ECOG-ACRIN Studies with Novel PET/CT Imaging David Mankoff Division of Nuclear Medicine Department of Radiology University of Pennsylvania

Molecular Imaging to Guide Therapy: Outline Guiding themes for novel PET/CT trials Highlight of completed, active, and develpng trials Tools for trials with novel PET/CT imaging

Anatomic versus Functional Imaging Anatomic Imaging Relies on tumor size, shape, density e.g., mammography, CT Measures response by changes in size Functional/molecular imaging Relies on in vivo tumor biology: perfusion, metabolism, molecular features e.g., MRI, PET Measures response by changes in functional/molecular processes

Imaging Modalities Used for Cancer Anatomic Computed Tomography (CT) Ultrasound Magnetic Resonance Imaging (MRI) Optical Imaging Magnetic Resonance Spectroscopy (MRS) Radionuclide imaging Positron Emission Tomography (PET) Single-Photon Emission Computed Tomography (SPECT) Functional and Molecular

PET/CT Combines Molecular and Anatomical Imaging (Alessio, Rad Clin N Amer, 2005)

Imaging and Cancer Therapy Novel Approaches to Biomarker Imaging Choosing the right patients Is the therapeutic target present? Choosing the right drug Does the drug reach the target? Getting the right result Is there a pharmacodynamic response? Predicting the outcome Will response lead to better patient survival?

ACRIN Experimental Imaging Sciences Committee (EISC)

ECOG-ACRIN EISC Trials active or completed: ACRIN 6682 - 64Cu-ATSM PET and cervical hypoxia ACRIN 6684 - 18F-FMISO PET and brain tumor hypoxia ACRIN 6687 - 18F- PET and prostate bone metastasis response ACRIN 6688 - 18F-FLT and breast cancer response ACRIN 6691 – Optical imaging of breast cancer response ACRIN 6701 - DCE-MRI test/re-test in prostate cancer opening: EAI141 – FLT PET/CT to measure AML response EAI142 – FES PET/CT to predict breast cancer response

Hypoxia as An Imaging Biomarker for Cancer: ACRIN 6682 and 6684 Why hypoxia? Promotes an aggressive phenotype –with accelerated angiogenesis and glucose metabolism, and enhanced survival An established resistance factor for radiotherapy An emerging target for systemic therapy Two tracers tested 18F-fluoromisonidazole – best tested and vlaidated 60Cu-ATSM – alternative approach; does not require cyclotron

Time-to-Locoregional Failure Imaging to Direct Hypoxia-Specific Treatment Rischin J Clin Oncol 24:298, 2006 Advanced H & N Ca Randomized to XRT + Cisplatin/5-FU XRT + Cisplatin/Tirapazamine (TPZ) FMISO PET (observational only) Time-to-Locoregional Failure FMISO+/TPZ FDG PET FMISO+/5FU FMISO PET

ACRIN 6682 Phase II Trial of 64Cu-ATSM PET/CT in Cervical Cancer Principal Investigator: Farrokh Dehdashti, MD 12 22 Sep 2011

Background Tumor hypoxia is an important prognostic factor in cervical cancer and predicts for decreased overall and disease-free survival Hypoxic-measuring tools are needed: To predict patient outcome To select hypoxia-specific interventions on an individual basis To evaluate response to hypoxia-specific interventions 13 22 Sep 2011

Measurement of Hypoxia with 60Cu- and 64Cu-ATSM-PET CT FDG-PET 60Cu-ATSM-PET 64Cu-ATSM-PET 15 22 Sep 2011

ACRIN 6682 Schema N=100, enrollment period=18 months Pre-therapy clinical whole-body FDG-PET/CT Stages IB2 –IVA invasive squamous cell carcinoma, scheduled to undergo radiation therapy and concurrent cisplatin chemotherapy Pre-therapy pelvic 64Cu-ATSM-PET/CT and analysis of tumor biopsy for hypoxic markers Concurrent chemoradiotherapy Clinical FDG-PET/CT three (3) months after completion of therapy Clinical follow-up for detection of recurrence and/or death N=100, enrollment period=18 months 16 22 Sep 2011

University of Washington KA Krohn

University of Washington FMISO PET Predicts outcome for GBM Patients Spence, Clin Cancer Res 14:2623, 2008 MRI FMISO PET (FMISO not hot) (FMISO hot) Hypoxic Not Hypoxic University of Washington

Multi-Center Trial of FMISO PET and MRI in Glioblastoma – ACRIN 6684 Single-Center Results Multi-Center Results FMISO PET MRI (Spence, Clin Cancer Res 14:2623, 2008)

ECOG-ACRIN EISC Trials active or completed: ACRIN 6682 - 64Cu-ATSM PET and cervical hypoxia ACRIN 6684 - 18F-FMISO PET and brain tumor hypoxia ACRIN 6687 - 18F- PET and prostate bone metastasis response ACRIN 6688 - 18F-FLT and breast cancer response ACRIN 6691 – Optical imaging of breast cancer response ACRIN 6701 - DCE-MRI test/re-test in prostate cancer opening: EAI141 – FLT PET/CT to measure AML response EAI142 – FES PET/CT to predict breast cancer response

2013 ASCO Annual Meeting – Oral Abstract Session: Genitourinary (Prostate) Cancer – Abstract 5003 18F-fluoride PET response to dasatinib in castration-resistant prostate cancer bone metastases correlates with progression-free survival: Preliminary results from ACRIN 6687 Evan Y. Yu, Fenghai Duan, Mark Muzi, Jeremy Gorelick, Bennett B. Chin, Joshi J. Alumkal, Mary-Ellen Taplin, Ben Herman, Celestia S. Higano, Robert K. Doot, Donna Hartfeil, Philip G. Febbo, David A. Mankoff Thank scientific committee on behalf of ACRIN, DOD PCCTC and all coauthors.

Fluoride PET/CT & Bone Metastasis Emission Image Emission, CT, and Fused

Genomic guided therapy with 18F-Fluoride PET imaging as a pharmacodynamic biomarker ACRIN 6687 and DOD PCCTC collaboration AR Activity Progress ion Progress ion Add Dasatinib 100 mg PO QD Nilutamide 150 mg PO QD Metastatic, Castration Resistant Prostate Cancer Evidence of disease progression Disease Amenable to Biopsy Biopsy ≥ 0.50 AR microarray signature determined from multiple AR expressing cell lines then validated with human samples with known AR hormone status, either hormone naïve or treated with neoadjuvant ADT. For all groups treated with ADT, heterogeneity of AR activity exists with 1/3 with persistant AR activity. Additionally in CRPC, about 1/3 still has significant AR. Then compared to 6 major published oncogenic signatures RAS, E2F, SRC, MYC, PI3K, and beta-catenin to see if loss of AR activity correlates with any of these. SRC had the strongest correlation with loss of AR signature. Additionally, those cells with greater inverse AR correlation have greater sensitivity to dasatinib. In this study through ACRIN and the DOD clinical trials consortium, we used 18F-fluoride PET in patients undergoing treatment with dasatinib to better understand the affect of the drug on both bone metabolism. < 0.50 Add Nilutamide 150 mg PO QD Dasatinib 100 mg PO QD 18F-Fluoride PET 18F-Fluoride PET 23

Univariate analysis with PCWG2 PFS Predictor Baseline or Δ response to dasatinib HR/OR (95% CI) P-Value Gleason* Baseline 1.121 (0.667-1.885) 0.6655 PSA Δ 1.002 (1.000-1.005) 1.001 (0.999-1.002) 0.0330 0.5242 UNTX 1.007 (1.001-1.013) 0.999 (0.980-1.019) 0.0278 0.9369 BAP 1.004 (0.999-1.008) 1.011 (0.994-1.028) 0.0918 0.2184 SUVmax 1.006 (0.969-1.045) 0.905 (0.816-1.002) 0.7442 0.0558 Flux (Ki) 46.790 (0.120-18,245.43) <0.001 (<0.001-0.761) 0.2064 0.0472 Transport (K1) 1.396 (0.091-21.416) 0.068 (<0.001-2,192.577) 0.8107 0.6116 However, we received some surprises in the univariate analysis for PFS. We chose to perform this analysis since all patients have reached PFS and the majority did not have a SRE or die. The sample size was very small. Under this circumstance, the outcome with more events are definitely much more reliable regarding their analyses. The univariate analysis points us towards possible relationships between baseline PSA, baseline UNTX, baseline BAP, as well as change in SUV and change in Ki to have relationship with PCWG2 PFS, which did allow clinical progression as well as radiographic progression. Note that for the change in PET parameters, the findings are surprising and contradictory to what we initially said in our published abstract. Rather than greater decrease in uptake by SUV or Ki of fluoride in tumor bone correlating with longer PFS, this actually demonstrates that greater decrease correlates with shorter PFS. That means patients with less decrease or even increase in uptake in bone had better outcomes. Again, my apologies, as this was erroneously stated in the abstract and the relationship is exactly opposite. This seems surprising, but we have to recall that dasatinib inhibits osteoclasts and might our measures be a supersensitive way of measuring a healing flare response in patients that might confer a better prognosis? *Focus of this abstract is PFS, but Gleason had statistically significant correlation with time to SRE and OS

ECOG-ACRIN EISC Trials active or completed: ACRIN 6682 - 64Cu-ATSM PET and cervical hypoxia ACRIN 6684 - 18F-FMISO PET and brain tumor hypoxia ACRIN 6687 - 18F- PET and prostate bone metastasis response ACRIN 6688 - 18F-FLT and breast cancer response ACRIN 6691 – Optical imaging of breast cancer response ACRIN 6701 - DCE-MRI test/re-test in prostate cancer opening: EAI141 – FLT PET/CT to measure AML response EAI142 – FES PET/CT to predict breast cancer response

Cellular Proliferation Biologic Events in Response to Successful Cancer Therapy Rationale for Measuring Early Response by Cell Proliferation Imaging Rx DNA Synthesis Cellular Proliferation or Cell Death Viable Cell Number Tumor size

ACRIN 6688: Phase II Study of FLT-PET in Invasive Breast Cancer PI: Lale Kostakoglu, MD May, 2014 ECOG-ACRIN Group Meeting, Chicago, IL

ACRIN 6688 Study Outline * 18FLT PET/CT (FLT-1) (FLT-2) (FLT-3) Obtain pre-treatment proliferative Indices Establish Eligibility Baseline Imaging Post-therapy Imaging Surgical Resection Chemotherapy cycle 1 Baseline organ function Pathologically confirmed disease Determine primary systemic Rx Ki-67, mitotic index on bx sample or re-biopsy (if available) 18FLT PET/CT (FLT-1) (FLT-3) (FLT-2) Obtain post-treatment proliferative Indices Pathologic response, Ki-67, mitotic index, surg. specimens Early therapy Imaging Chemotherapy last cycle ACRIN 6688 Study Outline *

ACRIN 6688: FLT PET to Measure Early Breast Cancer Response (PI: Lale Kostakoglu) Pre-Therapy 7 d Post- Best ΔSUVmax cut-off for predicting pCR = -51% (sensitivity 56%;specificity 79%). (Kostakoglu, J Nucl Med, 2015)

ECOG-ACRIN EISC Trials active or completed: ACRIN 6682 - 64Cu-ATSM PET and cervical hypoxia ACRIN 6684 - 18F-FMISO PET and brain tumor hypoxia ACRIN 6687 - 18F- PET and prostate bone metastasis response ACRIN 6688 - 18F-FLT and breast cancer response ACRIN 6691 – Optical imaging of breast cancer response ACRIN 6701 - DCE-MRI test/re-test in prostate cancer opening: EAI141 – FLT PET/CT to measure AML response EAI142 – FES PET/CT to predict breast cancer response

EAI141: EARLY ASSESSMENT OF TREATMENT RESPONSE IN AML USING [18F]FLT PET/CT IMAGING Robert Jeraj, Ryan Mattison, Lale Kostakoglu, Elisabeth Paietta, David Mankoff (EISC), Mark Litzov (Leukemia), Fenghai Duan (Statistics) rjeraj@wisc.edu

FLT PET as a response biomarker Pre-therapy Post-therapy (2 wks) CLINICAL OUTCOME (6 mo) Complete remission Chemo FLT PET 10 5 SUV Resistant disease Chemo Vanderhoek et al 2011, Leuk Res 35: 310

High NPV of FLT PET for predicting CR 10 5 SUV Complete Remission Day 2 Day 4 Day 5 Day 6 Post   SUVmean SUVmax Coefficient of Variation Complete Remission 0.81 ± 0.03 3.6 ± 0.4 0.33 ± 0.02 Resistant Disease 1.6 ± 0.1 11.4 ± 0.8 0.71 ± 0.04 Trends were consistent regardless of the time of assessment. Measurement of treatment response was not significantly affected by the time of assessment. Resistant Disease t-test: p<0.001 for SUVmean, SUVmax, CV Day 2 Post Vanderhoek et al 2011, Leuk Res 35: 310

EAI141 clinical trial

ECOG-ACRIN EISC Trials active or completed: ACRIN 6682 - 64Cu-ATSM PET and cervical hypoxia ACRIN 6684 - 18F-FMISO PET and brain tumor hypoxia ACRIN 6687 - 18F- PET and prostate bone metastasis response ACRIN 6688 - 18F-FLT and breast cancer response ACRIN 6691 – Optical imaging of breast cancer response ACRIN 6701 - DCE-MRI test/re-test in prostate cancer opening: EAI141 – FLT PET/CT to measure AML response EAI142 – FES PET/CT to predict breast cancer response

Endocrine Therapy Response Rate: Targeted Breast Cancer Therapy: The Estrogen Receptor (ER) and Endocrine Treatment Endocrine Therapy Response Rate: ER - < 5% ER + 50% - 75% (Johnson and Dowsett, Nar Rev Cancer 3:821, 2002)

[F-18]-Fluoroestradiol (FES): PET Estrogen Receptor (ER) Imaging * Relative Binding (FES vs Estradiol) ER 0.9 SHBG 0.2 - 0.8 (Kieswetter, J Nucl Med, 1984)

Validation: ER+ vs ER- Tumors FDG FES coronal axial ER- Liver ER+ Glucose Metabolism ER Expression

FES Uptake Predicts Breast Cancer Response to Hormonal Therapy Pre-Rx Post-Rx Example 1 Recurrent sternal lesion ER+ primary Recurrent Dz strongly FES+ Excellent response after 6 wks Letrozole FES Example 2 FDG FDG Newly Dx’d met breast CA ER+ primary FES-negative bone mets No response to several different hormonal Rx’s University of Washington (Linden, J Clin Onc, 2006)

ECOG-ACRIN Biomarker Trial of FES PET: EAI142 Dehdashti & Linden FES PET Primary Aim FDG PET MBC from ER+ Primary Endocrine Therapy Response PFS 3, 6 month assessment Validation Aim Biopsy First line therapy Stand-alone imaging trial: Clinical indication for endocrine therapy Standard Rx allowed (AI, FUL, TAM) Allow measurable and non-measurable disease Group Meeting • Nov 14-16, 2013

Clinical Trials and Novel Imaging: How are Novel PET Probes Supplied and Tested? Compound Development and Regulatory Authority NCI Cancer Imaging Program, public domain INDs for Fluoride, FLT, FMISO, FES Industry compounds – hold IP and IND Academic centers – Physician held INDs Probe supply Commercial regional cyclotron suppliers Academic Centers Support for multi-center clinical trials NCI – Phase I/II program NCI Clinical Trials Networks – e.g., SNM Clinical Trials Network

NCI Quantitative Imaging Network (QIN) Develop quantitative imaging (QI) methods that are automated, platform independent and reproducible to use in therapy trials Share, test, refine, validate, and finally evaluate these methods in therapy trials using four working groups organized across all sites 1 Image Data Collection & Variance Studies 3. Informatics & Data Sharing TCIA 2: Data Analysis & Software Tool Validation 4. Clinical Trial Design & Development QIN Tools Annotated image databases with metadata & outcomes Goal: Consensus on data collection /analysis & Technical resource for clinical trials Link to a Clinical Trial Tool Validation Development (courtesy of Larry Clarke)

Thank you!