High-throughput analysis of tissue microarrays using automated desorption electrospray ionization mass spectrometry

Tissue microarrays (TMAs) are commonly used for the rapid analysis of large numbers of tissue samples, often in morphological assessments but increasingly in spectroscopic analysis, where specific molecular markers are targeted via immunostaining. Here we report the use of an automated high-throughput system based on desorption electrospray ionization (DESI) mass spectrometry (MS) for the rapid generation and online analysis of high-density (6144 samples/array) TMAs, at rates better than 1 sample/second. Direct open-air analysis of tissue samples (hundreds of nanograms) not subjected to prior preparation, plus the ability to provide molecular characterization by tandem mass spectrometry (MS/MS), make this experiment versatile and applicable to both targeted and untargeted analysis in a label-free manner. These capabilities are demonstrated in a proof-of-concept study of frozen brain tissue biopsies where we showcase (i) a targeted MS/MS application aimed at identification of isocitrate dehydrogenase mutation in glioma samples and (ii) an untargeted MS tissue type classification using lipid profiles and correlation with tumor cell percentage estimates from histopathology. The small sample sizes and large sample numbers accessible with this methodology make for a powerful analytical system that facilitates the identification of molecular markers for later use in intraoperative applications to guide precision surgeries and ultimately improve patient outcomes

Second surgery for progressive glioblastoma: a multi‐centre questionnaire and cohort‐based review of clinical decision‐making and patient outcomes in current practice

PURPOSE: Glioblastoma prognosis is poor. Treatment options are limited at progression. Surgery may benefit, but no quality guidelines exist to inform patient selection. We sought to describe variations in surgical management at progression, highlight where further evidence is needed, and build towards a consensus strategy. METHODS: Current practice in selection of patients with progressive GBM for second surgery was surveyed online amongst specialists in the UK and Europe. We complemented this with an assessment of practice in a retrospective cohort study from six United Kingdom neurosurgical units. We used descriptive statistics to analyse the data. RESULTS: 234 questionnaire responses were received. Maintaining or improving patient quality of life was key to decision making, with variation as to whether patient age, performance status or intended extent of resection was relevant. MGMT methylation status was not important. Half considered no minimum time after first surgery. 288 patients were reported in the cohort analysis. Median time to second surgery from first surgery 390 days. Median overall survival 815 days, with no association between time to second surgery and time to death (p = 0.874). CONCLUSIONS: This is the most wide-ranging examination of contemporaneous practice in management of GBM progression. Without evidence-based guidelines, the variation is unsurprising. We propose consensus guidelines for consideration, to reduce heterogeneity in decision making, support data collection and analysis of factors influencing outcomes, and to inform clinical trials to establish whether second surgery improves patient outcomes, or simply selects to patients already performing well

Postoperative Deterioration in Health Related Quality of Life as Predictor for Survival in Patients with Glioblastoma: A Prospective Study

BACKGROUND: Studies indicate that acquired deficits negatively affect patients' self-reported health related quality of life (HRQOL) and survival, but the impact of HRQOL deterioration after surgery on survival has not been explored. OBJECTIVE: Assess if change in HRQOL after surgery is a predictor for survival in patients with glioblastoma. METHODS: Sixty-one patients with glioblastoma were included. The majority of patients (n = 56, 91.8%) were operated using a neuronavigation system which utilizes 3D preoperative MRI and updated intraoperative 3D ultrasound volumes to guide resection. HRQOL was assessed using EuroQol 5D (EQ-5D), a generic instrument. HRQOL data were collected 1-3 days preoperatively and after 6 weeks. The mean change in EQ-5D index was -0.05 (95% CI -0.15-0.05) 6 weeks after surgery (p = 0.285). There were 30 patients (49.2%) reporting deterioration 6 weeks after surgery. In a Cox multivariate survival analysis we evaluated deterioration in HRQOL after surgery together with established risk factors (age, preoperative condition, radiotherapy, temozolomide and extent of resection). RESULTS: There were significant independent associations between survival and use of temozolomide (HR 0.30, p = 0.019), radiotherapy (HR 0.26, p = 0.030), and deterioration in HRQOL after surgery (HR 2.02, p = 0.045). Inclusion of surgically acquired deficits in the model did not alter the conclusion. CONCLUSION: Early deterioration in HRQOL after surgery is independently and markedly associated with impaired survival in patients with glioblastoma. Deterioration in patient reported HRQOL after surgery is a meaningful outcome in surgical neuro-oncology, as the measure reflects both the burden of symptoms and treatment hazards and is linked to overall survival

Mathematical Modeling of Human Glioma Growth Based on Brain Topological Structures: Study of Two Clinical Cases

Gliomas are the most common primary brain tumors and yet almost incurable due mainly to their great invasion capability. This represents a challenge to present clinical oncology. Here, we introduce a mathematical model aiming to improve tumor spreading capability definition. The model consists in a time dependent reaction-diffusion equation in a three-dimensional spatial domain that distinguishes between different brain topological structures. The model uses a series of digitized images from brain slices covering the whole human brain. The Talairach atlas included in the model describes brain structures at different levels. Also, the inclusion of the Brodmann areas allows prediction of the brain functions affected during tumor evolution and the estimation of correlated symptoms. The model is solved numerically using patient-specific parametrization and finite differences. Simulations consider an initial state with cellular proliferation alone (benign tumor), and an advanced state when infiltration starts (malign tumor). Survival time is estimated on the basis of tumor size and location. The model is used to predict tumor evolution in two clinical cases. In the first case, predictions show that real infiltrative areas are underestimated by current diagnostic imaging. In the second case, tumor spreading predictions were shown to be more accurate than those derived from previous models in the literature. Our results suggest that the inclusion of differential migration in glioma growth models constitutes another step towards a better prediction of tumor infiltration at the moment of surgical or radiosurgical target definition. Also, the addition of physiological/psychological considerations to classical anatomical models will provide a better and integral understanding of the patient disease at the moment of deciding therapeutic options, taking into account not only survival but also life quality

Genetic variation associated with infection and the environment in the accidental pathogen Burkholderia pseudomallei

Funder: Thailand National Science and Technology Development Agency (FDA-CO-2562-8764-TH) and Thailand Science Research and Innovation fund (MRG6280226)Funder: Food Standards Agency Fellow and is supported by the BBSRC Institute Strategic Programme Microbes in the Food Chain BB/R012504/1 and its constituent projects BBS/E/F/000PR10348 (Theme 1, Epidemiology and Evolution of Pathogens in the Food Chain) and BBS/E/F/000PR10351 (Theme 3, Microbial Communities in the Food Chain)Abstract: The environmental bacterium Burkholderia pseudomallei causes melioidosis, an important endemic human disease in tropical and sub-tropical countries. This bacterium occupies broad ecological niches including soil, contaminated water, single-cell microbes, plants and infection in a range of animal species. Here, we performed genome-wide association studies for genetic determinants of environmental and human adaptation using a combined dataset of 1,010 whole genome sequences of B. pseudomallei from Northeast Thailand and Australia, representing two major disease hotspots. With these data, we identified 47 genes from 26 distinct loci associated with clinical or environmental isolates from Thailand and replicated 12 genes in an independent Australian cohort. We next outlined the selective pressures on the genetic loci (dN/dS) and the frequency at which they had been gained or lost throughout their evolutionary history, reflecting the bacterial adaptability to a wide range of ecological niches. Finally, we highlighted loci likely implicated in human disease

When is the Best Time to Sample Aquatic Macroinvertebrates in Ponds for Biodiversity Assessment?

Ponds are sites of high biodiversity and conservation value, yet there is little or no statutory monitoring of them across most of Europe. There are clear and standardized protocols for sampling aquatic macroinvertebrate communities in ponds but the most suitable time(s) to undertake the survey(s) remains poorly specified. This paper examined the aquatic macroinvertebrate communities from 95 ponds within different landuse types over three seasons (spring, summer and autumn) to determine the most appropriate time to undertake sampling to characterise biodiversity. The combined samples from all three seasons provided the most comprehensive record of the aquatic macroinvertebrate taxa recorded within ponds (alpha and gamma diversity). Samples collected during the autumn survey yielded significantly greater macroinvertebrate richness (76% of the total diversity) than either spring or summer surveys. Macroinvertebrate diversity was greatest during autumn in meadow and agricultural ponds but taxon richness among forest and urban ponds did not differ significantly temporally. The autumn survey provided the highest measures of richness for Coleoptera, Hemiptera and Odonata. However, richness of the aquatic insect order Trichoptera was highest in spring and lowest in autumn. The results illustrate that multiple surveys, covering more than one season, provide the most comprehensive representation of macroinvertebrate biodiversity. When sampling can only be undertaken on one occasion, the most appropriate time to undertake surveys to characterise the macroinvertebrate community biodiversity is during the autumn; although this may need to be modified if other floral and faunal groups need to be incorporated in to the sampling programme