MI_intro

University of Michigan tutorial- Introduction

Transcript

1. Julia Wrobel, PhD
   Department of Biostatistics and Informatics
   Introduction to multiplex single-cell
   imaging data
   

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2. What is single cell multiplex tissue imaging?
   • High dimensional analysis of tissue samples at the resolution of
   individual cells
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3. What is single cell multiplex tissue imaging?
   • Single cell refers to individual cell resolution
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4. What is single cell multiplex tissue imaging?
   • Multiplex refers to multiple types of proteins in the tissue that are
   tagged
   • Each protein label is called a marker
   • Phenotypic markers: used to define cell and/or tissue type
   • Functional markers: inform cell function
   • Present across multiple cell types
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5. What is single cell multiplex tissue imaging?
   • Multiplex refers to multiple types of proteins in the tissue that are
   tagged
   • Immunofluorescence based
   • Proteins stained with fluorescent antibodies then imaged using
   fluorescence microscopy
   • Mass cytometry based
   • Proteins tagged with metal isotypes (IMC, MIBI)
   

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6. What is single cell multiplex tissue imaging?
   • Imaging: biological spatial relationships in tissue are preserved
   • Precursor technologies required suspension of cells in solution,
   destroying spatial info
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7. What is single cell multiplex tissue imaging?
   • Images produced are multichannel TIFF (.tif) files
   • Each channel is a different protein marker
   • Each pixel contains a continuous intensity value for each marker
   • Example below with non-small cell lung cancer data
   • 8 channels, 3 shown (Left to Right: composite image, nuclei, CK, CD8)
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8. A brief comparison of MI technologies
   Platform Class Throughput Multiplexicity Software Publications*
   Vectra-Polaris IF high ~8 markers Proprietary > 100
   Discovery
   Ultra
   IF high 5+ markers Limited < 10
   CyTOF
   Imaging
   IMC low 37+ MatLab > 35
   MIBI IMC low 40+ Limited >5
   CODEX Barcode
   -based
   low 40+ Limited/proprietary >1
   * Since April 2020
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9. Cancer, multiplex imaging, and the tumor
   microenvironment
   The tumor microenvironment (TME) is the
   area within and surrounding a tumor,
   including tumor cells, infiltrating immune
   cells, blood vessels, and other tissue
   • What percentages of immune cell
   subtypes are present before and after
   chemotherapy?
   • Do patients with high spatial clustering of
   B-cells and Macrophages survive longer?
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10. Multiplex image data processing and analysis pipeline
    Phenotyping
    Segmentation
    Normalization
    Image processing
    Compositional
    data analysis
    Spatial data
    analysis
    Statistical analysis
    Image
    acquisition
    Image
    filtering/
    background
    correction
    Image pre-processing
    

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11. Image
    acquisition
    Image
    filtering/
    background
    correction
    Multiplex image data processing and analysis pipeline
    Image
    acquisition
    Image
    filtering/
    background
    correction
    Image pre-processing
    Phenotyping
    Segmentation
    Normalization
    Image processing
    

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12. Multiplex image data processing and analysis pipeline
    Cell 1
    Pixel
    1
    Marker
    a
    Marker
    b
    Pixel n
    Marker
    a
    Marker
    b
    Phenotyping
    Segmentation
    Normalization
    Image processing
    

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13. Cell types by immune markers
    Thanks to Brooke Fridley and Alex Soupir at the Moffitt Cancer Center for this image
    

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14. Multiplex image data processing and analysis pipeline
    Image
    ID
    Cell
    ID
    Tissue type Phenotype X Y Patient
    features
    1 1 Stroma CD4 T-cell … … …
    1 2 Stroma B-cell … … …
    1 3 Tumor Macrophage … … …
    1 4 Stroma CD8 T-cell … … …
    2 1 Tumor Tumor cell … … …
    Phenotyping
    Segmentation
    Normalization
    Image processing
    

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15. Multiplex image data processing and analysis pipeline
    Image
    ID
    Cell
    ID
    Tissue type Phenotype X Y Patient
    features
    1 1 Stroma CD4 T-cell … … …
    1 2 Stroma B-cell … … …
    1 3 Tumor Macrophage … … …
    1 4 Stroma CD8 T-cell … … …
    2 1 Tumor Tumor cell … … …
    Compositional
    data analysis
    Spatial data
    analysis
    Statistical analysis
    

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16. Multiplex image data processing and analysis pipeline
    Cell type, counts, proportions, or percentages
    Compositional
    data analysis
    Spatial data
    analysis
    Statistical analysis
    

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17. Multiplex image data processing and analysis pipeline
    Cell type, counts, proportions, or percentages
    Cell type clustering within an image or across
    patient subgroups
    Compositional
    data analysis
    Spatial data
    analysis
    Statistical analysis
    

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18. 1. Quantify characteristics / features of an image
    • Features: cell type proportions, degree of immune cell clustering
    2. Relate to patient-level or clinical outcome
    • Features -> model covariates
    • Outcomes: disease progression, tumor subtype, patient survival time
    How do multiplex images relate to patient outcomes?
    B Steinhart, KR Jordan, J Bapat, MD Post, LW Brubaker, BG Bitler, and J Wrobel. Molecular Cancer Research, 19(12) (2021)
    

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19. Shiny Boot Camp:
    Building Interactive Graphics and Dashboards in R
    • July 6-7, 2023; In-person training (NYC)
    • Two-day intensive course including seminars and hands-on coding
    sessions that teaches attendees to build interactive web applications in R
    • Instructor: Julia Wrobel (Colorado School of Public Health)
    • Scholarships available
    More info: publichealth.columbia.edu/Shiny
    

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