JM: Q to audience: anyone want an allowance for medication? We are willing to pay a lot 'for meds that don't do much' #guinformatics
2:32pm October 2nd 2014 via Hootsuite
JM: Rest of world? UK uses NICE, eval of cost/quality; or cash. Almost all we have access to, NICE is disallowed. #guinformatics
JM: Innovators charge more; illust. different medications, prices, toxicity. 'The bigger Ph.III study, smaller effect' #guinformatics
2:30pm October 2nd 2014 via Hootsuite
JM: FDA approves w/o concern to cost. CMS reimburses. 'We need to have a value discussion' of what is being approved #guinformatics
2:26pm October 2nd 2014 via Hootsuite
JM: Shows EGFR diagram; 638 genes in the network from 1 receptor, for one mutated pathway. Can we measure this? #guinformatics
2:23pm October 2nd 2014 via Hootsuite
JM: Shows pathway vs. network signalling: 2nd figure messy 'like my daughter's room'. 'We just shut the door' #guinformatics
2:22pm October 2nd 2014 via Hootsuite
John Marshall: 'As oncologists we think we are giving targeted therapy', but it is just one medication for just one pathway #guinformatics
2:20pm October 2nd 2014 via Hootsuite
DH: With J&J, tranSMART platform. 2010 publication: http://t.co/4g0L1uOFtx Millenium given access to db, dev signature #guinformatics
1:51pm October 2nd 2014 via Hootsuite
Dan Houseman (Deloitte) - working on Million Veterans Project, clinical & genetic info. More collections than data gen. #guinformatics
1:48pm October 2nd 2014 via Hootsuite
Deloitte's ConvergeHealth models; one for depression shown, where he put his own demographics up; risk went from 8% to 22% #guinformatics
1:47pm October 2nd 2014 via Hootsuite
Sponsor (Deloitte) talk: Thomas Savery's 1698 steam engine patent to remove water from coal mines. http://t.co/cmxyQgpmtD #guinformatics
1:45pm October 2nd 2014 via Hootsuite
.@PinkyG123 After ID of their 53 gene signature, subsequent samples done via NanoString. See their publication here: http://t.co/zQLPUxCmJu
1:17pm October 2nd 2014 via Hootsuite in reply to
.@atulbutte At today's #guinformatics talk you certainly emerged a rockstar. (First time I've heard you speak, an inspiring talk!)
12:12pm October 2nd 2014 via Hootsuite in reply to
KN: Shows complex flowchart - to account for sample sources, differences in dosage and other variables #guinformatics
12:11pm October 2nd 2014 via Hootsuite
KN: From only 113 samples: Manhattan plot shows interesting results but not passing significance test; larger #'s planned #guinformatics
12:10pm October 2nd 2014 via Hootsuite
KN: Review of genetic component of auto-immune diseases; PGx have a lack of selection, so large odds ratios, few samples #guinformatics
12:06pm October 2nd 2014 via Hootsuite
KN: Studied for many years; 60% of 2901 pts had immune related AE: lower GI, others. Looking for underlying variation #guinformatics
12:03pm October 2nd 2014 via Hootsuite
KN: Two immunotherapies are anti-CTLA4 in '11, anti-PD1 a few weeks ago.Tcell/APC blocking CTLA4 (ipilimumab) #guinformatics
12:01pm October 2nd 2014 via Hootsuite
KN: Geneticist by training; review of melanoma treatments in '11 for somatic BRAF mutations (~45% of pts). 2 immunotherapies #guinformatics
11:59am October 2nd 2014 via Hootsuite
Kathernine Nathanson (UPenn) "Germline predictive biomarkers of immune response and toxicity" #guinformatics
11:58am October 2nd 2014 via Hootsuite
JG:Q:How to discriminate predictive vs. prognostic? A:'all ongoing' b/c the tool has a lot of potential, new area #guinformatics
11:57am October 2nd 2014 via Hootsuite
JG: Referenced this paper on CD40 (next speaker) that came out last week for melanoma immunotherapy http://t.co/zklsx8tgeB #guinformatics
11:54am October 2nd 2014 via Hootsuite
JG: % of T-cells vs. clonality: those with high T-cells, high clonality were most likely to respond to anti-PD1 #guinformatics
11:51am October 2nd 2014 via Hootsuite
JG: Collab with UCLA Tony Ribas CTLA4 blockade data shown. Another: anti-PD1 therapy (unpubl., manuscript submitted) #guinformatics
JG: QuanTILfy(tm): prognosis for accurate staging based on count/clonality; work on standardization in progress #guinformatics
11:49am October 2nd 2014 via Hootsuite
JG: Also tumor immunol.; get TIL prognosis and clonality. Quantilfy / TIL-seq (same name); future app: transplantation #guinformatics
11:48am October 2nd 2014 via Hootsuite
JG: Offer cloud-based analysis - track clone of interest. For blood cancers: a clonality measurement. MRD assessment too #guinformatics
11:47am October 2nd 2014 via Hootsuite
JG: Can do this from tissue, blood, or sorted T/B cells. Has a service, will soon offer a kit. Back to company for analysis #guinformatics
11:45am October 2nd 2014 via Hootsuite
JG: Details of assay: T- and B-cell receptor sequencing. V-n-D-n-J, CDR3 regions. Assay can deliver TCR and Ig CDR3 #guinformatics
11:44am October 2nd 2014 via Hootsuite
Julie Gil (Adaptive Biotechnologies, WA) "ImmunoSequencing as a potential biomarker for cancer immunotherapy" #guinformatics
11:43am October 2nd 2014 via Hootsuite
YS: Showed data from GEO, Bayesian network analysis; describes work here (PubMed) http://t.co/ie0ZLoOcbe #guinformatics
11:37am October 2nd 2014 via Hootsuite
YS: Did lit search, picked up 446 genes, defined a 53 immune gene panel in mouse predictive of non-progression #guinformatics
11:33am October 2nd 2014 via Hootsuite
YS: Primary melanoma - small tissues, entire sample is FFPE, fresh-frozen not an option. NanoString: no amplification #guinformatics
11:30am October 2nd 2014 via Hootsuite
YS: Stage II-III resectable melanoma: did the primary tumor produce micro-metastases? #guinformatics
11:27am October 2nd 2014 via Hootsuite
Yvonne Saenger (Columbia) "A 53-gene immune panel measured using the NanoString assay correlates w/ (melanoma) outcomes" #guinformatics
11:26am October 2nd 2014 via Hootsuite
JM: Found signature in 30 different cancer types, across 14.4K solid tumor samples. Implemented now on Nanostring #guinformatics
11:18am October 2nd 2014 via Hootsuite
JM: Similarly, good prognosis for melanoma. In NSCLC: no signature, no structures. Can't easily be ID visually #guinformatics
11:16am October 2nd 2014 via Hootsuite
JM: Melanoma: 120 Stage IV non-lymph node mel. metastatis, all 12 to show tumor masses. Chemokines are cause of structures #guinformatics
11:14am October 2nd 2014 via Hootsuite
JM: These structures, ID by signature, meant indiv had much better survival prognosis (CR cancer) #guinformatics
11:13am October 2nd 2014 via Hootsuite
JM: (In colorectal cancer). Now doing LCM, b/c structures recognize indiv tumors. Have shown T-cells, what abt B-cells? #guinformatics
11:12am October 2nd 2014 via Hootsuite
JM: 12 chemokines uncovered in that group; going back to the tissues, found lymphoid infiltrates (microscopic) via IHC #guinformatics
11:10am October 2nd 2014 via Hootsuite
AB: Goal - can they predict clinical response rate? 2w study: Merck grouped genes into 50 groups. One was for T cell act. #guinformatics
11:09am October 2nd 2014 via Hootsuite
JM: 443K indiv., 105K consented, 35K tumor samples, 16K expression profiles. 2K sample PCA across Ca types shown #guinformatics
11:05am October 2nd 2014 via Hootsuite
JM: Database: Oncology Research Info Exchange Network (ORIEN) - to integrate #bigdata and daa sharing for cancer res. #guinformatics
11:03am October 2nd 2014 via Hootsuite
JM: Single protocol for all sites; lifetime followup, study sample w/ molecular tech., permission to re-contact for new trial #guinformatics
11:02am October 2nd 2014 via Hootsuite
JM: M2GEN's initiative: "Total Cancer Care Initiative". 19 community hospitals. Went to places with substantial volume #guinformatics
11:01am October 2nd 2014 via Hootsuite
JM: 8y ago: Consultants for a biz plan wanted big $. A few years later: Merck $100M for development. State of FL: $60M M2GEN #guinformatics
10:59am October 2nd 2014 via Hootsuite
James Mule (Moffitt) "Platform for rapid discovery and validation of tumor immune gene-regulated signatures" #guinformatics
10:57am October 2nd 2014 via Hootsuite
MA: Panel discuss different types of biomarkers: immune sig's, mRNA via Nanostring, ImmunoSeq to ID tumor types, GWAS markers #guinformatics
10:56am October 2nd 2014 via Hootsuite
MA: The problem now is too many targets; what combinations, optimal applications of novel immunotherapies, what biomarkers #guinformatics
10:54am October 2nd 2014 via Hootsuite
