Posts Tagged ‘cancer’

Breaking Into The Brain | Chemical & Engineering News

September 22, 2017

Breaking Into the #Brain
http://CEN.ACS.org/articles/92/i2/Breaking-Brain.html Contrasts potential for drug discovery in neuro-diseases v #cancer (which is “easier”)

interesting brain v cancer contrast

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Whole-genome landscapes of major melanoma subtypes : Nature : Nature Research

September 4, 2017

Hayward, Nicholas K., et al. "Whole-genome landscapes of major melanoma subtypes." Nature 545.7653 (2017): 175-180.

Whole-genome landscapes of…#melanoma subtypes http://www.Nature.com/nature/journal/vaop/ncurrent/full/nature22071.html Sun-exposed cutaneous w. many C>T SNVs v acral/mucosal w. many SVs

Naked mole rats: Can they help us cure cancer? – Slate Magazine

July 31, 2017

Naked mole rats: Can they help..cure cancer?
http://www.Slate.com/articles/health_and_science/the_mouse_trap/2011/11/naked_mole_rats_can_they_help_us_cure_cancer_.html Live >6x longer than C57BL/6 & have “insectile” queen-domimated society

FYI – Personalized Medicine: Redefining Cancer Treatment

July 3, 2017

https://www.kaggle.com/c/msk-redefining-cancer-treatment

A Big Bang model of human colorectal tumor growth : Nature Genetics : Nature Research

June 7, 2017

https://www.nature.com/ng/journal/v47/n3/full/ng.3214.html

Big Bang model of…tumor growth, v. slow #evolution under selection https://www.Nature.com/ng/journal/v47/n3/full/ng.3214.html #Cancer is born w/ key mutations all there

Andrea Sottoriva,
Haeyoun Kang,
Zhicheng Ma,
Trevor A Graham,
Matthew P Salomon,
Junsong Zhao,
Paul Marjoram,
Kimberly Siegmund,
Michael F Press,
Darryl Shibata
& Christina Curtis

Nature Genetics 47, 209–216 (2015) doi:10.1038/ng.3214

Cell Signaling by Receptor Tyrosine Kinases: Cell

May 20, 2017

[category scilit]

Cell signaling by #RTKs Nice 1st fig showing 20 sub-families and architecture of extra- & intra- cellular domains

A.I. Versus M.D.

May 7, 2017

AI v MD by @DrSidMukherjee http://www.NewYorker.com/magazine/2017/04/03/ai-versus-md great progress finding skin #cancer. Eventually, continuous monitoring via iPhone pics

QT:{{"
“In June, 2015, Thrun’s team began to test what the machine had learned from the master set of images by presenting it with a “validation set”: some fourteen thousand images that had been diagnosed by dermatologists (although not necessarily by biopsy). Could the system correctly classify the images into three diagnostic categories—benign lesions, malignant lesions, and non-cancerous growths? The system got the answer right seventy-two per cent of the time. …Two board-certified dermatologists who were tested alongside did worse: they got the answer correct sixty-six per cent of the time.

“There’s one rather profound thing about the network that wasn’t fully emphasized in the paper,” Thrun told me. In the first iteration of the study, he and the team had started with a totally naïve neural network. But they found that if they began with a neural network that had already been trained to recognize some unrelated feature (dogs versus cats, say) it learned faster and better. Perhaps our brains function similarly. Those mind-numbing exercises in high school—factoring polynomials, conjugating verbs, memorizing the periodic table—were possibly the opposite: mind-sensitizing.”
"}}

Genes, environment, and “bad luck” | Science

March 26, 2017

Genes, environment & bad luck
http://science.ScienceMag.org/content/355/6331/1266 To what degree are #cancer mutations due to replication error (3rd factor), not 1st 2?

discusses R v D correlation

Stem cell divisions, somatic mutations, cancer etiology, and cancer prevention Cristian Tomasetti1,2,*, Lu Li2, Bert Vogelstein3,*
Science 24 Mar 2017:
Vol. 355, Issue 6331, pp. 1330-1334
DOI: 10.1126/science.aaf9011
http://science.sciencemag.org/content/355/6331/1330

Transmissible Dog Cancer Genome Reveals the Origin and History of an Ancient Cell Lineage | Science

March 4, 2017

Transmissible Dog Cancer Genome Reveals…History of an Ancient Cell Lineage http://science.sciencemag.org/content/343/6169/437.full After 11k yrs 2M SNVs & 646 genes KO’ed

Elizabeth P. Murchison1,2,*,†,
David C. Wedge1,*,
Ludmil B. Alexandrov1,
Beiyuan Fu1,
Inigo Martincorena1,
Zemin Ning1,
Jose M. C. Tubio1,
Emma I. Werner1,
Jan Allen3,
Andrigo Barboza De Nardi4,
Edward M. Donelan3,
Gabriele Marino5,
Ariberto Fassati6,
Peter J. Campbell1,
Fengtang Yang1,
Austin Burt7,
Robin A. Weiss6,
Michael R. Stratton1,†

+ See all authors and affiliations

Science 24 Jan 2014:
Vol. 343, Issue 6169, pp. 437-440
DOI: 10.1126/science.1247167

TP53 copy number expansion is associated with the evolution of increased body size and an enhanced DNA damage response in elephants | eLife

March 4, 2017

TP53 copy number expansion is associated w…enhanced DNA damage response in elephants https://elifesciences.org/content/5/e11994 18 p53 retro- & pseudo- genes