Martignetti: Acknowledges Cassie Schumacher of Swift Biosciences for a lot of hard work #AGBT16
11:41am February 11th 2016 via Hootsuite
Martignetti:Showing Swift data of genes' overlap between cell pellet lavage and cell-free DNA. Strong overlap shown #AGBT16
11:39am February 11th 2016 via Hootsuite
Martignetti: Screening - a saline uterine lavage. Collection of cell-free, cell pellet. 'Swift has worked incredibly well for us' #AGBT16
11:38am February 11th 2016 via Hootsuite
Martignetti: With 5 gene panel, can do ctDNA. Published last month, showing PFS and OS differences PLoS One https://t.co/1jvUOw6g03 #AGBT16
11:36am February 11th 2016 via Hootsuite
Martignetti: The Accel-Amplicon 56G Oncology panel, validated using orthogonal technology, retrain and showed 5 genes, 82% #AGBT16
11:32am February 11th 2016 via Hootsuite
Martignetti: And from only 4 genes, used TCGA data as a training set. Predicted 86% into type1/2. Then went to SwiftBio 56G #AGBT16
11:31am February 11th 2016 via Hootsuite
Martignetti: Developed a tool MutationAssessor https://t.co/dA7W2n36ob came up with 15 gene AmpliSeq panel #AGBT16
11:30am February 11th 2016 via Hootsuite
Martignetti: In-revision paper Rykunov D NAR 2016, can look at Molecular Signature Method with a weighting scale #AGBT16
11:29am February 11th 2016 via Hootsuite
Martignetti: From this '13 @TCGAupdates paper: https://t.co/O6V2PTKfVP supports classic distinctions by grade by OS #AGBT16
11:27am February 11th 2016 via Hootsuite
Martignetti: Three points where change can be made: in the office, at surgery, and quarterly followup #AGBT16
11:26am February 11th 2016 via Hootsuite
Martignetti: From symptoms, to D&C in the office, pathology H&E grading, affecting surgical choice, another set of grading #AGBT16
11:24am February 11th 2016 via Hootsuite
Martignetti: Classification based on histology; problem is judgement of % in grade 1/2/3. Most reliable: 2 groups. #AGBT16
11:23am February 11th 2016 via Hootsuite
Martignetti: Lists symptoms, diagnosis (pelvic exam, pap smear, biopsy, D&C). No clinically useful mol markers / diagnostics #AGBT16
11:22am February 11th 2016 via Hootsuite
Martignetti: Endomet ca is 55K new cases, >10K deaths, incidence increasing due to obesity, increase in menarche #AGBT16
11:21am February 11th 2016 via Hootsuite
John Martignetti (Mount Sinai): A pre-operative, diagnostic gene panel for guiding primary treatment choices in endometrial cancer #AGBT16
11:20am February 11th 2016 via Hootsuite
Rapaport: Conclude - combination of RNA and DNA ID's a complex landscape of events, with prognostic and therapeutic impact #AGBT16
11:19am February 11th 2016 via Hootsuite
Rapaport: Second most common was MLL fusion. Goes on to subdivide by type of accompanying mutation by type (cell cycle etc.) #AGBT16
11:11am February 11th 2016 via Hootsuite
Rapaport: Showed samples on x-axis, genes on y-axis, shrt event, rearr, gain, loss: 36% BCR-ABL1. #AGBT16
11:10am February 11th 2016 via Hootsuite
Rapaport: Used FoundationOne Heme, 405 gene exons, 265 RNA fusions, 189 samples, 435x DNA coverage #AGBT16
11:09am February 11th 2016 via Hootsuite
Rapaport: The adult form is only deduced from the pediatric form (survival rate 80%, but in adults 30-40%). Higher BCR-ABL fusion #AGBT16
11:06am February 11th 2016 via Hootsuite
Franck Rapaport (Memorial Sloan Kettering) “Integrated DNA/RNA profiling for somatic alterations in adult B-cell ALL” #AGBT16
11:05am February 11th 2016 via Hootsuite
Diaz: Showed OS and PFS clear difference in MMR-def CRC. 1700 mut/genome in responders, few in non-responders #AGBT16
10:28am February 11th 2016 via Hootsuite
Diaz: After getting support,designed study of CRC and nonCRC with mismatch repair deficiency. Showed clear difference in response #AGBT16
10:27am February 11th 2016 via Hootsuite
Diaz: Explosion of immunotherapy: PD-1 pathway, spec for melanoma, lung ca. May be helpful in mismatch-repair tumors #AGBT16
10:24am February 11th 2016 via Hootsuite
Diaz: Need high-impact studies to drive overall survival. #AGBT16
10:23am February 11th 2016 via Hootsuite
Diaz:Limited more by 'biology rather than technology' in the future - need the clinical utility to move things forward #AGBT16
10:22am February 11th 2016 via Hootsuite
Diaz: Only about 12 mutations with targeted cancer therapies. MRD, early detection, or novel applications of Rx #AGBT16
Diaz: Not for every type of tumor - due to anatomic barriers (i.e. gliomas). Challenges: not all clonal events are cancer #AGBT16
10:21am February 11th 2016 via Hootsuite
Diaz: For liquid pap-smear specimens - able to get 100% sens for cervical, 41% for ovarian cancer. Up to 10% mutant fraction #AGBT16
10:19am February 11th 2016 via Hootsuite
Diaz: False-positive issues are minimized - due to nature of genomic rearrangement data in ctDNA #AGBT16
10:17am February 11th 2016 via Hootsuite
Diaz: From NIPT data: testing from 10's of thousands, found a total of 38 cases of CNV from cfDNA #AGBT16
Diaz: Another high-impact area for ctDNA: early detection. 1600 pts, 40% in stage I '14 ref https://t.co/iBSZZPQx48 #AGBT16
10:16am February 11th 2016 via Hootsuite
Diaz: Wrapping up a study, stage II CRC ctDNA measured 6-8 weeks post-op. Showing clear data for Br cancer https://t.co/m717UOwnkP #AGBT16
10:14am February 11th 2016 via Hootsuite
Diaz:Show BEAMing data from '08 Nature Med paper: https://t.co/NOyFZ74A4d Evidence of whether all of the tumor has been removed #AGBT16
10:12am February 11th 2016 via Hootsuite
Diaz: Shows figure from nice '14 JCO review https://t.co/HFB67RnFx7 ctDNA source comes from secretion, necrosis, apoptosis #AGBT16
10:07am February 11th 2016 via Hootsuite
Diaz: From somatic cancer genome data: to prognostic markers, dynamic biomarkers, immune antigens, predictive markers #AGBT16
10:03am February 11th 2016 via Hootsuite
.@h2so4hurts Looks like a nice #AGBT16 resource, Brian - thanks! (Hope to see you in Sept at the 'other' AGBT event...)
10:02am February 11th 2016 via Hootsuite in reply to h2so4hurts
Luis Diaz (Johns Hopkins) “Novel therapeutic and diagnostic applications of somatic mutations in solid tumor malignancies” #AGBT16
10:00am February 11th 2016 via Hootsuite
RT @LAbizar: #AGBT16 Chiu, host depletion very challenging therefore selected low cellularity samples.
Chiu: Shows Metrichor @nanopore software video with 2min recognition of Ebola virus. #AGBT16 https://t.co/e0IMWy7aU5
9:55am February 11th 2016 via Hootsuite
Chiu: Working with the FDA, offer a consult service, plan to launch in May '16 for CSF, plasma and lavage later in '16 #AGBT16
9:52am February 11th 2016 via Hootsuite
Chiu: Challenge was completeness of reference databases. #AGBT16
9:48am February 11th 2016 via Hootsuite
Chiu: 3rd:15yo w/T1D, hemorrhagic encephalitis 0.23% of reads of Balamuthia mandrillaris encephalitis by day 7; pt died day 1 #AGBT16
9:47am February 11th 2016 via Hootsuite
Chiu: Person likely contracted disease from undercooked crab in Fiji. Be careful! #AGBT16
9:46am February 11th 2016 via Hootsuite
Chiu: Case 2: 35yo on honeymoon, CSF WBC w/ rash and lesions in MRI. Ended up with a parasitic infection, a rat lungworm (yikes) #AGBT16
9:45am February 11th 2016 via Hootsuite
Chiu: 35 samples, wide variety. Presents cases: '14 NEJM https://t.co/tzOqYKW9C5 undiagnosed neuroleptospirosis (#AGBT14!) #AGBT16
9:44am February 11th 2016 via Hootsuite
Chiu: Showed results from plasmodium to rhinovirus to salmonella. Preparing a manuscript (Naccache et al '16) 27 pts over 22 months #AGBT16
9:42am February 11th 2016 via Hootsuite
Chiu: Three samples - plasma, lavage and CSF: less background, turnaround is 24h-48h #AGBT16
9:40am February 11th 2016 via Hootsuite
Chiu: SURPI bioinf. pipeline - '14 NAR ref https://t.co/QuTvT9dLXQ Reviews CLIA covers analyses as well, need for validation, QA #AGBT16
Chiu: Metagenomic sequencing - cast a wide net: a shotgun random approach, unbiased, feasible due to NGS capacity #AGBT16
9:38am February 11th 2016 via Hootsuite
