Just 5 #sunburns [when young] increase your #cancer risk, by 80% for
melanoma http://www.nhs.uk/news/2014/06June/Pages/Just-five-sunburns-increases-your-cancer-risk.aspx As determined from surveys of nurses
Posts Tagged ‘cancer’
Just five sunburns increase your cancer risk – Health News – NHS Choices
July 22, 2016Integrative analyses reveal a long noncoding RNA-mediated sponge regulatory network in prostate cancer : Nature Communications : Nature Publishing Group
July 2, 2016lncRNA-mediated sponge regulatory network in prostate cancer http://www.nature.com/ncomms/2016/160315/ncomms10982/full/ncomms10982.html Few explicitly noted #pseudogenes besides PTENP1
Lalonde E*, Ishkanian AS*, ….P’ng C, Collins CC, Squire JA, Jurisica I, Cooper C, Eeles R, Pintilie M, Dal Pra A, Davicioni E, Lam WL, Milosevic M, Neal DE, van der Kwast T, Boutros PC, Bristow RG (2014) “Tumour genomic a nd microenvironmental heterogeneity as integrated predictors for prostate cancer recurrence: a retrospective study” La ncet Oncology 15(13):1521-1532 (PMID: 25456371)
May 17, 2016Genomic & microenvironmental heterogeneity as integrated predictors for prostate #cancer recurrence
http://www.ncbi.nlm.nih.gov/pubmed/25456371 CNVs & hypoxia
* Lalonde E*, Ishkanian AS*, ….P’ng C, Collins CC, Squire JA, Jurisica I, Cooper C, Eeles R, Pintilie M, Dal Pra A, Davicioni E, Lam WL, Milosevic M, Neal DE, van der Kwast T, Boutros PC, Bristow RG (2014) “Tumour genomic and microenvironmental heterogeneity as integrated predictors for prostate cancer recurrence: a retrospective study” Lancet Oncology 15(13):1521-1532 (PMID: 25456371)
The novelty of the paper is that it is the first study integrating DNA-based signatures and microenviroment-based signature for cancer prognosis. The authors found four prognostic indices, i.e. cancer genomic subtype (generated from clusters of CNV profiles), genomic instability (represented by the percentage of genome alteration), DNA signature (276 genes identified from random forests), and tumor hypoxia (the microenvironment signature), to be effective in predicting patient survival in different groups. Standard clinical univariate and multivariate analyses were performed.
Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations : Nature Genetics : Nature Publishing Group
May 2, 2016Identification of [872] sig. mutated regions across #cancer types http://www.nature.com/ng/journal/v48/n2/full/ng.3471.html ranges from noncoding annotations to 3D structure
repository of PDX models of leukemia and lymphoma
April 21, 2016Epigenomic analysis detects aberrant super-enhancer DNA methylation in human cancer | Genome Biology | Full Text
April 17, 2016two papers for journal club:
1. What are super-enhancers? Pott et al., Nature Genetics (2015) http://www.nature.com/ng/journal/v47/n1/full/ng.3167.html
2. Epigenomic analysis detects aberrant super-enhancer DNA methylation in human cancer, Heyn et al., Genome Biology (2016)
https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0879-2
#Epigenomic analysis detects aberrant super-enhancer DNA methylation in human #cancer
https://GenomeBiology.biomedcentral.com/articles/10.1186/s13059-016-0879-2 hypo-Me of many large blocks
How Not to End Cancer in Our Lifetimes – WSJ
April 8, 2016How Not to End Cancer in Our Lifetimes
http://www.wsj.com/articles/how-not-to-end-cancer-in-our-lifetimes-1459811684“It’s extraordinarily hard to re-identify tissue” anonymously biobanked. True?
PLOS Genetics: A Simple Model-Based Approach to Inferring and Visualizing Cancer Mutation Signatures
February 27, 2016Model-Based Approach to Inferring…#Cancer Mutation Signatures http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1005657 Assuming independence betw 3 NTs, 11 v 95 parameters
QT:{{”
The first contribution of this paper is to suggest a more parsimonious approach to modelling mutation signatures, with the benefit of producing both more stable estimates and more easily interpretable signatures. In brief, we substantially reduce the number of parameters per signature by breaking each mutation pattern into “features”, and assuming independence across mutation features. For example, consider the case where a mutation pattern is defined by the substitution and its two flanking bases. We break this into three features
(substitution, 3′ base, 5′ base), and characterize each mutation signature by a probability distribution for each feature (which, by our independence assumption, are multiplied together to define a distribution on mutation patterns). Since the number of possible values for each feature is 6, 4, and 4 respectively this requires 5 + 3 + 3 = 11 parameters instead of 96 − 1 = 95 parameters. Furthermore, extending this model to account for ±n neighboring bases requires only 5 + 6nparameters instead of 6 × 42n − 1. For example, considering ±2 positions requires 17 parameters instead of 1,535. Finally,
incorporating transcription strand as an additional feature adds just one parameter, instead of doubling the number of parameters. “}}
Identification of neutral tumor evolution across cancer types : Nature Genetics : Nature Publishing Group
February 27, 2016Neutral tumor #evolution across #cancer types
http://www.nature.com/ng/journal/v48/n3/full/ng.3489.html Initial burst of driver events followed by random mutations
Similarity network fusion for aggregating data types on a genomic scale : Nature Methods : Nature Publishing Group
February 9, 2016Similarity #network fusion for aggregating data types
http://www.nature.com/nmeth/journal/v11/n3/full/nmeth.2810.html Combines mRNA, miRNA & gene fusions to classify cancer subtypes http://compbio.cs.toronto.edu/SNF/SNF
linkstream2 microblog 