Posts Tagged ‘cancer’

Boutros PC…., van der Kwast T, Bristow RG* (2015) “Spatial genomic heterogeneity within localized, mult i-focal prostate cancer” Nature Genetics 47(7):736-745 (PMID: 26005866)

January 25, 2016

Spatial genomic heterogeneity w/in…prostate #cancer
http://www.nature.com/ng/journal/v47/n7/full/ng.3315.html WGS analysis of many sites suggests divergent tumor evolution

Boutros…, van der Kwast, Bristow (2015) “Spatial genomic
heterogeneity within localized, multi-focal prostate cancer” Nature Genetics 47(7):736-745 (PMID: 26005866)

This work represents the first systematic relation of intraprostatic genomic heterogeneity to predicted clinical outcomes at the level of whole-genome sequencing (WGS). Five patients, with index tumors of Gleason score 7, were subjected to a WGS protocol with spatial sampling of 23 distinct tumor regions to assess intraprostatic heterogeneity. In their analysis, Boutros et al, discovered recurrent amplification of MYCL, which is associated with TP53 loss. This finding is one of the first clear functional distinctions between MYC family members in prostate cancer and suggests that MYCL amplification may be preferentially localized in the index lesion. Overall, the authors believe their results are useful in the development of prognostic biomarkers that are necessary to achieve personalized prostate cancer medicine. It is important to note that such diagnostic biopsy protocols can miss regions of more aggressive cancers resulting in the patient being under-staged.

Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution : Nature : Nature Publishing Group

January 23, 2016

Dynamics of genomic clones in breast #cancer PDX at #singlecell resolution http://www.nature.com/nature/journal/v518/n7539/full/nature13952.html Extensive trees of samples & some WGS

Peter Eirew,
Adi Steif,
Jaswinder Khattra,
Gavin Ha,

Jazmine Brimhall,
Arusha Oloumi,
Tomo Osako
et al.

Nature 518, 422–426 (19 February 2015) doi:10.1038/nature13952

Ewing AD*, Houlahan KE…..Stuart JM, Boutros PC (2015) “Combining accurate tumour genome simulation with crow d-sourcing to benchmark somatic single nucleotide variant detection” Nature Methods 12(7):623-630 (PMID: 25984700)

December 28, 2015

Tumor genome simulation w/ #crowdsourcing to benchmark…SNV detection http://www.nature.com/nmeth/journal/v12/n7/full/nmeth.3407.html Addresses lack of gold standards & privacy

Ewing, Houlahan…..Stuart, Boutros (2015) “Combining accurate
tumour genome simulation with crowd-sourcing to benchmark somatic
single nucleotide variant detection” Nature Methods 12(7):623-630
(PMID: 25984700)

A crowdsourced benchmark of somatic mutation detection algorithms was
introduced for the ICGC-TCGA DREAM challenge. This has the advantage
of dealing with the lack of gold standard data and the issue of
sharing private genomic data. All groups worked on three different
simulated tumor-normal pairs generated with BAMSurgeon, by directly
adding synthetic mutations to existing reads. An ensemble of
pipelines outperforms the best individual pipeline in all cases,
assessed on the basis of recall, precision and F-score.
Parameterization and genomic localization both have an effect on
pipeline performance, while characteristics of prediction errors
differed for most pipelines.

Humans 2.0

November 26, 2015

Humans 2.0 http://www.newyorker.com/magazine/2015/11/16/the-gene-hackers @eric_lander: “What I love: #CRISPR [can] KO every gene &
identify…the [cancer] cell’s Achilles’ heels”

QT:{{”
“What I love most about the CRISPR process is that you can take any cancer-cell line, knock out every gene, and identify every one of the cell’s Achilles’ heels,” Eric Lander, the fifty-eight-year-old director of the Broad, told me recently. Lander, who was among the leaders of the Human Genome Project, said that he had never
encountered a more promising research tool. “You can also use CRISPR to systematically study the ways that a cancer cell can escape from a treatment,” he said. “That should make it possible to build a comprehensive road map for cancer.”

Lander went on to say that each vulnerability of a tumor might be attacked by a single drug. But cancer cells elude drugs in many ways, and, to succeed, a therapy may need to block them all. That strategy has proved effective for infectious diseases like AIDS. “Remember the pessimism about H.I.V.,” he said, referring to the early years of the AIDS epidemic, when a diagnosis was essentially a death sentence. Eventually, virologists developed a series of drugs that interfere with the virus’s ability to replicate. The therapy became truly successful, however, only when those drugs, working together, could block the virus completely.
“}}

Cell-of-origin chromatin organization shapes the mutational landscape of cancer : Nature : Nature Publishing Group

September 2, 2015

#Chromatin…shapes the mutational landscape of cancer
http://www.nature.com/nature/journal/v518/n7539/full/nature14221.html Low DNase correlates w/ high SNVs in melanoma. True generally?

Glypican-1 identifies cancer exosomes and detects early pancreatic cancer : Nature : Nature Publishing Group

August 16, 2015

[Protein] Glypican-1 [uniquely] identifies [circulating] cancer #exosomes & detects…cancer
http://www.nature.com/nature/journal/v523/n7559/full/nature14581.html Maybe also for @exRNA

QT:{{”
Exosomes are lipid-bilayer-enclosed extracellular vesicles that contain proteins and nucleic acids. They are secreted by all cells and circulate in the blood. Specific detection and isolation of
…we identify a cell surface
proteoglycan, glypican-1 (GPC1), specifically enriched on
cancer-cell-derived exosomes. GPC1+ circulating exosomes (crExos) were monitored …”}}

http://www.nature.com/nature/journal/v523/n7559/full/nature14581.html

A subway map of cancer pathways

June 21, 2015

A subway map of #cancer #pathways
http://www.nature.com/nrc/poster/subpathways The cell cycle appears to be midtown. #DataViz via metaphor.

Recurrent somatic mutations in regulatory regions of human cancer genomes

June 10, 2015

http://www.nature.com/ng/journal/vaop/ncurrent/full/ng.3332.html

Structural insights into mis-regulation of protein kinase A in human tumors

June 8, 2015

Hendrickson cites: Structural insights into mis-regulation of PKA in…tumorshttp://www.pnas.org/content/112/5/1374 SNV stops reg. domain binding #ICSG2015

In other case showed recurring DnaJ–PKA fusion didn’t have coding effect but non-coding effect on promotor

vol. 112 no. 5
1374–1379, doi: 10.1073/pnas.1424206112
Structural insights into mis-regulation of protein kinase A in human tumors

Jonah Cheunga,1,
Christopher Gintera,
Michael Cassidya,
Matthew C. Franklina,
Michael J. Rudolpha,
Nicolas Robineb,
Robert B. Darnellb,c,d, and
Wayne A. Hendricksona,e,1

Similarity network fusion for aggregating data types on a genomic scale : Nature Methods : Nature Publishing Group

June 1, 2015

Similarity #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