Expression of neuroendocrine markers predicts increased survival in triple-negative breast cancer patients

BackgroundThe significance of neuroendocrine (NE) markers in triple-negative breast cancer (TNBC) patients has not been investigated. This study aims to clarify the incidence and prognostic significance of NE marker expression in TNBC, determine its association with other clinicopathological parameters, and further explore the pathological features and potential treatment options for TNBC patients expressing NE markers.MethodsClinicopathological data were collected from 396 TNBC patients undergoing radical breast cancer surgery at Peking Union Medical College Hospital from January 2002 to December 2014, with a final follow-up in July 2019. Immunohistochemistry (IHC) staining was performed for NE markers including chromogranin A (CgA) and synaptophysin (Syn). For TNBC patients with positive NE marker expression, IHC staining was then performed for alpha-thalassemia/mental retardation X-linked (ATRX), O(6)-methylguanine-methyltransferase (MGMT), somatostatin receptor 2 (SSTR2), and programmed death receptor-ligand 1 (PD-L1). The chi-square or Fisher exact test was used to evaluate the correlations between NE marker expression and other parameters. Survival curves were plotted using the Kaplan-Meier (K-M) method to assess the prognostic significance of NE markers in TNBC.ResultsNE marker-positive staining was observed in 7.6% (30/396) of all TNBC cases. Only 0.5% (2/396) cases had ≥ 90% neoplastic cells expressing NE markers. Positive NE marker expression was associated with negative basal-like marker expression. K-M survival analysis showed that the NE marker-positive TNBC patients had higher disease-free survival (DFS) rates than the NE marker-negative patients at the same stage. Among the 30 NE marker-positive TNBC cases, 13.3% and 26.7% showed negative IHC staining for ATRX and MGMT, respectively, while 13.3% had a 3+ score for SSTR2 IHC staining. For PD-L1 IHC staining, 13.3% of the 30 TNBC cases were higher than 10 scores in Combined Positive Score (CPS), and 10.0% were higher than 10% in Tumor Cell Proportion Score (TPS).ConclusionThere was a small proportion of TNBC patients expressing NE markers. TNBC patients with positive NE marker expression had a better prognosis than the negative group at the same stage. TNBC cases with positive NE marker expression may potentially benefit from immunotherapy or somatostatin analogue treatment

Anticancer Therapy-Induced Atrial Fibrillation: Electrophysiology and Related Mechanisms

Some well-established immunotherapy, radiotherapy, postoperation, anticancer drugs such as anthracyclines, antimetabolites, human epidermal growth factor receptor 2 blockers, tyrosine kinase inhibitors, alkylating agents, checkpoint inhibitors, and angiogenesis inhibitors, are significantly linked to cardiotoxicity. Cardiotoxicity is a common complication of several cancer treatments. Some studies observed complications of cardiac arrhythmia associated with the treatment of cancer, including atrial fibrillation (AF), supraventricular arrhythmias, and cardiac repolarization abnormalities. AF increases the risk of cardiovascular morbidity and mortality; it is associated with an almost doubled risk of mortality and a nearly 5-fold increase in the risk of stroke. The occurrence of AF is also usually researched in patients with advanced cancer and those undergoing active cancer treatments. During cancer treatments, the incidence rate of AF affects the prognosis of tumor treatment and challenges the treatment strategy. The present article is mainly focused on the cardiotoxicity of cancer treatments. In our review, we discuss these anticancer therapies and how they induce AF and consequently provide information on the precaution of AF during cancer treatment

Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries.

Importance: Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies. Objective: To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB. Design, Setting, and Participants: This diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019. Exposures: Blood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites. Main Outcomes and Measures: The PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation. Results: Of the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways. Conclusions and Relevance: This study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB

Prediction of gestational age using urinary metabolites in term and preterm pregnancies.

Assessment of gestational age (GA) is key to provide optimal care during pregnancy. However, its accurate determination remains challenging in low- and middle-income countries, where access to obstetric ultrasound is limited. Hence, there is an urgent need to develop clinical approaches that allow accurate and inexpensive estimations of GA. We investigated the ability of urinary metabolites to predict GA at time of collection in a diverse multi-site cohort of healthy and pathological pregnancies (n = 99) using a broad-spectrum liquid chromatography coupled with mass spectrometry (LC-MS) platform. Our approach detected a myriad of steroid hormones and their derivatives including estrogens, progesterones, corticosteroids, and androgens which were associated with pregnancy progression. We developed a restricted model that predicted GA with high accuracy using three metabolites (rho = 0.87, RMSE = 1.58 weeks) that was validated in an independent cohort (n = 20). The predictions were more robust in pregnancies that went to term in comparison to pregnancies that ended prematurely. Overall, we demonstrated the feasibility of implementing urine metabolomics analysis in large-scale multi-site studies and report a predictive model of GA with a potential clinical value

Polymeric Films for Buccal Drug Delivery

The aim of this research project is to evaluate whether or not pullulan films are suitable to buccal drug delivery of a phosphodiesterase5 (PDE5) inhibitor yonkenafil, which was discovered in our research group and currently is under phase II clinical trial for treatment of erectile dysfunction. Variable formulations of pullulan films were designed and the films were prepared. Mechanical properties of the films, in vitro drug release and polymer dissolution, in vitro drug penetration through porcine esophageal mucosa were investigated. The plasticization effects of solvents, polyols and acids to the films were studied by tensile test, and differential scanning calorimetry, thermogravimetric analysis, fourier transform-infrared, scanning electron microscopy, optical microscopy was applied to analyse the structure and chemical-bonding between pullulan and the additives within the films. Release mathematics models were used in the study of the mechanism of drug releases and polymer dissolutions. Ethanol, menthol, fatty acids, and sodium dodecyl sulphate were employed as penetration enhancers to pretreat the tissue. Various plasticizers and acids were applied into the films and the result showed polyethylene glycol 400 and 600 had the excellent plasticization effect on the drug-free pullulan films, while lactic acid was the best plasticizer for the drug-loaded films. Both PEG400 and lactic acid had a great effect on the drug release from the films in vitro, and all the results indicated that the hydroxyl and carboxyl groups of pullulan and the additives influenced the mechanical properties of the films significantly, and also altered drug release mechanisms. Ethanol shows the greatest enhancing ability on the drug permeation through the porcine esophageal mucosa. A possible mechanism for this is that ethanol interferes with the structure of the lipids in the mucosa, resulting in increased partitioning of the drug into the membrane.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A neural network based approach for path planning on costmap

In this thesis, a path planning method using a three-level hierarchical system model is proposed. In the top level of the hierarchy, the given location points to visit are taken as waypoints. The waypoint navigation process is formulated as a traveling salesman problem (TSP). The Lin-Kernighan algorithm is used to solve the TSP and transfer the solution to the lower level of the hierarchy. In the middle level, the path is represented by a grid-based costmap. A novel modified Grossberg neural network is designed to solve the point-to-point path planning. The bottom level of the hierarchy smoothens the path with kinematic constraints. The final results are simulated in a 3D virtual reality environment by using the MATLAB VR toolbox --Abstract, page iii

Polymeric films for buccal drug delivery

The aim of this research project is to evaluate whether or not pullulan films are suitable to buccal drug delivery of a phosphodiesterase5 (PDE5) inhibitor yonkenafil, which was discovered in our research group and currently is under phase II clinical trial for treatment of erectile dysfunction. Variable formulations of pullulan films were designed and the films were prepared. Mechanical properties of the films, in vitro drug release and polymer dissolution, in vitro drug penetration through porcine esophageal mucosa were investigated. The plasticization effects of solvents, polyols and acids to the films were studied by tensile test, and differential scanning calorimetry, thermogravimetric analysis, fourier transform-infrared, scanning electron microscopy, optical microscopy was applied to analyse the structure and chemical-bonding between pullulan and the additives within the films. Release mathematics models were used in the study of the mechanism of drug releases and polymer dissolutions. Ethanol, menthol, fatty acids, and sodium dodecyl sulphate were employed as penetration enhancers to pretreat the tissue. Various plasticizers and acids were applied into the films and the result showed polyethylene glycol 400 and 600 had the excellent plasticization effect on the drug-free pullulan films, while lactic acid was the best plasticizer for the drug-loaded films. Both PEG400 and lactic acid had a great effect on the drug release from the films in vitro, and all the results indicated that the hydroxyl and carboxyl groups of pullulan and the additives influenced the mechanical properties of the films significantly, and also altered drug release mechanisms. Ethanol shows the greatest enhancing ability on the drug permeation through the porcine esophageal mucosa. A possible mechanism for this is that ethanol interferes with the structure of the lipids in the mucosa, resulting in increased partitioning of the drug into the membrane