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Translating Genomes | Personalizing MedicineRNA-based screening in drug discovery – introducing sgRNA technologiesDr. Jon MooreCSO & VP Oncology

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Presenter

Jon Moore PhDCSO & VP Oncology

Jon has been CSO of Horizon since February of this year after joining Horizon in October 2012. His responsibilities include leading Horizon’s portfolio of target ID & validation alliances and internal research portfolio.

Prior to this, he worked on multiple drug discovery programmes at Vernalis, building on his extensive postdoctoral experience in the cell cycle field with Tim Hunt and Sally Kornbluth.

His core areas of expertise are in oncology cell biology and alliance management.

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Content of the Presentation

Introduction to Horizon Discovery

Horizon Discovery Research Division - Horizon’s services and collaboration platforms

RNA-based screening in drug discovery

• Use of X-MAN™ isogenic cell lines in RNAi screening approaches

• Comparison of siRNA and sgRNA screening approaches

• The challenges of genome-wide CRISPR-Cas9 knockout (GeCKO) screening

• Using CRISPR-Cas9 sgRNA for target identification and patient stratification

• Moving from screening hit to target validation

• sgRNA screening: not just KOs

Working with Horizon

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Translating genetic information into personalised medicine

Genomics Personalised MedicineTranslational Genomics

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Horizon is a specialized drug discovery CRO, with a broad range of in vitro and in vivo services

Drug Profiling, MOA studies, Isogenic Cell Lines

Custom Isogenic Cell Line Development

In vivo Models

Target Validation Studies,Knockdown Assessment

High Throughput Drug Combination

Screening Tumour Microenvironment,

3D Cell Assays

Target IdentificationsiRNA/sgRNA screening

Use of X-MAN™ isogenic cell lines in RNAiscreening approaches

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SL screening in X-MANTM isogenics: Landscape of tumour mutations

Sequencing has identified 100’s of potential driving mutations in cancer

Most “driver” mutations are rare and poorly characterised

The most common driver mutations are in tumour suppressors & can’t be drugged directly

Certain frequently mutated oncogenes (e.g. KRAS) are challenging to drug

Pan-cancer mutation rates (Tamberero et al., 2013)

Green boxes: druggable oncogenesRed boxes: undruggable oncogenes & tumour suppressors

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SL screening in X-MANTM isogenics: Overcoming heterogeneity?

Where tumour suppressor loss is the cancer initiating event, all tumour cells may share this mutation and any vulnerabilities it confers

Agents exploiting this loss may assist with overcoming tumour heterogeneity

Systematic de-orphaning is required to find key druggable downstream targets: these could follow either a co-dependence or a synthetic lethality paradigm

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SL screening in X-MAN™ isogenics: On isogenic cell lines

Horizon has collection of over 550 isogenic cell line pairs X-MAN™ cell lines

Horizon’s expert targeting team can also engineer a genetically validated cell line to a customer’s specification

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SL screening in X-MAN™ isogenics: Removing a key source of noise

X-MAN™ powered synthetic lethal screens

Exploits our genome editing technologies to make isogenic cells

Precisely control for target genotype & perfectly matched ‘normal’

Removes a key source of noise in SL-screens

Definitive; make any genotype of interest

siRNA and/or sgRNA libraries;Or drug re-profiling

+

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SL screening in X-MANTM isogenics: Our siRNA screening library

Composed of 2,200 druggable genes (hand-selected) to high-interest oncology target classes.

Client/partner can request specific additions to the library

Dharmacon siGENOME smartpools used (4 siRNAs/target)

• Equimolar mixtures for enhanced on-target effects and reduced off-target events

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SL screening in X-MANTM isogenics: A typical waterfall plot

Three technical replicates per screen (CVs liquid handling <2.5%; CVs +/- controls ~ 13%)

Blue line is the median parental response plotted as a 2D waterfall.

Green data points are the mutant response for the matching target gene

Figure: Synthetic lethality waterfall plot (HCT116 isogenics)

Hits with selective death in the mutant line

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SL screening in X-MAN™ isogenics: Hit confirmation workflow

siRNA Library Pooled TransfectionLipid complexed with siRNA

siRNA > Lipid > Cells

Library stamped out 20n Transfection stamped out

6n pooled for mRNA24, 48, 72 & 96hrs

16n pooled for protein72hrs

WBqRT-PCRKD and Biomarker analysis

AB staining for viabilityTypically, we follow the following process:

1. Deconvolute SMARTpool into single siRNAs

2. Retest viability in isogenic pair; correlate phenotype with degree of KD (RT-PCR & immunoblots)

3. Assess breadth of synthetic lethality in cell line panels (e.g. 5 lines with mutation vs. 5 lines w/o mutation)

4. Rescue KD phenotype with siRNA-resistant cDNA

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SL screening in X-MAN™ isogenics: Complex assay systems

Our compact siRNA library is suitable for assessing target dependency under non-standard conditions

Consider KRAS: in DLD1 cells KRASG13D is dispensable for 2D, but required for 3D growth

Activity of MEK, an effector of KRAS signalling is also required only under 3D

2D Adherent 3D Soft AgarDLD-1 KRASG13D

DLD-1 KRASG13D

KO

Response to MEK inhibitors in 2D vs. 3D

Log [M] ARRY162 (MEK inhibitor)

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SL screening in X-MAN™ isogenics: Complex assay systems

Small siRNA library vs. literature KRAS SL targets screened in DLD1 cells under 2D vs 3D conditions

If 3D assay is more KRAS dependent, knockdown of these targets should have a greater effect

siRNA ranked by effect in 2D

Very anti-proliferative

siRNAs

siRNA has no effect on

growth

Positive controls

Negative controls

Many siRNAs are more anti-proliferative in 3D

KEY

Comparison of siRNA and sgRNA screening approaches

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siRNA vs sgRNA: Limitations of siRNA/shRNA technology

Long experience with RNA interference highlights the following issues

1. Incomplete knockdown – leads to false negatives, especially when interrogating the function of enzymes such as kinases

2. Off target effects e.g from SeeD sequence: especially problematic with shRNA

3. Duration of KD achievable with siRNA

shRNA vs KIF11 have different performances Various mechanisms for off-target effects by shRNA

Transfection of siRNAs leads to partial KD of target expression followed by time-dependent recovery in mRNA levels

Fellman & Lowe, Nat Cell Biol, 2014

http://www.broadinstitute.org/achilles

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siRNA vs sgRNA: Are KO screens better?

The shRNA infrastructure is easily adaptable to knock-out screening

Lentiviruses can deliver Cas9 & sgRNAs into cells with sufficient efficiency to perform whole genome KO screens:

Custom sgRNA libraries can be readily assembled in a pooled format after array based oligosynthesis

Off-target effects don’t appear to be a major concern

CAS 9

Guide RNA

PAM sequence

Matching genomic sequence

Genomic DNA

Shalem et al., Science 2013

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siRNA vs sgRNA: Are KO screens better?

Indications are Cas9/sgRNA suppresses gene expression far more effectively than shRNA

+ve selection screens can ID genes whose inactivation is required for survival

Where GFP expression is placed under control of pathway reporters, +ve selection screens can be run outside of oncology

Shalem et al., Science 2013

The challenges of genome-wide CRISPR-Cas9 knockout (GeCKO) screening

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sgRNA screens: The challenges

-ve selection screens may be more problematic:

• sgRNAs efficacy is variable & KO efficiency likely depends on copy number:

• a typical sgRNA vs an essential gene is depleted ~ 4 fold from a 1n population, but only ~ 2-fold from a 2n population

Second generation libraries may improve performance of –ve selection screens

Wang et al. (2014)

Build algorithm

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sgRNA screens: The challenges

Horizon intends to be at the forefront of guide design

• Multiple CRISPR/Cas9 experts are on SAB

• Relationship with Tech start-up Desktop Genetics who have built gUIDEbook™ tool for Horizon so that the design algorithm can be updated

• We will assess the merits of guide design algorithms such as those presented by Doench et al. (2014)

Also exploring access to haploid cell lines to accelerate target ID

Prof. Feng Zhang

Broad InstituteCRISPR genome editing,

sgRNA screens

Prof. Keith Joung

Mass General HospitalZFN, TALEN, CRISPR

genome editing

Prof. Emmanuelle Charpentier

Helmholtz Institute for Infectious Disease

CRISPR/Cas9

Using CRISPR-Cas9 sgRNA for target identification and patient stratification

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sgRNA screens: Evaluation of the technology at Horizon

Feng Zhang’s lab has improved the lentiviral vector & sgRNA library (see Sanjan et al., 2014)

v2 single vector system yields approx. 7-fold higher titres

2-vector lentiviral system now available for hard-to-infect cell lines

Horizon have the GeCKO v2 human library in optimised single vector system, plentiCRISPRv2:

• 6 sgRNAs/gene

• Targets miRNA

• 1000 non-targeting control

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sgRNA screens: Evaluation of the technology at Horizon

Horizon have also generated a 2344 sgRNA subset library containing 21 guides vs. each of 100+ genes including:

71 tumour suppressors described in Vogelstein et al. (2013)

29 literature targets that have been linked to synthetic lethality with KRAS mutations

Evaluation screens are being performed on ~ the following schedule

Our plans are to make a 2nd generation library targeting the 2200 genes in STX siRNA library; currently selecting guide design algorithm

Sept 14 Oct14 Nov 14 Dec 14 Jan 15 Feb14Cell line Library Conditions

A375 TSG/KRAS SL Vemurafenib (R)

A375 TSG/KRAS SL 6-TG (R)

A375 TSG/KRAS SL Olaparib (S)

A375 TSG/KRAS SL R406 (S)

A375 GeCKO v2 Vemurafenib/Dabrafenib (R)

A375 GeCKO v2 Olaparib/R406

Undisclosed GeCKO Undisclosed (R)

Undisclosed GeCKO Undisclosed (S)

KRAS wt & mutant

TSG/KRAS SL 2D & LA growth

Screens beingrun together

Wet work at HDZ

NGS at GATC

Screens beingrun together

Screens beingrun together

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sgRNA screens: ID of vemurafenib resistance targets

Day -7Transduce 64x106 cells with

TSG sgRNA library

(3 µl virus/2x106 cells)

Day -6 to 0Select for transduced cells

with Puromycin

Day 1Seed 24x106 cells/condition

in duplicate

(~10.000 cells/sgRNA)

Day 1 to 14Treat cells with

PLX (2 µM) or DMSO

Harvest baseline timepoint

(Day 0) to check sgRNA

representation

Harvest end timepoint

(Day 14) to identify

sgRNA candidates

Screen readout(~8.500x library coverage)

Cell numbers during PLX screen (D1 to D14)

31% transduced cells:19.8x106 cells

(~8.500 cells/sgRNA)

TSG library contains sgRNAs vs hit genes: NF1, NF2 for PLX

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sgRNA screens: ID of vemurafenib resistance targets

Average of normalized sgRNA counts from replicate cultures

>100-fold enrichment D14: DMSO vs PLX: 3 sgRNAs(3x NF1: 1997, 1129, 1126)>10-fold enrichment D14: DSMO vs PLX: 31 sgRNAs(5x NF1, 5x NF2, 2x SMARCB1/MAPK9/ARID1A/SMAD4)

D0 D14_DMSO D14_PLX

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sgRNA screens: Enrichment of subset of NF1/NF2 sgRNAs by PLX treatment

>16-fold enrichment of NF1/NF2 sgRNAs

NF1 NF2

Log2

rat

io: s

gRN

Afr

equ

ency

PLX

vs

DM

SO

Log2 ratios of highlighted sgRNAsvs NF1/NF2 (in graph on the left):

>100x enrichment

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sgRNA screens: Log2 ratios of all NF1/NF2 sgRNAs after PLX treatment

NF1 NF2 NF14.8x

NF22.8x

Averageof all sgRNAs

Log2

rat

io: s

gRN

Afr

equ

ency

PLX

vs

DM

SO

NF1 NF2

NF1 NF2

Average of sgRNAs from different “backgrounds”:

Log2

rat

io: s

gRN

Afr

equ

ency

PLX

vs

DM

SO

Log2

rat

io: s

gRN

Afr

equ

ency

PLX

vs

DM

SO

Moving from screening hit to target validation

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sgRNA screening follow up: Decision tree

How does one move an interesting hit, perhaps exemplified by just a single sgRNA, towards a validated target?

The decision tree below outlines the kinds of steps Horizon would recommend

Is the hit exemplified by >1 sgRNA?

Repeat pooled screen with more sgRNAs vs targets.

May want to include other pathway elements

Move to well-based validation

Is there doubt about the penetrance of the

phenotype?

Assess whether target is essential

Assess whether target function is dependent on

its activityStart drug discovery

Abandon target

NO

NO

NO

NO

YES

YES YES

SUCCESS

SUCCESS

YES

FAILFAIL

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sgRNA screening follow up: Pool & array based hit confirmation

sgRNA-rescreening

• Assembly of custom focussed pooled lentivirallibraries with additional sgRNAs vs putative hits is very cost-effective.

• Transduced libraries into multiple cell lines; assess sgRNA-frequency by NGS after 14/21 days

Well-based validation

• sgRNA: first results in for arrayed expt.

A549 cells infected with one of 5 sgRNAs vs RAF1 or a Rosa26 control

Puro selected for 7 days prior to plating

All 5 sgRNAs vs RAF1 reduce proliferation; expression of Cas9 & sgRNA vs. Rosa26 still has phenotype

Further evaluation of controls & gene editing events required

• Upgrading 2-vector v2 lentiCRIPSR system to include fluorescent tags for rapid hit validation:

Shalem et al., Science 2013

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sgRNA screening follow up: Is my target essential?

We have devised a medium-throughput method that can shed light on the ambiguous results that emerge from siRNA/shRNA or sgRNA screens• shRNA only gives partial knockdown; growth phenotypes often partial too• Repair of Cas9-mediated ds breaks can result in in-frame indels that don’t disrupt protein function

Use lentiviruses to deliver Cas9 + sgRNA vs target to cells, allow 14-20 days for gene editing to occur and then culture colonies from single cells

Horizon’s cell-line engineering experience allows us to devise an analysis pipeline to characterise editing events on a clonal level

Assess length of fluorescent PCR products to check allele ratios and frame shift occurrence in 100’s colonies

Culture colonies from single cells

Infect cells targeting gene of interest

TARGET ESSENTIALColonies contain only in

frame indels

TARGET NON-ESSENTIALColonies contain frame shift

indels

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sgRNA follow up: Can an activity-dead allele of my target support its function?

• sgRNA + rAAV facilitates on-target engineering via HDR

• Very high editing efficiencies possible with selectable markers

• Multi-allele engineering likely in one step: Cas9/sgRNA will tend to cleave all alleles of targeted exon

• One or more alleles will be repaired by HDR; other allele(s) mis-repaired by NHEJ

• Horizon has a wealth of experience designing genome analysis protocols to ID desired clones

Horizon are exploring combining CRISPR/Cas9 nucleases with AAV donors to rapidly generate multi-allele knock-in mutations

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sgRNA follow up: Can an activity-dead allele of my target support its function?

Data from a recent project where Horizon used CRISPR + AAV to introduce a minigene into a novel target in diploid DLD1 cells

We have strong evidence for us having clones where one allele has been targeted by the AAV cassette and the other mis-repaired by NHEJ

Guide# Cas-9 #wells with cells# +ve for 5' and 3' screen

single MT 224 29

single WT 415 177

dual MT 203 4

dual WT 336 43

Single guide + WT cas-95’ screening gel

Single guide + WT and MT cas-9Amplification of non-targeted allele

* 518bp deletion* *

* 524bp deletion

Summary of targeting events:Cas9-wt + AAV minigene yields 42% on-target integrations

sgRNA screening: not just knock-outs!

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Activity dead Cas9 mutants can be repurposed as transcriptional regulators

Experience with ZFNs & TALENs can quickly be applied to Cas9

• CRISPRi: Best inhibition of expression comes from sgRNAs vs nt 0-50 3’ to TSS

• CRISPRia: Best activation of expression comes from sgRNAs vs nt 150-50 5’ to TSS

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Activity dead Cas9 mutants can be repurposed as transcriptional regulators

CRISPRi

Technology has potential to replace shRNA.

Likely to have fewer issue with off-target effects

Incomplete knockdown may be a limitation: not clear yet how this compares with shRNA

CRISPRa

Likely to have uses in compound deconvolution studies + studies of resistance

Limitation is that can only boost expression of intact genes

Not clear whether it can overcome epigenetic downregulation

Horizon plans to:

Clone mutant Cas9-chimeras into plenti-CRISPR system

Select small library of sgRNA for pilot study

Perform resistance/sensitisation screens with vemurafenib& olaparib – results potentially available in April/May

KRAB

RepositioningPatient

stratificationLOH2LTarget ValidationTarget ID

siRNA screens

sgRNA screens

TIDVAL alliances

KO to test essentiality

Activity dead KI mutations

Generation of isogenic cell lines MOA assays to support med chemCompound profiling in

isogenic cells

Combination assays

Compound profiling in large cell line panels

Target validation & early stage drug discovery collaborations

Finding a development path for stranded clinical assets

In vivo models

Working with Horizon: Collaborations & services available

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Discovery Research Services

Custom Cell Line Development

CombinatoRxCustom Screening

ServicesIn vivo models

Your Horizon Contact:

Horizon Discovery Group plc, Building 7100, Cambridge Research Park, Waterbeach, Cambridge, CB25 9TL, United Kingdom

Tel: +44 (0) 1223 655 580 (Reception / Front desk) Fax: +44 (0) 1223 862 240 Email: info@horizondiscovery.com Web: www.horizondiscovery.com

Dr. Jon Moore

CSO & VP Oncology

j.moore@horizondiscovery.com

+44 (0)1223 655580