2018/10/11

1

“ Targeting HIF-VHL deregulation in RCC and Hemangioblstoma”

Othon Iliopoulos, MD

Associate Professor of MedicineHarvard Medical School

Director, MGH GU Genetics Program/ VHL ClinicDirector, MGH Hemangioblastoma Clinic

Co‐Leader, DF/HCC Kidney Cancer Program

TCGA Mutations

RCC as metabolic disease

Preclinical validation

In vivo validation

GSEA Zebrafish Models of driver mutations

Clinical Trials

Identification and validation of therapeutic targets in Renal Cancer

VHLPBRM1BAP1SETD2KDM5CSDH

FLCN

TUMOR HYPOXIA

ROS

EGLN

HIFa

HIFa-ARNT

HIFa mRNA VHL

mTORAKTPI3K

ERB

PTEN

SDH

TSC1/2

VEGF PDGF TGF C‐MET

FH

Tumor hypoxia and cancer associated mutations promote HIF activity 

LKB1

AMPK

HIF is a validated target for RCC and other cancers

Direct targeting of HIF2a with small molecules

Synthetic lethality with HIF1a/2a expression based on metabolic reprogramming

Insights into the biology of Hemangioblastomas

2018/10/11

2

HIF2A TRANSLATION

No inhibitor

IRP1

Added inhibitor

IRP

WT + DMSO

VHL  null + DMSO

VHL  null  + 76 10nM

SV40‐Luc

4xHRE‐Luc786‐O

1.  Cell‐based assay for HTS

S

OO

NH

NS

N

OO

2.  HIF2a inhibitors

3.  Specificity by GSEA

4.  Mechanism of action5.  In vivo effects

Identification of HIF2a inhibitors

Zimmer M et al  Molecular Cell 2008Metelo AM et al  JCI 2015Noonan H et al DMM 2017

vhl-/- 1 µM 76vhl-/- DMSOWT DMSO

WT vhl-/-

DMSO -+- 1µM 3.5µM

-76 compound

+-

HIF2a inhibitor decreases abnormal erythropoiesis and angiogenesis in vhl-/- embryos

Hemoglobin O-dianisidine

staining

Erythrocytes+

Blood vessels0

15000

30000

45000

wt dmso nulls dmso nulls 100nM nulls1microM

Tota

l Int

ensi

ty fr

om

pixe

l-mac

hine

lear

ning

***

Ana Metelo et al JCI 2016

0

20

40

60

80

Stage I Stage II Stage III Stage IV

Percen

tage

 of cells (%

)

dmso 76 compound 1microM

0

200

400

600

800

vhl dmso vhl treated1microM

76

Mea

n intensity

 in th

e region

 of interest

76 1µMDMSOvhl-/-

WT VHL‐/‐ 1µM 76VHL‐/‐ 0.01% DMSO

*

***

Vhl‐/‐ DMSO

Vhl‐/‐ 1µM 7660x

60x

***

HIF2a inhibitor ameliorates pathologic angiogenesis and abnormalhematopoiesis in vhl-/- embryos

Fli‐GFP+ embryos

Ana Metelo et al JCI 2016

wt sibling

B

vhl-/-

C 00.010.020.030.040.05

wt vhl-/-

*

0369

1215

wt vhl-/-

**

wt sibling

❖

vhl-/-

vhl-/- 3000x

wt sibling 3000x

Kidney size

Lumen

Haley N et al. Disease Models Mech. 2016

Kidney of vhl ‐/‐embryos resembles premalignant ccRCC phenotype

0

0.001

0.002

0.003

0.004

0.005

DMSO 76 05 DMSO 76 05

*

vhl-/-Siblings

2018/10/11

3

SV40-Luc

Before Treatment After 76 Treatment Before Treatment After 76 Treatment

HRE-Luc

HIF2a inhibitors downregulate HIF2a signaling IN VIVO(Mouse xenograft model)

HIF2 inhibitors suppress RCC growth in mice

(PK unknown)

Direct targeting of HIF2a with small molecule inhibitors: Peloton (PT2297) compound interrupts HIF2a‐ARNT interaction

Phase I trials:  Well toleratedHas activity in heavily pre‐treated metastatic RCC patientsResistance linked to AQUIRED mutations in the binding pocket

Phase 2 clinical trial in RCC and VHL

Direct targeting of HIF2a with small molecules

Synthetic lethality with HIF1a/2a expression based on metabolic reprogramming

Insights into the biology of Hemangioblastomas

TCA metabolites link metabolism to HIF translation

IRP1

5’-UTR Coding message

TranslationStart

ACO1

+Fe(II)-Fe(II)

5’-UTR mRNAs:Ferritin eALASSDHb ferroportin

IRP1 KO mice develop EPO‐driven erythrocytosisand HIF2a‐dependent pulmonary hypertension

2018/10/11

4

OAA

α-kg

Isocit

CitOAA

Mal

Fum

SucCoASuc

Glutamate

Pyruvate AcCoA

FATTY ACIDS

TCA cycle

ACLAcCoA

ATP

Biomass

Energy (ATP)Reducing power

(NADPH)

GLUCOSE-6P

GLUTAMINE

PROLIFERATION

HK1

Enolase

PK-M2

NADPH

Nucleic Acids

PPPGLUT-1

Normal cells use Glucose for carbon source

ATP

NADPH

ATP x 32

OAA

α-kg

Isocit

CitOAA

Mal

Fum

SucCoASuc

Glutamate

PyruvateLACTATE AcCoA

FATTY ACIDS

TCA cycle

ACLAcCoA

ATP

Biomass

Energy (ATP)Reducing power

(NADPH)

GLUCOSE-6P

GLUTAMINE

PROLIFERATION

HK1

LDH-A

Enolase

PK-M2

NADPH

Nucleic Acids

PPPGLUT-1

VHL‐/‐ and HYPOXIC cells depend on Glutamine for growth

PDK-1

ATP

HIF1a/2a

GLS1

0%

20%

40%

60%

80%

100%

Normoxia Hypoxia

Glucose oxidation Glutamine reduction

% con

tribution to lipid carbon A549

Reductive carboxylation of GLUTAMINE derived carbons is theprimary pathway for lipid synthesis under hypoxia

Metallo CM et al Nature 2012

Citrate levels regulate Glutamine consumption: HIF1a/2a expression is necessary and sufficient to confer Glutamine

dependence

Metallo et al    Nature 2012Gameiro et al  Cell Metabolism 2013

GLS1

2018/10/11

5

Citrate

Reductive carboxylation form glutamine occurs in vivo

-10%

10%

30%

50%

70%

90%

0 100 200 300 400

% M

1 G

luta

min

e

Time (min)

Tumors Kidneys Plasma

0%

1%

2%

3%

4%

5%

6%

Control 30min 1hr 2hr 6hr

% M

1Citr

ate

from

[1

-13 C

1] G

luta

min

e

TumorKidneyPlasma

Control mouse [1-13C1] Glutamine Infused mouse

(6hours)

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 1 2 3 4 5 6 7Rel

ativ

e 13

Cen

richm

ent o

f tum

or

citra

te

Time (hours)

High-resolution 13C NMR spectra

[1-13C] glutamineExtract

metabolties from: TumorKidneyBlood

GC-MS analysis

13C NMR analysis

30’1hr2hr6hr(N = 3)

Citrate levels regulate Glutamine consumption: opportunities for targeted therapy

Metallo et al    Nature 2012Gameiro et al  Cell Metabolism 2013

GLS1 Inhibitors(BPTES, CB‐839)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

control 1.5μMBPTES

3μMBPTES

Rel

ativ

e C

ell G

row

th

UMRC2-vectorUMRC2-VHL

***

***

0.0

0.2

0.4

0.6

0.8

1.0

1.2

control 1.5μMBPTES

3μMBPTES

Rel

ativ

e C

ell G

row

th

RCC4-vectorRCC4-VHL

***

***

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

control 1.5μMBPTES

3μMBPTES

Rel

ativ

e C

ell G

row

th

UOK102-vectorUOK102-VHL

***

***

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0 1 10 100 1,000

Rel

ativ

e C

ell G

row

th

CB-839 cncentration (nM)

UMRC2-vectorUMRC2-VHL

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0 1 10 100 1,000

Rel

ativ

e C

ell G

row

th

CB-839 Concentration (nM)

RCC4-vectorRCC4-VHL

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0 1 10 100 1,000

Rel

ativ

e C

ell G

row

th

CB-839 Concentration (nM)

UOK102-vectorUOK102-VHL

0

5

10

15

20

25

30

35

40

UMRC2 RCC4 UOK102

GI5

0 (n

M)

vector

VHL

*

**

**

GLS Inhibition suppresses growth of VHL-Deficient RCC Cells Loss of VHL renders RCC cells/tumors sensitive to glutaminaseinhibition in vivo

00.10.20.30.40.50.60.7

Control BPTES

Tum

or w

eigh

t (g)

0

100

200

300

400

500

600

700

Day 0 Day 2 Day 4 Day 6 Day 8 Day10

Day12

Day14

Tum

or s

ize

(mm

3 )

Control BPTES*

*

** *

Gameiro et al  Cell Metabolism 2013

2018/10/11

6

Phase 1a/1b  CLINICAL TRIAL with oral GLS inhibitor CB‐839

MASSACHUSETTS GENERAL HOSPITAL

Phase 1a   All solid tumors

Phase 1b RCC  (CBE or CB + Nivolumab)TNBC  (CB+Placlitaxel)NSCLC  (CB+Placlitaxel)

Glutamine

Glutamate

GSH Fattyacids

Aminoacids

Nucleosides

GLS1 inhibitor

Nucleobases

Acetate

GlutamateαKG

Glucose

PDK1 HIF

ROS

NAC

Pyruvate

BiosynthesisRedox

balance

TCA cycle

Effects of GLS1 inhibitors on RCC metabolism

GLS

HCO3-

GLUTAMINE

NH3

Aspartate

GLUTAMATE

Carbamoyl-P

Krebs cycleGlutamateCPSII

ACTase

Carbamoyl-Aspartate

UMP

Ribonucleotides, deoxyribonucleotides

(e.g., CMP,TMP)Intact deoxyribonucleosides

De Novo pyrimidine synthesis pathway

Salvage pathway

De novo and Salvage Pathways for Pyrimidine biosynthesis

GLUCOSE

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

Met

abol

ite A

bund

ance

nor

mal

ized

by

the

sum

(a.u

.) UMRC2 pBABE

UMRC2 pBABE + BPTES

UMRC2 VHL

UMRC2 VHL + BPTES

VHL -/-vulnerability

GLS Inhibition Compromises De Novo Pyrimidine Synthesis in VHL-Deficient Cells

GLS

HCO3-

GLUTAMINE

NH3

GLUTAMATE

GlutamateCPSIIBPTES

Aspartate

Krebs cycle

GLUCOSE

Carbamoyl-P

ACTase*

**

*

*

Carbamoyl-Aspartate

(-) VHL

(+) VHL

Okazaki et al, Journal Clinical Investigation (2017)

2018/10/11

7

0

1

2

3

4

5

6

7D

CFD

A in

tens

ity(n

orm

aliz

ed to

uns

tain

ed

cont

rol)

UMRC2-vectorUMRC2-VHL

1.5 μM 3 μM 10 μMDMSOBPTES

A

*

******

** **

B

******

**

1.5 μM 3 μM 10 μMDMSOBPTES

GLS Inhibition increases ROS in VHL-Deficient RCC Cells

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Rel

ativ

e G

SH/G

SSG

ratio

UMRC2-vectorUMRC2-VHL

0.0

0.2

0.4

0.6

0.8

1.0

1.2

BPTES nucleobases NAC nucleobases+NAC

Rel

ativ

e ce

ll gr

owth

UMRC2-vector

UMRC2-VHL

*** ***

***** *

***

+BPTES

C

UMRC2-vector UMRC2-VHL

DM

SOB

PTES

BPT

ES+D

M-α

KG

0

5

10

15

20

25

30

35

40

0 2 4 6 8 10 12 14 16 18 20 22 24

% F

iber

s

0

5

10

15

20

25

30

35

40

0 2 4 6 8 10 12 14 16 18 20 22 24

% F

iber

s

DMSO

BPTES

BPTES+DM-αKG

0-2

2-4

4-6

6-8

8-10

10-1

2

12-1

4

14-1

6

16-1

8

18-2

0

20-2

2

22-2

4

Fiber length (μm)

0-2

2-4

4-6

6-8

8-10

10-1

2

12-1

4

14-1

6

16-1

8

18-2

0

20-2

2

22-2

4

Fiber length (μm)

DMSO

BPTES

BPTES+DM-αKG

GLS Inhibition Induces DNA Replication Stress in VHL-Deficient Cells

Okazaki et al, Journal Clinical Investigation (2017)

DNA synthesis

DNA damage

DNA repairCisplatin PARP inhibitor

(olaparib)

Hydroxyurea5‐fluorouracilOrotate dehydrogenase inhibitor (teriflunomide)

Treatment of of VHL-Deficient Cells:combination of GLS Inhibitors with other drugs

A B

BPTES(μM) 0 0.0625 0.125 0.25 0.5 1 2 -0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1 2 3 4 5 6 7

Rel

ativ

e ce

ll gr

owth

vector-BPTES

vector-olaparibvector-combination

VHL-BPTES

VHL-olaparibVHL-combination

0

1

2

0.0 0.5 1.0

Com

bina

tion

inde

x

Fraction Affected

UMRC2-vectorUMRC2-VHL

olaparib(μM) 0 1.25 2.5 5 10 20 40

C

D

control BPTES olaparib combination

EdU

PI

S

G1

G2/M

Inhibited DNAsynthesis

control BPTES olaparib combinationEd

U

PI

S

G1

G2/M

Inhibited DNAsynthesis

VHL-null

VHL-replete cells

Synergistic effect of GLS Inhibitors with Olaparib

2018/10/11

8

0

10

20

30

40

50

60

70

80

DMSO BPTES olaparib combination

Inhi

bite

d D

NA

synt

hesi

s/to

tal S

ph

ase(

(%Ed

U p

ositi

ve c

ells

) UMRC2-vector

UMRC2-VHL

***

**

***

BPTES - + +- - +olaparibUMRC2-vector UMRC2-VHL

0102030405060708090

100

% C

ells

15+

8-15 3-7

0-2

-+

- + +- - +

-+

foci/cell

0

1

2

3

4

5

6

0 2 4 6 8 10 12 14

Rel

ativ

e tu

mor

vol

ume

Days

vehicleCB-839olaparibcombination

p<0.05(Day14)

GLS Inhibitors synergize with Olaparib in killing VHL-Deficient Cells In vivo

Okazaki et al, Journal Clinical Investigation (2017)

Resistance to GLS1 inhibitor CB-839: identification of differentially expressed genes

Genotype‐separated drug‐driven changesTime‐frame separated drug‐driven changes

(drug incubation time)

Direct targeting of HIF2a with small molecules

Synthetic lethality with HIF1a/2a expression based on metabolic reprogramming

Insights into the biology of Hemangioblastomas

PDPN expressing

Hematopoietic cellEndothelial cell

Stromal cell

?

VHL-/-

Loss of 3p25 ‐ VHL inactivation

Gain of chromosomes 1 and 4

Loss of chromosomes 6, 9, 19 and 22q13 

Lipid accumulation

What do we know about human HB

HIF

2018/10/11

9

Years

Volu

me

1 2 3 4

The growth of HB is variable: lack of biomarker predicting growth WES revealed LOH or somatic point mutations leading to the inactivation of both VHL alleles in all VHL-related HB

Metelo et al (Submitted)

Loss of Chromosomes 3 and 8 are recurrent Copy Number Variation events in VHL-related HBs

Program GISTIC 2.0 amplificationdeletion

Metelo et al (Submitted)

Single Cell Sequencing from HB fresh tumors and HB-derived cell lines

Tumor Dissociation

Single Cell Sorting

Surgery Tumor Excision

RNA extraction

cDNA

Reverse Transcription

PCR pre‐amplification

PCR purification“WTA” (Whole Transcriptome Amplification) Quantification (Qubit Assay) and 

Quality control (Bioanalyzer)

Tagmentation (Fragments DNA and adds a tag)

PCR with Barcode primers

Library pooling (put 2.5 μl of each well of a 96‐well plate together)

Purify DNA Quantification (Qubit Assay) and Quality control (Tapestation)

Pool 4x libraries (4 nm final concentration)

DNA sequencing

Smart Seq2 Protocol

Cell of origin

Discovery of actionable signaling pathways

2018/10/11

10

HB-derived cell lines capture HB heterogeneity

Cellular Markers AM1 AM3 AM7

PDPN 7.1% 90.7% 10%

VEGFR2 70.4% 94.7% 1.2%

CD45 0.1% 0.7% 0.1%

CD31 1.7% 6.2% 0.5%

CD133 0% 0.8% 0%

CD11b 4.6% 16.3% 2%

CXCR4 27.2% 20.9% 0.5%

Cellular Markers AM1 AM2

PDPN 91.7% 87.1%

VEGFR2 0% 1%

CD45 17.1% 0.7%

CD31 0% 6.2%

CD133 0% 0.8%

CD11b 0.6% 16.3%

CXCR4 0% 1.7%

early early

earlylate intermediate

• AM1: VHL-related• AM2: Sporadic• AM3: VHL-related• AM7: VHL-related

Stromal cells

Endothelial cells/ Vascular tumors

Immune cells

Endothelial cells

Neuronal stem cells

Microglia/Macrophages

Hematopoietic stem cells

HB-derived cells generate HB in mice: a model for human HB (PDX)

AM1AM2

NOD/SCID

MRI FFPE IHC

HB cell‐derived xenografts are rich in intracellular lipids and highly vascularized 

The mobile lipids are detected by 1H MRS at 0.9 – 1.3 ppm They correspond to methyl (CH3) and methylene (CH2)n groups

Proton magnetic resonance spectroscopy

Quantification of intracellular lipidsADC measures the movement of H2O molecules This value is higher in the presence of angiogenesis, blood vessels, tumor necrosis or edema

Diffusion‐weighted imaging (DWI) 

Choline Lipids (singlet)

Choline

Lipids (singlet)

Cho

CrPCr NAA

NAA

CrPCr

Cho

Tumor Normal

Tumor Normal

Image 1 Image 2

Image 3 Image 4

Mouse model for HB

2018/10/11

11

Single Cell Sequencing from HB fresh tumors and HB-derived cell lines

Tumor Dissociation

Single Cell Sorting

Surgery Tumor Excision

RNA extraction

cDNA

Reverse Transcription

PCR pre‐amplification

PCR purification“WTA” (Whole Transcriptome Amplification) Quantification (Qubit Assay) and 

Quality control (Bioanalyzer)

Tagmentation (Fragments DNA and adds a tag)

PCR with Barcode primers

Library pooling (put 2.5 μl of each well of a 96‐well plate together)

Purify DNA Quantification (Qubit Assay) and Quality control (Tapestation)

Pool 4x libraries (4 nm final concentration)

DNA sequencing

Smart Seq2 Protocol

Cell of origin

Discovery of actionable signaling pathways

HB13‐CD45+ HB13‐CD45‐

HB14 HB15

Unsupervised analysis of sc-RNAseq clusters cells in distinct subgroups

Identification of cluster specific gene expression signatures

HB14

1

2

3

4

5

6

1 2 3 4 5 6Clusters

Clusters

Identification of clusters with high expression of HIF-target gene signature

2018/10/11

12

HIF upregulation is a major oncogenic event in VHL-related tumors

HIF can be directly targeted with small molecule inhibitors

HIF reprograms cancer cell metabolism and renders VHL-null cellsdependent on Glutamine – remains to be proven for HB

GLS inhibitors selectively kill VHL-null cells and synergize with PARPinhibitors -remains to be proven for HB

HB-derived cell lines recapitulate the cellular heterogeneity of the humanCNS HBs

A xenograft mouse model may guide the development of targeted therapyfor CNS HB

Summary AcknowledgementsIliopoulos Laboratory

Danos ChristodoulouKatja DinkelborgEvi KonstantakouRavi SundaramTianjin YiYun Liao

MGH Brain TumorFred BarkerBrain NahedAnat Stemmer‐RachamimovMario SuvaTracy Batchelor

NIH/NCI RO1 CA160458 DOD Ovarian CancerPROSTATE CANCER FOUNDATIONDF/HCC Kidney SPOREMGH GU Center Bertucci AwardKraft AwardISSELBACHER FOUNDATION

MGH CCRWilli HaasGaddy GetzShyamala MaheswaranMo MotamediShoba VasudevanToshi ShiodaLee ZouJonathan Whetstine

Kevin Hodgetts Lab (LDDN)Jun‐Yung AhnDawid FiejtekLin Lin