July 2010

Can we eradicate HIV…What do we need to answer the question?

Daria HazudaMerck and Co

Why can’t we cure HIV with ARV DrugsWhere is the virus and how is it maintained in the

face of “suppressive” therapy?

Residual replication•Sanctuaries; drug penetration•Efficacy, cell type differences

Persistent HIV expression•Replication competent?•Immune disfunction?

Latently infected cells

InflammationHomeostatic Proliferation

These are not mutually exclusive mechanisms; will multiple approaches be required?

Is it the same in all patients?

Time from infection (acute vs chronic)– Initiation of therapy and nadir CD4

Route of infectionAgeGenetic factors, including

– Race– Ethnicity– Gender

ARV regimenOther, eg., co-infection with HCV, HCMV etc.

Why can’t we cure HIV with ARV DrugsWhere is the virus and how is it maintained in the

face of “suppressive” therapy?

Residual replication•Sanctuaries; drug penetration•Efficacy, cell type differences

Persistent HIV expression•Replication competent?

Latently infected cells

InflammationHomeostatic Proliferation

These are not mutually exclusive mechanisms; will multiple approaches be required?

Rationale and Goal

Hypothesis– Reactivation of HIV-1 within latent reservoirs in the

presence of HAART will lead to elimination of latent reservoirs through a combination of cytopathic viral and immune mechanisms

Goal– Use small molecule(s) to reactivate latent HIV-1 genomes,

purge the reservoir and elicit a “sustained virologic response” in the absence of continued antiretroviral therapy

Functional Cure

Research & Discovery Process

FDA Review 1

5,000 – 10,000 Compounds

250 Compounds

5 Compounds

Drug Discovery

ClinicalTrials

Post-Marketing

Preclinical

2

Years

Phase IIIn=1000-5000

Phase IIn=100-500

Phase In=20-100

1DiMasi JA, Hansen RW, Grabowski HG Journal of Health Economics 22 (2003): 151-185

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1.5

5

Incr

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How do we test this hypothesis?From the test tube to humans

In vitro tools Compound or Target identification

Cell-based assays, siRNAs

Compounds/drug leads (One or more MOA?)

Animal modelsPD markers; Efficacy

Human studiesBiomarkers/clinical surrogates

Where are we now…

HIV LatencyCell Culture Models

Integrated LTR-reporter constructs– Advantages: LTR is inducible by compounds that activate latent HIV,

amenable to siRNA screening– Disadvantages: highly reductionist system

Chronically infected, inducible cell lines– Advantages: complete integrated HIV genome– Disadvantages: clonal, each line has a single integration site, some

have defective Tat/Tar

Retroviral vectors – Advantages: GFP reporters allow sorting of population of transduced

cells, mixed population– Disadvantages: Constructs integrated into heterochromatin; HIV is

more likely to integrate into transcribed genes (mixed population

HIV LatencyMore Complex Cell Culture Systems

Ex-vivo infected primary resting CD4+ T cells– minimal LTR reporters

LGIT – HIV-1 provirus

Resting CD4+ T cells Bcl-2-transduced resting CD4+ T cells

Resting CD4+ T cells isolated from HIV+ aviremic patients– Quantification of viral DNA/RNA in memory T cell subsets – Viral outgrowth assays

How do they compare? Which is most biologically relevant?

Merck High Thoughput Screen Assay for Activators of Latent HIV-1 Gene Expression

24 hours

Add Compounds

Hela P4/R5 cells

24 hours

-Galactosidase Assay

E.coli lacZHIV LTR polyA

-galactosidaseUninfected cell

E.coli lacZHIV LTR polyA

- galactosidase

Uninfected cell + compound

Activation of HIV-1 Gene Expression Correlates with HDACi Potency

~ 1.5 million compounds (MRL Library)

~ Confirmed 104 compounds (not known HDACIs)

~ 92 compounds that did not activate T-cell

~ 83 compounds with potential novel mechanism of

LTR-LTR-Gal HTSGal HTS

NFAT-BLA Jurkat cell assayNFAT-BLA Jurkat cell assay

HDAC activity assay (novel HDACIs)HDAC activity assay (novel HDACIs)

ToxicityToxicityChemical attractivenessChemical attractivenessFurther chacterization eg ACH-2, J1.1, primary cells, ex vivoFurther chacterization eg ACH-2, J1.1, primary cells, ex vivo

Non-mechanism based screening can identify novel HIV-1 activators

Characterizing novel activators

^ TW Chun; D Margolis; * Planelles et al, 2008; Yang et al, 2010; Tyagi et al, 2010; In-house Merck data** Archin et al, 2009; Kutsch et al, 2002; Reuse et al, 2009; Williams et al, 2004; Burnett et al, 2010 # In-house Merck data

HDACinhibition

NFκBactivation

pTEFbrelease

ClinicalSamples^

Ex-vivoCD4 T cells*

ProvirusJurkat**

LBITJurkat#

LTR-BgalHeLa#

VPA + +/- + + -TSA +/- + + +

HMBA +/- + + +

prostratin + + + +TNFa +/- + + -

novel - MERCK - + - - ++/-

Are these meaningful differences or a reflection of the spectrum of relevant biology?

Proposed mechanisms to affect latent proviral HIV-1 expression

Adapted from Richman et al, 2009

Me

MTInhibitor

MT

MeMT

Potential HIV-1 Latency Activation Therapies

Histone deacetylase (HDAC) inhibitors– Class I-selective: SAHA, others (MRL)– Non-selective: Trichostatin A (TSA), valproic acid (VPA)

NF-kB activators– Prostratin, PMA, TNFa

Akt/HEXIM-1 modulators– Hexamethylbisacetamide (HMBA)

Histone methyltransferase (HMT) inhibitors– DZNep: targets Ezh2 (trimethylates H3-K27/H4-K20)– Chaetocin: targets su(var)3-9 (methylates H3-K9)

Jak/Stat pathway– IL-7

Lessons from Oncology: Synergy with HDACIs

16

Synergistic reactivation of latent HIV-1Synergistic reactivation of latent HIV-1 Synergistic reactivation using combinations of agonists demonstrated in cell lines

Suggested as a potentially more robust approach to reactivate HIV-1 derived from various patients, viral subtypes, or LTR mutants

Low dose may result in diminished AEs in clinic

U1 cells J-Lat cells

Reuse et al, 2009

Burnett et al, 2010

SAHA in combination with MRL HIV “inducing” compounds synergize to activate the HIV LTR

1.40%

L127 1M

1.76%

L412 2.5 M

L495 2.5M

1.21%4.09%

L801 1M

SAHA +L127

1.89% 2.87%

SAHA +L412

SAHA +L495

73.3%

SAHA +L801

76.6%

1.21%

Untreated

SAHA 250nM

1.89%

Controls Compounds alone Compounds + SAHA

J89 Cells: latently infected Jurkat cell line with a single integrated copy of the HIV genome with EGFP as a marker for HIV expression upon stimulation of the LTR. METHODS: J89 cells were incubated with DMSO, L127, L412, L495 or L801 +/- SAHA for 19hrs. GFP expression was measured by flow cytometry. (Archin, et al unpublished)

A alone B alone A + SAHA B + SAHA

C alone D alone C + SAHA D + SAHA

Can Activation Alone “purge” the Reservoir?

Latent Cells Immune

HDACIs + ??? OR Modulator?

Activated cells

Can Activation Alone “purge” the Reservoir?

Latent Cells Immune HDACIs + ??? plus Modulator?

Activated cellsThX

VaccineImmunotoxin, anti-PD1, etc

Can you “reset” the immune system without therapy intensification and shutting off persistent antigen production?

HIV-1 Latency Pre-clinical In Vivo Models

Animal models are critical for understanding viral persistence and testing novel concepts– Can model HAART in HIV-infected humans (eg, RTIs and InSTIs)– Parameters such as time of infection and HAART initiation can be

standardized.– It is possible to extensively evaluate reservoirs in tissues eg, GALT & CNS– Viral rebound as an critical endpoint can be monitored.

Rodent Models – SCID-hu mouse (human transplants of thymus, fetal liver or PBMCs– BLT mouse (human bone marrow, liver, thymus)

More complete systemic reconstitution of all major human hematopoetic lineages including T, B, monocyte/macrophage, dendritic and NK cells.

Macaque Models: SIV, SHIV etc

Approaches that delay or decrease viral rebound can provide information for the design of novel and/or combination strategies.

RT-SHIV Study: HAART and Induction w/HDACI & PKC activator(Paul Luciw, et al unpublished)

6 wks 32 - 35 wks 8 wks 1wk

RT-SHIVInoculation

HAART(FTC + PMPA + Efavirenz)

HAART + Induction

Necropsy

Rebound (16 wks)No treatments

2 wks: 5 cycles 6 wks: 1 cycle per wk

Weekly/biweekly analysis: plasma viral RNA, CBC, FACS

Necropsy

0 5 10 15 20 25 30 350

1

2

3

4

5

6

7

8 36160

3625336348

3634936488

3654436661

Start Treatment

3635336166

Weeks Post Infection

Log

vRN

A C

opie

s/m

lLongitudinal Analysis of Viral Loads During HAART• Low-Level Viremia Persists Despite Effective HAART

Fig.3A

Treatment HAART + Induction + Rebound HAART + Rebound

  MonkeyMMU 36160

MMU 36349

MMU 36488

MMU 36353

MMU 36544

MMU 36913

MMU 35685

MMU 35940

MMU 36098

A. Resting lymphoid tissues  Axillary LN 53 1 1 1,100 26,000 92,000 3,000 10,000 350  Inguinal LN 250 68 45 3,200 54,000 25,000 23,000 8,700 2,700  Iliac LN 30 0 44 3,500 42,000 2,400 48,000 27,000 <5  Obturator LN 530 <1 6 550 90,000 ND ND ND NDB. Active lymphoid tissues

  Mesenteric LN 3 5 21 4 41,000 810 6,100 31,000 43  Cervical LN 1 <1 <1 <2 43,000 330 13 880 <1 Tonsil 520 0 430 3 13,000 69,000 47,000 360 440C. Primary lymphoid organs  Spleen 110 1 2 20 130,000 59,000 11,000 25,000 83  Thymus 0 <1 <1 <3 <1 710 <1 46 <1  Bone marrow <1 <1 <1 <8 18 <2 67 <1 <1D. GI tract tissues  Duodenum <1 <1 <1 1 2,100 830 <5 <2 55  Jejunum <1 68 <2 2 6,400 <3 230 15 15  Ileum <1 <1 <1 3 18,000 820 <4 <2 <1  Cecum 7 <1 1 1 4,600 2,700 <1 220 <2  Colon 61 <1 <4 3 9,900 580 610 38,000 140E. Other  Liver 1 <1 <2 <1 150 47 ND ND ND  Heart <1 <1 <2 <1 30 <1 ND ND ND  Lung <2 <1 <2 <1 330 <1 ND ND NDPlasma vRNA copies /ml 316 <50 <50 1850 1,292,699 916 179 1,238 <50 

Tissue vRNA levels are reduced following combination induction treatment and rebound

  TreatmentHAART + Induction + Rebound

HAART + Rebound

  Monkey MMU 36160MMU 36349MMU 36488

MMU 36353

MMU36544

MMU 36913

MMU 35685

MMU 35940

MMU 36098

A. Resting lymphoid tissues                    

  Axillary LN 230 180 640 2,000 2,500 1,200 140 <1 130

  Inguinal LN 150 100 450 4,600 2,500 6,000 1,100 930 1,200

  Iliac LN 170 140 61 730 6,100 27 400 670 <5

  Obturator LN 400 160 97 1,800 4,500 ND ND ND NDB. Active lymphoid tissues

  Mesenteric LN 550 170 720 1,700 2,200 6,400 340 1,500 760

  Cervical LN 9 54 37 59 6,100 290 <15 830 950

  Tonsil 100 9 110 150 6,000 2,800 3,900 1,900 570C. Primary lymphoid organs

  Spleen 110 15 110 650 12,000 680 74 660 180

  Thymus 6 <1 <1 13 44 16 51 <1 <1

  Bone marrow <1 <1 <1 <8 8 15 110 <1 <!D. GI tract tissues

  Duodenum 3 19 99 140 2,400 110 <4 <1 190

  Jejunum 15 37 49 76 610 140 520 200 69

  Ileum <2 14 70 210 830 69 <3 <1 <1

  Cecum 85 5 3 130 1,300 3,200 2 170 <2

  Colon 440 84 450 61 2,700 <1 ND ND 200E. Other

  Liver <1 <2 110 <1 52 <1 ND ND ND

  Heart 19 <1 <2 <1 58 <1 ND ND ND

  Lung 55 25 5 13 510 7 ND ND ND

6. Plasma vRNA copies/ml 316 <50 <50 1850 1,292,699 916 179 1,238 <50   

Tissue vDNA levels are reduced following combination induction treatment and rebound

No Difference in rebound plasma viremia after discontinuation of HAART and inducers

Group 1B = HAART plus induction; Group 3 = HAART only

Summary and Outstanding Issues

Multiple and perhaps “inter-dependent” processes contribute to the inability to eradicate HIV with ARV therapy

– Will any one approach be sufficient for eradication? – Will the same combination of interventions work for all patients?

Various interventions which can address at least some of these issues are being explored including small molecules which may activate latent viral gene expression

– Activators can manifest differential activity in different cell based assays; Are these differences biologically meaningful or reflect a specturm of biological mechanisms relevant in “non-uniform” systems?

– HDACIs appear to be the most robust, provide an anchor for combinations?– Will activation therapy be sufficient without modulation of the immune response;

can the immune response be modulated wiithout blocking pesistent viremia? Evaluating these approaches individually and in combination in well validated

animal models will be critical to understand many of these issues– What data will provide sufficient evidence to justify clinical evaluation?– What clinical surrogates can be used to provide an early signal of efficacy and

would be sufficiently robust to trigger therapy interruption?

Acknowledgements

Amy EspesethMarta MajdanCamil SayeghChris Tan

Collaborators: David Margolis Una O’Doherty Doug Richman Jeff Lifson Paul Luciw Tom North Warner Greene Eric Verdin

Many others

Tissue Fold95% Confidence

Interval

Group Outcome Estimate Lower Upper P-value

A Resting lymphoid vRNA 185 3.2 10806 0.015

B Chronic, active lymphoid vRNA 446 17.1 11648 0.0011

C Primary lymphoid vRNA 34 2.9 391 0.0078

D GI tract vRNA 151 18.5 1236 <0.0001

A-D vRNA 143 11.9 1706 0.0001

A Resting lymphoid vDNA 2.3 0.38 13.8 0.35

B Chronic, active lymphoid vDNA 13.9 3.7 52.2 0.0006

C Primary lymphoid vDNA 9.2 0.99 84.3 0.051

D GI tract vDNA 4.0 0.58 27.8 0.15

A-D vDNA 5.4 1.14 25.6 0.034

Statistical analysis comparing vRNA and vDNA tissue levels between induction

and non-induction groups