Genomics:

Personalized Medicine

in Brain Cancer?

Stephen Shiao MD, PhD

Assistant Professor

Cedars-Sinai Medical Center

Department of Radiation Oncology

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What is genomics?

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The relationship between DNA, RNA and Protein

www.whoi.edu

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Why genomics and cancer?

Cancer is a disease of

Identification of all the genomic changes

would help define new and more detailed

cancer subsets which has the potential to

transform drug targeting, diagnosis and

prevention of cancer

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Cancer and the Genomics Revolution

Cancer biology and genome sequencing technology have advanced together at extraordinary rates

Cancer genomics have identified over 500 genes associated with various cancers

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Next Generation Sequencing

Massively parallel sequencing has dramatically enhanced sequencing time: 1980s – slab gel sequencing, time to sequence a single human genome = 146 years 1990s – capillary sequencing, human genome = 7.5 years 2005 Massive parallel pyrosequencing, human genome = 33 days 2007 Sequencing by synthesis, human genome = 15 days 2010 Single molecule sequencing, human genome = 4 hours 2013 Multiple new parallel sequencing techniques, human genome = 15 minutes

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Next Gen Sequencing: Gene Regulation

Epigenetics (DNA,

Histone Methylation)

NoncodingRNA, MicroRNA

(lncRNA, miRNA)

Copy number alterations

(Single-nucleotide

polymorphism (SNP)

analysis)

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The Age of Bioinformatics:

Network and Functional Analysis

Mapping genomic data onto both known and inferred regulatory

networks is the next level of analysis being applied to cancer biology

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The Cancer Genome Atlas

Traditional pathologic classification has been problematic in that they have no biological basis and were unable to predict rational therapeutic strategies for any given tumor

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Glioblastomas are heterogeneous

Verhaak et al. Cancer Cell. 2010.

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Subtypes can predict survival

Lin et al. PLoSOne. 2014.

Why do subtypes

predict survival and can

we change our practice

to find better targets?

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The Dream

As a new generation of drugs are developed

that target specific protein targets,

personalized treatment for brain cancer will

mean more than classifying patients but rather

identifying small subset of patients who are

likely to respond to a particular agent.

Drug signatures may have the potential to

guide clinical trial by enabling the selection of

patients who have the best chance of

responding to the drug under investigation.

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Chemosensitivity can be tested in vitro

Pathway specific gene expression

Drug specific gene expression

signatures

Gene Chips

Foundation Medicine

Cedars-Sinai

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Genomics in Action: The Case of WEE1

Wuchty and colleagues

integrated miRNA and gene

expression data from glioma

tumor samples and found a

network of miRNAs strongly

associated with the kinase WEE1

Mir and colleagues profiled protein

expression level of all human

kinases between different cancers

and demonstrated that the Wee1-

like protein kinase is overexpressed

in GBM

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What is WEE1?

WEE1 is a kinase that mediates DNA-

damage induced cell cycle arrest which

allows mutated tumor cells to keep

dividing despite DNA damage

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From Genomics to Human Trials

Mir et al found that genetic or pharmacologic

inhibition of WEE1 sensitizes glioma cells to radiation

and DNA damaging agents in cells and mice

This observation led Merck to develop a WEE1

inhibitor (MK-1775)

NCT01849146:

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Challenges in the Age of Genomics:

Too much of a good thing?

Management and curation of large amounts

of genome-wide data

Integration of genomic data to understand

how diverse alterations in cellular networks

gives rise to brain tumors

Translation into therapy

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Genomics at Cedars: Ongoing Projects

Modeling GBM in mice (Breunig Laboratory)

Genomic pathway analysis for tailored therapy

(Cedars-Sinai Pathology and Foundation Medicine)

Genomic analysis – Genome Wide Association

Studies (GWAS) (Cedars-Sinai Medical Genetics

Research Institute)

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Conclusions

Database infrastructure is currently being developed and

deployed to efficiently warehouse information to allow both

computation and molecular biologists to perform integrated

genome-scale analysis of clinical tumor samples on scale

previously unimaginable

Bioinformaticians have developed approaches for analyzing

this information have led to improve classification of tumor

subtypes with corresponding insights into glioma biology

We are just beginning to probe the dense web of connected

intracellular pathways that drive the formation, progression

and response to treatment of brain tumors

The challenge for researchers, physicians and patients is now

to use this information to develop treatment plans that

incorporate this information to maximize the outcome for

each patient

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Useful Links

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http://cancergenome.nih.gov

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http://arstechnica.com/science/2009/09/a-

brief-guide-to-dna-sequencing/

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References

1. Riddick, G. & Fine, H.A. Integration and analysis of genome-scale data

from gliomas. Nature reviews. Neurology , 439-450 (2011).

2. Wuchty, S., et al. Prediction of Associations between microRNAs and

Gene Expression in Glioma Biology. PLoS One , e14681 (2011).

3. Mir, S.E., et al. In silico analysis of kinase expression identifies WEE1

as a gatekeeper against mitotic catastrophe in glioblastoma. Cancer

cell , 244-257 (2010).

4. Cancer Genome Atlas Research, N. Comprehensive genomic

characterization defines human glioblastoma genes and core

pathways. Nature , 1061-1068 (2008).

5. Verhaak, R.G., et al. Integrated genomic analysis identifies clinically

relevant subtypes of glioblastoma characterized by abnormalities in

PDGFRA, IDH1, EGFR, and NF1. Cancer cell , 98-110 (2010).

6. Brennan, C.W., et al. The somatic genomic landscape of glioblastoma.

Cell , 462-477 (2013).