Risks, alternative knowledge strategies and democratic legitimacy: the conflict over co-incineration of hazardous industrial waste in Portugal.

The decision to incinerate hazardous industrial waste in cement plants (the socalled ‘co-incineration’ process) gave rise to one of the most heated environmental conflicts ever to take place in Portugal. The bitterest period was between 1997 and 2002, after the government had made a decision. Strong protests by residents, environmental organizations, opposition parties, and some members of the scientific community forced the government to backtrack and to seek scientific legitimacy for the process through scientific expertise. The experts ratified the government’s decision, stating that the risks involved were socially acceptable. The conflict persisted over a decade and ended up clearing the way for a more sustainable method over which there was broad social consensus – a multifunctional method which makes it possible to treat, recover and regenerate most wastes. Focusing the analysis on this conflict, this paper has three aims: (1) to discuss the implications of the fact that expertise was ‘confiscated’ after the government had committed itself to the decision to implement co-incineration and by way of a reaction to the atmosphere of tension and protest; (2) to analyse the uses of the notions of ‘risk’ and ‘uncertainty’ in scientific reports from both experts and counter-experts’ committees, and their different assumptions about controllability and criteria for considering certain practices to be sufficiently safe for the public; and (3) to show how the existence of different technical scientific and political attitudes (one more closely tied to government and the corporate interests of the cement plants, the other closer to the environmental values of reuse and recycling and respect for the risk perception of residents who challenged the facilities) is closely bound up with problems of democratic legitimacy. This conflict showed how adopting more sustainable and lower-risk policies implies a broader view of democratic legitimacy, one which involves both civic movements and citizens themselves

p.Ala541Thr variant of MEN1 gene: A non deleterious polymorphism or a pathogenic mutation?

Context Multiple Endocrine Neoplasia Type 1 (MEN1) is an autosomal dominant inherited syndrome, related to mutations in the MEN1 gene. Controversial data suggest that the nonsynonymous p.Ala541Thr variant, usually considered as a non-pathogenic polymorphism, may be associated with an increased risk of MEN1-related lesions in carriers. Objective The aim of this study was to evaluate the pathogenic influence of the p.Ala541Thr variant on clinical and functional outcomes. Patients and methods We analysed a series of 55 index patients carrying the p.Ala541Thr variant. Their clinical profile was compared to that of 117 MEN1 patients. The biological impact of the p.Ala541Thr variant on cell growth was additionally investigated on menin-deficient Leydig cell tumour (LCT)10 cells generated from Men1+/Men1− heterozygous knock-out mice, and compared with wild type (WT). Results The mean age at first appearance of endocrine lesions was similar in both p.Ala541Thr carriers and MEN1 patients, but no p.Ala541Thr patient had more than one cardinal MEN1 lesion at initial diagnosis. A second MEN1 lesion was diagnosed in 13% of MEN1 patients and in 7% of p.Ala541Thr carriers in the year following preliminary diagnosis. Functional studies on LCT10 cells showed that overexpression of the p.Ala541Thr variant did not inhibit cell growth, which is in direct contrast to results obtained from investigation of WT menin protein. Conclusion Taken together, these data raise the question of a potential pathogenicity of the p.Ala541Thr missense variant of menin that commonly occurs within the general population. Additional studies are required to investigate whether it may be involved in a low-penetrance MEN1 phenotype

Targeted metabolomics as a tool in discriminating endocrine from primary hypertension

Context Identification of patients with endocrine forms of hypertension (EHT) (primary hyperaldosteronism [PA], pheochromocytoma/paraganglioma [PPGL], and Cushing syndrome [CS]) provides the basis to implement individualized therapeutic strategies. Targeted metabolomics (TM) have revealed promising results in profiling cardiovascular diseases and endocrine conditions associated with hypertension. Objective Use TM to identify distinct metabolic patterns between primary hypertension (PHT) and EHT and test its discriminating ability. Methods Retrospective analyses of PHT and EHT patients from a European multicenter study (ENSAT-HT). TM was performed on stored blood samples using liquid chromatography mass spectrometry. To identify discriminating metabolites a “classical approach” (CA) (performing a series of univariate and multivariate analyses) and a “machine learning approach” (MLA) (using random forest) were used. The study included 282 adult patients (52% female; mean age 49 years) with proven PHT (n = 59) and EHT (n = 223 with 40 CS, 107 PA, and 76 PPGL), respectively. Results From 155 metabolites eligible for statistical analyses, 31 were identified discriminating between PHT and EHT using the CA and 27 using the MLA, of which 16 metabolites (C9, C16, C16:1, C18:1, C18:2, arginine, aspartate, glutamate, ornithine, spermidine, lysoPCaC16:0, lysoPCaC20:4, lysoPCaC24:0, PCaeC42:0, SM C18:1, SM C20:2) were found by both approaches. The receiver operating characteristic curve built on the top 15 metabolites from the CA provided an area under the curve (AUC) of 0.86, which was similar to the performance of the 15 metabolites from MLA (AUC 0.83). Conclusion TM identifies distinct metabolic pattern between PHT and EHT providing promising discriminating performance

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

Identity by Descent Mapping of Founder Mutations in Cancer Using High-Resolution Tumor SNP Data

Dense genotype data can be used to detect chromosome fragments inherited from a common ancestor in apparently unrelated individuals. A disease-causing mutation inherited from a common founder may thus be detected by searching for a common haplotype signature in a sample population of patients. We present here FounderTracker, a computational method for the genome-wide detection of founder mutations in cancer using dense tumor SNP profiles. Our method is based on two assumptions. First, the wild-type allele frequently undergoes loss of heterozygosity (LOH) in the tumors of germline mutation carriers. Second, the overlap between the ancestral chromosome fragments inherited from a common founder will define a minimal haplotype conserved in each patient carrying the founder mutation. Our approach thus relies on the detection of haplotypes with significant identity by descent (IBD) sharing within recurrent regions of LOH to highlight genomic loci likely to harbor a founder mutation. We validated this approach by analyzing two real cancer data sets in which we successfully identified founder mutations of well-characterized tumor suppressor genes. We then used simulated data to evaluate the ability of our method to detect IBD tracts as a function of their size and frequency. We show that FounderTracker can detect haplotypes of low prevalence with high power and specificity, significantly outperforming existing methods. FounderTracker is thus a powerful tool for discovering unknown founder mutations that may explain part of the “missing” heritability in cancer. This method is freely available and can be used online at the FounderTracker website

Investigation of the role of SDHB inactivation in sporadic phaeochromocytoma and neuroblastoma

Germline mutations in the succinate dehydrogenase (SDH) (mitochondrial respiratory chain complex II) subunit B gene, SDHB, cause susceptibility to head and neck paraganglioma and phaeochromocytoma. Previously, we did not identify somatic SDHB mutations in sporadic phaeochromocytoma, but SDHB maps to 1p36, a region of frequent loss of heterozygosity (LOH) in neuroblastoma as well. Hence, to evaluate SDHB as a candidate neuroblastoma tumour suppressor gene (TSG) we performed mutation analysis in 46 primary neuroblastomas by direct sequencing, but did not identify germline or somatic SDHB mutations. As TSGs such as RASSF1A are frequently inactivated by promoter region hypermethylation, we designed a methylation-sensitive PCR-based assay to detect SDHB promoter region methylation. In 21% of primary neuroblastomas and 32% of phaeochromocytomas (32%) methylated (and unmethylated) alleles were detected. Although promoter region methylation was also detected in two neuroblastoma cell lines, this was not associated with silencing of SDHB expression, and treatment with a demethylating agent (5-azacytidine) did not increase SDH activity. These findings suggest that although germline SDHB mutations are an important cause of phaeochromocytoma susceptibility, somatic inactivation of SDHB does not have a major role in sporadic neural crest tumours and SDHB is not the target of 1p36 allele loss in neuroblastoma and phaeochromocytoma

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

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

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