Computational biology of cancer cell pathways

Modelling of cancer cell function and response to therapy

Signalling pathways

Signal from outside cell

Signal from inside cell

Source: Biocarta database

Epidermal growth factor (EGF) signalling

Signal from outside cell

Gene expression

Signal from outside or inside cell

Signal transmitted to genome

Changes in gene expression = cell

response to signal

Information about cell’s environment

and internal state is coupled to gene

expression

Signalling pathways

Receptors

E.g., kinases

Transcription factors

Mutations in cancer

• Point mutations - changes in protein sequence or control sequences

• Genome instability: Loss or gain of single genes or chromosome portions (many genes)

Abnormal amounts of proteins

Abnormal function, e.g always ‘switched on’ or inactivated

Signalling pathways in cancer cells

Mutations in cancer

• Point mutations - changes in protein sequence or control sequences

• Genome instability: Loss or gain of single genes or chromosome portions (many genes)

Abnormal amounts of proteins

Abnormal function, e.g always ‘switched on’ or inactivated

Changes in information processing underpin hallmarks of

cancer

Signalling pathways in cancer cells

Signalling pathwaysin cancer cells

Epidermal growth factor receptor (EGFR)

• Overexpression of EGFR is common in many solid tumours

• Correlates with increased metastasis, decreased survival and a poor prognosis

• Protects malignant tumour cells from the cytotoxic effects of chemotherapy and radiotherapy, making these treatments less effective

EGFR is the target for several new anticancer therapies

EGFR-targeted therapy

cell surface portion

binds epidermal growth factorintracellular tyrosine kinase transmit signal by phosphorylation

CE

LL M

EM

BR

AN

E

EGFR-targeted therapy

Small molecule inhibitors

Therapeutic antibody: Cetuximab (colorectal cancer)

Inhibition of EGFR

• Both types of inhibitors block signalling from the EGF receptor

• Inhibition limits tumour growth, dissemination, angiogenesis

• Reduces resistance to chemotherapy and radiotherapy

• Aids the induction of cell death (apoptosis)

Not a linear pathway, but a complex network

Genome

Growth factor (EGF)

Receptor tyrosine kinase

PLC Ras PI3K

PKC MAPK PKB/Akt

TFs Functional targets

CELL GROWTH AND PROLIFERATION

ERK

Cross-activation by other pathways

Not a linear pathway, but a complex network

Signal processing by the entire network and mutations or expression changes in signal proteins can limit response to therapy or cause side effects.

Not a linear pathway, but a complex network

Complexity needs to be modelled in the computer

Computer models of pathways need biochemical kinetic data for every connection.

Enable one to simulate – the change in concentration or– activation (eg. phosphorylation)of the proteins of the pathway

over time.

Modelling gives information on how signals are processed.

The effect of the number of active EGFR molecules on ERK activation

EGFR

PLC Ras PI3K

PKC MAPK PKB/Akt

TFs Functional targets

CELL GROWTH AND PROLIFERATION

ERK

The effect of the number of active EGFR molecules on ERK activation

Schoeberl et al., 2002, Nat. Biotech. 20: 370

500,000 active receptors

50,000 active receptors =

Inhibition by one order of magnitude

EGFR

PLC Ras PI3K

PKC MAPK PKB/Akt

TFs Functional targets

CELL GROWTH AND PROLIFERATION

ERK

The effect of active EGFR number on ERK activation

500,000 active receptors

50,000 active receptors

Can this be achieved by receptor inactivation alone?

The effect of active EGFR number on ERK activation

… Or, what might happen if

• ERK is overexpressed?

• Several proteins in the pathway are abnormally expressed?

The effect of active EGFR number on ERK activation

50,000 active receptors

with normal levels of ERK

or

ERK overexpression and cross-activation

Computer models of pathways• Integration of complex knowledge

– Biological processes are mediated by pathways in health and disease

– Modelling aids integrative understanding of relationships between physiology and clinical observations and the molecular level

• Analysis and simulation of signal processing in cancer cells

– Effects of mutations and abnormal gene expression– Discovery of new targets for therapy: key modulators of pathway

function– Effects of therapeutic inhibitors– Possible side effects

Effects of abnormal gene expression

• Roughly 90% of human cancers are epithelial in origin and exhibit a large number of changes in the structure and function of the genome.

• Abnormal expression levels can be observed for a a large number of genes.

• This complexity might be the reason for the clinical diversity of tumours (even with similar histology).

• A comprehensive analysis of the multiple genetic alterations present is required for an understanding of abnormal signal processing in cancer and differences between tumours.

Gene expression analysis

• The use of expression microarrays enables the large-scale analysis of mRNA expression (expression profiling) in tumour samples.

• Expression profiling can be used to simultaneously

assess the expression of the entire human genome.

• mRNA concentration is used as a surrogate for protein conc. - protein concentrations may be hypothetically inferred.

ER-positive breast tumour subtype has a distinct microarray expression profile

ER = oestrogen receptor

Example: Gene expression profiles from breast cancer patient samples

Role of ER and EGFR in anti-oestrogen therapy

• Response to tamoxifen is dependent on ER expression.

• Overexpression of EGFR is associated with tamoxifen resistance - EGFR as a target for therapy.

• Differences in expression of EGFR and other proteins in the network between patients?

• May account for different responses to therapy with EGFR inhibitors.

ER-positive tumours

genes

EGFR

EGFR as a target for therapy

Modelling of individual response

Gene expression of EGFR network genes in each individual tumour

Approximation of relative changes in protein expression

• Input in computer model

• Model signal processing in different tumours in response to EGFR inhibition

• Hypothesis generation re. response

• Validate with clinical response

Caveat: may be not directly comparable – direct measurement of protein concentration

Summary

Molecular changes in cancer are highly complex.

They affect signal processing in pathways and networks.

Changes in signal processing underpin hallmarks of cancer.

Computer modelling gives information on how signals are processed.

Modelling aids fundamental understanding of cancer, discovery of new targets for therapy, prediction of effects of therapy and possible side effects.