Reduced expression of Bax in small cell lung cancer cells is not sufficient to induce cisplatin-resistance

Resistance to cisplatin in the course of chemotherapy contributes to the poor prognosis of small cell lung cancer (SCLC). B cell lymphoma-2 is the founding member of a large family of proteins that either promote or inhibit apoptosis. We aimed at investigating if the pro-apoptotic members Bad, Bax, Bim and Bid are involved in cisplatin-resistance

Oral vinorelbine and cisplatin with concomitant radiotherapy in stage III non-small cell lung cancer (NSCLC): A feasibility study

Background: Concurrent chemoradiotherapy has improved survival in inoperable stage III non-small cell lung cancer (NSCLC). This phase I trial was performed in order to establish a dose recommendation for oral vinorelbine in combination with cisplatin and simultaneous radiotherapy. Patients and Methods: Previously untreated patients with stage IIIB NSCLC received concurrent chemoradiotherapy with 66 Gy and 2 cycles of cisplatin and oral vinorelbine which was administered at 3 different levels (40, 50 and 60 mg/m(2)). This was to be followed by 2 cycles of cisplatin/vinorelbine oral consolidation chemotherapy. The study goal was to determine the maximal recommended dose of oral vinorelbine during concurrent treatment. Results: 11 stage IIIB patients were entered into the study. The median radiotherapy dose was 66 Gy. Grade 3-4 toxicity included neutropenia, esophagitis, gastritis and febrile neutropenia. The dose-limiting toxicity for concurrent chemoradiotherapy was esophagitis. 9 patients received consolidation chemotherapy, with neutropenia and anemia/thrombocytopenia grade 3 being the only toxicities. The overall response was 73%. Conclusion: Oral vinorelbine 50 mg/m(2) (days 1, 8, 15 over 4 weeks) in combination with cisplatin 20 mg/m2 (days 1-4) is the recommended dose in combination with radiotherapy (66 Gy) and will be used for concurrent chemoradiotherapy in a forthcoming phase III trial testing the efficacy of consolidation chemotherapy in patients not progressing after chemoradiotherapy

Light echoes reveal an unexpectedly cool Eta Carinae during its 19th-century Great Eruption

Eta Carinae (Eta Car) is one of the most massive binary stars in the Milky Way. It became the second-brightest star in the sky during its mid-19th century "Great Eruption," but then faded from view (with only naked-eye estimates of brightness). Its eruption is unique among known astronomical transients in that it exceeded the Eddington luminosity limit for 10 years. Because it is only 2.3 kpc away, spatially resolved studies of the nebula have constrained the ejected mass and velocity, indicating that in its 19th century eruption, Eta Car ejected more than 10 M_solar in an event that had 10% of the energy of a typical core-collapse supernova without destroying the star. Here we report the discovery of light echoes of Eta Carinae which appear to be from the 1838-1858 Great Eruption. Spectra of these light echoes show only absorption lines, which are blueshifted by -210 km/s, in good agreement with predicted expansion speeds. The light-echo spectra correlate best with those of G2-G5 supergiant spectra, which have effective temperatures of ~5000 K. In contrast to the class of extragalactic outbursts assumed to be analogs of Eta Car's Great Eruption, the effective temperature of its outburst is significantly cooler than allowed by standard opaque wind models. This indicates that other physical mechanisms like an energetic blast wave may have triggered and influenced the eruption.Comment: Accepted for publication by Nature; 4 pages, 4 figures, SI: 6 pages, 3 figures, 5 table

Defining aggressive or early progressing nononcogene-addicted non-small-cell lung cancer: a separate disease entity?

A substantial proportion of patients with nononcogene-addicted non-small-cell lung cancer (NSCLC) has 'aggressive disease', as reflected in short time to progression or lack of disease control with initial platinum-based chemotherapy. Recently, clinical correlates of aggressive disease behavior during first-line therapy have been shown to predict greater benefit from addition of nintedanib to second-line docetaxel in adenocarcinoma NSCLC. Positive predictive effects of aggressive disease have since been reported with other anti-angiogenic agents (ramucirumab and bevacizumab), while such features may negatively impact on outcomes with nivolumab in nonsquamous NSCLC with low PD-L1 expression. Based on a review of the clinical data, we recommend aggressive nonsquamous NSCLC should be defined by progression within <6-9 months of first-line treatment initiation

Who should be prioritized for renal transplantation?: Analysis of key stakeholder preferences using discrete choice experiments

Background Policies for allocating deceased donor kidneys have recently shifted from allocation based on Human Leucocyte Antigen (HLA) tissue matching in the UK and USA. Newer allocation algorithms incorporate waiting time as a primary factor, and in the UK, young adults are also favoured. However, there is little contemporary UK research on the views of stakeholders in the transplant process to inform future allocation policy. This research project aimed to address this issue. Methods Discrete Choice Experiment (DCE) questionnaires were used to establish priorities for kidney transplantation among different stakeholder groups in the UK. Questionnaires were targeted at patients, carers, donors / relatives of deceased donors, and healthcare professionals. Attributes considered included: waiting time; donor-recipient HLA match; whether a recipient had dependents; diseases affecting life expectancy; and diseases affecting quality of life. Results Responses were obtained from 908 patients (including 98 ethnic minorities); 41 carers; 48 donors / relatives of deceased donors; and 113 healthcare professionals. The patient group demonstrated statistically different preferences for every attribute (i.e. significantly different from zero) so implying that changes in given attributes affected preferences, except when prioritizing those with no rather than moderate diseases affecting quality of life. The attributes valued highly related to waiting time, tissue match, prioritizing those with dependents, and prioritizing those with moderate rather than severe diseases affecting life expectancy. Some preferences differed between healthcare professionals and patients, and ethnic minority and non-ethnic minority patients. Only non-ethnic minority patients and healthcare professionals clearly prioritized those with better tissue matches. Conclusions Our econometric results are broadly supportive of the 2006 shift in UK transplant policy which emphasized prioritizing the young and long waiters. However, our findings suggest the need for a further review in the light of observed differences in preferences amongst ethnic minorities, and also because those with dependents may be a further priority.</p

UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

Background: Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Results: Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. Conclusions: The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.The National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0310-1004)