1. MultiOmyxTM: A novel platform for in situ, multiomic, hyper-plexed analyses of systems biology
Background: We describe a novel multiomic, hyper-plexed tissue analyses platform, MultiOmyxTM, which enables the imaging of protein and nucleic acid biomarkers at subcellular level in the same tissue slice. Unlike grind-and-find methods, imaging preserves the spatial architecture of tissue allowing interrogation of both intra and inter-cellular interactions/communications. Image analysis algorithms enable subcellular quantification of biomarkers in individual cells and enable novel systems-level insights into biological mechanisms.
Method: From a single tissue section, cells are molecularly profiled and visualized using MultiOmyxTM. They are clustered into families having similar phenotypes using associated and proprietary analysis software. Individual clusters are color-coded and transposed back to original images to provide a novel in situ visualization of patterns of heterogeneity and cellular interactions. Tissue visualization is combined with existing pathway visualization and analysis tools e.g. Cytoscape.
Results: The method was applied to a cohort of 747 colon cancer tissue microarray with particular focus on immune infiltration and mTOR and MAPK signal transduction. Cluster analysis of immune cell features showed robust adaptive and innate immune responses in many subjects and conversely, other patients showed a general lack of immune cell infiltration. Cluster analysis and visualization of mTOR and MAPK signal transduction pathway activation at the single cell level revealed unexpected patterns of coexpresssion and mutual exclusivity of common downstream phosphorylation events.
Conclusion: Quantitative tumor immunoprofiling and signal transduction analysis revealed extensive immune cell heterogeneity between subjects and unexpected signal transduction exclusivity and coexpression patterns highlighting the unique capability of this platform.
Background autofluorescent image
Stain slide with dye-labeled antibodies
.
Remove slide, inactivate signal
Dye Inactivation
>60 Proteins then DNA FISH
Multiplexing: Stain, Image, Erase and Repeat
Image & Data Analysis Workflow
Image Corrections
•Illumination correction
•Image registration
•Autofluorescence subtraction
QC
•Registration failures
•Poor focus
•Damaged tissue
•Illumination issues
Image Analysis
•Epithelium segmentation
•Stromal segmentation
•Single cell measurements
Data Transforms
•Data transformation (log etc.)
•Normalization
•Data integration with clinical data/other data types
Data Exclusion Rules
•Invalid cells
•Image periphery
•Image annotation
Statistical Feature Extraction
•Cell clustering
•Moments
•Proximity
•Thresholds
Outcome and Pathway Analysis
•Population level
•Cell level
•Survival/recurrence
•Classification
Images acquired on scanner
DNAseq mutations
Select
•Study
•Patient
•Tissue
•Sample
•Multiomic data
Pathway Maps
•KEGG
•Wikipathways
•NCI PID
•Reactome
•BioCarta
pathway scores
Cell Maps
High
Low
impact
MultiOmyx measures
Future: Visualize MultiOmyx Data in a Pathway Context using Cytoscape
ERK 1/2
Akt 1/2/3
EPCAM
phospho-ERK1/2 T202/Y204
PI3K p110α
CD31
Wnt5a
Indian Hedgehog
Fibronectin
β-Catenin
xCT
Vimentin
S6 ribosomal protein
GLUT1
β-Actin
phospho-S6 S235/S236
CA9
pan-cytokeratin (1,5,6,8)
HER2
ALDH1
α-Smooth Muscle Actin
4EBP1
TKLP1
NA+K+ATPase
phospho-4EBP1 T37/T46
COX2
Collagen IV
NDRG1
MLH1
Albumin
phospho-NDRG1 T346
MSH2
Cytokeratin 19
phospho-GSK3α S21
Lamin A/C
Cytokeratin 15
phospho-GSK3β S9
EZH2
Claudin1
EGFR
p21
E-Cadherin
phsopho-EGFR Y1068
FOXO3a
CD44v6
PTEN
FOXO1
CD20
phospho-MAPKAPK2 T334
Cleaved Caspase 3
CD68
Met
Cyclin B1
CD79
phospho-Met Y1349
p53
CD8
phospho-p38 MAPK T180/Y182
PCNA
CD3
Christine D. Kuslich, Christopher J. Sevinsky, Michael J. Gerdes, Fiona Ginty, John F. Graf, Vidya Kamath, Qing Li, Lee A. Newberg, Brian Ring, Alberto Santamaria-Pang, Anup Sood, Yunxia Sui, Maria I. Zavodszky, Brion D. Sarachan, GE Global Research and GE Healthcare
Analysis of a large cohort of colon cancer subjects
DAPI:
nucleus
E-cadherin:
epithelial cells
Na+K+ATPase: membrane
RPS6:
cytoplasm
Segmented cells
Nucleus
Membrane
Cytoplasm
stage I (n=192)
stage II (n=278)
stage III (n=252)
age
66 (27,89)
69 (35,94)
66 (32,91)
gender
F (96,50%)
F (136,49%)
F (118,47%)
grade=1
50 (26%)
39 (14%)
23 (9%)
grade=2
125(65%)
216(78%)
175(69%)
grade=3
12(6%)
19(7%)
51(20%)
recurrence
n=15
n=51
n=94
avg (range)
3.2 (0.7,6.8)
2 (0,9.5)
1.6(0.1,8.9)
Follow-up
n=177
n=227
n=157
avg (range)
5.3 (0.1,12.1)
5 (0,13)
4.5(0,11.8)
death from disease
n=11
n=44
n=82
avg (range)
3.6 (0.7,6)
2.2 (0,9.7)
2.1(0.2,7.5)
Follow-up
n=181
n=234
n=170
avg (range
5.2 (0.1,12.1)
5.3 (0,13)
4.7(0,11.8)
Subjects: 747 colorectal cancer patients – AJCC stage I-III – for summary statistics see Table.
Multiplexed immunofluorescence: directly conjugated Cy2, Cy3 and cy5 labeled primary antibodies to hallmarks of colorectal cancer and tissue microenvironment.
Sequential fluorescence microscopy: 38 rounds of imaging; 60 protein targets + baseline autofluorescence imaging
Automated image analysis: registration; single cell and subcellular nuclear, cytoplasmic and membrane segmentation; target quantification.
Abstract
Single cell segmentation and signal quantitation
Single cell cluster analysis:
mutually exclusive signal transduction
Heterogeneity:
cell level signal transduction
Cluster analysis of patient level signaling
Psuedo-colored
Clusters IDs mapped to cells
Immune cell profiling
Poor Prognosis
Favorable Prognosis
Single cell map
Single cell metrics
p4E-BP1 pS6 Nuclei
Low Immune cell infiltrate
High Immune cell infiltrate
Monitoring immune cell types
in the tumor microenvironment
Quantification of immune cell types in the tumor microenvironment
Quantification of immune cell types is prognostic