatory role as a competing endogenous RNA and upregulated the expression of E2F1 by sequestering miR­34c­5p in breast cancer cells. Furthermore, E2F1 promoted DANCR transcription by binding to its promoter in breast cancer cells. Notably, the DANCR/miR­34c­5p/E2F1 feedback loop enhanced cell proliferation, migration and invasion in breast cancer cells. Thus, these findings suggested that targeting DANCR may potentially provide a promising future therapeutic strategy for breast cancer treatment.

Mechanism and treatment of diarrhea associated with tyrosine kinase inhibitors.

Tyrosine kinase inhibitors (TKIs) have become first-line drugs for cancer treatment. However, their clinical use is seriously hindered since many patients experience diarrhea after receiving TKIs. The mechanisms of TKI-associated diarrhea remain unclear. Most existing therapies are symptomatic treatments based on experience and their effects are unsatisfactory. Therefore, clarification of the mechanisms underlying diarrhea is critical to develop effective anti-diarrhea drugs. This article summarizes several potential mechanisms of TKI-associated diarrhea and reviews current treatment progress.

Multi-omics approach identifies PI3 as a biomarker for disease severity and hyper-keratinization in psoriasis.

BACKGROUND: Psoriasis is an immune-mediated inflammatory skin disease. Psoriasis severity evaluation is important for clinicians in the assessment of disease severity and subsequent clinical decision making. However, no objective biomarker is available for accurately evaluating disease severity in psoriasis. OBJECTIVE: To define and compare biomarkers of disease severity and progression in psoriatic skin. METHODS: We performed proteome profiling to study the proteins circulating in the serum from patients with psoriasis, psoriatic arthritis and ankylosing spondylitis, and transcriptome sequencing to investigate the gene expression in skin from the same cohort. We then used machine learning approaches to evaluate different biomarker candidates across several independent cohorts. In order to reveal the cell-type specificity of different biomarkers, we also analyzed a single-cell dataset of skin samples. In-situ staining was applied for the validation of biomarker expression. RESULTS: We identified that the peptidase inhibitor 3 (PI3) was significantly correlated with the corresponding local skin gene expression, and was associated with disease severity. We applied machine learning methods to confirm that PI3 was an effective psoriasis classifier, Finally, we validated PI3 as psoriasis biomarker using in-situ staining and public datasets. Single-cell data and in-situ staining indicated that PI3 was specifically highly expressed in keratinocytes from psoriatic lesions. CONCLUSION: Our results suggest that PI3 may be a psoriasis-specific biomarker for disease severity and hyper-keratinization.

Clinicopathological analysis and prognostic treatment study of angiosarcoma of the breast: a SEER population-based analysis.

INTRODUCTION: Breast angiosarcoma is a rare malignancy of endovascular origin, accounting for less than 1% of all mammary cancers. Our aim was to explore clinicopathological features and the factors associated with prognosis. METHODS: We extracted information from the Surveillance, Epidemiology, and End Results Program (SEER) for all patients with breast angiosarcoma between 2004 and 2015. Chi-square analysis was used to compare the clinicopathological features in all patients. Overall survival (OS) was assessed using the Kaplan and Meier method. Univariate and multivariate analyses were performed to evaluate the factors associated with prognosis. RESULTS: A total of 247 patients were included in the analyses. The median OS of patients with primary breast angiosarcoma (PBSA) and secondary breast angiosarcoma (SBAB) was 38 months and 42 months, respectively. The 1-, 3- and 5-year OS with PBSA was 80%, 39%, and 25%, respectively, and the 1-, 3- and 5-year OS with SBAB was 80%, 42%, and 34%, respectively. Multivariate analysis revealed that tumor size (p = 0.001), tumor grade (p < 0.001), tumor extension (p = 0.015), and tumor spread (p < 0.001) were statistically significant factors for OS. Partial mastectomy with radiation (HR = 0.160, 95% CI, 0.036-0.719, p = 0.016), partial mastectomy with chemotherapy (HR = 0.105, 95% CI, 0.011-1.015, p = 0.052), and partial mastectomy (HR = 0.125, 95% CI, 0.028-0.583, p = 0.007) were related to significantly better OS outcomes in primary angiosarcoma. CONCLUSION: Primary breast angiosarcoma has a better clinical phenotype than secondary breast angiosarcoma. Although overall survival was not statistically significant, primary breast angiosarcoma was better than secondary breast angiosarcoma with systemic therapy. Depending on the outcome of survival, partial mastectomy is effective in treating primary breast angiosarcoma.

Multi-omics integration reveals a core network involved in host defence and hyperkeratinization in psoriasis.

OBJECTIVES: The precise pathogenesis of psoriasis remains incompletely explored. We aimed to better understand the underlying mechanisms of psoriasis, using a systems biology approach based on transcriptomics and microbiome profiling. METHODS: We collected the skin tissue biopsies and swabs in both lesional and non-lesional skin of 13 patients with psoriasis, 15 patients with psoriatic arthritis and healthy skin from 12 patients with ankylosing spondylitis. To study the similarities and differences in the molecular profiles between these three conditions, and the associations between the host defence and microbiota composition, we performed high-throughput RNA-sequencing to quantify the gene expression profile in tissues. The metagenomic composition of 16S on local skin sites was quantified by clustering amplicon sequences and counted into operational taxonomic units. We further analysed associations between the transcriptome and microbiome profiling. RESULTS: We found that lesional and non-lesional samples were remarkably different in terms of their transcriptome profiles. The functional annotation of differentially expressed genes showed a major enrichment in neutrophil activation. By using co-expression gene networks, we identified a gene module that was associated with local psoriasis severity at the site of biopsy. From this module, we found a 'core' set of genes that was functionally involved in neutrophil activation, epidermal cell differentiation and response to bacteria. Skin microbiome analysis revealed that the abundances of Enhydrobacter, Micrococcus and Leptotrichia were significantly correlated with the genes in core network. CONCLUSIONS: We identified a core gene network that associated with local disease severity and microbiome composition, involved in the inflammation and hyperkeratinization in psoriatic skin.

A Blood Protein Signature Stratifies Clinical Response to csDMARD Therapy in Pediatric Uveitis.

PURPOSE: To identify a serum biomarker signature that can help predict response to conventional synthetic disease-modifying antirheumatic drug (csDMARD) therapy in pediatric noninfectious uveitis. METHODS: In this case-control cohort study, we performed a 368-plex proteomic analysis of serum samples of 72 treatment-free patients with active uveitis (new onset or relapse) and 15 healthy controls. Among these, 37 patients were sampled at diagnosis before commencing csDMARD therapy. After 6 months, csDMARD response was evaluated and cases were categorized as "responder" or "nonresponder." Patients were considered "nonresponders" if remission was not achieved under csDMARD therapy. Serum protein profiles were used to train random forest models to predict csDMARD failure and compared to a model based on eight clinical parameters at diagnosis (e.g., maximum cell grade). RESULTS: In total, 19 of 37 (51%) cases were categorized as csDMARD nonresponders. We identified a 10-protein signature that could predict csDMARD failure with an overall accuracy of 84%, which was higher compared to a model based on eight clinical parameters (73% accuracy). Adjusting for age, sex, anatomic location of uveitis, and cell grade, cases stratified by the 10-protein signature at diagnosis showed a large difference in risk for csDMARD failure (hazard ratio, 12.8; 95% confidence interval, 2.5-64.6; P = 0.002). CONCLUSIONS: Machine learning models based on the serum proteome can stratify pediatric patients with uveitis at high risk for csDMARD failure. TRANSLATIONAL RELEVANCE: The identified protein signature has implications for the development of clinical decision tools that integrate clinical parameters with biological data to better predict the best treatment option.

RegEnrich gene regulator enrichment analysis reveals a key role of the ETS transcription factor family in interferon signaling.

Changes in a few key transcriptional regulators can lead to different biological states. Extracting the key gene regulators governing a biological state allows us to gain mechanistic insights. Most current tools perform pathway/GO enrichment analysis to identify key genes and regulators but tend to overlook the gene/protein regulatory interactions. Here we present RegEnrich, an open-source Bioconductor R package, which combines differential expression analysis, data-driven gene regulatory network inference, enrichment analysis, and gene regulator ranking to identify key regulators using gene/protein expression profiling data. By benchmarking using multiple gene expression datasets of gene silencing studies, we found that RegEnrich using the GSEA method to rank the regulators performed the best. Further, RegEnrich was applied to 21 publicly available datasets on in vitro interferon-stimulation of different cell types. Collectively, RegEnrich can accurately identify key gene regulators from the cells under different biological states, which can be valuable in mechanistically studying cell differentiation, cell response to drug stimulation, disease development, and ultimately drug development.

Lymphoid and myeloid immune cell reconstitution after nicotinamide-expanded cord blood transplantation.

Omidubicel (nicotinamide-expanded cord blood) is a potential alternative source for allogeneic hematopoietic cell transplantation (HCT) when an HLA-identical donor is lacking. A phase I/II trial with standalone omidubicel HCT showed rapid and robust neutrophil and platelet engraftment. In this study, we evaluated the immune reconstitution (IR) of patients receiving omidubicel grafts during the first 6 months post-transplant, as IR is critical for favorable outcomes of the procedure. Data was collected from the omidubicel phase I-II international, multicenter trial. The primary endpoint was the probability of achieving adequate CD4+ T-cell IR (CD4IR: > 50 × 106/L within 100 days). Secondary endpoints were the recovery of T-cells, natural killer (NK)-cells, B-cells, dendritic cells (DC), and monocytes as determined with multicolor flow cytometry. LOESS-regression curves and cumulative incidence plots were used for data description. Thirty-six omidubicel recipients (median 44; 13-63 years) were included, and IR data was available from 28 recipients. Of these patients, 90% achieved adequate CD4IR. Overall, IR was complete and consisted of T-cell, monocyte, DC, and notably fast NK- and B-cell reconstitution, compared to conventional grafts. Our data show that transplantation of adolescent and adult patients with omidubicel results in full and broad IR, which is comparable with IR after HCT with conventional graft sources.

Conserved human effector Treg cell transcriptomic and epigenetic signature in arthritic joint inflammation.

Treg cells are critical regulators of immune homeostasis, and environment-driven Treg cell differentiation into effector (e)Treg cells is crucial for optimal functioning. However, human Treg cell programming in inflammation is unclear. Here, we combine transcriptional and epigenetic profiling to identify a human eTreg cell signature. Inflammation-derived functional Treg cells have a transcriptional profile characterized by upregulation of both a core Treg cell (FOXP3, CTLA4, TIGIT) and effector program (GITR, BLIMP-1, BATF). We identify a specific human eTreg cell signature that includes the vitamin D receptor (VDR) as a predicted regulator in eTreg cell differentiation. H3K27ac/H3K4me1 occupancy indicates an altered (super-)enhancer landscape, including enrichment of the VDR and BATF binding motifs. The Treg cell profile has striking overlap with tumor-infiltrating Treg cells. Our data demonstrate that human inflammation-derived Treg cells acquire a conserved and specific eTreg cell profile guided by epigenetic changes, and fine-tuned by environment-specific adaptations.

Multiomics and Machine Learning Accurately Predict Clinical Response to Adalimumab and Etanercept Therapy in Patients With Rheumatoid Arthritis.

OBJECTIVE: To predict response to anti-tumor necrosis factor (anti-TNF) prior to treatment in patients with rheumatoid arthritis (RA), and to comprehensively understand the mechanism of how different RA patients respond differently to anti-TNF treatment. METHODS: Gene expression and/or DNA methylation profiling on peripheral blood mononuclear cells (PBMCs), monocytes, and CD4+ T cells obtained from 80 RA patients before they began either adalimumab (ADA) or etanercept (ETN) therapy was studied. After 6 months, treatment response was evaluated according to the European League Against Rheumatism criteria for disease response. Differential expression and methylation analyses were performed to identify the response-associated transcription and epigenetic signatures. Using these signatures, machine learning models were built by random forest algorithm to predict response prior to anti-TNF treatment, and were further validated by a follow-up study. RESULTS: Transcription signatures in ADA and ETN responders were divergent in PBMCs, and this phenomenon was reproduced in monocytes and CD4+ T cells. The genes up-regulated in CD4+ T cells from ADA responders were enriched in the TNF signaling pathway, while very few pathways were differential in monocytes. Differentially methylated positions (DMPs) were strongly hypermethylated in responders to ETN but not to ADA. The machine learning models for the prediction of response to ADA and ETN using differential genes reached an overall accuracy of 85.9% and 79%, respectively. The models using DMPs reached an overall accuracy of 84.7% and 88% for ADA and ETN, respectively. A follow-up study validated the high performance of these models. CONCLUSION: Our findings indicate that machine learning models based on molecular signatures accurately predict response before ADA and ETN treatment, paving the path toward personalized anti-TNF treatment.

Broad proteomic screen reveals shared serum proteomic signature in patients with psoriatic arthritis and psoriasis without arthritis.

OBJECTIVE: To identify novel serum proteins involved in the pathogenesis of PsA as compared with healthy controls, psoriasis (Pso) and AS, and to explore which proteins best correlated to major clinical features of the disease. METHODS: A high-throughput serum biomarker platform (Olink) was used to assess the level of 951 unique proteins in serum of patients with PsA (n = 20), Pso (n = 18) and AS (n = 19), as well as healthy controls (HC, n = 20). Pso and PsA were matched for Psoriasis Area and Severity Index (PASI) and other clinical parameters. RESULTS: We found 68 differentially expressed proteins (DEPs) in PsA as compared with HC. Of those DEPs, 48 proteins (71%) were also dysregulated in Pso and/or AS. Strikingly, there were no DEPs when comparing PsA with Pso directly. On the contrary, hierarchical cluster analysis and multidimensional scaling revealed that HC clustered distinctly from all patients, and that PsA and Pso grouped together. The number of swollen joints had the strongest positive correlation to ICAM-1 (r = 0.81, P < 0.001) and CCL18 (0.76, P < 0.001). PASI score was best correlated to PI3 (r = 0.54, P < 0.001) and IL-17 receptor A (r = -0.51, P < 0.01). There were more proteins correlated to PASI score when analysing Pso and PsA patients separately, as compared with analysing Pso and PsA patients pooled together. CONCLUSION: PsA and Pso patients share a serum proteomic signature, which supports the concept of a single psoriatic spectrum of disease. Future studies should target skin and synovial tissues to uncover differences in local factors driving arthritis development in Pso.

Proteomic Profiling of Two Distinct Populations of Extracellular Vesicles Isolated from Human Seminal Plasma.

Body fluids contain many populations of extracellular vesicles (EV) that differ in size, cellular origin, molecular composition, and biological activities. EV in seminal plasma are in majority originating from prostate epithelial cells, and hence are also referred to as prostasomes. Nevertheless, EV are also contributed by other accessory sex glands, as well as by the testis and epididymis. In a previous study, we isolated EV from seminal plasma of vasectomized men, thereby excluding contributions from the testis and epididymis, and identified two distinct EV populations with diameters of 50 and 100 nm, respectively. In the current study, we comprehensively analyzed the protein composition of these two EV populations using quantitative Liquid Chromatography-Mass Spectrometry (LC-MS/MS). In total 1558 proteins were identified. Of these, ≈45% was found only in the isolated 100 nm EV, 1% only in the isolated 50 nm EV, and 54% in both 100 nm and 50 nm EV. Gene ontology (GO) enrichment analysis suggest that both originate from the prostate, but with distinct biogenesis pathways. Finally, nine proteins, including KLK3, KLK2, MSMB, NEFH, PSCA, PABPC1, TGM4, ALOX15B, and ANO7, with known prostate specific expression and alternate expression levels in prostate cancer tissue were identified. These data have potential for the discovery of EV associated prostate cancer biomarkers in blood.

CXCL4 Links Inflammation and Fibrosis by Reprogramming Monocyte-Derived Dendritic Cells in vitro.

Fibrosis is a condition shared by numerous inflammatory diseases. Our incomplete understanding of the molecular mechanisms underlying fibrosis has severely hampered effective drug development. CXCL4 is associated with the onset and extent of fibrosis development in multiple inflammatory and fibrotic diseases. Here, we used monocyte-derived cells as a model system to study the effects of CXCL4 exposure on dendritic cell development by integrating 65 longitudinal and paired whole genome transcriptional and methylation profiles. Using data-driven gene regulatory network analyses, we demonstrate that CXCL4 dramatically alters the trajectory of monocyte differentiation, inducing a novel pro-inflammatory and pro-fibrotic phenotype mediated via key transcriptional regulators including CIITA. Importantly, these pro-inflammatory cells directly trigger a fibrotic cascade by producing extracellular matrix molecules and inducing myofibroblast differentiation. Inhibition of CIITA mimicked CXCL4 in inducing a pro-inflammatory and pro-fibrotic phenotype, validating the relevance of the gene regulatory network. Our study unveils that CXCL4 acts as a key secreted factor driving innate immune training and forming the long-sought link between inflammation and fibrosis.

Construction of Nomograms for Predicting Pathological Complete Response and Tumor Shrinkage Size in Breast Cancer.

PURPOSE: Pathological complete response (pCR) is the goal of neoadjuvant chemotherapy (NAC) for the HER2-positive and triple-negative subtypes of breast cancer and is related to survival benefit; however, luminal breast cancer is not sensitive to NAC, and the size of tumor shrinkage is a more meaningful clinical indicator for the luminal breast cancer subtype. We wanted to use a nomogram or formula to develop and implement a series of prediction models for pCR or tumor shrinkage size. PATIENTS AND METHODS: We developed a prediction model in a primary cohort consisting of 498 patients with invasive breast cancer, and the data were gathered from July 2016 to September 2018. The endpoint was pCR and tumor shrinkage size. In the primary cohort, the HER2-positive cohort, and the triple-negative cohort, multivariate logistic regression analysis was used to screen the significant clinical features and clinicopathological features to develop nomograms. In the luminal group, multivariate linear regression analysis was used to test the risk factors that affect tumor shrinkage size. The area under the receiver operating characteristic curve (AUC) and calibration curves were adopted to evaluate and analyze the discrimination and calibration ability of nomograms. Furthermore, we also performed internal validation and independent validation in the primary cohort. RESULTS: ER status, KI67 status, HER2 status, number of NAC cycles, and tumor size were independent predictive factors of pCR in the primary cohort. These indicators had good discrimination and calibration in the primary and validation cohorts (AUC: 0.873, 0.820). The nomogram for HER2-positive and triple-negative breast cancer (TNBC) had an AUC of 0.820 and 0.785, respectively. Both the HER2 positive and TNBC nomogram calibration curves indicated significant agreement. Moreover, the luminal subtype prediction model was Y (tumor shrinkage size) = -0.576 × (age at diagnosis) + 2.158 × (number of NAC cycles) + 0.233 × (pre-NAC tumor size) + 51.662. CONCLUSION: Utilizing this predictive model will enable us to identify patients at high probability for pCR after NAC. Clinicians can stratify these patients and make individualized and personalized recommendations for therapy.

CXCL4 suppresses tolerogenic immune signature of monocyte-derived dendritic cells.

RNA sequencing and DNA methylomic profiling were performed after differentiating monocytes for 6 days into moDCs with/without CXCL4 presence. We show that CXCL4 downregulates genes associated with tolerogenicity in DCs including C1Q. Expression profiles of C1Q genes were negatively correlated with their DNA methylation profiles and with immunogenic genes.

Leflunomide-hydroxychloroquine combination therapy in patients with primary Sjögren's syndrome (RepurpSS-I): a placebo-controlled, double-blinded, randomised clinical trial.

BACKGROUND: Primary Sjögren's syndrome is a systemic autoimmune disease characterised by secretory gland dysfunction, for which no effective therapy is available. Based on the complementary properties of leflunomide and hydroxychloroquine in inhibiting activation of key immune cells in primary Sjögren's syndrome, we aimed to evaluate the clinical efficacy and safety of leflunomide-hydroxychloroquine combination therapy in patients with primary Sjögren's syndrome. METHODS: We did a placebo-controlled, double-blinded, phase 2A randomised clinical trial in patients with primary Sjögren's syndrome at the University Medical Center Utrecht (Utrecht, Netherlands). Eligible patients were aged 18-75 years, had a European League Against Rheumatism (EULAR) Sjögren's syndrome disease activity index (ESSDAI) score of 5 or higher, and a lymphocytic focus score of 1 or higher in labial salivary gland biopsy specimens. Patients were randomly assigned (2:1) with block randomisation (block size of six) to receive leflunomide 20 mg and hydroxychloroquine 400 mg daily or placebo for 24 weeks. The primary endpoint was the between-group difference in change in ESSDAI scores from 0 to 24 weeks, adjusted for baseline ESSDAI score. Patients were analysed according to the intention-to-treat principle. This study is registered with EudraCT, 2014-003140-12. FINDINGS: Between March 7, 2016, and Nov 30, 2017, 37 patients were screened, of whom 29 patients (28 women and one man) were enrolled. 21 patients were assigned to receive leflunomide-hydroxychloroquine and eight patients were assigned to receive placebo. One patient in the placebo group required high-dose prednisone to treat polymyalgia rheumatica at week 13 and was excluded from the primary analysis. From 0 to 24 weeks, the mean difference in ESSDAI score, adjusted for baseline values, in the leflunomide-hydroxychloroquine group compared with the placebo group was -4·35 points (95% CI -7·45 to -1·25, p=0·0078). No serious adverse events occurred in the leflunomide-hydroxychloroquine group and two serious adverse events occurred in the placebo group (hospital admission for pancreatitis and hospital admission for nephrolithiasis). The most common adverse events in the leflunomide-hydroxychloroquine group were gastrointestinal discomfort (11 patients [52%] vs two [25%] in the placebo group), modest transient increases in alanine aminotransferase (ten [48%] vs one [13%]), and short episodes of general malaise and shivering (nine [43%] vs one [13%]). INTERPRETATION: Leflunomide-hydroxychloroquine was safe and resulted in a clinical response in patients with primary Sjögren's syndrome. These results warrant further evaluation of leflunomide-hydroxychloroquine combination therapy in larger clinical trials. FUNDING: ZonMw.

Circular RNA circ-Foxo3 induced cell apoptosis in urothelial carcinoma via interaction with miR-191-5p.

BACKGROUND: Circular RNAs (circRNAs) play a critical role in cancer. Emerging evidence has shown circ-Foxo3, a circRNA, was dysregulated in a variety of tumor types. However, the exact role of circ-Foxo3 in bladder cancer has never been studied. METHODS: We measured the expression level of circ-Foxo3 in human and murine bladder cancer tissues and in various human bladder cancer cell lines. We induced bladder cancer in mice by a carcinogen N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN). circ-Foxo3 was overexpressed in mice by lentiviral gene transfer and in cultured cells via overexpression plasmid. The effect of circ-Foxo3 on apoptosis was examined via apoptotic marker staining, Western blot, and flow cytometry. We further characterized the interaction between circ-Foxo3 and miR-191 and its functional impact on bladder cancer cells. RESULTS: circ-Foxo3 was downregulated in bladder cancer in vivo and in vitro, and was upregulated in response to apoptotic stress. Overexpression of circ-Foxo3 promoted bladder cancer cell apoptosis in BBN mice and in human bladder cancer cell lines. miR-191-5p suppressed circ-Foxo3 expression and the pro-apoptotic effect of circ-Foxo3 in bladder cancer cells via directly targeting the 3'-untranslated region (3'-UTR) of circ-Foxo3. CONCLUSION: circ-Foxo3 was downregulated in bladder cancer in vivo and in vitro, and promoted bladder cancer apoptosis via direct interaction with miR-191. circ-Foxo3 could be a potential therapeutic target for bladder cancer.