linkstream2 microblog

http://news.sciencemag.org/scienceinsider/2013/03/ready-for-more-10000-cancer-geno.html

https://www.cell.com/cancer-cell/abstract/S1535-6108(12)00520-X?switch=standard

Two papers in Science talking about recurrent mutations in TERT promoter in melanoma.

1) http://www.sciencemag.org/content/339/6122/957.full
Highly Recurrent TERT Promoter Mutations in Human Melanoma
Franklin W. Huang1,2,3,* Eran Hodis1,3,4,*,Mary Jue Xu1,3,4,Gregory V. Kryukov1,Lynda Chin5,6,Levi A. Garraway1,2,3,†

2) http://www.sciencemag.org/content/339/6122/959.full
TERT Promoter Mutations in Familial and Sporadic Melanoma
Susanne Horn1,2,Adina Figl1,2,P. Sivaramakrishna Rachakonda1,Christine Fischer3,Antje Sucker2,Andreas Gast1,2,Stephanie Kadel1,2,Iris Moll2,Eduardo Nagore4,Kari Hemminki1,5,Dirk Schadendorf2,*,†,Rajiv Kumar1,*,†

rnai, immuno, bact, viruses, nano

http://www.newscientist.com/article/mg21628861.800-the-five-most-promising-new-cancer-treatments.html?page=3

http://genome.cshlp.org/content/early/2012/11/01/gr.141382.112
analysis of 95 tumor genomes

http://genomemedicine.com/content/4/11/88

associated with transFIC method

This paper introduces a new method for detecting copy number variants in cancer genomes that addresses deficiencies of previous detection methods. The new method, dubbed HHCRF by the authors, adds the use of sequential correlations in selecting classification features for inferring copy numbers and identifying clinically relevant genes. This improvement results in higher accuracy on noisy data, and the identification of more clinically relevant genes, relative to previous methods. These results were obtained by testing HHCRF on both simulated array-CGH microarray data, and on actual breast cancer, uveal melanoma, and bladder tumor datasets.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2677736/
Bioinformatics. 2009 May 15;25(10):1307-13. Epub 2008 Dec 3. Aneuploidy prediction and tumor classification with heterogeneous hidden conditional random fields.
Barutcuoglu Z, Airoldi EM, Dumeaux V, Schapire RE, Troyanskaya OG.

http://www.ncbi.nlm.nih.gov/pubmed/22726445
Cell. 2012 Jun 22;149(7):1622-34.

From XJM:

A few references about nonsynonymous/synonymous ratio in Cancer: Here is a Nature paper finding nonsynonymous/synonymous ratio to be 3:1 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2712719/

Here is an article reporting the ratio to be about 4:1
http://www.nature.com/ng/journal/v43/n11/full/ng.950.html

Another one:
http://onlinelibrary.wiley.com/doi/10.1111/j.1755-148X.2012.00976.x/full

An online powerpoint reporting 2:1 ratio:
http://www.genome.gov/Pages/Research/DIR/DIRNewsFeatures/Next-Gen101/Samuels_WholeExomeSequencing.pdf

http://www.pnas.org/content/109/35/14087.abstract
Allusion to whole genome data, but focus is on coding regions & mitochondrial mutations