Moving cells on chips, microfluidics, and clinical medicine. Practical Gap in Biomedical Innovation:

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Kathryn Thompson
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Massachusetts General Hospital Harvard Medical School

Moving cells on chips, microfluidics, and clinical

17th, 2009 Practical Gap in Biomedical Innovation: Basic

1 Massachusetts General Hospital Harvard Medical School Harvard-MIT Division of Health Sciences and Technology Moving cells on chips, microfluidics, and clinical medicine Mehmet Toner PhD Daniel Irimia MD PhD UIUC June 17th, 2009 Practical Gap in Biomedical Innovation: Basic scientists have few incentives to move outside their comfort zone.

2 Bio-Medical Sciences & Technology Expertise in basic sciences, technology and clinical medicine Technology Biomedical Sciences Clinical Medicine Patients (end-users) physicians (practitioner)

3 DSC_0005 Mining Blood for Cellular Information CTC Team Group piture Daniel Haber Mehmet Toner Shyamala Maheswaran Sunitha Nagrath Lecia Sequist Daniel Irimia Shannon Stott Min Yu Matthew Smith Rick Lee Doug Dahl Chin Lee Wu Brian Nahed Tom Lynch David Ting Ronald Tompkins John Iafrate Ajay Shah Lyndsey Ulkus Brian Brannigan Ravi Kapur and Tom Barber Chey Collura Marshall Doughty Chia-hsien Hsu Octavio Hurtado Maria Kempner Ken Kotz Laura Libby Alessandra Moore Zev Nakamura Simeon Springer Dina Tsukrov Matthew Ullman Glenn Siegmann John Walsh Justin Wong

4 Metastatic Cancer 9 out of 10 cancer deaths are due to the metastasis

5 Why Study Circulating Tumor Cells? Metastatic Cancer: - Noninvasive sampling for genetic markers - Monitoring of drug responsiveness Localized Cancer: - Marker of vascular invasion - Early detection Biology of Metastasis - Properties of rare metastatic precursors - Novel drug targets and markers of response

6 Overall Process and CTC-chip Automated, single-step, gentle, uniform processing conditions 80,000 micro-posts coated with EpCAM-Ab Nagrath et al., Nature 2007

7 Processor for Blood Handling CTC-Chip Manifold for the CTC-Chip NAGRATH ET AL., NATURE 2007 Overall Process and CTC-chip Automated, single-step, gentle, uniform processing conditions

9 Enumeration of CTCs DAPI Cytokeratin CD45 Merge Leukocyte CTC NAGRATH ET AL., NATURE 2007 Patient Studies: CTC Capture Yield & Purity NAGRATH ET AL., NATURE 2007

(AKT activation through ErbB3) - Oncogene Addiction Clinical Response: - Rapid and profound tumor shrinkage - Median response < 1

10 Longitudinal Correlation of CTCs with Disease Course Epidemiology: Histology: Mutant EGFR: EGFR-mutant lung cancer - Nonsmokers - Women - Asian ethnicity - Adenocarcinoma/bronchoalveolar - Enhanced inhibition by TKIs (10-fold IC50) - Increased survival signals (AKT activation through ErbB3) - Oncogene Addiction Clinical Response: - Rapid and profound tumor shrinkage - Median response < 1 year - Acquired resistance: -- T90M-EGFR mutation -- MET gene amplification C lobe Iressa: before.after (4 weeks) Lynch et al, NEJM 2004

CTC Biopsy in Lung Cancer -- Detection of primary sensitizing EGFR mutation (del, L858R, others) -- Acquisition of secondary drug resistance (T790M-EGFR) del L747-P753insS del E746-A750 del L747-A750

11 CTC Biopsy in Lung Cancer -- Detection of primary sensitizing EGFR mutation (del, L858R, others) -- Acquisition of secondary drug resistance (T790M-EGFR) del L747-P753insS del E746-A750 del L747-A750 T790M N lobe L858R Inhibitor C lobe Lynch et al., NEJM 2004 Paez et al, Science 2004 Pao et al., PNAS 2005 Kobayashi, PNAS 2005 Serial monitoring of tumor genotypes during treatment and progression of cancer: CTC numbers, EGFR mutations, and radiographic tumor burdens MAHESWARAN ET AL., NEJM 2008

12 CD4 Microchip for Monitoring of HIV/AIDS Patients for Global Health Xuanhong Cheng, PhD Now, Lehigh University William Rodriguez, MD Rashid Bashir, PhD

13 After 9 months CD4 Count for Disease Monitoring and AIDS Treatment Decision HIV infection AIDS Risk of Death Intense monitor WHO guidelines for ART initiation

CD4 Microchip IMMUNO-AFFINITY ISOLATION N O O Anti-CD4

<10,000 CD4 7 µm 9 µm CONTROLLED FLOW FOR

14 CD4 Microchip IMMUNO-AFFINITY ISOLATION N O O Anti-CD4 Avidin O N O S (CH 2 ) 3 Si O O O CHALLENGE -- CD4+ T cells vs. CD4+ monocytes CD4+ T cells ~60,000 CD4 Monocytes <10,000 CD4 7 µm 9 µm CONTROLLED FLOW FOR DIFFERENTIATION LABEL-FREE CD4 COUNTING CHENG ET AL., LAB CHIP 2007; CHENG ET AL., LAB CHIP 2008; CHENG ET AL., J AIDS, 2008

15 CD4 Microchip: Clinical validation at Massachusetts General Hospital Non-optical CD4+ T-cell Counting

Investigators, 14 Institutions CALVANO ET

AL. PNAS 2005, 102(13), 4801-6 LAUDANSKI

16 Bill Rodriguez MGH A rugged, handheld, battery-operated CD4 cell counter with push-button operation with results in 8 minutes Systems Biology Approach to Burns and Trauma Biological Understanding NIH U54 GM Requires technologies that make translational studies feasible Collaborative Science Investigators, 14 Institutions CALVANO ET AL. NATURE 2005, 437(7061), COBB ET AL. PNAS 2005, 102(13), LAUDANSKI ET AL. PNAS 2006, 103(42), STOREY ET AL. PNAS 2005, 102(36),

Microfluidics for Granulocyte Isolation CD66b-Ab

PNAS 2005, 102(13), 4801-6 Laudanski et al.

17 Microfluidics for Granulocyte Isolation CD66b-Ab Single step from whole blood 15 minutes 30 ul/min Publications: Calvano et al. Nature 2005, 437(7061), Cobb et al. PNAS 2005, 102(13), Laudanski et al. PNAS 2006, 103(42), Storey et al. PNAS 2005, 102(36), Initial Clinical Use: Granulocyte Isolation

Fluorescent Staining CD66b-PE CD14-FITC DAPI Purity of

blood >94% purity Healthy volunteers; 13 severely burned

Inflammation Flow = 40µm/sec 25nM 10nM 0nM IL8 gradient

18 Fluorescent Staining CD66b-PE CD14-FITC DAPI Purity of Granulocytes Giemsa Staining ~400K cells from 150 µl whole blood >94% purity Healthy volunteers; 13 severely burned patients 20 µm Neutrophils and the Resolution of Inflammation Flow = 40µm/sec 25nM 10nM 0nM IL8 gradient always present RVD1 only btw 4 &17 min 200 µm Kasuga et al, J Immunol, 2009

02 (n=12) Ex-vivo Stimulation: Genomics LPS: lipopolysaccharide GM+I: GM-CSF and INF-γ Flow Cytometry Validation

19 Microfluidic Device Clinical Performance Six different clinical sites Burn (red) and trauma (blue) 1000 cassettes >20 ng RNA in 99% of samples RNA quality of 7.4 to 9.9 Correlation of gene expression between samples: 0.98±0.02 (n=12) Ex-vivo Stimulation: Genomics LPS: lipopolysaccharide GM+I: GM-CSF and INF-γ Flow Cytometry Validation Chip-to-chip correlations 98% >1500 Clinical samples processed Several genes validated with flow Good agreement with similar ex vivo stimulation studies

Ex-vivo Stimulation: Proteomics LPS: lipopolysaccharide GM+I:

digested protein/sample Protein distribution microfluidic vs.

Nucleus Membrane Unknown 8% Integrated Microfluidic Device:

Lymphocyte Capture Region Monocyte Capture Region Neutrophil

20 Ex-vivo Stimulation: Proteomics LPS: lipopolysaccharide GM+I: GM-CSF and INF-γ Chip-to-chip correlations 93% > 10 µg total digested protein/sample Protein distribution microfluidic vs. bulk 13% 6% 12% 6% 21% 50% 17% 57% 10% Cytoplasm Extracellular Nucleus Membrane Unknown 8% Integrated Microfluidic Device: One-step Isolation of Neutrophils, Lymphocytes, Monocytes Lymphocyte Capture Region Monocyte Capture Region Neutrophil Capture Region 10µm beads 2µm beads 1 cm On-line preprocessing using inertial focusing to de-bulk platelets

21 Cell Separation by Inertial focusing Size dependence of particle ordering Thank you!

Molecular scoring of circulating tumor cells

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