Bioinformatics. Sep 15, 2013; 29(18): 2223–2230.
Published online Jul 9, 2013. doi: 10.1093/bioinformatics/btt375 PMCID: PMC3753564
A comparative analysis of algorithms for somatic SNV detection in cancer
Why So Few Blockbuster #Drugs Invented Today? (Eroom’s law) http://www.nytimes.com/2014/11/16/magazine/why-are-there-so-few-new-drugs-invented-today.html Short answer: use of genomics v traditional pharmacology
QT:{{"
“If you read them now, the claims made for genomics in the 1990s sound
a bit like predictions made in the 1950s for flying cars and
anti-gravity devices,” Jack Scannell, an industry analyst, told me.
But rather than speeding drug development, genomics may have slowed it
down. So far it has produced fewer returns on greater investments.
Scannell and Brian Warrington, who worked for 40 years inventing drugs
for pharmaceutical companies, published a grim paper in 2012 that
showed the plummeting efficiency of the pharmaceutical industry. They
found that for every billion dollars spent on research and development
since 1950, the number of new drugs approved has fallen by half
roughly every nine years, meaning a total decline by a factor of 80.
They called this Eroom’s Law, because it resembled an inversion of
Moore’s Law (the observation, first made by the Intel co-founder
Gorden E. Moore in 1965, that the number of transistors in an
integrated circuit doubles approximately about every two years).
That’s not to say that target-based drug discovery, informed by
genomics, hasn’t had its share of spectacular successes. Gleevec, used
since 2001 to treat chronic myelogenous leukemia (C.M.L.) and a
variety of other cancers, is often pointed to as one of the great
gene-to-medicine success stories. Its design followed logically from
the identification of an abnormal protein caused by a genetic glitch
found in almost every cancer cell of patients with C.M.L.
Many of the drugs developed through target-based discovery, however,
work for only single-mutation diseases affecting a tiny number of
people. Seventy percent of new drugs approved by the F.D.A. last year
were so-called specialty drugs used by no more than 1 percent of the
population. The drug Kalydeco, for instance, was approved in 2012 for
people with a particular genetic mutation that causes cystic fibrosis.
But only about 1,200 people in the United States have the mutation it
corrects.
"}}
Dataset of 100 freely available STAD T/N pairs
http://www.nature.com/ng/journal/v46/n6/full/ng.2983.html#affil-auth
Kai Wang,
Siu Tsan Yuen,
Jiangchun Xu,
Siu Po Lee,
Helen H N Yan,
Stephanie T Shi,
Hoi Cheong Siu,
Shibing Deng,
Kent Man Chu,
Simon Law,
Kok Hoe Chan,
Annie S Y Chan,
Wai Yin Tsui,
Siu Lun Ho,
Anthony K W Chan,
Jonathan L K Man,
Valentina Foglizzo,
Man Kin Ng,
April S Chan,
Yick Pang Ching,
Grace H W Cheng,
Tao Xie,
Julio Fernandez,
Vivian S W Li,
Hans Clevers,
Paul A Rejto,
Mao Mao
& Suet Yi Leung
Nature Genetics 46, 573–582 (2014) doi:10.1038/ng.2983Received 01 August 2013 Accepted 18 April 2014 Published online 11 May 2014
Realizing the promise of cancer predisposition genes : Nature : Nature Publishing Group
http://www.nature.com/nature/journal/v505/n7483/full/nature12981.html
@markgerstein: .@rahman_nazneen mentions: Realizing the promise of cancer predisposition genes [of which there’s >100]
http://t.co/BbGNK6VJko #BTGCG14
@markgerstein: Navin mentions: Tracing the tumor lineage
http://t.co/pDTQBxmd54 Has nice schematic showing different tumor progression models #BTGCG14
http://www.sciencedirect.com/science/article/pii/S1574789110000323?via=ihub
@markgerstein: .nlbigas mentions: OncodriveCLUST: exploiting the [local] positional clustering of somatic mutations…
http://t.co/JbMYp6C7bF #BTGCG14
http://bioinformatics.oxfordjournals.org/content/29/18/2238.long
@markgerstein: .@nlbigas mentions: Evolution of the cancer genome http://t.co/DLwrOlzqch Drivers provide selective advantage #BTGCG14
@markgerstein: Korbel mentions: Criteria for Inference of
Chromothripsis in Cancer Genome
http://t.co/TslcrZsmNv #BTGCG14
http://www.sciencedirect.com/science/article/pii/S0092867413002122