Imaging in Personalized Medicine M. Hacker · Medizinische Universität Wien Univ.-Prof. Dr. med . M. Hacker Imaging in Personalized Medicine Summary PET has high potential to link

Medizinische Universität Wien Univ.-Prof. Dr. med. M. Hacker

Imaging in Personalized Medicine M. Hacker

Medizinische Universität Wien Univ.-Prof. Dr. med. M. Hacker Vogelstein Science 2013

Challenge: Tumor Heterogeneity


Personalizing Oncological Treatment

Herbst et al. N Engl J Med 2008


…, but how to get representative Tissue?


Mutation risk of heterogeous tumors underestimated by genetic analyses of tumor biopsies

Validation of oncological biomarkers from biopsy-material hampered

High potenial for selection of preexistent therapy refractary clones

Changes during therapy


Gerlinger et al. N Engl J Med 2012

How could PET Imaging help? System Biology approach

Multiple Lesions / different tumor regions

Real time Imaging, serially, non-invasive

Improved understanding of tumor biology in-vivo

Functional vs. non-functional expression analysis

Visualize and quantify specific targets


Understanding Cancer: Evolution of Technologies

IHC/FISH

Expression Analysis

Mutation Analysis

Functional Imaging

Sample-based Techniques

Imaging Techniques

Tumor Characterisation, Microenvironment: Metabolism, Angiogenesis, Proliferation, Apoptosis, Hypoxia,…

Medizinische Universität Wien Univ.-Prof. Dr. med. M. Hacker Wester HJ Clin Cancer Res 2007

Medizinische Universität Wien Univ.-Prof. Dr. med. M. Hacker Anthony Stevens, Medical Options London, with friendly permission

The Reality about PET


The “Working Horse” in PET Indications FDG PET/CT

Differentiation benign/malignant lesions

CUP

Staging

Radiation Therapy Planning

Therapy-Monitoring

Restaging /Differentiation Scar / Recurrence

Detecting Tumor Recurrence

Biopsy Guiding

Boellaard et al. FDG PET/CT: EANM procedure guidelines for tumour imaging V2.0. JNM 2014


Ipsi- and contralateral mediastinal LN metastases

PET/CT bei NSCLC

Primary Tumor / Staging


CT / PET / PET/CT

LN-Staging, NSCLC

Author Source Year n Sensitivity Specificity

Shim Radiology 2005 106 70% / 85% 69% / 84%

Pieterman N Engl J Med 2000 102 75% / 91% 66% / 86% Antoch Radiology 2003 27 70%/89%/89% 59%/ 89%/94%

FDG PET/CT: change of therapy management - in 30% compared to CT - in 26% compared to PET

Staging


Baseline

Therapy-Monitoring Gastrointestinal Stromal Tumor (GIST)

8 days after start of Imatinib therapy

(Tyrosin Kinase Inhibitor)

A B

Medizinische Universität Wien Univ.-Prof. Dr. med. M. Hacker Holdsworth, C. H. et al. Am. J. Roentgenol. 2007;189:W324-W330

Baseline

1 month after start of therapy

Therapy-Monitoring GIST, early respone to Imatinib (Gleevec)


Kaplan-Meier plots of population split (n = 58)

South Western Oncology Group (SWOG) criteria n.s.: p=0.55

p=0.00002

Holdsworth, C. H. et al. Am. J. Roentgenol. 2007;189:W324-W330

Therapy-Monitoring Gastrointestinal Stromal Tumor (GIST)

Medizinische Universität Wien Univ.-Prof. Dr. med. M. Hacker Kishino et al, JNM 2012

Limitations of FDG

Hypopharyngeal Cancer

Baseline 3 weeks after

Initiation of RT 4 weeks after

end of RT

HCC

Kornberg et al., Liver Transplantation 2012


Detection Diagnostic Accuracy

Therapy Monitoring / Risk Stratification

Serial Aquisitions Quantification

In-vivo Tissue Characterization Multi-Tracer Imaging Dynamic Imaging

Correlative Imaging Hybrid Imaging - PET/CT - SPECT/CT - MR/PET

Personalized Medicine - Individualized Biomarkers - Individualized Therapy

Individualized Therapy Management Targeted Therapies, Radionuclide Therapies

Clinic / Clinical Research

Medizinische Universität Wien Univ.-Prof. Dr. med. M. Hacker Hartenbach, Hacker et al., Clin Cancer Res 2014

From Detection to Characterization 18F-Ethylcholin PET plus MRT

36 Patienten mit bioptisch gesichertem PC

MRT (T2, STIR) und PET (FEC) nacheinander in identischer Position, Bildfusion

Goldstandard: Postoperative Histologie („whole mount sections“), 128 Läsionen

>


68Ga-PSMA PET/MRT

Hartenbach, Hacker, et al. MUW Vienna

Medizinische Universität Wien Univ.-Prof. Dr. med. M. Hacker Hartenbach, Hacker, Kenner, Shariat, et al.; unpublished data

Gleason 3

Gleason 4

Gleason 4

Gleason 3

BPH

[18F]Fluoromethylcholine [68Ga]PSMAHBED-CC H.E.

Gleason 3

Gleason 4

Tumor Characterization - Heterogeneity


1 - Specificity

0,0 0,2 0,4 0,6 0,8 1,0

Sen

sitiv

ity

0,0

0,2

0,4

0,6

0,8

1,0

AUC = 0,82; P=0,005

1 - Specificity

0,0 0,2 0,4 0,6 0,8 1,0

Sen

sitiv

ity

0,0

0,2

0,4

0,6

0,8

1,0

AUC = 0,82; P=0,007

1 - Specificity

0,0 0,2 0,4 0,6 0,8 1,0

Sen

sitiv

ity

0,0

0,2

0,4

0,6

0,8

1,0

AUC = 0,84; P=0,004

1 - Specificity

0,0 0,2 0,4 0,6 0,8 1,0

Sen

sitiv

ity

0,0

0,2

0,4

0,6

0,8

1,0

AUC = 0,74; P=0,037

1 - Specificity

0,0 0,2 0,4 0,6 0,8 1,0

Sen

sitiv

ity

0,0

0,2

0,4

0,6

0,8

1,0

AUC = 0,87; P=0,002

Mult.log.regression

Sens.: 79% (95%CI: 58-85) Spec.: 91% (95%CI: 65-100) Acc.: 84% (95%CI: 61-92) PPV: 92% (95%CI: 68-100) NPV: 77% (95%CI: 55-84)

relative risk: 4.0 (P=0.002; 95%CI: 1.5-10.9)

FMC COV dualtracer SUVmax ADC avg.

Multiparametric Tumor Characterization Gleason 3 (n=14) vs. Gleason 4 (n=16)

Hartenbach, Hacker, Kenner, Shariat, et al.; unpublished data


PET/MRI Characterization of PC PSMA dynamics



Sens.: 100% (95%CI: 61-100) Spec.: 70% (95%CI: 46-70) Acc.: 81% (95%CI: 52-81) PPV: 67% (95%CI: 40-67) NPV: 100% (95%CI: 66-100)

AUC: 0.80 (P=0.050; n=16)

Jan Pencik, Lukas Kenner et al., Nat Communications 2015

PET/MRI Characterization of PC STAT3 and/or p14 loss




Garraway JCO 2013


Comprehensive Cancer Center MUW Target Therapy

Abl Imatinib, Nilotinib EGER Mutation Exon 18-21 inkl. T790M Afatinib EDFR Mutation Exon 18-21 Everolimus, Gefitinib ALK rearrangement Crizotinib Androgenrezeptor Enzelutamide, Arbiraterone CD20 Rituximab Bcr-Abl Imatinib, Nilotinib BRAF Regorafenib, Vemurafenib BRAF V600E/K Dabrafenib, Vemurafenib cKIT Axitinib, lmatinib, Nilotinib, Pazobanib, Regorafenib, Sunitinib CSF Sunitinib EGFR Cetuximab, Vandetanib (Caprelsa) EGFR-Expr. Cetuximab (RAS w.t.), Panitumumab, Regorafenib EGFR-RTK Erlotinib (2nM) FGFR1 Regorafenib FLT Sunitinib HER-2 Lapatinib, Trastuzumab, Trastuzumab-Emtansine HER-2 Positive Herceptin (Trastuzumab) CTL-4 Ipilimumab KIT Regorafenib MEK1 Trametinib MEK2 Trametinib MET amplification Crizotinib mTOR Afinitor Oestrogen/Progesterone-receptor Anastrozol, Letrozol, Exemestane, Fulvestrant, Goserelin, Tamoxifen; Everolimus PDGF Sunitinib PDGFR lmatinib, Nilotinib, Pazopanib, Sunitinib PDGFR-a/beta Pazopanib PDGFR-beta Axitinib, Regorafenib PIGF Aflibercept RAF Sorafenib RAF-1 Regorafenib RET Regorafenib, Sunitinib ROS1 Translocation Crizotinib T1e2 Regorafenib TK EGFR Erlotinib, Lapatinib V600E Regorafenib VEGF Bevacizumab, Bevacizumab + IFN, Sunitinib, Temsirolismus VEGF-A Aflibercept, Bevacizumab VEGF-B Aflibercept VEGFR Bevacizumab, Imatinib. Pazopanib VEGFR-1 Axitinib, Pazopanib, Regorafenib VEGFR-2 Axitinib, Pazopanib, Ramuzirumab, Regorafenib VEGFR-3 Axitinib, Pazopanib, Regorafenib VEGFR-TKI Everolimus


Outlook Target Targeted Imaging Techniques – Human Applications Therapy Abl [124]I-SKI230; [11C]-Imatinib Imatinib, Nilotinib EGER Mutation Exon 18-21 inkl. T790M Afatinib EDFR Mutation Exon 18-21 [11C]-gefitinib, [18F]-gefitinib Everolimus, Gefitinib ALK rearrangement Crizotinib Androgenrezeptor / PSMA expression [18F]-FDHT / [68Ga]-PSMA Enzelutamide, Arbiraterone CD20 [89Zr]-Rituximab Rituximab Bcr-Abl [124]I-SKI230; [11C]-Imatinib Imatinib, Nilotinib BRAF Regorafenib, Vemurafenib BRAF V600E/K Dabrafenib, Vemurafenib cKIT Axitinib, lmatinib, Nilotinib, Pazobanib, Regorafenib, Sunitinib CSF Sunitinib EGFR morpholino-[(124)I]IPQA; [89Zr]-Cetuximab; [11C]PD153035;

[18F]-ML04 Cetuximab, Vandetanib (Caprelsa)

EGFR-Expr. [89Zr]-panitumumab; [18F]-FBEM-Cys-Z(EGFR:1907) Cetuximab (RAS w.t.), Panitumumab, Regorafenib EGFR-RTK Erlotinib (2nM) FGFR1 Regorafenib FLT Sunitinib HER-2 [89Zr]-trastuzumab; [124I]-Z(HER2:4)

[64Cu]-trastuzumab Lapatinib, Trastuzumab, Trastuzumab-Emtansine

HER-2 Positive [89Zr]-trastuzumab Herceptin (Trastuzumab) CTL-4 Ipilimumab KIT Regorafenib MEK1 Trametinib MEK2 Trametinib MET amplification [89Zr]-DN30 Crizotinib mTOR [11C]GSK2126458; [18F]GSK2126458 Afinitor Oestrogen/Progesterone-receptor [18F]-tamoxifen; 16-[18F]-fluoro-17-estradiol Anastrozol, Letrozol, Exemestane, Fulvestrant, Goserelin, Tamoxifen; Everolimus PDGF Sunitinib PDGFR lmatinib, Nilotinib, Pazopanib, Sunitinib PDGFR-a/beta Pazopanib PDGFR-beta Axitinib, Regorafenib PIGF Aflibercept RAF Sorafenib RAF-1 Regorafenib RET Regorafenib, Sunitinib ROS1 Translocation Crizotinib T1e2 Regorafenib TK EGFR Erlotinib, Lapatinib V600E Regorafenib VEGF [124I]-VG76 Bevacizumab, Bevacizumab + IFN, Sunitinib, Temsirolismus VEGF-A [89Zr]-bevacizumab; [64Cu]-NOTA-bevacizumab Aflibercept, Bevacizumab VEGF-B Aflibercept VEGFR Bevacizumab, Imatinib. Pazopanib VEGFR-1 Axitinib, Pazopanib, Regorafenib VEGFR-2 Axitinib, Pazopanib, Ramuzirumab, Regorafenib VEGFR-3 Axitinib, Pazopanib, Regorafenib VEGFR-TKI Everolimus


Understanding Cancer: Evolution of Technologies

IHC/FISH

Expression Analysis

Mutation Analysis

Functional Imaging

Sample-based Techniques

Imaging Techniques

Tumor Characterisation, Microenvironment: Metabolism, Angiogenesis, Proliferation, Apoptosis, Hypoxia,…

Targeted Imaging Techniques


(Serial) In-vivo Tumor Characterization

18F-DOPA: DOPA-Decarboxylase

68Ga-DOTA-TATE: Somatostatin-Receptor

Tissue Characterization

NET Pancreas


Patient Selection, Therapy Guiding

Haug AR et al. J Nucl Med 2010, Haug AR et al. J Nucl Med 2011

68Ga-DOTA-TATE

177Lu-DOTA-TATE effective?

• n=33 with well differentiated NET • mean follow-up 22 months • monitoring after 1. Cycle of PRRT


Estrogen Receptor – Breast CA

16α-[18F]-fluoro-17β-estradiol (FES-PET)

High NPV for anti-estrogen therapy

Gemignani et al. JNM 2013; Peterson et al. Mol Imag Biol 2013; Linden et al. JCO 2006


Estrogen-Receptor PET in Breast CA

Van Kruchten et al, Lancet Oncol 2013

Meta analysis from 4 studies

138 Patients, endocrine therapy with

• 76 Aromatase-Inhibitor

• 45 Tamoxifen

• 17 Fulvestrant


HER2neu Recepor – Breast CA

64Cu-DOTA-Trastuzumab

89Zr-Trastuzumab

Mortimer et al. JNM 2014 Gaykema et al. Clin Cancer Res 2014


EGF Receptor - NSCLC

11C-PD153035 High affinity for EGFR

NSCLC therapy Erlotinib

Liu et al. JNM 2009; Meng et al. JNM 2011


Imaging in Personalized Medicine Summary

PET has high potential to link target identification with treatment and, thus, to personalize treatment

High potential for in-vivo Tissue Characterization to improve Biosy guiding, Response prediction and therapy monitoring

Work to do Increase Imaging Read-out Improve Quantification Increase avaibility of radiopharmaceuticals

Documents

Imaging in Personalized Medicine M. Hacker · Medizinische Universität Wien Univ.-Prof. Dr. med . M. Hacker Imaging in Personalized Medicine Summary PET has high potential to link