genomics: personalised medicine in brain cancer?
DESCRIPTION
Stephen Shiao MD, PhD, Assistant Professor Cedars-Sinai Medical Center, Department of Radiation OncologyTRANSCRIPT
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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
-
http://cancergenome.nih.gov
-
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).