1. Strategy Description Discovery Validation Application
- Identify genes down-regulated after CDK2 knockdown
- Filter genes based on co-expression
- Do they form a protein-protein interaction network?
Discovery
Identify a CDK2 Signature
Examine signature’s ability to
predict CDK2 activity
- Does Signature correlate with E2F activity?
- Does perturbing Rb/E2f affect Signature?
- Does Signature correlate to CDK2 kinase activity?
- Is it responsive to small molecule CDK inhibitors?
Validation
Assess signature’s ability to predict
cell cycle dynamics
- Does Signature rapidly mirror kinase activity in cell cycle?
- Use same strategy to develop CDK1, 4 & 8 signatures
- Does each signature respond as predicted to inhibitors?
Assess signature specificity
CDK2 activity and mitosis in cancer
CDK2 activity in human tissues
Risk assessment in cancer
- Does the CDK2 Signature predict population doubling time in vitro (NCI60 data) and in vivo (TCGA, The Protein Atlas)?
- What are Signature levels in different human tissues?
- Does Signature predict outcome in any human cancer?
- How does it compare with other predictors?
Application
Supplementary Figure 1 Discovery, validation and application of the CDK2 Signature

2. Mined normalized/background corrected microarray data
Gene 1
Gene 1 7
+2.5
Normalize expression
of each gene across all
Samples using Z-Scores
Gene 2
Gene 2 12 +2
Density
Density
Gene 3
Gene 3
13.5 +4 7 14 -5 +5
RNA Expression
(all samples in a study)
Z-Score
Median Z-Score
(+2.5)
Supplementary Figure 2 Signature Score calculation methodology for a given sample.
Before the broad activity of several genes could be summarized into a score, we first ensured that gene expression distribution and medians were similar across each sample via quantile normalization (if needed). In this 3-gene signature example, each distribution represents the expression of a given gene across all samples. Since the mean of each gene is different, we cannot directly compare the expression and summarize all three genes easily. Thus, we transformed the expression values of each gene into a Z-score across samples. In this new scale, gene expression can be directly compared in reference to the mean of the samples. Here, samples with a higher than average expression of signature genes will have a positive score and can be summarized into a single metric using median.

3. A A B Enriched in CDK2 Signature High Cell lines NOTCH4 ERC1 MAPK1 RB1
Enriched in CDK2 Signature Low Cell lines B
Low CDK2 Signature Cell Lines (n=202)
High CDK2 Signature Cell Lines (n=204)
Supplementary Figure 3 CDK2 Signature enriches for RB1 mutant cell lines.
(A) >1000 cell lines from the CCLE were divided into thirds based on the percentile of their CDK2 Signature Score. The y-axis depicts the log2 fold difference in the CDK2 Signature High versus the CDK2 Signature Low cell lines that share a common gene alteration (x-axis). The copy number and mutation status of 462 oncogenes and tumor suppressors was downloaded from cBioPortal ( and matched to the CDK2 Signature High and Signature Low groups. The alterations shown in color are those that were present in > 20 cell lines in both the High and Low CDK2 Signature groups. Alterations are summarized as MUT (blue, exonic mutation), AMP (red, amplification) or HOMDEL (green, homozygous deletion). Alterations that were present in < 20 lines are not shown. (B) Lollipop plots indicating the locations and frequency of damaging (frameshift deletions/insertions, nonsense, or splice; red) and missense mutations (green) in the RB1 locus. The plots were generated using

4. p = 1.7e-07
p = 2.0e-07
p = 8.1e-07
Supplementary Figure 4 Protein-Protein Interactions are enriched in CDK2 Signature genes.
Using the protein-protein interaction (PPI) data from Genemania, each CDK Signature gene list was inputted and networks were drawn. The number of genes in a PPI network were counted and displayed as a fraction of the total gene list. p values were determined by performing a pairwise Fisher’s Exact Test with FDR correction (all p values are in comparison to CDK2 Signature).

5. Supplementary Figure 5 Global specificity of CDK2 inhibitors.
Legend
Kinase Activity (%) 20 40 60
100
Supplementary Figure 5 Global specificity of CDK2 inhibitors.
Kinase activity data (44) was mined for a variety drugs that could inhibit CDK2 activity greater than 50%. The activity of 300 recombinants kinases is displayed as a heatmap.

6. Supplementary Figure 6 Specificity of CDK2 inhibitors
References
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Supplementary Figure 6 Specificity of CDK2 inhibitors
The indicated studies used the indicated method to assess the effect of the indicated drugs on the indicated members of the CDK family.

7. A B Adrenocortical Carcinoma Adrenocortical Carcinoma
p =
p =
Supplementary Figure 7 CDK2 activity signature correlates to mitotic index in vivo.
(A-B) Transcriptome data was mined from adrenocortical carcinoma clinical samples (TCGA). We calculated the CDK2 Signature Scores for each adrenocortical carcinoma sample depending on their mitotic rate (>5/50 HPF [n =28], or below [n =28]) (A) and atypical mitotic figures (n = 28 per group) (B).

8. A B CCLE TCGA High High Mid Mid Low Low
Supplementary Figure 8 CDK2 Signature distribution across cancer cell lines and patient samples.
(A-B) Transcriptome data was downloaded from the CCLE (A) and TCGA (B) and used to calculate the CDK2 Signature score. The values are arranged in ascending order. Black dotted lines indicate the 20th/80th percentile points in each plot.

9. A B Overall Survival (fraction) Time (days)
Recurrence-Free Survival (fraction)
High CDK2 Signature
Medium CDK2 Signature
Low CDK2 Signature
Supplementary Figure 9 KM curves for tumor-specific CDK2 scores
(A) Transcriptome data was downloaded from the TCGA and used to calculate the CDK2 Signature score within each tumor type. Matched clinical information was used in conjunction with CDK2 activity to generate Kaplan-Meier curves across various tumors. The normalized Z-Scores for each gene within the CDK2 Signature was divided into three bins based on percentile within a cancer type. Red lines indicated CDK2 Signatures scores in the 66th percentile, black lines indicate samples in the 33rd-66th percentile, and blue lines indicate samples in the 33rd percentile. (B) The same analysis was performed except using recurrence-free survival data. Cancers with significant HRs are highlighted using a box with a dotted red line. Detailed statistics are in Supplementary Table 5.