Subcellular localization of NEDD9 and HMB45 with AQUA technology to distinguish Spitz nevi from melanoma

SUBCELLULAR LOCALIZATION OF NEDD9 AND HMB45 WITH AQUA TECHNOLOGY TO DISTINGUISH SPITZ NEVI FROM MELANOMA. Matthew C. McRae, Rossitza Lasova, Bonnie Gould-Rothberg, David Rimm (Sponsored by Deepak Narayan). Section of Plastic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT. Our hypothesis is that the expression level and subcellular localization of HMB45 and NEDD9 as demonstrated by the ln(nuclear/non-nuclear) Automated Quantitative Analysis (AQUA) score, defined as the subcellular AQUA ratio, will be consistently altered between benign nevi and melanoma and between Spitz nevi and Spitzoid melanoma. Our specific aims are to assess quantitative expression and subcellular localization of HMB45 and NEDD9 to aid in the diagnosis of benign Spitz nevi and malignant Spitzoid melanoma. This remains a vexing clinical problem with important implications for treatment and patient care. The quantitative expression and subcellular AQUA ratio will be assessed in the following samples: benign derived versus malignant derived cell lines, human benign nevi, human primary melanoma, human metastatic melanoma, typical Spitz nevi, atypical Spitz nevi and Spitzoid melanoma. AQUA was used to quantify protein expression levels in subcellular compartments using fluorescence-based immunohistochemistry. Tissue Microarrays (TMA) analysis was used for cell line, benign nevi and malignant melanoma while whole section analysis was used for Spitz nevi and Spitzoid melanoma. NEDD9 subcellular AQUA ratio was significantly reduced in primary melanoma (mean=-0.645, std dev=0.29) versus benign nevi (mean = -0.429, std dev=0.108) on YTMA98-2 (p=0.0086), significantly reduced in melanoma metastases (mean=-0.482, std dev=0.149) versus benign nevi (mean= -0.342, std dev=0.159) on YTMA66A (p\u3c0.0001), and significantly reduced in primary melanoma (mean= -0.435, std. dev.=0.185) and melanoma metastases (mean= -0.42, std. dev.= 0.188) versus benign nevi (mean= -0.319, std. dev.= 0.141) in SPORE84 array (p=0.0003, Tukey/Kramer post-hoc significance p\u3c0.05). HMB45 subcellular AQUA ratio was significantly reduced in primary melanoma (mean=-0.463, std. dev.=0.264) versus benign nevi (mean=-0.159, std. dev.=0.158) on YTMA 98-2 array (p=0.0001). On whole section analysis, the HMB45 and NEDD9 subcellular AQUA ratio shared a similar distribution between Spitz nevi, atypical Spitz nevi and Spitzoid melanoma. Subcellular localization using the subcellular AQUA ratio of HMB45 and NEDD9 defines benign nevi from melanoma on TMA but is not useful in discriminating between benign Spitz nevi and melanoma with Spitzoid features. The maximum HMB45 AQUA score in the tumor mask in a single 20X high-powered field of a whole tissue section was deemed promising on discovery analysis at differentiating between Spitz nevi and melanoma with Spitzoid features (p=0.007, receiver operating characteristic area under curve 0.711) but requires validation on an independent cohort

The contribution of X-linked coding variation to severe developmental disorders

Over 130 X-linked genes have been robustly associated with developmental disorders, and X-linked causes have been hypothesised to underlie the higher developmental disorder rates in males. Here, we evaluate the burden of X-linked coding variation in 11,044 developmental disorder patients, and find a similar rate of X-linked causes in males and females (6.0% and 6.9%, respectively), indicating that such variants do not account for the 1.4-fold male bias. We develop an improved strategy to detect X-linked developmental disorders and identify 23 significant genes, all of which were previously known, consistent with our inference that the vast majority of the X-linked burden is in known developmental disorder-associated genes. Importantly, we estimate that, in male probands, only 13% of inherited rare missense variants in known developmental disorder-associated genes are likely to be pathogenic. Our results demonstrate that statistical analysis of large datasets can refine our understanding of modes of inheritance for individual X-linked disorders. Developmental disorders (DDs) are more prevalent in males, thought to be due to X-linked genetic variation. Here, the authors investigate the burden of X-linked coding variants in 11,044 DD patients, showing that this contributes to similar to 6% of both male and female cases and therefore does not solely explain male bias in DDs.Peer reviewe

Multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults

The molecular factors which control circulating levels of inflammatory proteins are not well understood. Furthermore, association studies between molecular probes and human traits are often performed by linear model-based methods which may fail to account for complex structure and interrelationships within molecular datasets.In this study, we perform genome- and epigenome-wide association studies (GWAS/EWAS) on the levels of 70 plasma-derived inflammatory protein biomarkers in healthy older adults (Lothian Birth Cohort 1936; n = 876; Olink® inflammation panel). We employ a Bayesian framework (BayesR+) which can account for issues pertaining to data structure and unknown confounding variables (with sensitivity analyses using ordinary least squares- (OLS) and mixed model-based approaches). We identified 13 SNPs associated with 13 proteins (n = 1 SNP each) concordant across OLS and Bayesian methods. We identified 3 CpG sites spread across 3 proteins (n = 1 CpG each) that were concordant across OLS, mixed-model and Bayesian analyses. Tagged genetic variants accounted for up to 45% of variance in protein levels (for MCP2, 36% of variance alone attributable to 1 polymorphism). Methylation data accounted for up to 46% of variation in protein levels (for CXCL10). Up to 66% of variation in protein levels (for VEGFA) was explained using genetic and epigenetic data combined. We demonstrated putative causal relationships between CD6 and IL18R1 with inflammatory bowel disease and between IL12B and Crohn’s disease. Our data may aid understanding of the molecular regulation of the circulating inflammatory proteome as well as causal relationships between inflammatory mediators and disease

Evidence for 28 genetic disorders discovered by combining healthcare and research data

De novo mutations in protein-coding genes are a well-established cause of developmental disorders. However, genes known to be associated with developmental disorders account for only a minority of the observed excess of such de novo mutations. Here, to identify previously undescribed genes associated with developmental disorders, we integrate healthcare and research exome-sequence data from 31,058 parent–offspring trios of individuals with developmental disorders, and develop a simulation-based statistical test to identify gene-specific enrichment of de novo mutations. We identified 285 genes that were significantly associated with developmental disorders, including 28 that had not previously been robustly associated with developmental disorders. Although we detected more genes associated with developmental disorders, much of the excess of de novo mutations in protein-coding genes remains unaccounted for. Modelling suggests that more than 1,000 genes associated with developmental disorders have not yet been described, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of genes associated with developmental disorders

Making new genetic diagnoses with old data:iterative reanalysis and reporting from genome-wide data in 1,133 families with developmental disorders

Purpose Given the rapid pace of discovery in rare disease genomics, it is likely that improvements in diagnostic yield can be made by systematically reanalyzing previously generated genomic sequence data in light of new knowledge. Methods We tested this hypothesis in the United Kingdom–wide Deciphering Developmental Disorders study, where in 2014 we reported a diagnostic yield of 27% through whole-exome sequencing of 1,133 children with severe developmental disorders and their parents. We reanalyzed existing data using improved variant calling methodologies, novel variant detection algorithms, updated variant annotation, evidence-based filtering strategies, and newly discovered disease-associated genes. Results We are now able to diagnose an additional 182 individuals, taking our overall diagnostic yield to 454/1,133 (40%), and another 43 (4%) have a finding of uncertain clinical significance. The majority of these new diagnoses are due to novel developmental disorder–associated genes discovered since our original publication. Conclusion This study highlights the importance of coupling large-scale research with clinical practice, and of discussing the possibility of iterative reanalysis and recontact with patients and health professionals at an early stage. We estimate that implementing parent–offspring whole-exome sequencing as a first-line diagnostic test for developmental disorders would diagnose >50% of patients.</p

C3 glomerulopathy-associated CFHR1 mutation alters FHR oligomerization and complement regulation

C3 glomerulopathies (C3G) are a group of severe renal diseases with distinct patterns of glomerular inflammation and C3 deposition caused by complement dysregulation. Here we report the identification of a familial C3G-associated genomic mutation in the gene complement factor H–related 1 (CFHR1), which encodes FHR1. The mutation resulted in the duplication of the N-terminal short consensus repeats (SCRs) that are conserved in FHR2 and FHR5. We determined that native FHR1, FHR2, and FHR5 circulate in plasma as homo- and hetero-oligomeric complexes, the formation of which is likely mediated by the conserved N-terminal domain. In mutant FHR1, duplication of the N-terminal domain resulted in the formation of unusually large multimeric FHR complexes that exhibited increased avidity for the FHR1 ligands C3b, iC3b, and C3dg and enhanced competition with complement factor H (FH) in surface plasmon resonance (SPR) studies and hemolytic assays. These data revealed that FHR1, FHR2, and FHR5 organize a combinatorial repertoire of oligomeric complexes and demonstrated that changes in FHR oligomerization influence the regulation of complement activation. In summary, our identification and characterization of a unique CFHR1 mutation provides insights into the biology of the FHRs and contributes to our understanding of the pathogenic mechanisms underlying C3G

The National Lung Matrix Trial: translating the biology of stratification in advanced non-small-cell lung cancer

© The Author 2015.Background: The management of NSCLC has been transformed by stratified medicine. The National Lung Matrix Trial (NLMT) is a UK-wide study exploring the activity of rationally selected biomarker/targeted therapy combinations. Patients and methods: The Cancer Research UK (CRUK) Stratified Medicine Programme 2 is undertaking the large volume national molecular pre-screening which integrates with the NLMT. At study initiation, there are eight drugs being used to target 18 molecular cohorts. The aim is to determine whether there is sufficient signal of activity in any drug-biomarker combination to warrant further investigation. A Bayesian adaptive design that gives a more realistic approach to decision making and flexibility to make conclusions without fixing the sample size was chosen. The screening platform is an adaptable 28-gene Nextera next-generation sequencing platform designed by Illumina, covering the range of molecular abnormalities being targeted. The adaptive design allows new biomarker-drug combination cohorts to be incorporated by substantial amendment. The pre-clinical justification for each biomarker-drug combination has been rigorously assessed creating molecular exclusion rules and a trumping strategy in patients harbouring concomitant actionable genetic abnormalities. Discrete routes of pathway activation or inactivation determined by cancer genome aberrations are treated as separate cohorts. Key translational analyses include the deep genomic analysis of pre- and post-treatment biopsies, the establishment of patient-derived xenograft models and longitudinal ctDNA collection, in order to define predictive biomarkers, mechanisms of resistance and early markers of response and relapse. Conclusion: The SMP2 platform will provide large scale genetic screening to inform entry into the NLMT, a trial explicitly aimed at discovering novel actionable cohorts in NSCLC