The kinome 'at large' in cancer

Key Points

  • Application of high-throughput omics technologies has provided important and complementary insights into dysregulation of protein kinases in human cancer and their functional roles.

  • By interrogating a series of recent studies aimed at identifying cancer 'driver' genes causally implicated in cancer development from analysis of cancer genomes, we have identified a list of 91 protein kinases that represent likely cancer drivers. However, the number of protein kinases subject to functionally relevant mutations is likely to be greater, in part reflecting the incidence of non-recurrent mutations that affect signalling networks in a highly context-dependent manner.

  • The list of high-confidence protein kinase cancer drivers includes kinases with well-established roles in cancer development, such as various receptor tyrosine kinases, as well as novel oncogenes and tumour suppressors, such as TATA box binding protein-associated factor 1 (TAF1) and never in mitosis A-related kinase 9 (NEK9).

  • Approximately three-quarters of the high-confidence drivers are either targets for US Food and Drug Administration-approved therapies or amenable to therapeutic targeting through repurposing of existing therapies or further development of those at the preclinical stage. However, there is a substantial need to develop therapeutic strategies that exploit the vulnerabilities conferred by loss of function alterations in specific tumour suppressor kinases.

  • High-throughput analysis of cancer proteomes and sub-proteomes by application of reverse phase protein arrays and mass spectrometry has identified cancer-associated perturbations in protein kinase expression and activity that would not be detected by genomic and transcriptomic approaches. This reflects post-transcriptional regulation of kinase activity at the level of protein expression and post-translational modification.

  • Novel insights provided by proteomics approaches include identification of patterns of kinase activation conserved across various different cancers, the determination of specific tyrosine kinases implicated in non-small-cell lung cancer and basal breast cancer, and characterization of kinome remodelling in response to administration of particular targeted therapies.

  • Functional genomic approaches enable characterization of context-dependent cellular dependency on particular protein kinases and identification of protein kinases that sensitize cancer cells to specific therapies.

  • Integration of particular omics approaches often provides novel insights not provided by individual methodologies, and enables a network-level understanding of kinase signalling that can lead to novel therapeutic opportunities.

Abstract

Over the past decade, rapid advances in genomics, proteomics and functional genomics technologies that enable in-depth interrogation of cancer genomes and proteomes and high-throughput analysis of gene function have enabled characterization of the kinome 'at large' in human cancers, providing crucial insights into how members of the protein kinase superfamily are dysregulated in malignancy, the context-dependent functional role of specific kinases in cancer and how kinome remodelling modulates sensitivity to anticancer drugs. The power of these complementary approaches, and the insights gained from them, form the basis of this Analysis article.

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Figure 1: Driver protein kinases identified by genomic studies.
Figure 2: Assignment of driver kinases to core cellular pathways and processes.
Figure 3: Status of therapeutic development for driver kinases.
Figure 4: Comparison of deregulated protein kinases in non-small-cell lung cancer detected by genomic studies and phosphoproteomic profiling.
Figure 5: Different omics approaches provide complementary information regarding kinase function in cancer.

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Acknowledgements

R.J.D. is supported by a National Health and Medical Research Council (Australia) Principal Research Fellowship (APP1058540), J.W. is supported by a Cancer Council New South Wales grant (SRP11-01), and E.D.G.F. was supported by the Dutch Cancer Society for her postdoctoral position in Australia.

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Correspondence to Jianmin Wu or Roger J. Daly.

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Glossary

PTEN

A phosphatidylinositol 3,4,5-trisphosphate 3-phosphatase that antagonizes the PI3K signalling pathway and represents an important tumour suppressor in several human cancers.

Reverse phase protein arrays

(RPPAs). Microarrays carrying large numbers of protein samples printed as individual spots, with detection of particular antigens achieved via incubation with a specific antibody.

Breast cancer mRNA subtypes

Breast cancer can be subclassified into four major subtypes through gene expression profiling: luminal A, luminal B, HER2 and basal.

Inositol polyphosphate 4-phosphatase type II

A phosphatidylinositol 3,4-bisphosphate 4-phosphatase that antagonizes the PI3K signalling pathway and represents a tumour suppressor.

Liquid chromatography–tandem mass spectrometry

(LC–MS/MS). When applied to proteomics, the liquid chromatography fractionates the peptides present in a sample and the tandem MS determines peptide mass and then additional characteristics through fragmentation.

Metal or metal oxide affinity chromatography

A technique used to purify phosphopeptides that exploits their binding to metal ions (such as iron) or metal oxides (such as titanium dioxide).

Pseudokinase

A protein with a protein kinase-related domain that does not exhibit kinase activity owing to the absence of one or more conserved amino acid sequence motifs.

NCI-60 cell line panel

A panel of 60 diverse human cancer cell lines used by the US National Cancer Institute to screen large numbers of chemical compounds, drugs and natural products for their biological activity.

Sleeping Beauty transposon system

A technique that introduces a DNA vector at random sites throughout the mouse genome and thereby alters the expression of genes close to the insertion site.

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Fleuren, E., Zhang, L., Wu, J. et al. The kinome 'at large' in cancer. Nat Rev Cancer 16, 83–98 (2016). https://doi.org/10.1038/nrc.2015.18

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