EFFECT OF FEEDING WITH MIXTURE OF COLOURD RICE ON SERUM LIPID PROFILE AND ANTIOXIDANT STATUS IN EXPERIMENTAL RATS

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Real time investigations during sputter deposition for tailoring optical properties of metal-polymer interfaces

Poster presented at the 16th International Conference on Small-Angle Scattering, held on 13-18th September, 2015, Berlin (Germany).Tailoring optoelectronic properties of metal-polymer interfaces using self-assembly of nanoparticles is of crucial importance in organic electronics and organic photovoltaics [1]. In particular, metal sputter deposition on block-co-polymers is one widely used method to fabricate nanostructured metal layers on a large scale exploiting the selective wetting and doping of metals on polystyrene domains [2,3]. In order to obtain full control over the nanostructural evolution at the metal-polymer interface and its impact on optoelectronic properties, we employed a combination of in situ time-resolved microfocus Grazing Incidence Small Angle X-ray Scattering (μGISAXS) with in situ UV/Vis Specular Reflectance Spectroscopy (SRS) during sputter deposition of gold (Au) on thin polystyrene films (PS). We monitored the evolution of the metallic layer morphology according to changes in the key scattering features by geometrical modeling [4] and correlate the nanostructural development to optical properties. The changes of optoelectronic properties induced by metal nanoparticle growth during the sputter deposition process were exemplarily monitored using SRS. The morphological characterization is complemented by X-ray reflectivity and electron microscopy. This enables us to identify the different growth regimes including their specific thresholds and permits better understanding of the growth kinetics of gold clusters and their self-organization into complex nanostructures on polymer substrates. Thus, our findings are of great interest for applications in organic photovoltaics [5] and organic electronics, which benefit from tailored metal-polymer interfaces

Tumour-derived alkaline phosphatase regulates tumour growth, epithelial plasticity and disease-free survival in metastatic prostate cancer

BACKGROUND: Recent evidence suggests that bone-related parameters are the main prognostic factors for overall survival in advanced prostate cancer (PCa), with elevated circulating levels of alkaline phosphatase (ALP) thought to reflect the dysregulated bone formation accompanying distant metastases. We have identified that PCa cells express ALPL, the gene that encodes for tissue nonspecific ALP, and hypothesised that tumour-derived ALPL may contribute to disease progression. METHODS: Functional effects of ALPL inhibition were investigated in metastatic PCa cell lines. ALPL gene expression was analysed from published PCa data sets, and correlated with disease-free survival and metastasis. RESULTS: ALPL expression was increased in PCa cells from metastatic sites. A reduction in tumour-derived ALPL expression or ALP activity increased cell death, mesenchymal-to-epithelial transition and reduced migration. Alkaline phosphatase activity was decreased by the EMT repressor Snail. In men with PCa, tumour-derived ALPL correlated with EMT markers, and high ALPL expression was associated with a significant reduction in disease-free survival. CONCLUSIONS: Our studies reveal the function of tumour-derived ALPL in regulating cell death and epithelial plasticity, and demonstrate a strong association between ALPL expression in PCa cells and metastasis or disease-free survival, thus identifying tumour-derived ALPL as a major contributor to the pathogenesis of PCa progression.British Journal of Cancer advance online publication, 22 December 2016; doi:10.1038/bjc.2016.402 www.bjcancer.com

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment