Five minute presentations

Detec%on of Soma%c Muta%ons by Targeted NGS

Considera%ons for clinical valida%on of assay and informa%cs: 1.  DNA input quan%ty and quality

•  Small tumor biopsies leading to low library complexity •  FFPE specimens and variability of fresh %ssue quality

2.  Low frequency variant/low allele burden detec%on •  Soma%c variants present in a frac%on of the genomes sampled (10-‐25% or lower)

‒  Presence of non-‐tumor derived DNA ‒  Clonal complexity ‒  Future considera%on: minimal residual disease detec%on

3.  Indel, copy number varia%on, and transloca%on detec%on •  NGS references should incorporate the spectrum of varia%ons and variant complexity

Andy Bredemeyer Washington University in St. Louis

Pathology Consult Service Genomics and Pathology Services

Washington University’s Cancer Muta%on Profiling Test •  1000X avg coverage •  25 genes reported clinically

•  Detec%on of SNVs, indels, structural varia%on

•  High sensi%vity of coding region variants at 10% AF

One slide introduction : John West, CEO, Personalis Inc.

•  New VC-backed startup in Menlo Park, CA (www.personalis.com) •  Clinical-quality genome sequencing & medically-relevant interpretation •  Founders from Stanford (majority MD’s) & Solexa / Illumina •  Collaborations : Stanford, Harvard, ISB •  Extensive publication record in genetic analysis accuracy issues (esp. NGS) •  Work guided by extensive manually-curated databases linking genetic

variation with disease & drug metabolism •  2010 : Quake-genome clinical interpretation •  2009-2011 : Family quartet genome analysis •  Current work :

–  Larger families including CEPH1463 / NA12878; Multiplatform –  Lab & informatics for accuracy (vs absolutely lowest cost)

•  Using “gold-standard” genomes to characterize error mechanisms •  Design lab & informatic methods to address them •  Interested in joining NIST consortium

Jim Mullikin, Director NIH Intramural Sequencing Center (NISC)

•  Computa%onal genomics researcher from the days of the ramp-‐up of the human genome project in 1997.

•  Involved in The SNP Consor%um project, and later the HapMap project.

•  I worked on the early structural varia%on analysis with Evan Eichler and selected NA12878 as one of the eight samples for that project.

•  The 1000 genomes project selected this individual as well

–  She is of European ancestry

–  Together with her parents cons%tuted one of the trios for the 1000G pilot project

•  NISC is keenly interested in working with new sequencing technologies.

•  The Genome-‐in-‐a-‐Bocle goal of providing a standard human reference sample for this field will be invaluable.

Church et al., 2011 PLoS Biology

http://genomereference.org

GRCh37 (hg19)

http://genomereference.org

7 alternate haplotypes at the MHC

Alternate loci released as: FASTA AGP

Alignment to chromosome

UGT2B17 MHC MAPT

MHC (chr6) Chr 6 representa%on (PGF)

Alt_Ref_Locus_2 (COX)

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Which Picture Do You Believe?

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Office of Surveillance, Epidemiology, and Laboratory Services Laboratory Science, Policy and Practice Program Office

CDC/NCBI Clinical NGS RM Project q  Two human cell lines (NA19240, NA12878)

q  Existing AND new sequence data (NGS & Sanger) from 36 clinical gene panels, WES, WGS (volunteer labs)

q  Assess data quality (coverage, quality scores, etc); accept data which meets predefined criteria

q  NCBI will analyze and host data files online for public access. Will display: q  All data sets with metrics (coverage, platform, software, etc) q  Consensus sequence track- regions of “high, medium or low”

sequence confidence indicated q  Develop guidance for using online data files as tools for test validation

and NGS trouble-shooting q  Publish manuscript of this process and the findings

q  This data is available to NIST

CDC/NCBI Clinical NGS RM Project §  Subramanian Ajay - Illumina §  Tina Hambuch- Illumina §  Elaine Lyon- ARUP §  Rong Mao - ARUP §  Karl Voelkerding- ARUP §  Nazneen Aziz- CAP §  Ephram Chin- Baylor §  Victor Wei Zhang - Baylor §  Cristina Da Silva - Emory §  Madhuri Hegde- Emory §  John Compton- GeneDx §  Soma Das- U. Chicago §  Dan Farkas- Sequenome §  Matt Ferber- Mayo §  Ed Highsmith- Mayo §  Manohar Furtado- Life Technologies §  Ute Geigenmuller – Harvard §  Birgit Funke- Partners

Participants: §  Sivakumar Gowrisankar - Partners §  Srinka Ghosh- Complete Genomics §  Jay Kaufman- Complete Genomics §  Richard Leach- Complete Genomics §  Shashi Kulkarni- Wash. U §  Elaine Mardis- Wash U. §  Savita Shrivastava – Wash U. §  Marc Salit- NIST §  Justin Zook- NIST §  Richa Agarwala - NCBI §  Deanna Church - NCBI §  Donna Maglott – NCBI §  Jim Ostell - NCBI §  Chris O’Sullivan – NCBI §  Wendy Rubinstein - NCBI §  Steve Sherry- NCBI §  Chunlin Xiao – NCBI §  Lorraine Toji- Coriell §  Lisa Kalman- CDC

The findings and conclusions in this report are those of the author and do not necessarily represent the official position of the Centers for Disease Control and Prevention/the Agency for Toxic Substances and Disease Registry.

The Disclaimer:

Lisa Kalman, PhD [email protected]

ACMG Efforts regarding WGS/WES 1.  Technical guidelines for NextGenera%on sequencing (from

Lab QA Commicee). 1.  Addresses Targeted mul%-‐gene panes, WES, and WGS 2.  Content, method, data analysis, variant filtering, sequencing of regions with homology, companion

technologies and result confirma%on) 3.  Ini%al Valida%on (test, plalorm) 4.  Data analysis op%miza%on 5.  Metrics and performance parameters (analy%c sensi%vity/specificity, false posi%ve/nega%ve,

clinical sensi%vity, assay robustness/precision, limits of detec%on) 6.  Ongoing valida%on of modifica%ons of test, plalorm, analysis pipeline 7.  Reference materials for QC and PT. Includes warning about using cell lines. Includes possibility of

using simulated electronic sequence (for non-‐wet lab component).

2.  Development of model consent for WGS/WES 3.  List of “secondary findings” that should be reported 4.  Collabora%on amongst ACMG/CAP/AMP/ASHG to develop recommended

terminology for variant classifica%on in rela%on to disease risk/causa%on 5.  New CPT codes – will gene%c tests be paid on the Clinical Lab or Physician

Fee Schedules, or both

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Horizon Discovery – reference standards for Next Genera6on Sequencing

1.   HorizonDx combines three core capabili6es •  Highly accurate gene engineering technology à generates isogenic human cell lines •  FFPE %ssue modelling capability à FFPE blocks containing defined cell ra%os •  World-‐class molecular characteriza%on à droplet digital PCR, STR and SNP6

2.   HorizonDx developing a mul6-‐plex reference standard for NGS •  Combining >10 clinically relevant oncogene muta%ons into a single gDNA/FFPE standard •  Staggered allele burdens from ranging from 1-‐25% •  First commercially available NGS standard

3.   The case for including MCF10a as a reference genome •  Normal cell line, well characterized and highly u%lized for cancer research •  Would pave the way for the crea%on of a disease reference genome , or analyte specific reference

material which offers high prac%cal u%lity •  Horizon has >100 knock-‐in/knock-‐out cell lines in MCF10a background to leverage into the consor%um

To find out more: visit: www.horizondx.com or contact Joshua Kapp at [email protected]

RNA-Sequencing Standards Groups

1.  FDA: Sequencing Quality Control (SeQC)- Helicos, 454, SOLiD, Illumina

2.  ABRF: NGS Study: 454, IonTorrent (PGM & Proton) Illumina, Pacific Biosciences

Noise

Biological

Informa%c Chemical/Op%cal

Samples Cluster Beau6fully (Sadly) by Prep SOPs Essen6al Internal Controls Needed

Across Test Sites

Make Enough Reference Material

Aligner Claims are a Siren’s Call

Every PlaUorm Has Pros/Cons

Base Modifica%ons of known biological

importance

DNA: 5-‐methylcytosine 5-‐hydroxymethylcytosine 8-‐oxoguanine glucosylated 5-‐hydroxymethylcytosine 4-‐methylcytosine 6-‐methyladenine 8-‐oxoadenine 5-‐formylcytosine 5-‐carboxycytosine β-‐D-‐Glucosyl-‐hydroxymethyluracil (J base) Phosphorothioa%on (backbone) 1-‐methyladenine 3-‐methylcytosine Inosine 5-‐hydroxycytosine O6-‐methylguanine O4-‐methylthymine 5-‐hydroxyuracil 5-‐hydroxymethyluracil The four ribonucleo%des (backbone) RNA: 6-‐methyladenosine 1-‐methyladenosine Forterre and Grosjean, 2009

Five minute presentations

Technology

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