Detecting and exploiting amino acid vulnerabilities in cancer - - PowerPoint PPT Presentation

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Detecting and exploiting amino acid vulnerabilities in cancer - - PowerPoint PPT Presentation

Sep 26, 2023 147 likes •536 views

Detecting and exploiting amino acid vulnerabilities in cancer Oncode Institute - NKI-AVL Reuven Agami Course Basic and Translational Oncology 2018 How to -specifically- kill cancer cells? Target DNA replication (chemotherapy) Suffocate them

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SLIDE 1

Reuven Agami

Oncode Institute - NKI-AVL

Detecting and exploiting amino acid vulnerabilities in cancer

Course Basic and Translational Oncology 2018

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SLIDE 2

How to -specifically- kill cancer cells?

Target DNA replication (chemotherapy) Suffocate them (inhibit signalling pathways) Re-activate the immune system (immunotherapy) Starve them to death

?

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SLIDE 3

Epigenetics Nucleotides Oxidative stress Lipids

cell proliferation

poly-peptide amino acids

Essential Non-essential

Proteins

Amino acid usage

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SLIDE 4

Epigenetics Nucleotides Oxidative stress Lipids

cell proliferation

Proteins

Cancer

poly-peptide amino acids

Essential Non-essential

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SLIDE 5

Nature 1953

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SLIDE 6

Broome J.D. et al., Nature 1961

L-Asparaginase

Nature 1961

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SLIDE 7

Since 1977 (introduction of high dose Asparaginase treatment) cure of childhood ALL was raised to >90% Resistance does occur: mostly related to re-expression of Asparagine synthetase (ASNS) in tumours

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SLIDE 8

Asparagine Glutamine Asparagine synthetase ASNS Asparagine circulating in blood Diet/ Synthesis in liver ALL tumor cell Aspartic acid Asparaginase Aspartic acid

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SLIDE 9

2018

Hannon and colleagues Nature 2018

Asparagine Depletion affects BC metastasis

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SLIDE 10

Future

» Sense bottlenecks in the demand of (solid) tumours » Exploit to identify cancer vulnerabilities

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SLIDE 11

The problem

amino acid vulnerability

defect in production tumour vascularisation uptake demand for protein synthesis use for energy tRNA synthetase mutant tRNA use for replication

How to sense amino acid shortage?

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SLIDE 12

Ribosomes - the translation machinery

~ 4000 kDa protein subunits Ribosomal RNA

David Goodsell, RCSB PDB

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SLIDE 13

Ingolia NT et al Science 2009

Ribosome profiling

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SLIDE 14

DIfferential RIbosome COdon REading

Loayza-Puch et al., Nature 2016

Cell state #1 Cell state #2 Potential amino acid shortage

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SLIDE 15

State I (Normal tissue) State 2 (Tumor tissue)

Sensing amino acid shortages in cancer

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SLIDE 16

Position-based analysis Codon-based analysis Infer changes in amino acid related pathways Measure changes in codon usage

Diricore analysis

  • Loayza. et al., Nature 2016
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SLIDE 17

A P E

HIS

A P E

diricore treated/ctrl.

3-Amino-1,2,4-triazole

3-AT

Evaluation 1

Position-based analysis Codon-based analysis

b d

Sub-sequence abundance shift 3-AT vs Control Position 15 Codons

GCA GCC GCG GCT AGA AGG CGA CGC CGG CGT AAC AAT GAC GAT TGC TGT CAA CAG GAA GAG GGA GGC GGG GGT CAC ATT CTA CTG CTT TTA TTG AAA AAG ATG TTC TTT CCA CCC CCG GTT CCT AGC AGT TCA TCC TCG TCT ACA ACC ACG ACT TGG TAC TAT GTA GTC GTG CAT ATA ATC CTC

5 10

  • 5

His Sub-sequence abundance shift

A R N K F M D C Q E G H I L P S T WY V

† Codons

2

  • 2

CAC (His) TTC (Phe)

15 30

  • 30
  • 15

TTT (Phe) CAT (His)

15 30

  • 30
  • 15

2

  • 2
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SLIDE 18

Cephalotaxus harringtonia Harringtonine

Evaluation 2

Position-based analysis

d e

Codons Sub-sequence abundance shift

Harringtonine vs Control Position 12

GCA GCC GCG GCT AGA AGG CGA CGC CGG CGT AAC AAT GAC GAT TGC TGT CAA CAG GAA GAG GGA GGC GGG GGT CAC ATT CTA CTG CTT TTA TTG AAA AAG ATG TTC TTT CCA CCC CCG GTT CCT AGC AGT TCA TCC TCG TCT ACA ACC ACG ACT TGG TAC TAT GTA GTC GTG CAT ATA ATC CTC

2 4

  • 2

Met

A R N K F M D C Q E G H I L P S T WY V

Codons

A R N K F M D C Q E G H I L P S T WY V

†

Codons

Codon-based analysis

e

4

  • 4

ATG(Start) Relative read density Harringtonine vs Control TTC (Phe)

15 30

  • 30
  • 15

Position respect to codon TTT (Phe) ATG (Other)

15 30

  • 30
  • 15

4

  • 4
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SLIDE 19

Evaluation 3

AAC (Asn) AAT (Asn) TTC (Phe) TTT (Phe)

  • 0.5

0.5

  • 0.5

0.5

Position respect to codon Relative read density ASNase vs Control

15 30

  • 30
  • 15

15 30

  • 30 -15

g

Sub-sequence abundance shift

1

  • 0.5

0.5

GCA GCC GCG GCT AGA AGG CGA CGC CGG CGT AAC AAT GAC GAT TGC TGT CAA CAG GAA GAG GGA GGC GGG GGT CAC ATT CTA CTG CTT TTA TTG AAA AAG ATG TTC TTT CCA CCC CCG GTT CCT AGC AGT TCA TCC TCG TCT ACA ACC ACG ACT TGG TAC TAT GTA GTC GTG CAT ATA ATC CTC

Asn Codons

A R N K F M D C Q E G H I L P S T WY V

ASNase vs Control Position 15

f

†

un-charged tRNA levels

Relative tRNA uncharging levels

Asn-GTT Asn-ATT Leu-CAG Val-TAC

2 4

** ** h

Control ASNase Position respect to codon

PC3 Cells

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SLIDE 20

Kidney Cancer tumor/normal

β-a Codons

A R N K F M D C Q E G H I L P S T WY V

GCA GCC GCG GCT AGA AGG CGA CGC CGG CGT AAC AAT GAC GAT TGC TGT CAA CAG GAA GAG GGA GGC GGG GGT CAC ATT CTA CTG CTT TTA TTG AAA AAG ATG TTC TTT CCA CCC CCG GTT CCT AGC AGT TCA TCC TCG TCT ACA ACC ACG ACT TGG TAC TAT GTA GTC GTG CAT ATA ATC CTC

1

A A A A R R R R R R N N D D C C Q Q E E G G G G H H I I I L L L L L L K K M F F P P P P S S S S S S T T T T W Y Y V V V V

0.5 1

  • 0.5

Position 12 T1 vs N2 Pro Met

logFC=0.1, FDR=8.1e−01 logFC=−1.4, FDR=2.6e−08

Differential ribosome codon reading (Diricore)

  • Loayza. et al., Nature 2016
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SLIDE 21

Prolin production pathway

Shortage High production

High production = Shortage

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SLIDE 22

PYCR1 high PYCR1 low

Overall survival: Kidney tumors

Poor survival of PYCR1 high cancers

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SLIDE 23

PYCR1 Control KO1 KO3 β-actin T P 9 5 1

  • M

U S

e

1 2 3 4

0.4 0.8 1.2

Codons

A R N K F M D C Q E G H I L P S T WY V

0.5

  • 0.5

GCA GCC GCG GCT AGA AGG CGA CGC CGG CGT AAC AAT GAC GAT TGC TGT CAA CAG GAA GAG GGA GGC GGG GGT CAC ATT CTA CTG CTT TTA TTG AAA AAG ATG TTC TTT CCA CCC CCG GTT CCT AGC AGT TCA TCC TCG TCT ACA ACC ACG ACT TGG TAC TAT GTA GTC GTG CAT ATA ATC CTC

Position 15 Sub-sequence abundance shift y t i s n e d d a e r e v i t a l e R Position respect to codon

TGC (Cys) TGT (Cys)

15 30

  • 30
  • 15

15 30

  • 30 -15

0.5

Cultured 1 vs Cultured 2

0.5 0.5 0.5

Pro Codons

A R N K F M D C Q E G H I L P S T WY V

0.5

  • 0.5

GCA GCC GCG GCT AGA AGG CGA CGC CGG CGT AAC AAT GAC GAT TGC TGT CAA CAG GAA GAG GGA GGC GGG GGT CAC ATT CTA CTG CTT TTA TTG AAA AAG ATG TTC TTT CCA CCC CCG GTT CCT AGC AGT TCA TCC TCG TCT ACA ACC ACG ACT TGG TAC TAT GTA GTC GTG CAT ATA ATC CTC

Position 15 Sub-sequence abundance shift y t i s n e d d a e r e v i t a l e R

CCA (Pro) CCC (Pro)

Position respect to codon

TGC (Cys) TGT (Cys)

15 30

  • 30
  • 15

15 30

  • 30 -15

0.5

Tumor 2 vs Cultured 2

0.5 0.5 0.5

b a c

PYCR1 C

  • n

t r

  • l

K O 1 K O 3

  • actin

T P 9 5 1

  • M

U S R e l a t i v e c e l l g r

  • w

t h Gln (4mM) Gln (1mM)

f

Pro (10mM): - - + - - + - - + Control PYCR1 KO1 PYCR1 KO3

0.1 1 10 100 1000 10000 4 6 8

100 200 300 400 5 10 15 20 25 30 35

Days

Cell proliferation

d e g

Codons

A R N K F M D C Q E G H I L P S T WY V

0.5

  • 0.5

GCA GCC GCG GCT AGA AGG CGA CGC CGG CGT AAC AAT GAC GAT TGC TGT CAA CAG GAA GAG GGA GGC GGG GGT CAC ATT CTA CTG CTT TTA TTG AAA AAG ATG TTC TTT CCA CCC CCG GTT CCT AGC AGT TCA TCC TCG TCT ACA ACC ACG ACT TGG TAC TAT GTA GTC GTG CAT ATA ATC CTC

Position 15 Sub-sequence abundance shift y t i s n e d d a e r e v i t a l e R

CCA (Pro) CCC (Pro)

Position respect to codon

TGC (Cys) TGT (Cys)

15 30

  • 30
  • 15

15 30

  • 30 -15

0.5

Tumor 1 vs Tumor 2

0.5 0.5 0.5

Pro Codons

A R N K F M D C Q E G H I L P S T WY V

0.5

  • 0.5

GCA GCC GCG GCT AGA AGG CGA CGC CGG CGT AAC AAT GAC GAT TGC TGT CAA CAG GAA GAG GGA GGC GGG GGT CAC ATT CTA CTG CTT TTA TTG AAA AAG ATG TTC TTT CCA CCC CCG GTT CCT AGC AGT TCA TCC TCG TCT ACA ACC ACG ACT TGG TAC TAT GTA GTC GTG CAT ATA ATC CTC

Position 15 Sub-sequence abundance shift y t i s n e d d a e r e v i t a l e R

CCA (Pro) CCC (Pro)

Position respect to codon

GTA (Val) GTC (Val)

15 30

  • 30
  • 15

15 30

  • 30 -15

0.5

Tumor 1 vs Cultured 1

0.5 0.5 0.5

h i

1 2 3 4 5

PYCR1 expression Breast IDBC C u l t u r e d 1 v s C u l t u r e d 2 T u m

  • u

r 1 v s T u m

  • u

r 2 T u m

  • u

r 2 v s C u l t u r e d 2 T u m

  • u

r 1 v s C u l t u r e d 1

* *

NS

A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A

GFP- Trap

Cell Lysate GFP IP Ribo-Seq Diricore RNAse I digestion RPL10a eGFP Tumor Lysate

CCA (Pro) CCC (Pro)

PYCR1 KO3 PYCR1 KO1 Control T u m

  • u

r V

  • l

u m e ( m m ) Days PYCR1 KO3 PYCR1 KO1 Control

* *

3

***

Control PYCR1 KO3 Control PYCR1 KO3 tRNA Pro (AGG) tRNA Pro (TGG) Gln (4mM) Gln (1mM) Gln (1mM) + Pro (4mM) R e l a t i v e t R N A u n

  • c

h a r g i n g l e v e l s

* * * *

† ‡

Pro Pro

NS NS

β-a

f

0.1 1 10 100 1000 10000 4 6 8

Days

Cell proliferation

g h

PYCR1 KO3 PYCR1 KO1 Control

The importance of PYCR1 for tumor growth

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SLIDE 24

1 validated -> improved 100x

Screen

Blocking PYCR1 activity for cancer therapy

+ NADH/NAD absorbance measurement An activity assay

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SLIDE 25

Arginine

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SLIDE 26

Far reaching consequences

Out balance Mutations

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SLIDE 27

Why only childhood leukaemia?

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SLIDE 28

Evaluation 3

AAC (Asn) AAT (Asn) TTC (Phe) TTT (Phe)

  • 0.5

0.5

  • 0.5

0.5

Position respect to codon Relative read density ASNase vs Control

15 30

  • 30
  • 15

15 30

  • 30 -15

g

Sub-sequence abundance shift

1

  • 0.5

0.5

GCA GCC GCG GCT AGA AGG CGA CGC CGG CGT AAC AAT GAC GAT TGC TGT CAA CAG GAA GAG GGA GGC GGG GGT CAC ATT CTA CTG CTT TTA TTG AAA AAG ATG TTC TTT CCA CCC CCG GTT CCT AGC AGT TCA TCC TCG TCT ACA ACC ACG ACT TGG TAC TAT GTA GTC GTG CAT ATA ATC CTC

Asn Codons

A R N K F M D C Q E G H I L P S T WY V

ASNase vs Control Position 15

f

†

un-charged tRNA levels

Relative tRNA uncharging levels

Asn-GTT Asn-ATT Leu-CAG Val-TAC

2 4

** ** h

Control ASNase Position respect to codon

PC3 Cells

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SLIDE 29

Metabolic feedback

−6 −4 −2 2 4 6

log1(Fg)

1 2 3 4 5

−log1((P−value)

1262 AA66 C361 6A56 A616 AA56 3HGDH 7508 606 GA56 CA56 5A56 2DC1 GL21 A661 (I)5A D0GDH 36A71 ALDH1L2 (356 A616D1 GC6H 087 A3I3 376 6LC7A7 CB6 A65GL1 G036 A737A 6H072 DI23 G)371 71)

G2:0006520 (FHOOuODU DPLnR DFLG PHtDEROLF SURFHss) G2:0006528 (DsSDUDgLnH PHtDEROLF SURFHss) hLghOLghtHG Ln UHG 6LzH sFDOHG Ey ORg(C30) D( dDtD A6NDse vs. Ctrl (exSs. 3524, 3626)

−6 −4 −2 2 4 6

log1(Fg)

1 2 3 4 5

−log1((P−value)

1262 AA66 C361 6A56 A616 AA56 3HGDH 7508 606 GA56 CA56 5A56 2DC1 GL21 A661 (I)5A D0GDH 36A71 ALDH1L2 (356 A616D1 GC6H 087 A3I3 376 6LC7A7 CB6 A65GL1 G036 A737A 6H072 DI23 G)371 71)

G2:0006520 (FHOOuODU DPLnR DFLG PHtDEROLF SURFHss) G2:0006528 (DsSDUDgLnH PHtDEROLF SURFHss) hLghOLghtHG Ln UHG 6LzH sFDOHG Ey ORg(C30) D( dDtD A6NDse vs. Ctrl (exSs. 3524, 3626)

ASNase vs Ctrl.

Control ASNase

120 120

ASNS

300 bp

g h

PC3 Cells

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SLIDE 30

Metabolic feedback

ASNase treatment Ribosomes profile Stimulation of synthetase ASNS Asparagine shortage

Amino acid sensing machinery

GCN1/2 ATF4

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SLIDE 31

Vulnerability

PC3 Cells

0% 20% 40% 60% 80% 100% 120%

Ctrl. ASNase

0% 20% 40% 60% 80% 100% 120%

Ctrl. ASNase

  • ctrl. sgRNA

ASNS sgRNA #1

Days 3 6 Days 3 6 % proliferation % proliferation

ATF4 sgRNA Ctrl. ASNase GCN2 sgRNA

0% 20% 40% 60% 80% 100% 120%

0% 20% 40% 60% 80% 100% 120%

Ctrl. ASNase

Days 3 6 Days 3 6 % proliferation % proliferation

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SLIDE 32

Model for ASNase treatment

ASNase treatment Ribosomes profile Stimulation of asparagine synthetase

GCN1/2 ATF4

Asparagine shortage?

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SLIDE 33

Prostate cancer cells (PC3)

Shortage High production

L-Asparaginase in treatment of solid tumors

The amino acid sensing machinery: GCN1/2 (EIF2AK4) and ATF4

?

  • Loayza. et al., Nature 2016
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SLIDE 34

A genetic screen to sensitize PC3 cells to L-Asparaginase

  • 2
  • 1

1 2 2 4 6 8

Log2 FC

  • log10(p-value)

ASNS EIF2AK4 F8A1 SLC25A1 SLC1A3

D E

Time (Hours)

EIF2AK4

C

Mock Transduction with genome wide sgRNA library ASNase PCR amplification

  • f sgRNA inserts

Comparison of sgRNA abundance using NGS

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SLIDE 35
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SLIDE 36

Asparagine Glutamine Asparagine synthetase ASNS Solid tumor cell Aspartic acid ALL tumor cell Asparaginase Aspartic acid Nucleotides Asparagine circulating in blood Diet/ Synthesis in liver Inhibitor

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SLIDE 37

Dr.Steiner stiftung Gozde Korkmaz Ruiqi Han Li Li Remco Nagel Jane Sun Itamar Kozlovski Yuval Malka Julien Champagne Behzad Moumbeini Abhi Pataskar

Agami group

NKI Genomics core facility Marja Nieuwland Roel Kluin Ron Kerkhoven FACS facility Anita and Frank Wilbert Zwart Ekaterina Nevedomskaya Koen Flach

Acknowledgements

Ran Elkon Zohar Manber Elzo de Wit Hans Teunissen Miao P Chien Fabrizio Loayza-Puch Koos Rooijers Celia Berkers Esther Zaal