Delineation of Tumor Habitats based on Dynamic Contrast Enhanced MRI

Tumor heterogeneity can be elucidated by mapping subregions of the lesion with differential imaging characteristics, called habitats. Dynamic Contrast Enhanced (DCE-)MRI can depict the tumor microenvironments by identifying areas with variable perfusion and vascular permeability, since individual tumor habitats vary in the rate and magnitude of the contrast uptake and washout. Of particular interest is identifying areas of hypoxia, characterized by inadequate perfusion and hyper-permeable vasculature. An automatic procedure for delineation of tumor habitats from DCE-MRI was developed as a two-part process involving: (1) statistical testing in order to determine the number of the underlying habitats; and (2) an unsupervised pattern recognition technique to recover the temporal contrast patterns and locations of the associated habitats. The technique is examined on simulated data and DCE-MRI, obtained from prostate and brain pre-clinical cancer models, as well as clinical data from sarcoma and prostate cancer patients. The procedure successfully identified habitats previously associated with well-perfused, hypoxic and/or necrotic tumor compartments. Given the association of tumor hypoxia with more aggressive tumor phenotypes, the obtained in vivo information could impact management of cancer patients considerably

Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways.

The QT interval is an electrocardiographic measure representing the sum of ventricular depolarization and repolarization, estimated by QRS duration and JT interval, respectively. QT interval abnormalities are associated with potentially fatal ventricular arrhythmia. Using genome-wide multi-ancestry analyses (>250,000 individuals) we identify 177, 156 and 121 independent loci for QT, JT and QRS, respectively, including a male-specific X-chromosome locus. Using gene-based rare-variant methods, we identify associations with Mendelian disease genes. Enrichments are observed in established pathways for QT and JT, and previously unreported genes indicated in insulin-receptor signalling and cardiac energy metabolism. In contrast for QRS, connective tissue components and processes for cell growth and extracellular matrix interactions are significantly enriched. We demonstrate polygenic risk score associations with atrial fibrillation, conduction disease and sudden cardiac death. Prioritization of druggable genes highlight potential therapeutic targets for arrhythmia. Together, these results substantially advance our understanding of the genetic architecture of ventricular depolarization and repolarization

Expert consensus document:Cholangiocarcinoma: current knowledge and future perspectives consensus statement from the European Network for the Study of Cholangiocarcinoma (ENS-CCA)

Cholangiocarcinoma (CCA) is a heterogeneous group of malignancies with features of biliary tract differentiation. CCA is the second most common primary liver tumour and the incidence is increasing worldwide. CCA has high mortality owing to its aggressiveness, late diagnosis and refractory nature. In May 2015, the "European Network for the Study of Cholangiocarcinoma" (ENS-CCA: www.enscca.org or www.cholangiocarcinoma.eu) was created to promote and boost international research collaboration on the study of CCA at basic, translational and clinical level. In this Consensus Statement, we aim to provide valuable information on classifications, pathological features, risk factors, cells of origin, genetic and epigenetic modifications and current therapies available for this cancer. Moreover, future directions on basic and clinical investigations and plans for the ENS-CCA are highlighted

Grau de complexidade dos cuidados de enfermagem: readmissões hospitalares de pessoas com câncer de mama

Resumo OBJETIVO Avaliar o grau de complexidade dos cuidados de enfermagem de pacientes com câncer de mama readmitidas na oncologia clínica. MÉTODOS Estudo transversal com 108 pessoas com câncer de mama readmitidas na oncologia clínica num centro de alta complexidade de oncologia do Rio de Janeiro durante 2015. Realizada análise documental sendo dados analisados estatisticamente. RESULTADOS Os graus de complexidade de cuidados de enfermagem predominantes foram semi-intensivos (36,1%) e cuidados intensivos (36,1%). Na análise multivariada, apenas a performance status (p<0,001) e a hipertensão arterial (p=0,024) permaneceram associados ao grau de complexidade. CONCLUSÕES O grau de complexidade dos pacientes readmitidos foi predominantemente semi-intensivo e intensivo. Essa avaliação implica no gerenciando do cuidado por meio do conhecimento do perfil dos pacientes com câncer de mama em readmissão hospitalar e da detecção das características associadas ao grau de complexidade

Radiogenomics Profiling for Glioblastoma-related Immune Cells Reveals CD49d Expression Correlation with MRI parameters and Prognosis

Abstract Although there have been a plethora of radiogenomics studies related to glioblastoma (GBM), most of them only used genomic information from tumor cells. In this study, we used radiogenomics profiling to identify MRI-associated immune cell markers in GBM, which was also correlated with prognosis. Expression levels of immune cell markers were correlated with quantitative MRI parameters in a total of 60 GBM patients. Fourteen immune cell markers (i.e., CD11b, CD68, CSF1R, CD163, CD33, CD123, CD83, CD63, CD49d and CD117 for myeloid cells, and CD4, CD3e, CD25 and CD8 for lymphoid cells) were selected for RNA-level analysis using quantitative RT-PCR. For MRI analysis, quantitative MRI parameters from FLAIR, contrast-enhanced (CE) T1WI, dynamic susceptibility contrast perfusion MRI and diffusion-weighted images were used. In addition, PFS associated with interesting mRNA data was performed by Kaplan-Meier survival analysis. CD163, which marks tumor associated microglia/macrophages (TAMs), showed the highest expression level in GBM patients. CD68 (TAMs), CSF1R (TAMs), CD33 (myeloid-derived suppressor cell) and CD4 (helper T cell, regulatory T cell) levels were highly positively correlated with nCBV values, while CD3e (helper T cell, cytotoxic T cell) and CD49d showed a significantly negative correlation with apparent diffusion coefficient (ADC) values. Moreover, regardless of any other molecular characteristics, CD49d was revealed as one independent factor for PFS of GBM patients by Cox proportional-hazards regression analysis (P = 0.0002). CD49d expression level CD49d correlated with ADC can be considered as a candidate biomarker to predict progression of GBM patients