linkstream2 microblog

PanCancer.info has fantastic #viz of the progress & int’l effort in the Pan-#Cancer Analysis of Whole #Genomes (#PCAWG) project

Science. 2008 Nov 28;322(5906):1377-80. doi: 10.1126/science.1164266.

Mullighan CG1, Phillips LA, Su X, Ma J, Miller CB, Shurtleff SA, Downing JR.

Interesting older paper

Genomic analysis of the clonal origins of relapsed ALL
http://www.sciencemag.org/content/322/5906/1377.abs Older paper, describing relapse as arising from minor subclone

NYT recently ran an article as well:
http://www.nytimes.com/2014/04/08/business/cancer-analysis-tools-circumvent-biopsies.html

http://www.nature.com/nm/journal/v20/n4/abs/nm.3511.html

An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage
http://www.nature.com/nm/journal/vaop/ncurrent/abs/nm.3519.html

http://stm.sciencemag.org/content/6/224/224ra24
http://www.nejm.org/doi/full/10.1056/NEJMoa1213261

http://stm.sciencemag.org/content/4/162/162ra154.full
DIAGNOSTICS: Detection of Chromosomal Alterations in the Circulation of Cancer Patients with Whole-Genome Sequencing

we can play in meetings, and tell people we are working on cancer research.
http://scienceblog.cancerresearchuk.org/2014/02/04/download-our-revolutionary-mobile-game-to-help-speed-up-cancer-research

http://www.nature.com/ncomms/2014/140409/ncomms4644/full/ncomms4644.html

Original article emphasizing the importance of networks to cancer

http://www.nature.com/nature/journal/v408/n6810/full/408307a0.html

A paper that was done by Vogelstein, Lane and Levine in Nature (2000, November 16) that talks about how cancer is associated with a network and these network of genes associated with p53. This is in response to the idea that p53 is such a crucial molecule in cancer as a tumor suppressor and it marks well known cancer biologists discussing this from a network perspective.

QT:"We show that many translocation-prone pairs of regions genome-wide, including the cancer translocation partners BCR-ABL and MYC-IGH, display elevated Hi-C contact frequencies in normal human cells."

Overlap of Hi-C & gene fusions

http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0044196

http://ac.els-cdn.com/S0092867414001457/1-s2.0-S0092867414001457-main.pdf?_tid=82c57e74-c01a-11e3-95b3-00000aacb35e&acdnat=1397070764_5c441e4c90a317cc7642b6873f888eb6

http://www.sciencedirect.com/science/article/pii/S0092867414001457

paper from RECOMB 2014 might be interesting to you, which uses
hitting time in random walk to identify cancer drivers.

http://link.springer.com/chapter/10.1007%2F978-3-319-05269-4_23

HIT.nDRIVE: Multi-Driver Gene Prioritization based on Hitting Time

Raunak Shrestha, Ermin Hodzic, Jake Yeung, Kendric Wang, Thomas
Sauerwald, Phuong Dao, Shawn Anderson, Himisha Beltran, Mark A. Rubin,
Colin Collins, Gholamreza Haffari and S. Cenk Sahinalp.

Looks like 88 freely available liver cancer genome datasets
http://gigadb.org/dataset/100034