Systems Approaches to Blood Based C Cancer Biomarkers Bi k S - - PowerPoint PPT Presentation

Systems Approaches to Blood Based C Bi k Cancer Biomarkers S Hanash

• S. Hanash

shanash@mdanderson.org

Why so few biomarkers to date? y f

• Developing biomarkers shares some of the same

challenges as developing drugs, yet the investment in biomarkers is far, far less!

• Requires a road map from discovery to validation for

specific/intended clinical applications specific/intended clinical applications

• Need to establish a mechanistic link to the disease

process beyond statistical associations

Targeted cancers

If we screen for it and catch it early does it save lives? does it save lives?

Challenges with CT based screening Challenges with CT based screening

• High percentage of false positives. 96.4%
• f pulmonary nodules identified by LDCT

p y y are non-malignant  unnecessary work- ups ups.

• If all smokers and former smokers do

C S three CT scan per NLST protocol, the health care system can’t afford it. y

LUNG CANCER Number of lives that could be saved h h each year with CT screening

8 100 8,100

Estimated today’s costs per life saved:

$ 100,000 ‐ 240,000 $ 100,000 240,000

Goulart et al J Natl Compr Canc Netw 2012;10:267‐275

CONCEPTUAL FRAMEWORK CONCEPTUAL FRAMEWORK

The TUMOR INFILTRATING The MICROENVIRONMENT

In tumor initiation, d l d

TUMOR CELLS INFILTRATING CELLS ANGIOGENESIS

development and progression

FIBROBLASTS

S t i h t Systemic host response

Mouse models

Genomics Genomics Glycomics Glycomics Proteomics Proteomics

Bi k l Bi k l

y

Biomarker panels Biomarker panels

Cancer cells Human studies

l / h l ll Metabolomics Metabolomics

Immunomics Immunomics

♦ plasma/serum ♦ tissues ♦ whole cell extracts ♦ secretome/exosome ♦ surface proteins ♦ nuclear proteins Metabolomics Metabolomics

Immunomics Immunomics

From the tumor to blood From the tumor….to ….. blood

Mass Spectrometry Capability: 30,000 LC/MS runs

3,000 proteins 8‐10,000 proteins 4‐6,000 proteins 3,000 proteins 8 10,000 proteins 4 6,000 proteins

Proteomic signatures

Chemical Chemical Modifications eg altered glycosylation Protein Cleavages eg Alternative Splicing Isoforms Protein Cleavages eg shed receptors and adhesion molecules Formation of Altered dynamics of i i Formation of complexes eg immune complexes protein sorting eg release of chaperone proteins

Translational Translational Translational Translational Implications Implications

+/- various treatments

O NH2 N H2 OH

Cells In Culture

Heavy LYS Light LYS

2

Cell surface Protein biotinylation Cell culture media

CELL SURFACE mix heavy and light SECRETOME TOTAL EXTRACT

concentration Lysis and affinity t Gl copeptide Cell Lysis capture Elution Glycopeptide Capture

PHOSPHOPROTEINS NUCLEAR PROTEINS

Conditioned media Proteins localization

Source of conditioned media proteins

2%

Conditioned media Proteins localization using Uniprot Database

19374

• Pre-

filtration

• Pre-

filtration

29% 7% 20% 42% Cytoplasm Nuclear Surface Extracellular space

2480

• Post-

filtration

• Post-

filtration

Unknown

Hi h V l t t

61% Ratio S/M >2 32% Ratio: 1- 2 7% Ratio <1

176

High Value targets

Cell line Compartment MS2 counts H1993 Media 65

1 913

Cytoplasmic domain T b d i

DDR1 protein: epithelial discoidin domain-containing receptor 1

H1373 Media 51 HPC9 Media 37 H1993 Surface 103 H1373 Surface 73 Transmembrane domain Extracellular domain Signal Peptide HPC9 Surface 78

• I. Babel

A B Function of cytosolic and nuclear proteins released into conditioned media

Biological Process (Gene

• ntology Term)

Number of proteins p‐value Bonferroni Macromolecule metabolic process 48 1.88E‐02 Cellular component organization 30 2 84E 02

A B

p g at cellular level 30 2.84E‐02 Cellular localization 22 9.99E‐03 Establishment of localization in cell 21 5.58E‐03 Protein transport 19 1.72E‐03 P i l li i 19 4 95E 02 Protein localization 19 4.95E‐02 Intracellular transport 18 1.99E‐03 Intracellular protein transport 17 9.94E‐07 Cellular protein localization 17 3.05E‐05 Carbohydrate metabolic process 15 2.73E‐02 Oli h id b li Oligosaccharide metabolic process 8 2.79E‐05 Polysaccharide catabolic process 5 3.88E‐02 Oligosaccharide catabolic process 3 8.64E‐03 Glycosphingolipid catabolic process 3 4.28E‐02 p

Macromolecule metabolic process Lysosomal enzymes Cellular localization Nuclear localization Component organization p g

H920 A B

Nuclear proteins are released by lung cancer cells in exosomes H920

Exo FT Media Nucleus TCE

A B

XPO1 XPOT ALIX

Exosome marker

TNPO1

200 nm Note: from 300mL of media: 20x more exosome fraction from cancer cell lines than transformed control cell

Blood Based biomarkers

Newly Diagnosed and post Rx for predictive markers 0 2 yrs pre diagnostic 3+ yrs pre diagnostic 0-2 yrs pre-diagnostic for early detection 3+ yrs pre-diagnostic For risk markers

Blood Based biomarkers

Newly Diagnosed and post Rx for predictive markers 0 2 yrs pre diagnostic 3+ yrs pre diagnostic 0-2 yrs pre-diagnostic for early detection 3+ yrs pre-diagnostic For risk markers

Intact Protein Analysis System (IPAS)

Case Control

I m m unodepletion (Top six proteins) Concentration, buffer I m m unodepletion (Top six proteins) Concentration, buffer

Ig bound fraction: MS bound fraction: MS

, exchange and labeling SAMPLE A Light Acrylam ide SAMPLE B Heavy Acrylam ide Reduction w ith DTT and Alkylation , exchange and labeling SAMPLE A Light Acrylam ide SAMPLE B Heavy Acrylam ide Reduction w ith DTT and Alkylation SAMPLES MIXED ANI ON EXCHANGE CHROMATOGRAPHY SAMPLES MIXED ANI ON EXCHANGE CHROMATOGRAPHY REVERSE-PHASE CHROMATOGRAPHY REVERSE-PHASE CHROMATOGRAPHY Shotgun LC/ MS/ MS 96 fractions Shotgun LC/ MS/ MS 96 fractions

Mouse models

♦ Lung cancer

EGFR: TetO-EGFRL858R/CCSP-rtTA (H. Varmus/K. Politi) K T O K 4bG12D/CCSP TA (H V /K P li i) Kras: TetO-Kras4bG12D/CCSP-rtTA (H. Varmus/K. Politi) Urethane: introperitoneal injection of urethane (C. Kemp) SCLC: Trp53F2-10/F2-10; Rb1F19/F19 (J. Sage)

♦ Breast cancer ♦ Breast cancer

HER2: MMTV-rtTA/TetO-NeuNT (L. Chodosh) PyMT 0.5cm: Tg(MMTV-PyMT)634Mul (C. Kemp) PyMT 1.0cm: Tg(MMTV-PyMT)634Mul

♦ Pancreas cancer

PanIN: Pdx1-Cre; LSL-KrasG12D; Ink4a/Arflox/lox (R. DePinho, N. Bardeesy) PDAC: Pdx1-Cre; LSL-KrasG12D; Ink4a/Arflox/lox

C ♦ Colon cancer: ApcΔ580/+ (R. Kucherlapati, K. Hung)

Kras model (R. DePinho) Mlh1 and Msh2 mutant models (R. Kucherlapati)

♦ Ovarian cancer: LSL K

G12D/+ Pt loxP/loxP (D Di

l T J k )

♦ Ovarian cancer: LSL-KrasG12D/+; PtenloxP/loxP (D, Dinulescu, T. Jacks) ♦ Prostate ca (Strain comparison): Ptenpc-/-, Ptenpc-/-;Smad4pc-/- (R. DePinho) ♦ Inflammation

A t C i l t ti (C K ) Acute: Carrageenan-sponge implantation (C. Kemp) Chronic: intradermal injection of type II collagen (C. Kemp)

Plasma signature for lung adenocarcinoma driven in part by the master regulator NKX2‐1

Validation in humans of mouse lung adenocarcinoma blood markers

Newly diagnosed set 8 1.0 y g 0.6 0.8 eFraction

A ssay Norm al Cancer T-test Mann W hitney test New ly diagnosed set

0.4 e Positive

y y EGFR 1.00 ± 0.067 0.77 ± 0.041 0.0094 0.004 SFTPB 1.00 ± 0.135 1.43 ± 0.205 0.0708 0.0332 W FDC2 1.00 ± 0.233 4.70 ± 1.145 0.0005 < 0.0001 A NGPTL3 1.00 ± 0.073 1.53 ± 0.205 0.008 0.0038

0.2 True

Com bin ed (AU C= 0.882 ) EG FR (AU C= 0.708 ) SFT PB (AU C= 0.654 ) W FDC2 (AU C= 0.864 )

0.0 0.2 0.4 0.6 0.8 1.0 0.0 False Positive Fraction

AN G PT L3 (AU C= 0.709 )

a se os t e act o

Is there evidence that blood markers could be useful? Validation in the pan Canadian Lung Ca screening study

Red: Base model”|: AUC= .642 Blue: Base model + 1 marker (AUC = 736 Blue: Base model + 1 marker (AUC .736 Difference in AUCs p = .0002 Sin et al JCO in press

Harnessing the immune response to tumor antigens for lung cancer early detection

• Humoral immune response to tumor antigens occurs early

during tumor development g p

• Immune response is not limited to mutated or otherwise

lt d t i altered proteins

• Implementation of a proteomic strategy to identify proteins

Implementation of a proteomic strategy to identify proteins in lung cancer that induce an autoantibody response

Search for antigens that induce an antibody response in lung cancer

• Recombinant protein arrays
• Natural protein arrays

M t t f i l ti ti

• Mass spectrometry of circulating antigen‐

antibody complexes

• Peptide arrays (in collaboration with Roche)

Search for antigens that induce an antibody response in cancer

The complete repertoire of peptides encoded in The complete repertoire of peptides encoded in the human genome on a chip + (Mutant peptides and pathogen peptides) (Mutant peptides and pathogen peptides)

Potential of marker panels to detect l l lung cancer early

.0 .0 .0 Pre-diagnostic set .8 1 . c tio n .8 1 . c tio n .8 1 . c tio n 4 .6 s itiv e F ra c t 4 .6 s itiv e F ra c t 4 .6 s itiv e F ra c t .2 .4 T ru e P

• s

.2 .4 T ru e P

• s

.2 .4 T ru e P

• s

C

• m

bined all (AU C = 0.898 ) C

• m

bined ELISA (AU C = 0.808 ) t tib d l (AU C 0 828 )

0 0 0 2 0 4 0 6 0 8 1 0 .0 0 0 0 2 0 4 0 6 0 8 1 0 .0 0 0 0 2 0 4 0 6 0 8 1 0 .0

autoantibody panel (AU C = 0.828 ) EG FR (AU C = 0.677 ) SFT PB (AU C = 0.74 ) WFD C 2 (AU C = 0.632 ) AN G PT L3 (AU C = 0.615 )

0.0 0.2 0.4 0.6 0.8 1.0 False Positive Fraction 0.0 0.2 0.4 0.6 0.8 1.0 False Positive Fraction 0.0 0.2 0.4 0.6 0.8 1.0 False Positive Fraction

A validation study of biomarkers involving A validation study of biomarkers involving 10,000 subjects at risk for lung cancer in USA

Primary Objective Primary Objective: Develop and test a biomarker panel in combination with CT to reduce the false positive rate of CT and reduce unnecessary reduce the false positive rate of CT and reduce unnecessary invasive work‐up by 30% Secondary Objective: Assess need for CT screening based on biomarker panel. Target performance PPV equivalent of better than LDCT (>= 3 6% which corresponds to 40% sensitivity at 95 % specificity) 3.6% which corresponds to 40% sensitivity at 95 % specificity)

Paradigm shift in the development

• f biomarkers

Partnership between academia Partnership between academia, philanthropy, government and p py, g industry

Pre-validation of markers (construct refine and nail down panel) (construct, refine, and nail down panel)

MDACC Markers

Pre-Dx cohorts: (eg PLCO…) Retrospective Screening Cohorts (eg PanCan, NLST)

Other markers Other markers

Marker panel + Imaging + risk model

Prospective Screening Cohorts (USA, China)

validated panel for intended clinical application

Unbiased, in-depth, quantitative High throughput, Sensitive, affordable q

Cancer Biomarker platforms

Oncoproteome database Oncoproteome database

• Proteomics technologies have matured to the

point of significantly impacting clinical p g y p g applications

• A collaborative integrative effort with
• A collaborative integrative effort with

adequate resources and rigorous experimental l f h l f design is critical for the development of biomarkers

Acknowledgements

• Hanash Lab: Ingrid Babel, Clayton Boldt, Muge Celiktas,Tim

Chao, Alice Chin, Lili Chu, Dilsher Dillon, Vitor Faca, Sandra Faca Song Gao Rebecca Israel Askandar Ikbal Melissa Faca, Song Gao, Rebecca Israel, Askandar Ikbal, Melissa Johnson, Hiroyuki Katayama, Jon Ladd, Min-Hee Lee, Amin Momin, Sophie Paczesny, Sharon Pitteri, Ji Qiu, Mark Schliekelman Melissa Silva Jinfeng Suo Ayumu Taguchi Schliekelman, Melissa Silva, Jinfeng Suo, Ayumu Taguchi, Allen Taylor, Sati Tripathi, Nese Unver, Hong Wang, Dong Wang, Chee-Hong Wong, Qing Zhang

• Collaborators: Aaron Aragaki, Nabeel Bardeesy, Robert Bast,

Ron DePinho, Daniela Dinulescu, Nora Disis, Kim-Ahn Do, F i E t Zidi F Oli Fi h S G bhi Francisco Esteva, Ziding Feng, Oliver Fiehn, Sam Gambhir, David Gandara, Guillermo Garcia-Mareno, Adi Gazdar, Gary Goodman, Bill Hancock, Kenneth Hung, Chris Kemp, Raju K h l ti St L P l L C lit L b ill Ch i Kucherlapati, Steven Lam, Paul Lampe, Carlito Lebrilla, Chris Li, Karen Lu, Phil Mack, Suzanne Miyamoto, Peyman Moghaddem, Ed Ostrin, Katerina Politi, Peggy Porter, Ross g ggy Prentice, Julian Sage, Karen Spratt, Martin Tammemagi, Harold Varmus, Shan Wan

FUNDING SUPPORT

Foundations Canary Canary Uniting Against Lung Cancer Protect Your Lungs/Lungevity g g y Lustgarten Avon Komen Government National Cancer Institute National Cancer Institute National Heart Lung and Blood Institute DOD