heatmaps generated using morpheus  (Broad Institute Inc)

Journal: eLife

Article Title: Genome-wide CRISPR screens of oral squamous cell carcinoma reveal fitness genes in the Hippo pathway

doi: 10.7554/eLife.57761

Figure Lengend Snippet: ( A ) Significantly enriched KEGG pathway based on non-core fitness genes of individual cell lines. Binary heatmap of top 50 most common KEGG pathways enriched by respective non-core fitness genes in the 21 OSCC cell lines. Those with p-values less than 0.05 are indicated in red. ( B ) KEGG pathway enrichment analysis of the 918 non-core fitness genes shows significant enrichment for cancer-related pathways, potentially harboring more targetable cancer-specific genes. ( C ) Functional classification of 918 non-core fitness genes using PANTHER protein class database, separated based on their tractability group.

Article Snippet: Subsequently, cell lines and OSCC tumors were analyzed using hierarchical clustering and visualize with heatmap (generated using Morpheus, Broad Institute: https://software.broadinstitute.org/morpheus ) using the ‘YAP1 dependency signature score’, ‘WWTR1 dependency signature score’ and ‘Compensable signature score’.

Techniques: Functional Assay

Journal: eLife

Article Title: Genome-wide CRISPR screens of oral squamous cell carcinoma reveal fitness genes in the Hippo pathway

doi: 10.7554/eLife.57761

Figure Lengend Snippet: ( A ) Common oncogenic pathways altered among HNSCC samples of TCGA were annotated with frequency of dependency. Non-core fitness genes are indicated in red and the percentage of OSCC cell lines that were dependent on the genes are shown. The Drug Gene Interaction database (DGIdb) ( http://www.dgidb.org/ ) was used to determine if the gene is clinically actionable while the availability of drugs were determined using Open Targets Platform ( https://www.targetvalidation.org/ ). ( B ) Heatmap of gene essentiality of the 44 HNSCC cancer genes in the 21 OSCC lines. These are consensus cancer genes for HNSCC curated from and . ( C ) CRISPR scores of genes with driver mutations in at least one of the 21 OSCC cell lines. Cell lines labeled in green with mutation are examples of those showing oncogene addiction on mutated genes, for example on PIK3CA (ORL-150, BICR10, and HSC-2) and NFE2L2 (Ho-1-u-1). ( D ) Pathway enrichment analysis for fitness genes that are differentially enriched among the seven betel-quid associated OSCC. ( E ) Distribution of the 918 fitness genes based on their small molecule inhibitors tractability assessment. Tractability is defined as detailed in where: tractability group one included targets with approved drugs (Bucket 1) or drugs in clinical/pre-clinical development (Bucket 2, 3); tractability group two included targets with evidence supporting tractability albeit no drugs are available yet; while the least tractable group three included targets that lacks evidence informing tractability. Figure 2—source data 1. Analysis results of targetable genes and pathways in OSCC.

Article Snippet: Subsequently, cell lines and OSCC tumors were analyzed using hierarchical clustering and visualize with heatmap (generated using Morpheus, Broad Institute: https://software.broadinstitute.org/morpheus ) using the ‘YAP1 dependency signature score’, ‘WWTR1 dependency signature score’ and ‘Compensable signature score’.

Techniques: CRISPR, Labeling, Mutagenesis

Journal: eLife

Article Title: Genome-wide CRISPR screens of oral squamous cell carcinoma reveal fitness genes in the Hippo pathway

doi: 10.7554/eLife.57761

Figure Lengend Snippet: ( A ) Essentiality profile (depicted with CRISPR scores heatmap) of YAP1, WWTR1, PIK3CA, TP63 and SOX2 across 21 OSCC cell lines derived from the CRISPR/Cas9 screen. Dependency on these genes were depicted as grey box in the bottom panel, according to the MAGeCK definition of significant depletion at FDR ≤ 0.05. No cell lines were dependent on TP63 or SOX2. The degree of essentiality differs across the lines. Some subsets of the cell lines are only dependent on either YAP1 or WWTR1, while neither gene appears to be essential in another subset of cell lines. PIK3CA, TP63 and SOX2 are genes implicated in HNSCC carcinogenesis that are often co-amplified with WWTR1, located on chromosome 3q25-28. All WWTR1-dependent cell lines had copy number amplification on these genes while all PIK3CA mutated cell lines are not dependent on either YAP1 or WWTR1. ( B ) Western blot images showing the protein level of YAP1 and WWTR1 on day 4 upon transducing the Cas-9 expressing cell lines with lentivirus carrying gene-specific sgRNA. Two sgRNAs were used per target gene. ( C ) Co-competition assay was used to validate the essentiality of YAP1 and WWTR1 on the selected cell lines. The growth of the BFP-positive transduced population was compared to the non-transduced population throughout the 18 days assay. The percentage of BFP-positive cells obtained at different time points were normalized to the day 4 readings for respective sgRNA (except ORL-204 which had time points normalized to the day 6 readings for respective sgRNA). PLK1 is a core essential gene included as a positive control. Negative controls include CHAT which is a non-essential gene across the panel of cell lines, and NT serves as a non-targeting control. Data are shown as mean ± SD (n = 2 biological repeats). ( D ) qPCR results show suppression of downstream targets of YAP1 and WWTR1 only when the respective fitness gene is being knocked-out. Down-regulation of CTGF and CYR61 gene expression was observed when YAP1 is knocked-out in the YAP1-dependent cell lines (ORL-48 and ORL-204). In the WWTR1-dependent cell lines (ORL-214, PE/CA-PJ15), CTGF and CYR61 expression is only suppressed when WWTR1 is knocked-out. Data are shown as mean ± SD (n = 2 independent experiments with technical triplicates). Figure 3—source data 1. All raw data related to and its figure supplements on analysis result of YAP1 and WWTR1 as fitness genes for OSCC.

Article Snippet: Subsequently, cell lines and OSCC tumors were analyzed using hierarchical clustering and visualize with heatmap (generated using Morpheus, Broad Institute: https://software.broadinstitute.org/morpheus ) using the ‘YAP1 dependency signature score’, ‘WWTR1 dependency signature score’ and ‘Compensable signature score’.

Techniques: CRISPR, Derivative Assay, Amplification, Western Blot, Expressing, Competitive Binding Assay, Positive Control, Control, Gene Expression

Journal: eLife

Article Title: Genome-wide CRISPR screens of oral squamous cell carcinoma reveal fitness genes in the Hippo pathway

doi: 10.7554/eLife.57761

Figure Lengend Snippet: ( A ) Analysis workflow for using differentially expressed gene (DEG) signature derived from cell lines to compute dependency score and to identify OSCC samples with similar gene signature and predicted dependency on YAP1 and WWTR1. Three representative OSCC cell lines with validated dependency patterns on YAP1 and WWTR1 were selected and used to generate a list of DEGs. Next, gene expression data for 315 OSCC samples (TCGA) were downloaded and for each sample, Z-score was generated for all the DEGs. Z-score for the upregulated genes were averaged, subtracted with the average of all Z-score for the downregulated genes, to derive the respective ‘dependency signature score’/”Compensable signature score’. Samples with YAP1 dependency signature score >0.5 were considered as core samples predicted to be YAP1-dependent; Samples with WWTR1 dependency signature score >0.5 were core samples for WWTR1-dependent; while samples with compensable signature score >0.5 were considered core samples for which YAP1 and WWTR1 can compensate for one another. ( B ) Heatmap of the gene expression of all DEGs (supervised clustering), used to derive the ‘YAP1 dependency signature score’, ‘WWTR1 dependency signature score’ and ‘Compensable signature score’, from the nine representative OSCC cell lines.

Article Snippet: Subsequently, cell lines and OSCC tumors were analyzed using hierarchical clustering and visualize with heatmap (generated using Morpheus, Broad Institute: https://software.broadinstitute.org/morpheus ) using the ‘YAP1 dependency signature score’, ‘WWTR1 dependency signature score’ and ‘Compensable signature score’.

Techniques: Derivative Assay, Gene Expression, Generated

Journal: eLife

Article Title: Genome-wide CRISPR screens of oral squamous cell carcinoma reveal fitness genes in the Hippo pathway

doi: 10.7554/eLife.57761

Figure Lengend Snippet: ( A ) Heatmap with hierarchical clustering using the computed signature scores showed clustering of the OSCC cell lines into three groups, based on their validated dependency. ( B ) Heatmap with hierarchical clustering of OSCC tumors using the computed signature scores. The three clusters found from cell lines were also present among the OSCC tumors. For labeling convenience, OSCC with high YAP1 dependency signature score is referred as ‘YAP1-dependent’; ‘WWTR1-dependent’ – high WWTR1 dependency signature score; ‘Compensable’ – high compensable signature score. ( C ) GSEA of the OSCC cell lines and those OSCC tumors with similar gene signatures showed overlapping hallmarks enrichment, while distinct hallmarks were associated with each of the three groups. Only common hallmarks (between cell lines and tumors) with positive normalized enrichment score (NES) of >0.5 were shown. Full GSEA results can be found in . ( D ) OSCC with high WWTR1 dependency signature score showed significantly lower stromal infiltration, but higher immune infiltration compared to the other two groups. ( E ) By comparing the immune expression signatures from , OSCCs with high WWTR1 dependency signature score are associated with significantly higher IFN-gamma response and cytolytic CD8 T-cells and lower TGF-beta response. ( F ) mRNA expression of PD-L1 (CD274) were significantly elevated among OSCC tumors with high WWTR1 dependency signature score. ( G ) OSCC with high WWTR1 dependency signature score showed significantly higher enrichment score for the 18-gene T-cell inflamed GEP, which is a clinically validated biomarker of response towards checkpoint blockade. For panels D-G, unpaired Welch’s t-test with Welch’s correction was used due to unequal sample size (n = 43, 31, 30, respectively).

Article Snippet: Subsequently, cell lines and OSCC tumors were analyzed using hierarchical clustering and visualize with heatmap (generated using Morpheus, Broad Institute: https://software.broadinstitute.org/morpheus ) using the ‘YAP1 dependency signature score’, ‘WWTR1 dependency signature score’ and ‘Compensable signature score’.

Techniques: Labeling, Expressing, Biomarker Discovery