The speaking vocabulary of kindergarten, grade I, grade II, and grade III

Thesis (Ed.M.)--Boston Universit

Detection of BRCA1, BRCA2, and ATM Alterations in Matched Tumor Tissue and Circulating Tumor DNA in Patients with Prostate Cancer Screened in PROfound

Circulating tumor DNA; Prostate cancerADN tumoral circulante; Cáncer de próstataADN tumoral circulant; Càncer de pròstataPurpose: Not all patients with metastatic castration-resistant prostate cancer (mCRPC) have sufficient tumor tissue available for multigene molecular testing. Furthermore, samples may fail because of difficulties within the testing procedure. Optimization of screening techniques may reduce failure rates; however, a need remains for additional testing methods to detect cancers with alterations in homologous recombination repair genes. We evaluated the utility of plasma-derived circulating tumor DNA (ctDNA) in identifying deleterious BRCA1, BRCA2 (BRCA), and ATM alterations in screened patients with mCRPC from the phase III PROfound study. Patients and Methods: Tumor tissue samples were sequenced prospectively at Foundation Medicine, Inc. (FMI) using an investigational next-generation sequencing (NGS) assay based on FoundationOne®CDx to inform trial eligibility. Matched ctDNA samples were retrospectively sequenced at FMI, using an investigational assay based on FoundationOne®Liquid CDx. Results: 81% (503/619) of ctDNA samples yielded an NGS result, of which 491 had a tumor tissue result. BRCA and ATM status in tissue compared with ctDNA showed 81% positive percentage agreement and 92% negative percentage agreement, using tissue as reference. At variant-subtype level, using tissue as reference, concordance was high for nonsense (93%), splice (87%), and frameshift (86%) alterations but lower for large rearrangements (63%) and homozygous deletions (27%), with low ctDNA fraction being a limiting factor. Conclusions: We demonstrate that ctDNA can greatly complement tissue testing in identifying patients with mCRPC and BRCA or ATM alterations who are potentially suitable for receiving targeted PARP inhibitor treatments, particularly patients with no or insufficient tissue for genomic analyses.This study was funded by AstraZeneca and is part of an alliance between AstraZeneca and Merck Sharp & Dohme Corp

miR-630 targets IGF1R to regulate response to HER-targeting drugs and overall cancer cell progression in HER2 over-expressing breast cancer

Background: While the treatment of HER2 over-expressing breast cancer with recent HER-targeted drugs has been highly effective for some patients, primary (also known as innate) or acquired resistance limits the success of these drugs. microRNAs have potential as diagnostic, prognostic and predictive biomarkers, as well as replacement therapies. Here we investigated the role of microRNA-630 (miR-630) in breast cancer progression and as a predictive biomarker for response to HER-targeting drugs, ultimately yielding potential as a therapeutic approach to add value to these drugs. Methods: We investigated the levels of intra- and extracellular miR-630 in cells and conditioned media from breast cancer cell lines with either innate- or acquired- resistance to HER-targeting lapatinib and neratinib, compared to their corresponding drug sensitive cell lines, using qPCR. To support the role of miR-630 in breast cancer, we examined the clinical relevance of this miRNA in breast cancer tumours versus matched peritumours. Transfection of miR-630 mimics and inhibitors was used to manipulate the expression of miR-630 to assess effects on response to HER-targeting drugs (lapatinib, neratinib and afatinib). Other phenotypic changes associated with cellular aggressiveness were evaluated by motility, invasion and anoikis assays. TargetScan prediction software, qPCR, immunoblotting and ELISAs, were used to assess miR-630’s regulation of mRNA, proteins and their phosphorylated forms. Results: We established that introducing miR-630 into cells with innate- or acquired- resistance to HER-drugs significantly restored the efficacy of lapatinib, neratinib and afatinib; through a mechanism which we have determined to, at least partly, involve miR-630’s regulation of IGF1R. Conversely, we demonstrated that blocking miR-630 induced resistance/insensitivity to these drugs. Cellular motility, invasion, and anoikis were also observed as significantly altered by miR-630 manipulation, whereby introducing miR-630 into cells reduced cellular aggression while inhibition of miR-630 induced a more aggressive cellular phenotype. Conclusions: Taken together, our findings suggest miR-630 as a key regulator of cancer cell progression in HER2 over-expressing breast cancer, through targeting of IGF1R. This study supports miR-630 as a diagnostic and a predictive biomarker for response to HER-targeted drugs and indicates that the therapeutic addition of miR-630 may enhance and improve patients’ response to HER-targeting drugs

Design, Synthesis And Biological Evaluation Of A Novel Bioactive Indane scaffold 2-(diphenylmethylene)c-2,3-dihydro-1H-inden-1-one with potential anticancer activity

Over the past decades, designing of privileged structures has emerged as a useful approach to the discovery and optimisation of novel biologically active molecules, and many have been successfully exploited across and within different target families. Examples include indole, quinolone, isoquinoline, benzofuran and chromone, etc. In the current study, we focus on synthesising a novel hybrid scaffold constituting naturally occurring benzophenone (14) and indanone (22) ring systems, leading to a general structure of 2-(diphenylmethylene)-2,3-dihydro-1H-inden-1-one (23). It was hypothesised this new hybrid system would provide enhanced anti-cancer activity owing to the presence of the common features associated with the tubulin binding small molecule indanocine (10) and the estrogen receptor (ER) antagonist tamoxifen (24). Key hybrid molecules were successfully synthesised and characterised, and the in vitro cytotoxicity assays were performed against cancer cell lines: MCF7 (breast) and SKBR3 (breast), DU145 (prostate) and A549 (lung). The methyl-, chloro- and methoxy-, para-substituted benzophenone hybrids displayed the greatest degree of cytotoxicity and the E-configuration derivatives 45, 47 and 49 being significantly most potent. We further verified that the second benzyl moiety of this novel hybrid scaffold is fundamental to enhance the cytotoxicity, especially in the SKBR3 (HER2+) by the E-methyl lead molecule 47, MCF7 (ER+) by 45 and 49, and A549 (NSCLC) cell lines by 49. These hybrid molecules also showed a significant accumulation of SKBR3 cells at S-phase of the cell cycle after 72 hrs, which demonstrates besides of being cytotoxic in vitro against SKBR3 cells, 47 disturbs the replication and development of this type of cancer causing a dose-dependent cell cycle arrest at S-phase. Our results suggest that DNA damage might be involved in the induction of SKBR3 cell death caused by the hybrid molecules, and therefore, this novel system may be an effective suppressor of HER2+/Neu-driven cancer growth and progression. The present study points to potential structural optimisation of the series and encourages further focussed investigation of analogues of this scaffold series toward their applications in cancer chemoprevention or chemotherapy

Drivers of potentially avoidable emergency admissions in Ireland: an ecological analysis

Background: Many emergency admissions are deemed to be potentially avoidable in a well-performing health system. Objective: To measure the impact of population and health system factors on county-level variation in potentially avoidable emergency admissions in Ireland over the period 2014–2016. Methods: Admissions data were used to calculate 2014–2016 age-adjusted emergency admission rates for selected conditions by county of residence. Negative binomial regression was used to identify which a priori factors were significantly associated with emergency admissions for these conditions and whether these factors were also associated with total/other emergency admissions. Standardised incidence rate ratios (IRRs) associated with a 1 SD change in risk factors were reported. Results: Nationally, potentially avoidable emergency admissions for the period 2014–2016 (266 395) accounted for 22% of all emergency admissions. Of the population factors, a 1 SD change in the county-level unemployment rate was associated with a 24% higher rate of potentially avoidable emergency admissions (IRR: 1.24; 95% CI 1.04 to 1.41). Significant health system factors included emergency admissions with length of stay equal to 1 day (IRR: 1.20; 95% CI 1.11 to 1.30) and private health insurance coverage (IRR: 0.92; 95% CI 0.89 to 0.96). The full model accounted for 50% of unexplained variation in potentially avoidable emergency admissions in each county. Similar results were found across total/other emergency admissions. Conclusion: The results suggest potentially avoidable emergency admissions and total/other emergency admissions are primarily driven by socioeconomic conditions, hospital admission policy and private health insurance coverage. The distinction between potentially avoidable and all other emergency admissions may not be as useful as previously believed when attempting to identify the causes of regional variation in emergency admission rates

An interrupted time-series analysis of the impact of emergency department reconfiguration on regional emergency department trolley numbers in Ireland from 2005 to 2015

Objectives: To understand the impact of emergency department (ED) reconfiguration on the number of patients waiting for hospital beds on trolleys in the remaining EDs in four geographical regions in Ireland using time-series analysis. Setting: EDs in four Irish regions; the West, North-East, South and Mid-West from 2005 to 2015. Participants: All patients counted as waiting on trolleys in an ED for a hospital bed in the study hospitals from 2005 to 2015. Intervention: The system intervention was the reconfiguration of ED services, as determined by the Department of Health and Health Service Executive. The timing of these interventions varied depending on the hospital and region in question. Results: Three of the four regions studied experienced a significant change in ED trolley numbers in the 12-month post-ED reconfiguration. The trend ratio before and after the intervention for these regions was as follows: North-East incidence rate ratio (IRR) 2.85 (95% CI 2.04 to 3.99, p<0.001), South IRR 0.68 (95% CI 0.51 to 0.89, p=0.006) and the Mid-West IRR 0.03 (95% 1.03 to 2.03, p=0.03). Two of these regions, the South and the Mid-West, displayed a convergence between the observed and expected trolley numbers in the 12-month post-reconfiguration. The North-East showed a much steeper increase, one that extended beyond the 12-month period post-ED reconfiguration. Conclusions: Findings suggest that the impacts of ED reconfiguration on regional level ED trolley trends were either non-significant or caused a short-term shock which converged on the pre-reconfiguration trend over the following 12 months. However, the North-East is identified as an exception due to increased pressures in one regional hospital, which caused a change in trend beyond the 12-month post reconfiguration

Text mining of adverse events in clinical trials: Deep learning approach

Background: Pharmacovigilance and safety reporting, which involves processes for monitoring the use of medicines in clinical trials, plays a critical role in the identification of previously unrecognized adverse events or changes in the patterns of adverse events. Objective: This study aimed to demonstrate feasibility of automating the coding of adverse events described in the narrative section of the serious adverse event report forms to enable a statistical analysis of the aforementioned patterns. Methods: We used the Unified Medical Language System (UMLS) as the coding scheme, which integrates 217 source vocabularies, thus enabling coding against other relevant terminologies such as ICD-10, MedDRA and SNOMED. We used MetaMap, highly configurable dictionary lookup software, to identify mentions of the UMLS concepts. We trained a binary classifier using Bidirectional Encoder Representations from Transformer (BERT), a transformer-based language model that captures contextual relationships, to differentiate between mentions of the UMLS concepts that represent adverse events and those that do not. Results: The model achieved a high F1 score of 0.8080 despite the class imbalance. This is 10.15 percent points lower than human-like performance, but also 17.45 percent points higher than the baseline approach. Conclusions: These results confirmed that automated coding of adverse events described in the narrative section of the serious adverse event reports is feasible. Once coded, adverse events can be statistically analyzed so that any correlations with the trialed medicines can be estimated in a timely fashion. Keywords: natural language processing; deep learning; machine learning; classificatio