linkstream2 microblog

mis-sense change (G84E) in HOXB13 was found overall in 1.4% of prostate cancer cases and in 0.1% of unaffected controls

http://www.ncbi.nlm.nih.gov/pubmed/22236224

QT:{{”
So this is a therapy that goes by a somewhat unwieldy name of CAR T cell therapy….
So it’s sort of combining a few different types of
therapy; it’s the gene therapy, although the genetic modifications happen outside of the
person’s body, that’s one piece. It’s what’s called an immunotherapy, which means it’s
trying to kind of harness the immune system to fight cancer. And it’s also highly
personalized because every patient’s therapy is their own; you can’t just create T cells
and give them to everybody, it’s sort of a unique batch for each patient. “}}

Dizzying Journey to a New #Cancer Arsenal: CAR Tcell therapy combines gene therapy, immunotherapy & personalization into an effective treatment for ~$50K
http://www.sciencemag.org/content/340/6140/1514.summary

Steve #Jobs Left a Legacy on Personalized Medicine: $100K on his own #cancer genome as a progenitor to Foundation Med
http://www.technologyreview.com/view/519686/steve-jobs-left-a-legacy-on-personalized-medicine

Mutational landscape and significance across 12 major #cancer types: Common genes mutated in different cancers
http://www.nature.com/nature/journal/v502/n7471/full/nature12634.html

http://www.sciencedaily.com/releases/2013/10/131016132143.htm

Mutational landscape and significance across 12 major cancer types http://www.nature.com/nature/journal/v502/n7471/full/nature12634.html

Summary for:

“Epigenomic Alterations in Localized and Advanced Prostate Cancer” Lin PC, Giannopoulou E, Park K, Mosquera JM, Sboner A, Tewari AK, Garraway LA, Beltran H, Rubin MA*, Elemento O*. 2013. Epigenomic alterations in localized and advanced prostate cancer. Neoplasia

http://www.ncbi.nlm.nih.gov/pubmed/23555183

In this paper, the authors take advantage of new advances in reduced representation bisulfite sequencing, a method for measuring DNA methylation patterns genome-wide, with high coverage and
single-nucleotide resolution, to study methylation patterns in prostate cancer. Working with a prostate cancer cohort already studied with DNA-Seq and RNA-Seq analyses, the authors identified
differentially methylated regions (DMRs), comparing the methylation of prostate cancer samples to benign prostate samples. The analysis found an increase in DNA methylation in prostate cancer samples, and that the methylation was more diverse and heterogeneous compared to the patterns of benign samples. Furthermore, it was found that genes near hypermethylated DMRs tended to have decreased expression, while genes near hypomethylated DMRs tended to have increased expression. Additional analyses revealed that breakpoints associated with prostate-cancer-specific deletions, duplications, and translocations tended to be highly methylated in benign prostate tissue. Finally, a study of CpG islands at different stages of prostate cancer (benign vs. PCa vs. CRPC (castration-resistant prostate cancer)) revealed that certain islands become increasingly methylated with disease severity. The authors used this data as the basis for two classification models: one to discriminate between benign prostate tissue and PCa tissue, and another to discriminate between PCa tissue and CRPC tissue. Both models demonstrated high sensitivity and specificity, indicating that CpG islands with high discriminatory power could serve as a diagnostic basis for predicting disease aggressiveness. Finally, additional analyses revealed that breakpoints associated with
prostate-cancer-specific deletions, duplications, and translocations tended to be highly methylated in benign prostate tissue.

http://tcga.github.io/
http://tcga.github.io/Roadmap

http://www.citeulike.org/user/neils/article/12718324?utm_source=twitterfeed&utm_medium=twitter

Genome Biol. 2012 Dec 13;13(12):R115.

Whole-genome reconstruction and mutational signatures in gastric cancer. Nagarajan N, Bertrand D, Hillmer AM, Zang ZJ, Yao F, Jacques PE, Teo AS, Cutcutache I, Zhang Z, Lee WH, Sia YY, Gao S, Ariyaratne PN, Ho A, Woo XY, Veeravali L, Ong CK, Deng N, Desai KV, Khor CC, Hibberd ML, Shahab A, Rao J, Wu M, Teh M, Zhu F, Chin SY, Pang B, So JB, Bourque G, Soong R, Sung WK, Tean Teh B, Rozen S, Ruan X, Yeoh KG, Tan PB, Ruan Y.

http://www.ncbi.nlm.nih.gov/pubmed/23237666

Some thoughts, much from WC:

Looks like the data is freely available via GEO ID : GSE30833 http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE30833

The article by Nagarajan et al. highlights the authors efforts to utilize de novo genome assembly of gastric cancer genomes to detect not only single nucleotide variants (SNV’s) and short
insertions/deletions (indels), but also larger scale genomic structural variation (SV) that could be signatures of cancer genomes. It is to be applauded that this is a whole genome analysis.

The authors present several interesting findings such as enrichment for C->A and T->A mutations in both cancer genomes, enrichment for C->A and C->T mutations in the H. pylori infected cancer genome (evidence of cytosine specific transcription mediated DNA repair due to deamination), and amplification and deletion of regions on chromosome 12 in the non-H. pylori infected genome.

Although copy number variants (CNV) could potentially be detected by exome sequencing alone, whole genome sequence enables the precise localization of such events, as well as the detection of variation in non-coding regions.

Their methodology relies on combining high-throughput short-read sequencing with longer DNA-PET (paired end tags) in order to construct higher confidence de novo assemblies with longer contiguous regions.

http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.2651.html

Network-based stratification of tumor mutations

Matan Hofree,
John P Shen,
Hannah Carter,
Andrew Gross
& Trey Ideker

Nature Methods(2013)doi:10.1038/nmeth.2651

500 whole-genome cancer sequences

http://www.nature.com/nature/journal/vaop/ncurrent/full/nature12477.html