EGFR-Mutationsanalyse beim nichtkleinzelligen Lungenkarzinom: Erfahrungen aus der Routinediagnostik

Zusammenfassung: Hintergrund: Einige Patienten mit einem nichtkleinzelligem Lungenkarzinom (NSCLC) sprechen hervorragend auf Tyrosinkinase-Hemmer (TKI) an. Eine somatische Mutation im epidermalen Wachstumsfaktor-Rezeptor (EGFR) gilt dabei als wichtiger prädikativer Faktor. Patienten und Methode: Wir untersuchten 307 NCSLC auf EGFR-Mutationen (Exone 18-21) und überprüften deren Assoziation mit klinisch-pathologischen Parametern. Ergebnisse: Unter 178 histologischen und 129 zytologischen Tumorproben fanden sich 25 (8,1%) relevante EGFR-Mutationen. Am häufigsten waren Deletionen in Exon19 (50%), gefolgt von der Punktmutation L858R in Exon21 (12,5%). EGFR-Mutationen waren bei Frauen im Vergleich zu Männern (16,8% vs. 2,7%; p<0,001) und in Adenokarzinomen im Vergleich zu den übrigen Karzinomen (11,4% vs. 3,8%; p=0,017) gehäuft. Mutierte NSCLC waren zu 96% TTF-1-positiv. Schlussfolgerung: Therapierelevante EGFR-Mutationen kommen in <10% der mitteleuropäischen NSCLC-Patienten vor und sind gehäuft bei Frauen und TTF-1-positiven Adenokarzinomen. Histologische und zytologische Proben aus der Routinediagnostik sind in gleichem Maße für eine Mutationsanalyse geeigne

HOX D13 expression across 79 tumor tissue types.

HOX genes control normal development, primary cellular processes and are characterized by a unique genomic network organization. Locus D HOX genes play an important role in limb generation and mesenchymal condensation. Dysregulated HOXD13 expression has been detected in breast cancer, melanoma, cervical cancer and astrocytomas. We have investigated the epidemiology of HOXD13 expression in human tissues and its potential deregulation in the carcinogenesis of specific tumors. HOXD13 homeoprotein expression has been detected using microarray technology comprising more than 4,000 normal and neoplastic tissue samples including 79 different tumor categories. Validation of HOXD13 expression has been performed, at mRNA level, for selected tumor types. Significant differences are detectable between specific normal tissues and corresponding tumor types with the majority of cancers showing an increase in HOXD13 expression (16.1% normal vs. 57.7% cancers). In contrast, pancreas and stomach tumor subtypes display the opposite trend. Interestingly, detection of the HOXD13 homeoprotein in pancreas-tissue microarrays shows that its negative expression has a significant and adverse effect on the prognosis of patients with pancreatic cancer independent of the T or N stage at the time of diagnosis. Our study provides, for the first time, an overview of a HOX protein expression in a large series of normal and neoplastic tissue types, identifies pancreatic cancer as one of the most affected by the HOXD13 hoemoprotein and underlines the way homeoproteins can be associated to human cancerogenesis

Multicenter phase II trial of gefitinib first-line therapy followed by chemotherapy in advanced non-small-cell lung cancer (NSCLC): SAKK protocol 19/03

Background: Gefitinib is active in patients with pretreated non-small-cell lung cancer (NSCLC). We evaluated the activity and toxicity of gefitinib first-line treatment in advanced NSCLC followed by chemotherapy at disease progression. Patients and methods: In all, 63 patients with chemotherapy-naive stage IIIB/IV NSCLC received gefitinib 250 mg/day. At disease progression, gefitinib was replaced by cisplatin 80 mg/m2 on day 1 and gemcitabine 1250 mg/m2 on days 1, 8 for up to six 3-week cycles. Primary end point was the disease stabilization rate (DSR) after 12 weeks of gefitinib. Results: After 12 weeks of gefitinib, the DSR was 24% and the response rate (RR) was 8%. Median time to progression (TtP) was 2.5 months and median overall survival (OS) 11.5 months. Never smokers (n = 9) had a DSR of 56% and a median OS of 20.2 months; patients with epidermal growth factor receptor (EGFR) mutation (n = 4) had a DSR of 75% and the median OS was not reached after the follow-up of 21.6 months. In all, 41 patients received chemotherapy with an overall RR of 34%, DSR of 71% and median TtP of 6.7 months. Conclusions: First-line gefitinib monotherapy led to a DSR of 24% at 12 weeks in an unselected patients population. Never smokers and patients with EGFR mutations tend to have a better outcome; hence, further trials in selected patients are warrante

Dual HLA B*42 and B*81-reactive T cell receptors recognize more diverse HIV-1 Gag escape variants

Closely related HLA alleles presenting similar HIV-1 epitopes can be associated with variable clinical outcome. Here the authors report their findings on CD8+ T cell responses to the HIV-1 Gag-p24 TL9 immunodominant epitope in the context of closely related protective and less protective HLA alleles, and their differential effect on viral contro

Alcoholic and Nonalcoholic Liver Disease: Diagnostic Assessment and Therapeutic Perspectives

Abstract non disponibil

Defining the expression hierarchy of latent T-cell epitopes in Epstein-Barr virus infection with TCR-like antibodies

Epstein-Barr virus (EBV) is a gamma herpesvirus that causes a life-long latent infection in human hosts. The latent gene products LMP1, LMP2A and EBNA1 are expressed by EBV-associated tumors and peptide epitopes derived from these can be targeted by CD8 Cytotoxic T-Lymphocyte (CTL) lines. Whilst CTL-based methodologies can be utilized to infer the presence of specific latent epitopes, they do not allow a direct visualization or quantitation of these epitopes. Here, we describe the characterization of three TCR-like monoclonal antibodies (mAbs) targeting the latent epitopes LMP1[subscript 125–133], LMP2A[subscript 426–434] or EBNA1[subscript 562–570] in association with HLA-A0201. These are employed to map the expression hierarchy of endogenously generated EBV epitopes. The dominance of EBNA1[subscript 562–570] in association with HLA-A0201 was consistently observed in cell lines and EBV-associated tumor biopsies. These data highlight the discordance between MHC-epitope density and frequencies of associated CTL with implications for cell-based immunotherapies and/or vaccines for EBV-associated disease

Effects of Autonomy on Worker Performance

Having autonomy can produce positive effects on an individual’s well-being as well as overall job-satisfaction. Research has shown that background music influences listener attention and is associated with the listeners fondness of the music (Huang & Shih, 2011). This study investigates the effects that autonomy may also have on performance levels in the workplace. Specifically, the effects of listening to music of preference and the effects it has on attention, concentration, and enjoyment of task. In this study worker autonomy is operationally defined as preferred genre of music. Performance will be measured by participants score on a recall task that mimics a medical scenario where a healthcare worker would have to recall specific patient information. We hypothesize that participants autonomy preferred background music will have a positive effect on worker performance. If the predicted results are found, this research could be beneficial to companies that are considering implementing new policies to encourage autonomy and in turn produce greater success in the workplace

Simultaneous detection of lung fusions using a multiplex RT-PCR next generation sequencing-based approach:A multi-institutional research study

Contains fulltext : 195300.pdf (publisher's version ) (Open Access

anomalyDetection: Implementation of Augmented Network Log Anomaly Detection Procedures

As the number of cyber-attacks continues to grow on a daily basis, so does the delay in threat detection. For instance, in 2015, the Office of Personnel Management discovered that approximately 21.5 million individual records of Federal employees and contractors had been stolen. On average, the time between an attack and its discovery is more than 200 days. In the case of the OPM breach, the attack had been going on for almost a year. Currently, cyber analysts inspect numerous potential incidents on a daily basis, but have neither the time nor the resources available to perform such a task. anomalyDetection aims to curtail the time frame in which anomalous cyber activities go unnoticed and to aid in the efficient discovery of these anomalous transactions among the millions of daily logged events by i) providing an efficient means for pre-processing and aggregating cyber data for analysis by employing a tabular vector transformation and handling multicollinearity concerns; ii) offering numerous built-in multivariate statistical functions such as Mahalanobis distance, factor analysis, principal components analysis to identify anomalous activity, iii) incorporating the pipe operator (%\u3e%) to allow it to work well in the tidyverse workflow. Combined, anomalyDetection offers cyber analysts an efficient and simplified approach to break up network events into time-segment blocks and identify periods associated with suspected anomalies for further evaluation

Cyber Anomaly Detection: Using Tabulated Vectors and Embedded Analytics for Efficient Data Mining

Firewalls, especially at large organizations, process high velocity internet traffic and flag suspicious events and activities. Flagged events can be benign, such as misconfigured routers, or malignant, such as a hacker trying to gain access to a specific computer. Confounding this is that flagged events are not always obvious in their danger and the high velocity nature of the problem. Current work in firewall log analysis is manual intensive and involves manpower hours to find events to investigate. This is predominantly achieved by manually sorting firewall and intrusion detection/prevention system log data. This work aims to improve the ability of analysts to find events for cyber forensics analysis. A tabulated vector approach is proposed to create meaningful state vectors from time-oriented blocks. Multivariate and graphical analysis is then used to analyze state vectors in human–machine collaborative interface. Statistical tools, such as the Mahalanobis distance, factor analysis, and histogram matrices, are employed for outlier detection. This research also introduces the breakdown distance heuristic as a decomposition of the Mahalanobis distance, by indicating which variables contributed most to its value. This work further explores the application of the tabulated vector approach methodology on collected firewall logs. Lastly, the analytic methodologies employed are integrated into embedded analytic tools so that cyber analysts on the front-line can efficiently deploy the anomaly detection capabilities