Kim: Cas9 xf protein showed to degrade in 12h. Via plasmid, lasts 3d. RNPs can reduce off-target effects, tested with 2bp mismatch #AACR14
5:56pm April 5th 2014 via Hootsuite
Kim: Listed five (of many) CRISPR papers. Looking at guide RNA's and off-target effect dependencies PubMed: http://t.co/2oc9OTb7Ve #AACR14
5:55pm April 5th 2014 via Hootsuite
Kim: Moving onto CRISPR - Cas9 used for knockouts; Cas9 uses guide RNA's for specificity. Electroporate Cas9 protein, cloning-free #AACR14
5:52pm April 5th 2014 via Hootsuite
Kim: TALEN library resource, helped >200 researchers last year. http://t.co/hUltDKuCh7 #AACR14
5:49pm April 5th 2014 via Hootsuite
Kim: Moving on to TALENs, reviewed his work published 2013 Nature Biotech PubMed http://t.co/r97q5qW4Fj 99% successful #AACR14
5:48pm April 5th 2014 via Hootsuite
Kim: Then their group developed a series of ZfN's for targeted knock-outs. But: in cell lines, ass'd with cytotoxicity #AACR14
5:46pm April 5th 2014 via Hootsuite
Kim: Carroll et al paper in 2009 using ZfN for genome engineering in Drosophila PubMed: http://t.co/Vptt3JEIKs #AACR14
5:44pm April 5th 2014 via Hootsuite
Kim: Focus is now on CRISPR. Review of Fok I nucleases + first zinc-finger nuclease at Hopkins 96 PubMed http://t.co/woTsSDOf2h #AACR14
5:42pm April 5th 2014 via Hootsuite
Kim: Genome editing - concurrent dsDNA breaks, can induce translocations, 'method of the year' in 2012 Nature Methods #AACR14
5:40pm April 5th 2014 via Hootsuite
Next up: Jin-Soo Kim Nat'l Univ Seoul "Targeted gene disruption in mammalian cell lines using programmable nucleases" #AACR14
5:38pm April 5th 2014 via Hootsuite
Carette: Q:Stable karyotype after screening? A:Do see diploid cells that overgrow the haploid ones; doesn't happen very often. #AACR14
Carette: Adv: complete knockout, high coverage (>100/gene), no obv. off-target effect, Disadv: limited to haploid cell lines; pooled #AAC
5:34pm April 5th 2014 via Hootsuite
Carette: Suggest dom. negative AXIN2 function #AACR14
5:33pm April 5th 2014 via Hootsuite
Carette: + Wnt regulators, many known +'ve regulators ID'd; novel: AXIN, part of destruction complex. not 5' insertion as usual #AACR14
5:32pm April 5th 2014 via Hootsuite
Carette: Looked at Wnt / GFP reporter; selected for +/- regulators; found 2 negative regulators #AACR14
5:30pm April 5th 2014 via Hootsuite
Carette: Able to look at drug mode of action w haploid genetic screen in 5 cmpds, and ID'd genes '11 PubMed http://t.co/9R2bEnGlOI #AACR14
5:26pm April 5th 2014 via Hootsuite
Carette: Mapping of insertions, looked at significance of distance, found 2 favored locations (CASP8 and FADD) #AACR14
5:22pm April 5th 2014 via Hootsuite
Carette: Mutagenized 100M cells, select using TRAIL (apoptotic mech), amplify insertion sites, NGS to determine location #AACR14
5:20pm April 5th 2014 via Hootsuite
Carette: 1M mutagenized cells, 900K insertion sites in appox 50% in genes. Every gene hit ave 30-fold #AACR14
Carette: Put in a retroviral gene trap, being able to do forward genetics with complete knockouts (showed Western data) #AACR14
5:19pm April 5th 2014 via Hootsuite
Carette: Did insertional mutagenesis in haploid human cells. Carette Science 09 PubMed http://t.co/ODnMS7Qcy5 #AACR14
5:18pm April 5th 2014 via Hootsuite
Carette: Yeast is haploid, but wanted a yeast-like genetic approach for LS mutagenesis in human cells #AACR14
5:17pm April 5th 2014 via Hootsuite
Carette: X-ray irradiation of Drosophila - pioneered in '27 Muller - but mammalian cells are diploid, no crossings #AACR14
5:16pm April 5th 2014 via Hootsuite
Carette: Large-scale disruption approach, not shRNA or CRISPR based #AACR14
5:15pm April 5th 2014 via Hootsuite
From: "Loss of Function Genetics in Mammalian Cells" session: Jan Carette, Stanford "Haploid genetic screens in human cells" #AACR14
RT @splon: #AACR14 @rahman_nazneen feels most cancer genetic guidelines were designed to limit testing when it was a limited resource.
5:01pm April 5th 2014 via Hootsuite
Rahman: Starting with ovarian ca, as there is >10% BRCA risk without family history of cancer #AACR14
.@DrStelling But they are looking at a predisposition (germline) model, that's not so time-sensitive.
4:59pm April 5th 2014 via Hootsuite in reply to
Rahman: 96 samples / 14d; can do 576/week on a HiSeq 2.5K. #AACR14
4:56pm April 5th 2014 via Hootsuite
Rahman: Constructed extensive classifications of all possible (42K) BRCA potential variants and their effect from multiple datasets #AACR14
4:55pm April 5th 2014 via Hootsuite
Rahman: Confounding is population-specific SNPs - thus the need for other kinds of variant data #AACR14
4:51pm April 5th 2014 via Hootsuite
Rahman: CIGMA data inputs are of many types - from in silico prediction, to control data, functional assays, case variant data #AACR14
Rahman: CIGMA: divided into mgmt categories; informed, evidence-based; HTP; dynamic and iteratively improved #AACR14
4:50pm April 5th 2014 via Hootsuite
Rahman: Collectively rare variants are common - and all are suspect, cannot be ruled out. Analysis tool called CIGMA #AACR14
4:49pm April 5th 2014 via Hootsuite
Rahman: From 1000 samples: 117 var's/sample; 3-4 rare; >80% rare (<1%); appx 10% has a rare BRCA var. #AACR14
4:48pm April 5th 2014 via Hootsuite
Rahman: VUS - she receives 'several emails per day' about this (VUS = variant of unknown significance) #AACR14
4:47pm April 5th 2014 via Hootsuite
Rahman: The new bottleneck - what does it mean, how to deliver it. Interpretation tool developed. #AACR14
4:46pm April 5th 2014 via Hootsuite
Rahman: 96 samples / 8h found 100% sensitivity / specificity for BRCA #AACR14
4:45pm April 5th 2014 via Hootsuite
Rahman: Analysis is called GAMA, much more complicated than anticipated; 'you will need to tailor it for your setting' investment #AACR14
4:44pm April 5th 2014 via Hootsuite
Rahman: They helped developed the ILMN TruSight Cancer, 50ng input, 95% of samples 95% target at least 50x, median 1000x coverage #AACR14
Rahman: MCG 'likely to change to WES / WGS in time' but a few years before it happens #AACR14
4:43pm April 5th 2014 via Hootsuite
Rahman: The MCG effort focuses on targeted, HTP assays. "Must be at least equiv. to existing ones" #AACR14
4:42pm April 5th 2014 via Hootsuite
Rahman: Mainstreaming Cancer Genetics website http://t.co/kYF6ssMF0B #AACR14
4:40pm April 5th 2014 via Hootsuite
Rahman: (By the way, the speaker can be found on Twitter here: http://t.co/Dh6oeDMJjy ) #AACR14
4:39pm April 5th 2014 via Hootsuite
Rahman: Pedigree example shared; look at the potential for cancer prevention where future generations would be aware of status #AACR14
4:38pm April 5th 2014 via Hootsuite
Rahman: CPG's have impacts on management - co-risk of other cancer types with BRCA. PARP inh, as example for personalized effort #AACR14
4:35pm April 5th 2014 via Hootsuite
.@splon You are so generous!
4:33pm April 5th 2014 via Hootsuite in reply to
Rahman:Looking at germline predisposition in cancer. >100 Cancer Predisposition Genes (CPG) #AACR14 PubMed http://t.co/hqOpBZlz2b
4:33pm April 5th 2014 via Hootsuite
Next: N Razman Inst Cancer Res "Implementing large-scale testing of cancer predisposition genes: Maximising benefits, minimising harms"
4:31pm April 5th 2014 via Hootsuite
Strong: Showed KRAS amplification example from this Mohan et al PLoS Genet 2014 PubMed http://t.co/uAxbhzgotX #AACR14
4:29pm April 5th 2014 via Hootsuite
