Makrigiorgos: Using digital PCR, able at 0.05%, always seems to get some kind of FP background. 2 pt smpls went from 0.14% to 5% #MDxE16
8:42am April 6th 2016 via Hootsuite
Makrigiorgos: Can enrich for multiple KRAS mutations w/single overlapped probes. Shows sens. down to 0.5% w/nice amplification #MDxE16
8:40am April 6th 2016 via Hootsuite
Makrigiorgos: Data showing enrichment w/ ddPCR before/after ampl: input of 0.5% after is 83% using KRAS G12V #MDxE16
8:31am April 6th 2016 via Hootsuite
Makrigiorgos: Probes that match get cut; w/mutation mismatch no cuts. WT isn't amplified. #MDxE16
8:30am April 6th 2016 via Hootsuite
Makrigiorgos: Any mutation in the overlap region will enriched by the action of the enzyme. Illustrates WT and mutant copies #MDxE16
8:29am April 6th 2016 via Hootsuite
Makrigiorgos: '02 ref https://t.co/snLKeKmGEo used this method for SNP detection. Overlapping +/- strand probes w/overlap #MDxE16
8:28am April 6th 2016 via Hootsuite
Makrigiorgos: Nuclease-assisted Mutation Enrichment using Probe Overlap (NaME-PrO) using duplex-spec nuclease; dsDNA digested #MDxE16
8:27am April 6th 2016 via Hootsuite
Makrigiorgos: But issues w/COLD-PCR - limited multiplex (3-fold) due to denaturation/anneal temps; also PCR errors #MDxE16
8:25am April 6th 2016 via Hootsuite
Makrigiorgos: His group works on enriching mutations prior to sequencing. First approach is COLD-PCR; licensed to Transgenomic #MDxE16
8:24am April 6th 2016 via Hootsuite
Makrigiorgos: But whatever method: high depth is lower throughput; vast majority of coverage is wasted. #MDxE16
8:22am April 6th 2016 via Hootsuite
Makrigiorgos: 'Application of magic' - Safe-Seq (PNAS '11 Kinde) barcoding; TAm-Seq of (STM '12 Forshew) #MDxE16
8:21am April 6th 2016 via Hootsuite
Makrigiorgos: Thus ctDNA WGS isn't feasible. 2nd problem: noise. Showed 2% dilution at 1629x depth detection. 1%, 1300x not det. #MDxE16
8:20am April 6th 2016 via Hootsuite
Makrigiorgos: NGS enables asking of new questions; is it good enough for low-level mutations? Depth for 1%? (1K) Depth for 0.1%? #MDxE16
8:19am April 6th 2016 via Hootsuite
Makrigiorgos: Excess of WT DNA is always an unavoidable problem. Low-level mutations are the rule. '13 ref https://t.co/RH6vVZWCsb #MDxE16
8:18am April 6th 2016 via Hootsuite
Makrigiorgos: Also cffDNA use for pre-natal Dx, infectious disease, and transplan rejection #MDxE16
8:16am April 6th 2016 via Hootsuite
Makrigiorgos: Low-level mut's may (or not) be significant. And detectable in plasma; may be better than biopsy to asses tumor laod #MDxE16
8:15am April 6th 2016 via Hootsuite
Makrigiorgos: Demonstratio of intratumor heterogeneity: '12 NEJM https://t.co/PGfa8b7dt0 'papers springing up like mushrooms' #MDxE16
8:14am April 6th 2016 via Hootsuite
Makrigiorgos: The challenge is on: technology to do this in other cases with small fraction of tumor-derived DNA. #MDxE16
8:12am April 6th 2016 via Hootsuite
Makrigiorgos: Nucleosome footprint '16 Cell https://t.co/kWePCj9y2L Kun PNAS 2015 (Lo) tissue-of-origin, only proof of principle #MDxE16
Makrigiorgos: It looks very promising; no shortage of high-profile papers. "Migrant DNA keeps its home address" #MDxE16
8:10am April 6th 2016 via Hootsuite
Makrigiorgos: Feels that early det (screening) results will be 'soon'. Recent ref https://t.co/3dSxNrbXSt ctDNA predicted recurr #MDxE16
Makrigiorgos: Feels that all are useful; no shortage of applications - metastatic; localized or refractory ca; cancer screening #MDxE16
8:08am April 6th 2016 via Hootsuite
Makrigiorgos: Liquid biopsy 'is a hot topic'; whether CTCs, ctDNAs, or exosomes, all from a single blood sample. Obtain all of them #MDxE16
8:07am April 6th 2016 via Hootsuite
Mike Makrigiorgos (Dana Farber US): Novel methods for enrichment of mutations and diff methylated sequences from liquid biopsies #MDxE16
8:06am April 6th 2016 via Hootsuite
Grosu: But questions of sensitivity - low level detection? Specificity - what about false alarms? Could be random mosaic changes. #MDxE16
8:04am April 6th 2016 via Hootsuite
Grosu: Both clinicians and business-people see the opportunity of ctDNA, whether as a general screen or a $20B market in 10y #MDxE16
8:03am April 6th 2016 via Hootsuite
Daniel Grosu (Sequenom US): Intro remarks at #MDxE16 for circulating tumor DNA (ctDNA) session. "ctDNA has captured the imagination"
Q: NanoString vs RT-qPCR? Lang: Wanted high-thruput approaches; 1/2 used for RNA-Seq; add'l analyses precluded utility of qPCR #MDxE16
4:47am April 6th 2016 via Hootsuite
Q: By stage? Lang: Both Stg II-III; last data was Stg IV #MDxE16
4:45am April 6th 2016 via Hootsuite
Lang: Heterogeneity for CTCs a considerable challenge for clinical trials. #MDxE16
4:42am April 6th 2016 via Hootsuite
Lang: Angle's system suitable for gene exp for both RNA-Seq and NanoString. 'Consid heterogeneity exists w/in and between CTCs' #MDxE16
4:40am April 6th 2016 via Hootsuite
Lang: Did clinically actionable genes in br ca; a biased pre-determined analysis; CTCs vs Mets; color-coded by n=8 samples #MDxE16
4:37am April 6th 2016 via Hootsuite
Lang: Since PAM50 includes many housekeeping genes, were able to normalize their datasets. Some amplification bias for NanoString #MDxE16
4:36am April 6th 2016 via Hootsuite
Lang: Analysis by comparison to Human Protein Atlas data shown; onto NanoString's PAM50 collaboration. #MDxE16
4:35am April 6th 2016 via Hootsuite
Lang: Pairwise cp between CTCs and peripheral blood, Mets vs PB, 'vast heterogeneity'; 'each pt must serve as its own control' #MDxE16
4:32am April 6th 2016 via Hootsuite
Lang: n=8, cp between primary and metastatic, very high concordance in br ca biomarkers. Cp to CTC genes less so #MDxE16
Lang: (Showed preliminary unpubl. data, found clear differentiation between CTC and metastatic tissue, collection of genes) #MDxE16
4:30am April 6th 2016 via Hootsuite
Lang: Shows Angle system - size and deformability; great enrichment but there is background. 7.5mL EDTA blood, processed w/in 20 min #MDxE16
4:28am April 6th 2016 via Hootsuite
Lang: Angle Parsortix - initiated trial w/ question: can RNA-Seq of CTCs serve as surrogate biopsies of macrometasases? #MDxE16
4:27am April 6th 2016 via Hootsuite
Lang: 158 diff expressed genes; PCA clear separation between CTC and primary tumor; Ingenuity analysis - DNA damage resp top gene #MDxE16
4:26am April 6th 2016 via Hootsuite
Lang: Using unsupervised clustering, clear distinctions between ER+ / ER-; HER2+/Her2-; TN vs non-TN; pCR vs No pCR (pathologic CR) #MDxE16
4:25am April 6th 2016 via Hootsuite
Lang: RNA-Seq of 20 pts CTCs and 5 primaries. IE/FACS isolation distinct from peripheral blood (via qPCR for CD45) #MDxE16
4:23am April 6th 2016 via Hootsuite
Lang: CTCs from 29/33 pts, 0/33 healthy, via FACS approach. Median number is 7 cells, range 0-65. Also NanoString assays, RT-qPCR #MDxE16
4:22am April 6th 2016 via Hootsuite
Lang: R=0.87 of RNA Seq between bulk and single-cell. Used Helicos single-molecule (this was '09). Ongoing St II-III study next #MDxE16
4:21am April 6th 2016 via Hootsuite
Lang: Showed gene exp profiles from 250pg (25 cells) with 90% accuracy. '09 BMC Genomics https://t.co/gOFi6m2AIk #MDxE16
4:20am April 6th 2016 via Hootsuite
Lang: Ring '15 ref https://t.co/QGDkUJw21P First few hours in EDTA, showing abundance of recovered cells drops in a matter of hours #MDxE16
4:18am April 6th 2016 via Hootsuite
Lang: Yu '13 Science https://t.co/Y6TyTeNzhc showed dynamics of EMT in CTCs. Cell recovery is time-sensitive and subtype dependent. #MDxE16
4:17am April 6th 2016 via Hootsuite
Lang: SWOG S0500 concludes studying the biology would be useful to help predictive value. #MDxE16
4:15am April 6th 2016 via Hootsuite
Lang: CTCs in clinical trials: SWOG S0500 (Stage IV breast cancer); CTCs were prognostic, but switching Rx didn't improve survivial #MDxE16
Julie Lang (Univ So Calif US): Gene expression profiling of circulating tumor cells in non-metastatic breast cancer #MDxE16
4:14am April 6th 2016 via Hootsuite
