An audit of the management of elderly patients with glioblastoma in the UK: have recent trial results changed treatment?

Aim: We investigated uptake of short-course chemo-radiotherapy and compared outcomes with other treatment schedules in elderly patients with glioblastoma (GBM). Methods: Patients aged 65 or over with a diagnosis of GBM were identified from an 18-month period from three centers in the UK. The primary end point of this study was overall survival from the date of diagnosis. Results: The analysis included 210 patients. Overall median survival was 5.0 months. Approximately 31.9% of patients received combined chemoradiation; multivariate analysis showed that patients who received standard chemoradiation were at a reduced risk of death than those receiving hypofractionated chemoradiation. Discussion: In this retrospective study, patients treated with standard chemoradiation experienced better outcomes than patients receiving hypofractionated chemoradiation. Patient selection likely contributed to these findings

Open chromatin profiling identifies AP1 as a transcriptional regulator in oesophageal adenocarcinoma.

Oesophageal adenocarcinoma (OAC) is one of the ten most prevalent forms of cancer and is showing a rapid increase in incidence and yet exhibits poor survival rates. Compared to many other common cancers, the molecular changes that occur in this disease are relatively poorly understood. However, genes encoding chromatin remodeling enzymes are frequently mutated in OAC. This is consistent with the emerging concept that cancer cells exhibit reprogramming of their chromatin environment which leads to subsequent changes in their transcriptional profile. Here, we have used ATAC-seq to interrogate the chromatin changes that occur in OAC using both cell lines and patient-derived material. We demonstrate that there are substantial changes in the regulatory chromatin environment in the cancer cells and using this data we have uncovered an important role for ETS and AP1 transcription factors in driving the changes in gene expression found in OAC cells.Our work received funding from the Wellcome Trust (https://wellcome.ac.uk/) the National Institute for Health Research (https://www.nihr.ac.uk/) and Cancer Research UK (http:// www.cancerresearchuk.org/)

External validation and recalibration of an incidental meningioma prognostic model - IMPACT: protocol for an international multicentre retrospective cohort study.

INTRODUCTION: Due to the increased use of CT and MRI, the prevalence of incidental findings on brain scans is increasing. Meningioma, the most common primary brain tumour, is a frequently encountered incidental finding, with an estimated prevalence of 3/1000. The management of incidental meningioma varies widely with active clinical-radiological monitoring being the most accepted method by clinicians. Duration of monitoring and time intervals for assessment, however, are not well defined. To this end, we have recently developed a statistical model of progression risk based on single-centre retrospective data. The model Incidental Meningioma: Prognostic Analysis Using Patient Comorbidity and MRI Tests (IMPACT) employs baseline clinical and imaging features to categorise the patient with an incidental meningioma into one of three risk groups: low, medium and high risk with a proposed active monitoring strategy based on the risk and temporal trajectory of progression, accounting for actuarial life expectancy. The primary aim of this study is to assess the external validity of this model. METHODS AND ANALYSIS: IMPACT is a retrospective multicentre study which will aim to include 1500 patients with an incidental intracranial meningioma, powered to detect a 10% progression risk. Adult patients ≥16 years diagnosed with an incidental meningioma between 1 January 2009 and 31 December 2010 will be included. Clinical and radiological data will be collected longitudinally until the patient reaches one of the study endpoints: intervention (surgery, stereotactic radiosurgery or fractionated radiotherapy), mortality or last date of follow-up. Data will be uploaded to an online Research Electronic Data Capture database with no unique identifiers. External validity of IMPACT will be tested using established statistical methods. ETHICS AND DISSEMINATION: Local institutional approval at each participating centre will be required. Results of the study will be reported through peer-reviewed articles and conferences and disseminated to participating centres, patients and the public using social media

Volumetric Growth and Growth Curve Analysis of Residual Intracranial Meningioma.

BackgroundAfter meningioma surgery, approximately 1 in 3 patients will have residual tumor that requires ongoing imaging surveillance. The precise volumetric growth rates of these tumors are unknown.ObjectiveTo identify the volumetric growth rates of residual meningioma, growth trajectory, and factors associated with progression.MethodsPatients with residual meningioma identified at a tertiary neurosurgery center between 2004 and 2020 were retrospectively reviewed. Tumor volume was measured using manual segmentation, after surgery and at every follow-up MRI scan. Growth rates were ascertained using a linear mixed-effects model and nonlinear regression analysis of growth trajectories. Progression was defined according to the Response Assessment in Neuro-Oncology (RANO) criteria (40% volume increase).ResultsThere were 236 patients with residual meningioma. One hundred and thirty-two patients (56.0%) progressed according to the RANO criteria, with 86 patients being conservatively managed (65.2%) after progression. Thirteen patients (5.5%) developed clinical progression. Over a median follow-up of 5.3 years (interquartile range, 3.5-8.6 years), the absolute growth rate was 0.11 cm 3 per year and the relative growth rate 4.3% per year. Factors associated with residual meningioma progression in multivariable Cox regression analysis were skull base location (hazard ratio [HR] 1.60, 95% CI 1.02-2.50) and increasing Ki-67 index (HR 3.43, 95% CI 1.19-9.90). Most meningioma exhibited exponential and logistic growth patterns (median R 2 value 0.84, 95% CI 0.60-0.90).ConclusionAbsolute and relative growth rates of residual meningioma are low, but most meet the RANO criteria for progression. Location and Ki-67 index can be used to stratify adjuvant treatment and surveillance paradigms

Biomarkers of anti-angiogenic therapy in breast cancer

The hunt for biomarkers for anti-VEGF agent bevacizumab is ongoing since last decade with no success. Identifying robust biomarkers for stratifying patients and for monitoring response is important for the future use of bevacizumab in breast cancer. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) analysis and genome wide gene expression analysis are two promising approaches to understand the molecular mechanisms and search for biomarker of anti-angiogenic therapy. Firstly, with the retrospective pilot study, a close link between DCE-MRI findings and the molecular mechanisms assisting cancer survival and metastasis was established. Secondly, the prospective window of opportunity study conducted using single cycle of bevacizumab given before neoadjuvant chemotherapy and by performing detailed pharmacodynamic analyses with DCE-MRI and gene expression before and two weeks after bevacizumab had shown a wide variation in responses to bevacizmab both at genomic and imaging level. A close link between changes in DCE-MRI and the changes in gene expression profile was further established suggesting DCE-MRI has potential to serve as non-invasive biomarkers of antiangiogenic therapy. Tumours with high baseline values of forward transfer constant Ktrans showed the maximum response as assessed by DCE-MRI after bevacizumab. By performing biopsy after single cycle of bevacizumab, the changes in genes related to immune response, metabolism and cell signalling were observed that gives a useful insight into mechanisms governing response and resistance to bevacizumab. Also the certain gene expression changes observed with post bevacizumab biopsies, such as down regulation of endothelial cell specific molecule-1 (ESM1), cyclin E1 (CCNE1) and up regulation of pyruvate dehydrogenase kinase 1 (PDK1), cyclic GMP-inhibited phosphodiesterase B (PDE3B) could be helpful in decision-making about future therapy with bevacizumab at an early stage. This study has suggested that using bevacizumab in combination with other targeted agents could overcome resistance.This thesis is not currently available in ORA

Zika Virus Epidemic in Pregnant Women, Dominican Republic, 2016–2017

Zika virus infection during pregnancy may result in birth defects and pregnancy complications. We describe the Zika virus outbreak in pregnant women in the Dominican Republic during 2016–2017. We conducted multinomial logistic regression to identify factors associated with fetal losses and preterm birth. The Ministry of Health identified 1,282 pregnant women with suspected Zika virus infection, a substantial proportion during their first trimester. Fetal loss was reported for ≈10% of the reported pregnancies, and 3 cases of fetal microcephaly were reported. Women infected during the first trimester were more likely to have early fetal loss (adjusted odds ratio 5.9, 95% CI 3.5–10.0). Experiencing fever during infection was associated with increased odds of premature birth (adjusted odds ratio 1.65, 95% CI 1.03–2.65). There was widespread morbidity during the epidemic. Our findings strengthen the evidence for a broad range of adverse pregnancy outcomes resulting from Zika virus infection

Radiogenomics Monitoring in Breast Cancer Identifies Metabolism and Immune Checkpoints as Early Actionable Mechanisms of Resistance to Anti-angiogenic Treatment

Anti-VEGF antibody bevacizumab has prolonged progression-free survival in several cancer types, however acquired resistance is common. Adaption has been observed pre-clinically, but no human study has shown timing and genes involved, enabling formulation of new clinical paradigms. In a window-of-opportunity study in 35 ductal breast cancer patients for 2 weeks prior to neoadjuvant chemotherapy, we monitored bevacizumab response by Dynamic Contrast-Enhanced Magnetic Resonance [DCE-MRI], transcriptomic and pathology. Initial treatment response showed significant overall decrease in DCE-MRI median Ktrans, angiogenic factors such ESM1 and FLT1, and proliferation. However, it also revealed great heterogeneity, spanning from downregulation of blood vessel density and central necrosis to continued growth with new vasculature. Crucially, significantly upregulated pathways leading to resistance included glycolysis and pH adaptation, PI3K-Akt and immune checkpoint signaling, for which inhibitors exist, making a strong case to investigate such combinations. These findings support that anti-angiogenesis trials should incorporate initial enrichment of patients with high Ktrans, and a range of targeted therapeutic options to meet potential early resistance pathways. Multi-arm adaptive trials are ongoing using molecular markers for targeted agents, but our results suggest this needs to be further modified by much earlier adaptation when using drugs affecting the tumor microenvironment

ETV1 binding regions are associated with open chromatin.

<p>(A) ChIP-seq (left) and ATAC-seq (right) tag densities compared in a 2 kb window around summit (indicated by arrow) of ETV1 binding regions. (B) Plot of normalised Tn5 cleavage events +/-1 kb from the peak summits of the ETV1 binding regions. Data are plotted from OE33 (red) and HET1A (blue) cells. (C) Heat map showing the relative accessibility (normalised ATAC-seq reads) found in 500 bp windows surrounding the summit of ETV1 binding regions in the HET1A (normal derived) cell line and the three cancer derived cell lines OE33, OE19 and MFD-1. Replicates were merged for OE33 and HET1A. Regions are clustered using hierarchical clustering. (D) UCSC browser track showing ETV1 binding peaks compared to input sample in OE33 cells (top two tracks) at the <i>DUSP6</i> and <i>ADAP1</i> loci and ATAC-seq signal in the same regions in the OE19, OE33, FLO1 and HET1A cells. Intragenic (grey boxes) and promoter proximal (blue boxes) peaks are highlighted. (E) Plot of normalised Tn5 cleavage events +/-75bp from the motif centre around the AP-1 (left) and ETS (right) motifs found at ETV1 binding regions. Data are plotted from OE33 (red) and HET1A (blue) cells. (F) Heatmap of relative gene expression data for the indicated ETV1 target genes and PEA3 and AP1 family transcription factors from 73 OAC biopsy samples. Target genes were selected based on being associated with an ETV1 binding region which is open in OE33 cancer cells and contains either an AP1 or ETS motif (or both) (indicated by yellow boxes). Data were generated by RT-qPCR on the BioMark HD System (Fluidigm) and are plotted as row Z scores of–ΔCT (<i>GAPDH</i> normalised) values. Data are clustered according to Pearson’s correlations and prominent subclusters indicated (SC1-3).</p

ATAC-seq reveals in patient samples identifies AP1 and ETS proteins as regulators of OAC.

<p>(A) PCA analysis of the 9 tissue samples across the top 50,000 accessibility regions derived from merging reads from all samples and recalling peaks using MACS2. Tumour samples are shown in red and normal samples in blue. (B) Pie chart showing the genomic distribution of the top 50,000 accessible regions across all tissue samples (bottom) or the 1015 differentially more accessible regions (top) in OAC cancer samples (promoter = +/- 1 kb from TSS). (C) Heatmap of normalised Tn5 cleavage events (log₂) in 500 bp windows at the regions showing significant differential accessibility between normal and tumour tissue samples (+/- linear fivefold change, P<0.05). Data are subjected to hierarchical clustering using 1-Pearson’s correlation. (D) UCSC browser track showing open chromatin regions at the <i>IHH</i>, <i>ZNF471</i> and <i>ZFP28</i> loci in the indicated patient-derived normal and tumour tissue samples. Intergenic and intragenic (grey boxes) and promoter proximal (blue boxes) peaks are highlighted. Aggregated data from either two normal (-N) or three OAC (-T) cell lines is also shown. (E) Heatmap (left) and average tag profile (right) of normalised H3K27ac ChIP-seq tag density (GSM1013127) in normal oesophageal tissue (shown in a +/- 2 kb region around summit of each differentially accessible peak). Average profiles are shown for regions that are either more open in cancer (red line) or more open in normal (blue line) samples. (F) AP-1 and ETS motifs identified via de novo motif discovery, at regions that are more open in cancer (n = 962) against CpG matched background. (G) Heatmaps (left) and average ATAC-seq cleavage events (right) of ATAC-seq tag density in normal (blue line) and tumour (red line) samples from patient 006. Data are shown in a +/- 1 kb region relative to the summit of the ETV1 binding peaks defined by ChIP-seq in OE33 cells. Regions in the heatmaps are ranked according to ETV1 ChIP-seq signal (shown on the left).</p