Integrated functional, gene expression and genomic analysis for the identification of cancer targets

Abstract

The majority of new drug approvals for cancer are based on existing therapeutic targets. One approach to the identification of novel targets is to perform high-throughput RNA interference (RNAi) cellular viability screens. We describe a novel approach combining RNAi screening in multiple cell lines with gene expression and genomic profiling to identify novel cancer targets. We performed parallel RNAi screens in multiple cancer cell lines to identify genes that are essential for viability in some cell lines but not others, suggesting that these genes constitute key drivers of cellular survival in specific cancer cells. This approach was verified by the identification of PIK3CA, silencing of which was selectively lethal to the MCF7 cell line, which harbours an activating oncogenic PIK3CA mutation. We combined our functional RNAi approach with gene expression and genomic analysis, allowing the identification of several novel kinases, including WEE1, that are essential for viability only in cell lines that have an elevated level of expression of this kinase. Furthermore, we identified a subset of breast tumours that highly express WEE1 suggesting that WEE1 could be a novel therapeutic target in breast cancer. In conclusion, this strategy represents a novel and effective strategy for the identification of functionally important therapeutic targets in cancer.

Figure 1. Cell viability screens with a kinase siRNA library.

a. Scatter plots of Z scores from cell viability screens carried out in parallel in MCF7, CAL51, HeLa, A549 and NCI-H226 cancer cell lines. Black diamonds – individual siRNA SMARTpools targeting 779 kinase genes per cell line. Z scores≤−3 represent significant loss of viability effects. b. Distribution plots of Z scores from the parallel siRNA screens. Z scores≤−3 represent significant loss of viability effects. c. Kinases can be classified on the basis of the effect of silencing on cell viability across all five cancer cell lines. siRNAs that had no significant effect on cell viability in any of the cell lines studied likely target nonessential kinases (or the siRNA was not functional). siRNAs that cause significant loss of cell viability in all of the cell lines studied likely target kinases that are essential for viability in most tumour types or those that are essential for the viability of both normal and tumour cells. siRNAs that only cause significant lethality in some but not all cell lines likely target kinases that may not be critical for the viability of all cells but represent tumour-specific effects. d. Parallel RNAi screens identify a known oncogene, PIK3CA. Cell viability effects of PIK3CA targeting are shown in five cell lines. MCF7 cells were selectively sensitive to targeting of PIK3CA as demonstrated by a Z score of ≤−3. siRNAs that cause significant lethality in some but not all cell lines are likely to target kinases that are not critical for the viability of all cells but represent tumour-specific effects. In some instances this may be explained by the occurrence of an activated oncogene as is the case with MCF7 cells, which harbour an activating PIK3CA mutation.

Figure 2. Correlation between siRNA loss of viability and gene expression.

a–d. Z scores from the siRNA screens, Z scores≤−3 are highlighted with a red dotted box. e–h. Normalised expression levels calculated from Illumina expression profiling. High expression correlated with sensitivity to siRNA, highlighted with a red dotted box. Error bars represent the standard error of the mean (SEM). The significance of differences in genes expression between cell lines was assessed by one-way ANOVA and p value displayed for each cell lines. i–l. comparison of Z values with normalised expression levels. The dashed line represents the Z = −3 threshold for significant loss of viability effects (p<0.0015). For the four genes shown, an elevated level of expression is consistent with loss of viability after siRNA transfection. See Table 1 for Pearson correlation of Z vs expression.

Figure 3. Correlation between gene copy number and gene expression.

Scatter plots illustrating the relationship between gene copy number and gene expression. Vertical dashed lines represent the threshold for copy number gains (aws ratios>0.12).

Figure 4. WEE1 expression correlates with sensitivity to WEE1 inhibition.

a. Western blot analysis of lysates prepared from HeLa, CAL51, MCF7, A549, NCI-H226, PC3, DU145 and MCF10A cells. An antibody recognising WEE1 was used with β-tubulin as a loading control. WEE1 expression is significantly increased in HeLa and CAL51 cells compared to MCF7, A549, NCI-H226, PC3, DU145 and MCF10A cells. b. Left panel: Cell viability assay in cells transfected with WEE1 ONTARGETplus SMARTpool, or ONTARGETplus siControl. WEE1 silencing was selectively lethal to WEE1 overexpressing HeLa and CAL51 cells. Error bars represent the SEM from triplicate transfections. Right panel: Western blot analysis of lysates prepared from CAL51 cells transfected with WEE1 ONTARGETplus SMARTpool or ONTARGETplus siControl. An antibody recognising WEE1 was used with β-tubulin as a loading control. WEE1 ONTARGETplus SMARTpool significantly reduced WEE1 protein expression compared to siControl transfected cells. c. Cell viability assay in cells treated with WEE1 inhibitor. WEE1 inhibition was selectively lethal to WEE1 overexpressing HeLa and CAL51 cells. Error bars represent the SEM from triplicate cell treatments. d. Left hand panel: Western blot analysis of lysates prepared from cells treated with 5 µM WEE1 inhibitor for 0, 6, 24 and 48 hours. An antibody recognising PARP was used with β-tubulin as a loading control. After 24 hours WEE1 inhibition induced PARP cleavage (Clvd PARP) in WEE1 overexpressing HeLa and CAL51 cells but did not induce PARP cleavage in MCF7 and NCI-H226 cells which express WEE1 at normal levels. Right hand panel: Caspase 3,7 activity in cells treated with 5 µM WEE1 inhibitor for 24 hours. WEE1 inhibition induced caspase 3,7 activation in WEE1 overexpressing HeLa and CAL51 cells but did not induce caspase 3,7 activation in MCF7 and NCI-H226 cells which express WEE1 at normal levels. Error bars represent the SEM from triplicate cell treatments. e. Left hand panel: Western blot analysis of lysates prepared from cells transfected with WEE1 ONTARGETplus SMARTpool or ONTARGETplus siControl. An antibody recognising PARP was used with β-tubulin as a loading control. Silencing of WEE1 induced PARP cleavage in WEE1 overexpressing HeLa and CAL51 cells but did not induce PARP cleavage in MCF7 and NCI-H226 cells which express WEE1 at normal levels. Right hand panel: Caspase 3,7 activity in cells transfected with WEE1 ONTARGETplus SMARTpool or ONTARGETplus siControl. Silencing of WEE1 induced caspase 3,7 activation in WEE1 overexpressing HeLa and CAL51 cells but did not induce caspase 3,7 activation in MCF7 and NCI-H226 cells which express WEE1 at normal levels. Error bars represent the SEM from triplicate transfections.

Figure 5. WEE1 is overexpressed in a subset of tumours.

a. WEE1 immunohistochemical staining in formalin-fixed, paraffin-embedded breast cancer cell lines and invasive breast cancers. Note the low levels of WEE1 expression in H226 cells and a basal-like breast cancer and the high levels of WEE1 expression in CAL51 cells and luminal and HER2 breast cancers. (Harris Haematoxylin/DAB staining; original magnification ×200). b. High levels of WEE1 expression are preferentially expressed in luminal breast cancers. Cases were scored according to the Allred scoring system as described in the materials and methods. For each tumour type the percentage of tumours with high WEE1 expression is shown. High WEE1 expression showed a statistically significant direct correlation with expression of oestrogen and progesterone receptors and cyclin D1, and a significant inverse correlation with tumour size, histological grade and expression of epidermal growth factor receptor (EGFR), cytokeratin (Ck) 14, Ck 5/6, Ck 17, MIB-1 labelling index and caveolins 1 and 2. No correlations between WEE1 immunohistochemical expression and presence of lympho-vascular invasion, lymph node metastasis, HER2 expression or gene amplification, p53 expression, and CCND1 and MYC gene amplification was found , (data not shown). All cases were classified into luminal, HER2 and basal-like groups according to the immunohistochemical panel described by Nielsen et al. .