Molecular scoring of circulating tumor cells

Transcription

1 Molecular scoring of circulating tumor cells Daniel Haber MD PhD Massachusetts General Hospital Cancer Center Harvard Medical School Howard Hughes Medical Institute

2 Disclosures Scientific Advisory Boards Janssen Co-Founder Torpedo Diagnostics

3 Liquid Biopsies: Complementary technologies Haber and Velculescu, Cancer Discovery

4 Liquid Biopsies: Complementary technologies Haber and Velculescu, Cancer Discovery

5 Presentation Outline 1. Automated RNA-digital scoring of CTCs 2. Proof of Concept Clinical Applications - Hepatocellular cancer: - Early detection in background of liver cirrhosis - Breast cancer: - Monitoring ER signaling with hormonal therapies - Prostate cancer: - Predicting response to AR targeting - Melanoma: - Monitoring response to checkpoint immunotherapies

6 CTC-iChip Microfluidic depletion of hematopoietic cells untagged CTCs Anti-WBC magnetic beads RBCs, platelets Whole blood Hydrodynamic Cell Sorting Inlet exit Mehmet Toner Ozkumur, Shah et al., Sci Transl Med, 2013

7 CTC-iChip Microfluidic depletion of hematopoietic cells untagged CTCs Anti-WBC magnetic beads RBCs, platelets Whole blood Hydrodynamic Cell Sorting Inertial Focusing Inlet exit Mehmet Toner Ozkumur, Shah et al., Sci Transl Med, 2013

8 CTC-iChip Microfluidic depletion of hematopoietic cells untagged CTCs Anti-WBC magnetic beads RBCs, platelets B Whole blood Hydrodynamic Cell Sorting Inertial Focusing Inlet Magnetophoresis exit Mehmet Toner Ozkumur, Shah et al., Sci Transl Med, 2013

9 CTC-iChip Microfluidic depletion of hematopoietic cells untagged CTCs Anti-WBC magnetic beads RBCs, platelets B CTCs Whole blood Deflected WBCs Hydrodynamic Cell Sorting Inertial Focusing Magnetophoresis WBCs Inlet exit Mehmet Toner Ozkumur, Shah et al., Sci Transl Med, 2013

10 CTC-iChip 12 Blood Hydrodynamic Cell Sorting Inertial Focusing Product Magnetopheresis TorpedoDx

11 Automated sample processing Rate: 10ml blood/hr Volume: up to 30 ml TorpedoDx

12 Clinical applications of CTC detection early detection Complex CTC scoring methods are major hurdles to clinical applications of CTC measurements. CTC-iChip (automated) Fluorescence microscopy -- antibody-dependent -- signal thresholding -- manual scoring

13 Single cell RNA seq of patient-derived CTCs Negative depletion of leukocytes preserves intact RNA within unmanipulated CTCs David Miyamoto

14 Clinical applications of CTC detection Developing a molecular signature of CTCs using RNA-digital PCR 1. Automated and high throughput

15 Clinical applications of CTC detection Developing a molecular signature of CTCs using RNA-digital PCR Liver cell transcripts 1. Automated and high throughput 2. Specific RNA lineage in blood cell background

16 Clinical applications of CTC detection Developing a molecular signature of CTCs using RNA-digital PCR Liver cell transcripts 1. Automated and high throughput 2. Specific RNA lineage in blood cell background 3. Sensitive molecular amplification

17 Clinical applications of CTC detection Developing a molecular signature of CTCs using RNA-digital PCR Liver cell transcripts 1. Automated and high throughput 2. Specific RNA lineage in blood cell background 3. Sensitive molecular amplification 4. Preserved marker distribution

18 Presentation Outline 1. Automated RNA-digital scoring of CTCs 2. Proof of Concept Clinical Applications - Hepatocellular cancer: - Early detection in background of liver cirrhosis Mark Kalinich Irun Bhan

19 Proof HCC Occurs of concept: in defined Hepatocellular At-Risk Populations cancer At-risk populations to focus surveillance efforts 80-90% HCC occurs in cirrhosis HCC develops in 0.5 to 8%/year, depending on risk 200M individuals at high risk from chronic hepatitis B

20 Hepatocellular Proof of concept: carcinoma: Hepatocellular Digital CTC cancer detection CTC-Scores Across Cohorts ROC Curve (Untreated HCC) No Cross-Validation Log10(CTC-Score+1) *** ** TPR AUC = 0.88 p < ROC Curve (Untreated HCC) Leave-one-out-cross-validation Healthy age-matched donors N= 26 HD Liver disease (cirrhosis) N= 31 CLD HCC HCC Untreat. Treat. HCC NED Hepatocellular cancer Untreated N= 16 Under treatment N=32 Resected (NED) N=15 TPR AUC = 0.80 p = FPR Kalinich, Bhan et al., PNAS 2017

21 Proof of concept: Hepatocellular cancer Hepatocellular Carcinoma: Digital CTC Detection CTC-Scores Across Cohorts ROC Curve (Untreated HCC) No Cross-Validation Log10(CTC-Score+1) *** ** TPR AUC = 0.88 p < ROC Curve (Untreated HCC) Leave-one-out-cross-validation Healthy age-matched donors N= 26 HD Liver disease (cirrhosis) N= 31 CLD HCC HCC Untreat. Treat. HCC NED Hepatocellular cancer Untreated N= 16 Under treatment N=32 Resected (NED) N=15 TPR AUC = 0.80 p = FPR Kalinich, Bhan et al., PNAS

22 Hepatocellular carcinoma: Monitoring response Concordant with serum AFP Informative when serum AFP is negative Progression Surgical resection Surgical resection & recurrence Immune Rx then embolization Kalinich, Bhan et al., PNAS 2017

23 CTC-Score + AFP for early detection of liver cancer Untreated HCC Patients Serum AFP [ng/ul] CTC-Score AFP+ CTC: 5 CTC only: 4 AFP only: 1 Combined: 10/15 of newly diagnosed HCC CTC-Score AFP >100 ng/ml Imaging Kalinich, Bhan et al., PNAS 2017

24 Presentation Outline 1. Automated RNA-digital scoring of CTCs 2. Proof of Concept Clinical Applications - Hepatocellular cancer: - Early detection in background of liver cirrhosis - Breast cancer: - Monitoring ER signaling with hormonal therapies Tanya Kwan Aditya Bardia

25 Proof of concept: ER+ Breast cancer 2 nd Line Treatment of ER+ Metastatic Breast Cancer Endocrine Therapy: Aromatase Inhibitor Fulvestrant Tamoxifen AI+Everolimus Chemotherapy: Capecitabine Eribulin Navelbine Doxil??? Targeted Therapy: - CDK 4/6 Inhibitor - PI3K Inhibitor

26 Proof of concept: ER+ Breast cancer Treatment of ER+ Metastatic Breast Cancer Endocrine Therapy: Aromatase Inhibitor Fulvestrant Tamoxifen AI+Everolimus Chemotherapy: Capecitabine Eribulin Navelbine Doxil??? Targeted Therapy: - CDK 4/6 Inhibitor - PI3K Inhibitor Metastatic Breast Cancer vsbiopsy Negative Controls N=42 Blood Cell Expression Breast Tissue Expression

27 HCC ER+ Occurs breast in cancer: defined 2 nd At-Risk line therapy Populations prospective cohort N=88 low CTC-Score high CTC-Score Pretreatment CTC-Score Kwan and Bardia et al., Cancer Discovery 2018

28 HCC ER+ Occurs breast in cancer: defined 2 nd At-Risk line therapy Populations prospective cohort N=88 low CTC-Score high CTC-Score Pretreatment CTC-Score N=62 low baseline, further drop on treatment low baseline, no change high baseline, drop on treatment high baseline, persistent On-treatment CTC-Score (3-4 weeks) Kwan and Bardia et al., Cancer Discovery 2018

29 ER+ breast cancer: Measuring on-treatment signaling HCC Occurs in defined At-Risk Populations Persistent estrogen signaling within CTCs in non-responders to hormonal therapy 3-4 weeks on-treatment. Kwan and Bardia et al., Cancer Discovery 2018 Resistance Signature (RS) correlates with persistent ER signaling in tamoxifen-resistant breast cancer cells

30 ER+ breast cancer: Measuring on-treatment signaling HCC Occurs in defined At-Risk Populations Failure of drug treatment to suppress CTC-RNA Resistance Signature (3-4 weeks) predicts shorter time to progression (TTP) N=25 Absent ER signaling within CTCs Persistent ER signaling within CTCs Kwan and Bardia et al., Cancer Discovery 2018

31 ER+ breast cancer: Measuring on-treatment signaling HCC Occurs in defined At-Risk Populations Comparing ER signaling with ESR1 mutations N=36 Wild-type ESR1 within CTCs or tumor Mutant ESR1 within CTCs or tumor Partial RS/ESR1 overlap: not all persistent ER signaling is due to ESR1 mutation ESR1 mutation + (N=5) CTC-RNA Resistance Score (RS+) (N=13) Kwan and Bardia et al., Cancer Discovery 2018

32 HCC Early Occurs breast in cancer: defined Neoadjuvant At-Risk Populations treatment Prospective trial of CTC-Score in predicting residual disease after neoadjuvant therapy N=37 Kwan and Bardia et al., Cancer Discovery 2018 with Mark Kalinich

33 Presentation Outline 1. Automated RNA-digital scoring of CTCs 2. Proof of Concept Clinical Applications - Hepatocellular cancer: - Early detection in background of liver cirrhosis - Breast cancer: - Monitoring ER signaling with hormonal therapies - Prostate cancer: - Predicting response to AR targeting David Miyamoto Rick Lee

34 Prostate Cancer Proof of concept: Prostate cancer Localized Cancer Metastatic Cancer Diagnosis PSA Biopsy Localized Surgery Radiation Active surveillance Recurrence Metastatic Castrate-Sensitive Androgen deprivation Metastatic Castrate-Resistant Abiraterone Enzalutamide Cabazitaxel Docetaxel Radium-223 Sipuleucel-T Miyamoto, Lee et al., Cancer Discovery 2018

35 Predicting outcome of anti-androgen therapy: metastatic prostate cancer Prospective clinical trial of first-line abiraterone in mcrpc. N=27 Progression-Free Survival Overall Survival Low Baseline CTC-Score High Baseline CTC-Score Baseline CTC-Score Miyamoto, Lee et al., Cancer Discovery 2018

36 Predicting outcome of anti-androgen therapy: metastatic prostate cancer Prospective clinical trial of first-line abiraterone in mcrpc. N=27 Low Baseline CTC-HoxB13 High Baseline CTC-HoxB13 Baseline CTC-RNA: HOXB13 Miyamoto, Lee et al., Cancer Discovery 2018

37 Predicting outcome of anti-androgen therapy: metastatic prostate cancer Prospective clinical trial of first-line abiraterone in mcrpc. N=27 Baseline CTC-RNA: HOXB13 Baseline CTC-RNA: AR-V7 Miyamoto, Lee et al., Cancer Discovery 2018

38 Predicting outcome of anti-androgen therapy: metastatic prostate cancer Prospective clinical trial of first-line abiraterone in mcrpc. Combining CTC Markers: Men with early death on first line abiraterone: 6/22 (27%) 6/6 HOXB13 + PPV: 54% NPV: 100% 2/6 ARV7 + PPV: 100% NPV: 80% Miyamoto, Lee et al., Cancer Discovery 2018

39 Localized HCC Occurs prostate in cancer: defined Predicting At-Risk invasion Populations Men with localized prostate cancer treated with prostatectomy N=34 SVI or LN + SVI and LN - CTC Score: 3/6 men with positive pelvic lymph nodes and/or seminal vesicle invasion CTC Score: 100% PPV 90% NPV D Amico Score: 33% PPV 88% NPV

40 Presentation Outline 1. Automated RNA-digital scoring of CTCs 2. Proof of Concept Clinical Applications - Hepatocellular cancer: - Early detection in background of liver cirrhosis - Breast cancer: - Monitoring ER signaling with hormonal therapies - Prostate cancer: - Predicting response to AR targeting - Melanoma: Xin Hong Ryan Sullivan - Monitoring response to checkpoint immunotherapies

41 HCC Occurs in defined At-Risk Populations Proof of concept: Melanoma Highly heterogeneous expression of lineage markers Neural crest lineage, Carcino-testis antigen, Cancer-related transcripts (19 markers) --all absent in blood cells Hong, Sullivan et al., Cancer Discovery 2018

42 HCC Occurs in defined At-Risk Populations Proof of concept: Melanoma Highly heterogeneous expression of lineage markers Assay sensitivity with spiking controls and positive scores in patients before and after treatment Hong, Sullivan et al., Cancer Discovery 2018

43 HCC Occurs in defined At-Risk Populations Proof of concept: Melanoma Highly heterogeneous expression of lineage markers Performance of 19 markers and of lineage, cancer testis antigen, cancer related subsets in metastatic melanoma. Hong, Sullivan et al., Cancer Discovery 2018

44 Melanoma: Tracking response to therapy B-RAF V600E + B-RAF V600E - CTC-Score monitors response and progression on B-RAF targeted therapies and chemotherapy Hong, Sullivan et al., Cancer Discovery 2018

45 Melanoma: Tracking response to therapy B-RAF V600E + B-RAF V600E - CTC-Score monitors response and progression on Pembrolizumab And Ipilumimab checkpoint therapies Hong, Sullivan et al., Cancer Discovery 2018

46 Melanoma: Early prediction of response Prospective clinical trial of single agent immune checkpoint inhibitor N=49 Pretreatment CTC score does not predict response to checkpoint inhibitors Hong, Sullivan et al., Cancer Discovery 2018

47 Melanoma: Early prediction of response Prospective clinical trial of single agent immune checkpoint inhibitor N=49 Change in CTC score at 7 weeks on-treatment is highly predictive of PFS and Overall Survival Hong, Sullivan et al., Cancer Discovery 2018

48 Clinical Applications and Unique Opportunities A. Screening for liver cancer (Hepatocellular Carcinoma, HCC) in high risk individuals with liver cirrhosis/hepatitis. B. Monitoring early response in women with breast cancer treated with second/third line hormonal therapy. C. Identifying men with metastatic prostate cancer who are unlikely to have sustained response to hormonal therapy. D. Monitoring early response in patients with melanoma receiving checkpoint immunotherapy. 48

49 The MGH Team: Convergence Science Molecular Shyamala Maheswaran Risa Burr Val Comaills Christina Constantino Taronish Dubash Richard Ebright Hongshan Guo Xin Hong Elad Horwitz Mark Kalinich Laura Libby Satoru Matsuda Doug Micalizzi Stefanie Morgan (Tanya Kwan) (Yu Zheng) David Ting Irun Bhan David Miyamoto Bio-engineering Mehmet Toner Ravi Kapur Rebecca Sandlin Shannon Stott John Edd Linda Nieman John Walsh Computational Ben Wittner Mike Lawrence Sridhar Ramaswamy Clinical Lecia Sequist Aditya Bardia Ray Chung Rick Lee Ryan Sullivan Andrew Zhu Pathology Dennis Sgroi Chin Lee Wu