Czwan: 5 areas: oncology, hereditary, cardiology, metabolism and pediatrics #ESHG2016
9:48am May 23rd 2016 via Hootsuite
Czwan: Sophia DDM has 3 core tech: Muskat (CNV), Pepper (SNV, INDEL), Moka adv variant annotation in public, private db's #ESHG2016
9:47am May 23rd 2016 via Hootsuite
Czwan: Sensitivity, specificity, reproducibility, repeatability. They have designed xGen tech into kits. #ESHG2016
9:46am May 23rd 2016 via Hootsuite
Czwan: Expect 80K samples analyzed in 2016. 'Research and Diagnostics are completely different' #ESHG2016
9:45am May 23rd 2016 via Hootsuite
Czwan: Have focused on clinical diag and NGS; 80 empl, ISO13584 and ISO for medical security. >200 labs in Europe, 45K samples #ESHG2016
9:44am May 23rd 2016 via Hootsuite
Esteban Czwan (Sophia Genetics, Switzerland): Raising the bar in diagnostics - hereditary cancer solution #ESHG2016
9:43am May 23rd 2016 via Hootsuite
IDT: Presented poster here for low freq var detection from FFPE and ctDNA down to 0.5% using barcoding #ESHG2016
9:37am May 23rd 2016 via Hootsuite
IDT: Reviews this '15 Nature Methods using duplex seq for low freq variant detection https://t.co/AVciQQiPST #ESHG2016
9:36am May 23rd 2016 via Hootsuite
IDT: They can also do RNA probes, and showed sequencing of an ALK fusion. Also cDNA capture w/WashU data #ESHG2016
9:33am May 23rd 2016 via Hootsuite
IDT: Have AML, pan-cancer, inherited, and exome as std product. showed nice coverage results from Foundation Medicine #ESHG2016
9:27am May 23rd 2016 via Hootsuite
IDT data: 20 gene panel, 395 exons, 71kb footprint, 805 probes. On-target of 50%; including flanking rises to 65% #ESHG2016
9:22am May 23rd 2016 via Hootsuite
IDT: 3 scales; min 200 probes. Showed customer data of on-target % increasing some 30% #ESHG2016
9:21am May 23rd 2016 via Hootsuite
IDT: They don't need redundant tiling, due to their oligo QC and ability to ensure all oligos are present. #ESHG2016
9:19am May 23rd 2016 via Hootsuite
IDT: Have xGen blocking oligo, also use Cot-1, to increase on-target Lockdown probe is biotinylated for streptavidin pull-down #ESHG2016
9:18am May 23rd 2016 via Hootsuite
Attending @idtdna workshop. Lockdown probes: 120nt oligo's, full-length yield 55%. Exome: 430K, 30Mb footprint, six iterations #ESHG2016
9:16am May 23rd 2016 via Hootsuite
Kumar: DTC = disseminated tumor cell. Can derive clonal phylogenetic tree; CNAs give them needed data to make connection #ESHG2016
8:28am May 23rd 2016 via Hootsuite
Kumar: Single-cell copy-number via WGS cp to primary tumor; did find genuine DTCs and normal cells. #ESHG2016
8:24am May 23rd 2016 via Hootsuite
Kumar: DTCs bone marrow; stained for cytokeratins, manually picked up. n=6, Used bulk and between 1-10 cells cp to primary #ESHG2016
8:23am May 23rd 2016 via Hootsuite
P Kumar (KU Leuven Belgium) : Tracing the origin of disseminated tumor cells in breast cancer using single-cell sequencing #ESHG2016
8:21am May 23rd 2016 via Hootsuite
Sartori: Compared to TCGA, looked for assoc'd survival genes. MPO gene - K-M curve median surv 761d vs 336d. #ESHG2016
8:16am May 23rd 2016 via Hootsuite
Sartori: Several hundred DEGs were specific to AML1 or 2; goes on to show network map (Cytoscape 3) #ESHG2016
8:14am May 23rd 2016 via Hootsuite
Sartori: Use Seurat tool, ID'd 3 clusters; n=2 individuals w/AML (called AML1/2). DEG via D(3)E tool, 187 overlap between AML1/2 #ESHG2016
8:11am May 23rd 2016 via Hootsuite
Sartori: CD34/33/38; from bone marrow, 0.15% of original sample's cells. From 267 cells, did RNA-Seq #ESHG2016
8:09am May 23rd 2016 via Hootsuite
Sartori: Post-treatment, <1% resistant to chemotherapy, result in relapse. Approach is single-cell (sc) CD marker selected by flow #ESHG2
8:08am May 23rd 2016 via Hootsuite
Sartori: AML - 352K cases/yr; BM xplant, <40% 5y survival. Leukemia stem cell has multiple pathways in. #ESHG2016
8:06am May 23rd 2016 via Hootsuite
Ambra Sartori (Univ Geneva, Switzerland) Single-cell transcriptional profiling ID's rare cell types with gene markers in AML #ESHG2016
8:05am May 23rd 2016 via Hootsuite
Joosse: Concludes w/contrast / complementary nature between ctDNA and CTCs '13 NEJM https://t.co/jUpwMS0T42 #ESHG2016
6:38am May 23rd 2016 via Hootsuite
Joosse: Interesting work - mouse cells integrate ctDNA from human tumor plasma - biological fn of ctDNA https://t.co/p32Crx8JuP #ESHG2016
6:34am May 23rd 2016 via Hootsuite
Joosse: Investigating heterogeneity '15 ref https://t.co/BFYnIF8KpX #ESHG2016
6:33am May 23rd 2016 via Hootsuite
Joosse:' For MRD, in breast cancer, where relapse could be detected much earlier than scans '15 ref https://t.co/IS6j0a5LLG #ESHG2016
6:30am May 23rd 2016 via Hootsuite
Joosse: For monitoring, mBC Guttery et al '15 https://t.co/cTsnfVh2JA looking at early ESR1 mutations to change course of trtmt #ESHG2016
6:28am May 23rd 2016 via Hootsuite
Joosse: Sructural var TMPRSS2-ERG fusion '13 Heitzer review https://t.co/dplSep2wty #ESHG2016
6:23am May 23rd 2016 via Hootsuite
Joosse: Stratification: 76% concordance between tumor biopsy (n=17, mBC) and ctDNA. 64% w/mCRC, n=39 in another study #ESHG2016
6:22am May 23rd 2016 via Hootsuite
Joosse: aCGH reviewed, figure from '07 https://t.co/Ewqku9mj2C Shows ctDNA of cancer vs normal 'you can see a lot going on' in CNV #ESHG2016
6:19am May 23rd 2016 via Hootsuite
Joosse: Shows size distribution in HCC '15 PNAS https://t.co/d1vfCwL2fL #ESHG2016
6:17am May 23rd 2016 via Hootsuite
Joosse: Before / after treatment, shows data (201/105bp ratio in another publication) goes down in another tumor type #ESHG2016
6:15am May 23rd 2016 via Hootsuite
Joosse: Showed DNA integrity with '06 ref using Alu27/Alu115 in br cancer pts https://t.co/7gxtwQeglL #ESHG2016
6:14am May 23rd 2016 via Hootsuite
Joosse: Size of ctDNA around 166bp. Shares data from '13 ref https://t.co/QoDmDSJ0LX Also small 320bp peak #ESHG2016
6:12am May 23rd 2016 via Hootsuite
Joosse: Pt stratification, can monitor response, can early detect, can look at intra- and inter-tumor heterogeneit #ESHG2016
6:11am May 23rd 2016 via Hootsuite
Joosse: Main cause of cancer-related deaths is metastasis. Shows figure from '15 ref https://t.co/8H4ss7m80r Focus today on ctDNA #ESHG2016
6:09am May 23rd 2016 via Hootsuite
Simon Joosse (Uni Med Ctr Hamburg Germany) Cell-free DNA as liquid biopsy in the management of cancer patients #ESHG2016
6:07am May 23rd 2016 via Hootsuite
Triviño: Clinical CNVs need to have reliable control groups; how many; how variable. Showed nice bar chart of exon lengths #ESHG2016
5:55am May 23rd 2016 via Hootsuite
Triviño: Reviews advantages of targeted sequencing, utility of paired-ends, split reads, de novo, statistical read-depth for CNV #ESHG2016
5:53am May 23rd 2016 via Hootsuite
Triviño: Shows growth of dbSNP, HGMD mutations, disease assoc'd genes, and the # of FDA-approved drugs (far, far behind of course) #ESHG2016
5:46am May 23rd 2016 via Hootsuite
Juan Carlos Triviño (Sistemas Genomicos Spain) CNVs and other methodologies applied to diagnosis #ESHG2016
5:45am May 23rd 2016 via Hootsuite
Vendrell: Carrier rate is low, but frequency is higher than previously reported. #ESHG2016
5:40am May 23rd 2016 via Hootsuite
Vendrell: Scenario 2 - Gamete donor, screening for suitable donors. Of 500 cases, 4 variants/individ, 12% of high risk couples #ESHG2016
5:39am May 23rd 2016 via Hootsuite
Vendrell: Details on their Preconception test here: https://t.co/xYqKvrr9mM Scenario 1 - couple with concern about consanguinuity ESHG2016
5:38am May 23rd 2016 via Hootsuite
Vendrell: 320 genes, 340 disorders, detects 5177 dels <11bp, 519 indels, 295 insertions <5bp. Showed validation / QC steps #ESHG2016
5:35am May 23rd 2016 via Hootsuite
Vendrell: Complement with 'traditional' techniques (PCR-based), and karyotyping. Onto their unique 'Preconception Geneprofile' #ESHG2016
5:33am May 23rd 2016 via Hootsuite
