Case Report: Step-by-step procedures for total intracorporeal laparoscopic kidney autotransplantation in a patient with distal high-risk upper tract urothelial carcinoma

A 47-year-old man presented to the emergency department with right abdominal pain and a new onset of painless haematuria two weeks earlier. Urine cytology test results suggested urothelial carcinoma. Computed tomography urography (CTU) showed a filling defect in the lower right ureter with right hydronephrosis. Lymphadenopathy and any signs of metastatic disease were absent on CTU. Cystoscopy appeared normal. Creatinine level was also normal before surgery. After the treatment options were discussed, the patient chose to undergo 3D total intracorporeal laparoscopic kidney autotransplantation, bladder cuff excision, and segmental resection of the proximal two-thirds of the ureter based on the membrane anatomy concept. After more than one year of follow-up, the patient was in good health and showed no signs of haematuria. Surveillance cystoscopy and CTU examination showed no evidence of disease recurrence. Therefore, it is reasonable to assume that kidney-sparing surgery may be considered for carefully selected patients with high-grade upper tract urothelial carcinoma

Development of a prognostic nomogram and risk stratification system for upper thoracic esophageal squamous cell carcinoma

BackgroundThe study aimed to develop a nomogram model to predict overall survival (OS) and construct a risk stratification system of upper thoracic esophageal squamous cell carcinoma (ESCC).MethodsNewly diagnosed 568 patients with upper ESCC at Fujian Medical University Cancer Hospital were taken as a training cohort, and additional 155 patients with upper ESCC from Sichuan Cancer Hospital Institute were used as a validation cohort. A nomogram was established using Cox proportional hazard regression to identify prognostic factors for OS. The predictive power of nomogram model was evaluated by using 4 indices: concordance statistics (C-index), time-dependent ROC (ROCt) curve, net reclassification index (NRI) and integrated discrimination improvement (IDI).ResultsIn this study, multivariate analysis revealed that gender, clinical T stage, clinical N stage and primary gross tumor volume were independent prognostic factors for OS in the training cohort. The nomogram based on these factors presented favorable prognostic efficacy in the both training and validation cohorts, with concordance statistics (C-index) of 0.622, 0.713, and area under the curve (AUC) value of 0.709, 0.739, respectively, which appeared superior to those of the American Joint Committee on Cancer (AJCC) staging system. Additionally, net reclassification index (NRI) and integrated discrimination improvement (IDI) of the nomogram presented better discrimination ability to predict survival than those of AJCC staging. Furthermore, decision curve analysis (DCA) of the nomogram exhibited greater clinical performance than that of AJCC staging. Finally, the nomogram fairly distinguished the OS rates among low, moderate, and high risk groups, whereas the OS curves of clinical stage could not be well separated among clinical AJCC stage.ConclusionWe built an effective nomogram model for predicting OS of upper ESCC, which may improve clinicians’ abilities to predict individualized survival and facilitate to further stratify the management of patients at risk

Long Noncoding RNA FAM201A Mediates the Radiosensitivity of Esophageal Squamous Cell Cancer by Regulating ATM and mTOR Expression via miR-101

Background: The aim of the present study was to identify the potential long non-coding (lnc.)-RNA and its associated molecular mechanisms involved in the regulation of the radiosensitivity of esophageal squamous cell cancer (ESCC) in order to assess whether it could be a biomarker for the prediction of the response to radiotherapy and prognosis in patients with ESCC.Methods: Microarrays and bioinformatics analysis were utilized to screen the potential lncRNAs associated with radiosensitivity in radiosensitive (n = 3) and radioresistant (n = 3) ESCC tumor tissues. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was performed in 35 ESCC tumor tissues (20 radiosensitive and 15 radioresistant tissues, respectively) to validate the lncRNA that contributed the most to the radiosensitivity of ESCC (named the candidate lncRNA). MTT, flow cytometry, and western blot assays were conducted to assess the effect of the candidate lncRNA on radiosensitivity in vitro in ECA109/ECA109R ESCC cells. A mouse xenograft model was established to confirm the function of the candidate lncRNA in the radiosensitivity of ESCC in vivo. The putative downstream target genes regulated by the candidate lncRNA were predicted using Starbase 2.0 software and the TargetScan database. The interactions between the candidate lncRNA and the putative downstream target genes were examined by Luciferase reporter assay, and were confirmed by PCR.Results: A total of 113 aberrantly expressed lncRNAs were identified by microarray analysis, of which family with sequence similarity 201-member A (FAM201A) was identified as the lncRNA that contributed the most to the radiosensitivity of ESCC. FAM201A was upregulated in radioresistant ESCC tumor tissues and had a poorer short-term response to radiotherapy resulting in inferior overall survival. FAM201A knockdown enhanced the radiosensitivity of ECA109/ECA109R cells by upregulating ataxia telangiectasia mutated (ATM) and mammalian target of rapamycin (mTOR) expression via the negative regulation of miR-101 expression. The mouse xenograft model demonstrated that FAM201A knockdown improved the radiosensitivity of ESCC.Conclusion: The lncRNA FAM201A, which mediated the radiosensitivity of ESCC by regulating ATM and mTOR expression via miR-101 in the present study, may be a potential biomarker for predicting radiosensitivity and patient prognosis, and may be a therapeutic target for enhancing cancer radiosensitivity in ESCC

Negative Regulation of Interferon-β Gene Expression during Acute and Persistent Virus Infections

The production of type I interferons (IFNs) in response to viral infections is critical for antiviral immunity. However, IFN production is transient, and continued expression can lead to inflammatory or autoimmune diseases. Thus, understanding the mechanisms underlying the negative regulation of IFN expression could lead to the development of novel therapeutic approaches to the treatment of these diseases. We report that the transcription factor IRF3 plays a central role in the negative regulation of interferon-β (IFNβ) expression during both acute and persistent (chronic) virus infections. We show that the degradation of IRF3 during acute infections, rather than the activation of transcriptional repressors, leads to the down regulation of IFNβ expression. We also show that the block to IFNβ expression in mouse embryonic fibroblasts that are persistently infected with Sendai virus (SeV) correlates with the absence of transcriptionally active IRF3. Remarkably, ongoing protein synthesis and viral replication are required to maintain repression of the IFNβ gene in persistently infected cells, as the gene can be activated by the protein synthesis inhibitor cycloheximide, or by the antiviral drug ribavirin. Finally, we show that the SeV V protein inhibits IRF3 activity in persistently infected cells. Thus, in conjunction with the known interference with STAT1 by the SeV C protein, both IFN activation and its signaling pathways are blocked in persistently infected cells. We conclude that the transcription factor IRF3 is targeted for turnover and inactivation through distinct mechanisms from both the host cells and virus, leading to the inhibition of IFNβ gene expression during acute and persistent viral infections. These observations show that IRF3 plays a critical role, not only in the activation of the IFNβ gene, but also in the controlling the duration of its expression. (284 words

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

A Prion-like Trigger of Antiviral Signaling

The MAVS protein plays a critical role in the assembly of an antiviral signaling complex on mitochondrial membranes. Hou et al. (2011) now report that virus infection induces a conformational change in MAVS, leading to the prion-like formation of functional self-aggregates that provide a sensitive trigger for antiviral signaling

Chromatin Structure and Transcription of the R1- and R2-Inserted rRNA Genes of Drosophila melanogaster

About half of the rRNA gene units (rDNA units) of Drosophila melanogaster are inserted by the retrotransposable elements R1 and R2. Because transcripts to R1 and R2 were difficult to detect on blots and electron microscopic observations of rRNA synthesis suggested that only uninserted rDNA units were transcribed, it has long been postulated that inserted rDNA units are in a repressed (inactive) chromatin structure. Studies described here suggest that inserted and uninserted units are equally accessible to DNase I and micrococcal nuclease and contain similar levels of histone H3 and H4 acetylation and H3K9 methylation. These studies have low sensitivity, because psoralen cross-linking suggested few (estimated <10%) of the rDNA units of any type are transcriptionally active. Nuclear run-on experiments revealed that R1-inserted and R2-inserted units are activated for transcription at about 1/5 and 1/10, respectively, the rate of uninserted units. Most transcription complexes of the inserted units terminate within the elements, thus explaining why previous molecular and electron microscopic methods indicated inserted units are seldom transcribed. The accumulating data suggest that all units within small regions of the rDNA loci are activated for transcription, with most control over R1 and R2 activity involving steps downstream of transcription initiation