broadinstitute/2021_04_07_proteinkinaseinhibitors_nathanaelgray

ProteinKinase_NathanaelGray

Goal:

• Characterization of selective Protein kinase inhibitors using Cellpainting assay
• Identifying novel phenotypes associated with each kinase inhibitor

2021_04_07_proteinkinaseinhibitors_nathanaelgray's Issues

Pairwise comparison of features between Controls and Protein Kinase Inhibitors (SECRET)

A549

Welch ttest used to perform pairwise feature comparison

Total no of features = 595

1. DMSO and BSJ-03-136
2. DMSO and BSJ-04-030

95th percentile threshold of Control_Active {-log10[p-values]} used to select features

Features list:

['Cytoplasm_Correlation_Correlation_DNA_Mito',
'Cytoplasm_Correlation_Correlation_DNA_RNA',
'Cells_Intensity_MedianIntensity_DNA',
'Cells_Intensity_MADIntensity_DNA',
'Cells_Intensity_MinIntensityEdge_RNA',
'Cells_Texture_Gabor_RNA_20',
'Cells_Texture_InverseDifferenceMoment_RNA_5_0',
'Cells_Texture_Gabor_Mito_20',
'Cells_Texture_Gabor_ER_20',
'Cells_Correlation_Correlation_DNA_Mito',
'Cells_Intensity_MeanIntensity_ER',
'Cytoplasm_Texture_Gabor_AGP_5',
'Cytoplasm_Intensity_UpperQuartileIntensity_DNA',
'Cells_Texture_Contrast_DNA_5_0',
'Cells_Correlation_Correlation_DNA_ER',
'Cells_Correlation_Correlation_DNA_RNA',
'Cytoplasm_Texture_DifferenceVariance_AGP_20_0',
'Cytoplasm_Texture_Contrast_Mito_10_0',
'Cells_Texture_Gabor_RNA_10',
'Cells_Texture_DifferenceVariance_Mito_20_0',
'Cells_Intensity_UpperQuartileIntensity_DNA',
'Nuclei_Neighbors_SecondClosestObjectNumber_2',
'Cells_Texture_Gabor_AGP_20',
'Cells_Texture_Correlation_RNA_10_0',
'Cytoplasm_AreaShape_Solidity',
'Cytoplasm_Intensity_MADIntensity_DNA',
'Cells_Texture_Correlation_RNA_5_0',
'Cells_Texture_Gabor_RNA_5',
'Cells_Texture_DifferenceVariance_Mito_10_0',
'Cytoplasm_Texture_Gabor_RNA_5']

Density plots

Unsupervised clustering analysis

The main aim of this project to identify protein kinase inhibitors (Active, Inactive forms) which produce distinct cellpainting profiles in two cancer cell lines (A549, U2OS)

DMSO and positive and negative controls

In both cells, Negative control clustered along with DMSO samples while positive controls are clustered separately in UMAP space

DCLK1

Drugs(Active, Inactive) forms targeting DCLK1 showed similar profiles in both cell lines

ERK5

AX15836 (active inhibitor of ERK5) didn't work and clustered with DMSO samples
while JWG-071 (active) and JWG-119 (inactive) showed slight difference in profiles in both cell lines

FAK

We got only one compound of FAK inhibitor

PIN1

Both active and inactive compounds targeting PIN1 clustered with DMSO

CDK14pan-TAIRE

Note:

FMF-04-159-2(covalent) and FMF-05-176-1 (reversible) drugs targeting CDK14pan-TAIRE displayed distinct profiles only in A549 cells while FMF-05-176-1 (reversible) in U2oS cells didn't seem to work

SECRET

Note:

active and inactive Protein kinases targeting SECRET pathway displayed distinct profiles only in A549 cells

Features mapping for CDK14 / pan-TAIRE

Features are grouped together for AreaShape and Neighors category and absolute difference of mean of z-scores values are calculated for:

Target_pathway: CDK14 / pan-TAIRE

DMSO Controls
FMF-04-159-2 Covalent
FMF-05-176-1 Reversible

1. Covalent vs DMSO
2. Reversible vs DMSO
3. Covalent vs Reversible

AreaShape & Neighbors Features

All other Features

Top 10 Intensity features in comparison of Covalent vs Reversible drug

1. Nuclei_Intensity_StdIntensityEdge_ER
2. Cytoplasm_Intensity_MaxIntensityEdge_ER
3. Nuclei_Intensity_MaxIntensity_ER
4. Cells_Intensity_MeanIntensity_ER
5. Nuclei_Intensity_StdIntensity_ER
6. Cytoplasm_Intensity_StdIntensity_ER
7. Nuclei_Intensity_LowerQuartileIntensity_ER
8. Nuclei_Intensity_MeanIntensity_ER
9. Nuclei_Intensity_MeanIntensityEdge_ER
10. Cells_Intensity_MaxIntensityEdge_ER

Top 10 RadialDistribution Features of Mito Channel

1. Cytoplasm_RadialDistribution_RadialCV_Mito_4of4
2. Cells_RadialDistribution_MeanFrac_Mito_1of4
3. Cells_RadialDistribution_RadialCV_Mito_4of4
4. Cells_RadialDistribution_RadialCV_Mito_3of4
5. Cytoplasm_RadialDistribution_RadialCV_Mito_3of4
6. Cytoplasm_RadialDistribution_MeanFrac_Mito_2of4
7. Cells_RadialDistribution_RadialCV_Mito_2of4
8. Cells_RadialDistribution_RadialCV_Mito_1of4
9. Nuclei_RadialDistribution_RadialCV_Mito_1of4
10. Cytoplasm_RadialDistribution_RadialCV_Mito_1of4

Top 10 RadialDistribution Features of RNA Channel

1. Cytoplasm_RadialDistribution_RadialCV_RNA_4of4
2. Cytoplasm_RadialDistribution_RadialCV_RNA_3of4
3. Cells_RadialDistribution_RadialCV_RNA_4of4
4. Cytoplasm_RadialDistribution_MeanFrac_RNA_1of4
5. Cells_RadialDistribution_RadialCV_RNA_3of4

**Top 6 Nuclei AreaShape Features **

1. Nuclei_AreaShape_Zernike_2_2
2. Nuclei_AreaShape_Zernike_5_1
3. Nuclei_AreaShape_Eccentricity
4. Nuclei_AreaShape_Zernike_6_4
5. Nuclei_AreaShape_Zernike_8_4
6. Nuclei_AreaShape_Zernike_0_0
7. Nuclei_AreaShape_Compactness

Mapping of Features for SECRET pathway

Features are grouped together for AreaShape and Neighors category and absolute difference of mean of z-scores values are calculated for:

1. Inactive vs Controls
2. Active vs Controls
3. Active vs Inactive

Note: we do observe differences in Cell and Cytoplasm AreaShape features more obvious in Active Protein Kinase inhibitor (PK) compared with the inactive form of the inhibitor. There is no such obvious differences observed between active and inactive PK inhibitors. Neighbors features also have high values??? suggesting more density of cells?

Other Feature groups

1. Overall differences are higher in Active PK inhibitor relative to Controls than Inactive vs controls
2. Intensity features of DNA, Mito, ER and Radial features of Mito, ER and RNA showed high differences relative to controls
3. Granularity features for all channels showing differences relative to controls
4. However, Intensity and Radia ldistribution features of Mito and ER showed high differences in Active vs Inactive Protein kinase inhibitor.

Density plot of Features importance

Features

Category:"Neighbors"

list of differential features between active and inactive compound of SECRET pathway

['Cells_Neighbors_FirstClosestDistance_Adjacent',
'Nuclei_Neighbors_SecondClosestObjectNumber_2',
'Nuclei_Neighbors_AngleBetweenNeighbors_2',
'Cells_Neighbors_AngleBetweenNeighbors_Adjacent',
'Cells_Neighbors_PercentTouching_Adjacent']

Category: "RadialDistribution" Channel: "Mito"

1. Cells_RadialDistribution_RadialCV_Mito_4of4
2. Cytoplasm_RadialDistribution_RadialCV_Mito_4of4
3. Cells_RadialDistribution_MeanFrac_Mito_1of4
4. Cytoplasm_RadialDistribution_RadialCV_Mito_3of4
5. Cells_RadialDistribution_RadialCV_Mito_3of4
6. Cytoplasm_RadialDistribution_MeanFrac_Mito_2of4
7. Cells_RadialDistribution_MeanFrac_Mito_3of4
8. Cytoplasm_RadialDistribution_RadialCV_Mito_1of4
9. Nuclei_RadialDistribution_RadialCV_Mito_1of4
10. Cells_RadialDistribution_RadialCV_Mito_2of4
11. Cells_RadialDistribution_FracAtD_Mito_3of4
12. Cells_RadialDistribution_RadialCV_Mito_1of4
13. Nuclei_RadialDistribution_FracAtD_Mito_3of4
14. Nuclei_RadialDistribution_FracAtD_Mito_1of4'

Category: "RadialDistribution" Channel: "ER"

1. 'Cytoplasm_RadialDistribution_MeanFrac_ER_2of4',
2. 'Cytoplasm_RadialDistribution_MeanFrac_ER_4of4',
3. 'Cells_RadialDistribution_RadialCV_ER_4of4',
4. 'Cytoplasm_RadialDistribution_MeanFrac_ER_3of4',
5. 'Cells_RadialDistribution_RadialCV_ER_3of4',
6. 'Cytoplasm_RadialDistribution_RadialCV_ER_4of4',
7. 'Nuclei_RadialDistribution_RadialCV_ER_3of4',
8. 'Cells_RadialDistribution_MeanFrac_ER_1of4',
9. 'Nuclei_RadialDistribution_RadialCV_ER_2of4',
10. 'Cytoplasm_RadialDistribution_FracAtD_ER_1of4',
11. 'Nuclei_RadialDistribution_RadialCV_ER_1of4',
12. 'Cytoplasm_RadialDistribution_RadialCV_ER_1of4',
13. 'Cells_RadialDistribution_MeanFrac_ER_3of4',
14. 'Cells_RadialDistribution_RadialCV_ER_2of4',
15. 'Nuclei_RadialDistribution_MeanFrac_ER_1of4',
16. 'Cells_RadialDistribution_RadialCV_ER_1of4',
17. 'Cells_RadialDistribution_FracAtD_ER_3of4',
18. 'Nuclei_RadialDistribution_RadialCV_ER_4of4'

Category: "Intensity" Channel: "Mito"

1. Cells_Intensity_MassDisplacement_Mito
2. Nuclei_Intensity_MassDisplacement_Mito
3. Cytoplasm_Intensity_IntegratedIntensity_Mito
4. Cells_Intensity_MinIntensityEdge_Mito
5. Cells_Intensity_StdIntensityEdge_Mito
6. Cytoplasm_Intensity_MADIntensity_Mito
7. Cytoplasm_Intensity_IntegratedIntensityEdge_Mito
8. Nuclei_Intensity_MinIntensityEdge_Mito
9. Cells_Intensity_IntegratedIntensityEdge_Mito

Category: "Intensity" Channel: "ER"

1. Cells_Intensity_MassDisplacement_ER
2. Cytoplasm_Intensity_MassDisplacement_ER
3. Nuclei_Intensity_MeanIntensity_ER
4. Nuclei_Intensity_IntegratedIntensityEdge_ER
5. Nuclei_Intensity_IntegratedIntensity_ER
6. Cells_Intensity_IntegratedIntensity_ER
7. Nuclei_Intensity_MADIntensity_ER
8. Nuclei_Intensity_MassDisplacement_ER
9. Cytoplasm_Intensity_StdIntensityEdge_ER'
10. Nuclei_Intensity_LowerQuartileIntensity_ER
11. Cytoplasm_Intensity_MADIntensity_ER
12. Nuclei_Intensity_StdIntensity_ER
13. Nuclei_Intensity_MaxIntensity_ER
14. Cells_Intensity_MeanIntensity_ER
15. Nuclei_Intensity_MeanIntensityEdge_ER
16. Cytoplasm_Intensity_MaxIntensityEdge_ER
17. Cells_Intensity_StdIntensity_ER
18. Nuclei_Intensity_StdIntensityEdge_ER
19. Cells_Intensity_MADIntensity_ER
20. Cytoplasm_Intensity_IntegratedIntensityEdge_ER
21. Cells_Intensity_MaxIntensityEdge_ER
22. Cytoplasm_Intensity_StdIntensity_ER

Preliminary analysis

Goals: Exploratory analysis to ensure everything is working as expected and look for relationships between perturbations

Conclusion:

Selection of potential Protein kinase inhibitors

Two independent unsupervised clustering approaches revealed that following two Protein Kinase inhibitors targeting (SECRET pathway) have distinct morphological profiles from DMSO as well as from each other in A549 cell line. However this is not seen in case of U2oS cell line.

1. BSJ-03-136 (Active)
2. BSJ-04-030 (Inactive)

UMAP

PCA

Clustering of Single cell data [SECRET]

Note: Single Cell clustering revealed interesting pattern in Active compound most of the cell profiles are pushed on the top of UMAP space. While in case of DMSO few no of cell occupy the same space. In case of inactive compound it has showed mixed response.

Single cell Images for Active and Inactive Inhibitor of SECRET Pathway

https://docs.google.com/presentation/d/1_hEevgvMqt1aJVqE_bTzZe8bG9Bne5gcbUbNG4ozuhE/edit#slide=id.g99bd36cb6c_2_126

Metadata & Platemap

Plates: 2

BR00100032
BR00100037

s3://imaging-platform/projects/2018_11_20_GeneCpdFollowup/workspace/backend/2018_11_20_Batch1/

s3://imaging-platform/projects/2018_11_20_GeneCpdFollowup/workspace/metadata/2018_11_20_Batch1/barcode_platemap.csv

Platemap:

Both plates have same platemap

• C-7210-01-CMP-008-gray

s3://imaging-platform/projects/2018_11_20_GeneCpdFollowup/workspace/metadata/2018_11_20_Batch1/platemap/C-7210-01-CMP-008-gray.txt

Celllines:

1. U2OS
2. A549

Positive Controls:

C3 -------- BRD-K97963946-001-01-3 [ Drug Repurposing Hub]
C4 -------- BRD-K97309399-001-09-4 [Drug Repurposing Hub
Negative Controls:

C1 -------- BRD-A15435692-003-02-3 [Drug Repurposing Hub]
C2 -------- BRD-K90789829-001-07-8 [ Drug Repurposing Hub]

Technical Replicates per plate:

DMSO: 272
Positive controls : 4
Tested Drugs : 8

Features mapping for ERK5

Features are grouped together for AreaShape and Neighors category and absolute difference of mean of z-scores values are calculated for:

Target_pathway: ERK5

There were two active drugs AX15836 and JWG-071 and one inactive JWG-119 targeting ERK5 kinases. However,
one active AX15836 drug didn't seems to work in either of the cell lines

In creating feature grid, we are using only
**JWG-071 ** Active
JWG-119. Inactive

AreaShape & Neighbors Features

Other Features

Replicate correlation

Cytominer workflow used for preprocessing, Feature normalization and selection and mean aggregated well profiles were created

Note: As in this experiment we randomly sampled 112 DMSO's from each plate and used them for normalization of variables

A total of 598 Features selected and used in downstream analysis

Median replicate correlation analysis is performed and most of compounds have high replicate correlative with the exception of two compounds both of them displayed low replicate correlation in both celllines

1. BJP-06-115-3
2. BJP-06-005-3

Similarity correlation analysis is performed where each row represents each replicate well sample and each column represent features. Protein kinase inhibitors, in the top and bottom highlighted region displayed distinct profile compared to DMSO, shown in the middle of the figure.

Similarity correlation analysis for aggregated profiles for each compound

A549

U2oS