Zill: Study suggests high correlation between ctDNA and tumor. Intro: clin practicable, 'global summery' of tumor heterogeneity #AACR16
5:26pm April 19th 2016 via Hootsuite
Oliver Zill (Guardant Health CA) Comparison of over 10K clinical NGS circ tumor DNA profiles to tissue-derived genomic compendia #AACR16
5:24pm April 19th 2016 via Hootsuite
Engelman: "We are getting only two snapshots of resistance: before and after" #AACR16
11:00am April 19th 2016 via Hootsuite
Engelman: After TKIs - usually a lot of cancer left; w/o continuing trtmnt will flare. chromatin-mediated https://t.co/l8e9nEDCFT #AACR16
10:59am April 19th 2016 via Hootsuite
Engelman: Recent work '16 Nature Med https://t.co/0fNy9B64Pz Reviews prior work of pre-existing resistant mutations. #AACR16
10:57am April 19th 2016 via Hootsuite
Engelman: 2nd: bypass tracks, downstream PIK3 and MEK, restoring signalling. Combination Rx to target (MET, HER2, FGFR3) #AACR16
10:55am April 19th 2016 via Hootsuite
Engelman: 1 mech: EGFR T790M, five ALK. More potent inhibitors have made their way to first-line Rx #AACR16
10:54am April 19th 2016 via Hootsuite
Engelman: '14 Science https://t.co/O0kShere0D method - discovers resistant mechanism, now done from 100's of samples #AACR16
10:53am April 19th 2016 via Hootsuite
Engelman: At MGH, their '15 OS shows this improvement in OS in NSCLC https://t.co/o7V3SXfVwY #AACR16
10:52am April 19th 2016 via Hootsuite
Engelman: Range of PFS 2mo to 8y Resistant cancers continue original EGFR or ALK; PD-1 blockade not effective; OS now 4-5y #AACR16
10:50am April 19th 2016 via Hootsuite
Engelman: NSCLC - dist of driver genes shown. KRAS 25%, EGFR 17%, ALK 8%, EGFR (other) 4%. Dev of resistance - median PFS is 1-2y #AACR16
10:49am April 19th 2016 via Hootsuite
Jeffrey Engelman (Massachusetts General Hosp MA) The evolution of cancer in response to targeted therapies #AACR16
10:48am April 19th 2016 via Hootsuite
Regev: Also building a normal cell / tumor cell atlas at single-cell resolution. #AACR16
10:46am April 19th 2016 via Hootsuite
Regev: Spatial 'DNA microscopy' - in dev to determine where molecule are in 2D in-situ (Feng Zhang, unpubl) #AACR16
10:45am April 19th 2016 via Hootsuite
Regev: Future view: partners with Garraway, Center for Cancer Pres Med; still tech to develop. Scale Drop-Seq to 100K cells, 20min #AACR16
10:44am April 19th 2016 via Hootsuite
Regev: Concl: single-cell can be applied to diverse fresh tumor cell types; can infer microenv; t-cell subsets; resolve cell types #AACR16
10:43am April 19th 2016 via Hootsuite
Regev: In malignant cells: building on bulk work on MITF and AXL '14 https://t.co/4e30oSTlct now at single-cell #AACR16
10:41am April 19th 2016 via Hootsuite
Regev: Onto cell-cell interactions - CAF exp of chomkines and complement w/high Tcell infiltration via bulk vs single-cell analysis #AACR16
10:39am April 19th 2016 via Hootsuite
Regev: Now looking across tumors, finding shared programs, and diverse one. #AACR16
10:34am April 19th 2016 via Hootsuite
Regev: More cytotoxic, more exhausted they appear. From 1pt: has activation-indep variation in exhaustion cells #AACR16
10:33am April 19th 2016 via Hootsuite
Regev: Able to distinguish all T-cell types, look at state. Look at naive, cytotoxic states. See CD8+ most, CD4+ least #AACR16
10:32am April 19th 2016 via Hootsuite
Regev: With DFCI - 19 met melanoma, distinguish malignancy (total 4600 cells) from CNVs inferred from RNA-Seq #AACR16
10:31am April 19th 2016 via Hootsuite
Regev: Model is undiff cancer cells propagate IDH1 in glioblastoma #AACR16
10:30am April 19th 2016 via Hootsuite
Regev: Every glioma has cells with astro-like, oligo-like, and stem-like states; cycling cells are in undiff state #AACR16
10:29am April 19th 2016 via Hootsuite
Regev: Hypothesized that cell cycle state may keep signature hierarchy. Majority of cells are quiescent. #AACR16
10:25am April 19th 2016 via Hootsuite
Regev: Has a set of genes that are astro- or oligo-like in oligodendrolioma via PCA analysis. #AACR16
10:24am April 19th 2016 via Hootsuite
Regev: Saw 1q deletion, aberrations validated in bulk WES. #AACR16
10:21am April 19th 2016 via Hootsuite
Regev: 4K cells, from GBM (no models), did single-cell analysis for CNV (not possible for DNA) via RNA, inferring ampl/del #AACR16
10:20am April 19th 2016 via Hootsuite
Regev: W/Brad Bernstein and others at MGH '14 Science https://t.co/jKA9GtlKyv Dev hierarchies in GBM #AACR16
10:19am April 19th 2016 via Hootsuite
Regev: Single-cell genomics: can dissect enormous diversity. Which cells, molecular status, partners? #AACR16
10:18am April 19th 2016 via Hootsuite
Aviv Regev (The Broad Inst MA) Dissecting the complex ecosystem of malignant tumors with single cell RNA-Seq #AACR16
10:17am April 19th 2016 via Hootsuite
Ley: 'Cells w/initiating events persist from beginning to end, and must be eliminated for cures' #AACR16
10:16am April 19th 2016 via Hootsuite
Ley: 'Same story': discordant subclonal response. But w/TP53 mut's, disease clearance #AACR16
10:13am April 19th 2016 via Hootsuite
Ley: Most elderly pts (>65yo) cannot receive std of care chemo. decitabine commonly used, 45% resp w/in 10d. #AACR16
10:12am April 19th 2016 via Hootsuite
RT @SeraCare: At #AACR16? Say hi to @DaleYuzuki at booth 2552! https://t.co/UU2BzL0oHe https://t.co/0YEHSI1WeW
10:10am April 19th 2016 via Twitter Web Client
Ley: Shows illus. of complete clearance and incomplete, and progression events as a result of Rx #AACR16
10:09am April 19th 2016 via Hootsuite
Ley: With treatment - fig from '15 Cell Systems https://t.co/89dPB0WYUG Is it hopeless? '15 JAMA https://t.co/FqYOWaSDON #AACR16
10:07am April 19th 2016 via Hootsuite
Ley: Long list of subclone properties - some have unique immunophenotypes, etc FLT3, IDH1, NPMc, DNMT3A. #AACR16
10:04am April 19th 2016 via Hootsuite
Ley: Using 260 gene panel, WES, WGS: 30x vs 300x: <10% VAF. Why it matters: every subclone grows faster #AACR16
10:03am April 19th 2016 via Hootsuite
Ley: Shows graphs of founding clone, then add'l clones; coverage typically for WGS and WES not high enough for detection of add'l #AACR16
10:02am April 19th 2016 via Hootsuite
Ley: From random background (DNMT3A), clonal exp, founding clone, explosive subclone (FLIT3) #AACR16
10:01am April 19th 2016 via Hootsuite
Ley: By age 50, 1/2 chance of sig p53 mutation in one of your stem cells. Shows neat 3D illust. '14 ref https://t.co/HlikuX6ZiV #AACR16
10:00am April 19th 2016 via Hootsuite
Ley: Risk assessment: mutational complexity; clonal complexity; clonal evolution w/trtmt; epigenetic (not addressed today) #AACR16
9:58am April 19th 2016 via Hootsuite
Ley: WGS of short vs long remission AML - nothing predictive at time of presentation. Why: clonal evolution #AACR16
9:57am April 19th 2016 via Hootsuite
Ley: 23 sign. mutated genes; 260 recurr mutated genes, 1627 singletons. TCGA map; but defining coding muts hasn't solved risk Q #AACR16
9:56am April 19th 2016 via Hootsuite
Ley: Imperfect risk classification via cyto. Fig from '02 Blood ref https://t.co/lKaQK5o4PM #AACR16
9:54am April 19th 2016 via Hootsuite
Ley: Treated pts from 18-60 yo; majority are older and die at home. Rx not changed in 30y. anthracycline, cytarabine "7+3" d trtmt #AACR16
9:52am April 19th 2016 via Hootsuite
Ley: AML 20K new cases, 11K deaths (US). Often explosive presentations, die w/in a few weeks or months. MDS/AML diseases of aging #AACR16
9:51am April 19th 2016 via Hootsuite
Ley: Quotes Peter Nowell Science 1976 https://t.co/c93bJpDOuP about branched evolution. "He used single cell tech" (cyto) #AACR16
9:50am April 19th 2016 via Hootsuite
Tim Ley (Washington Univ MO): The AML genome(s) #AACR16
9:47am April 19th 2016 via Hootsuite
