genomic analysis methods for identification of cancer ... fall ci4cc 2017.pdf · isabel bjork holly...

Lauren Sanders, PhD student Treehouse Childhood Cancer Initiative

UC Santa Cruz

CI4CC Fall 2017 Symposium & Workshop October 24, 2017

Genomic Analysis Methods for Identification of Cancer Driver

Pathways in Childhood Brain Tumors

•  Treehouse genomic analysis of pediatric tumors

•  Motivation

•  Gene expression outlier analysis

•  Outlier analysis of diffuse intrinsic pontine glioma

•  Outlier gene identification in DIPG cohort

•  Validation in DIPG cell lines

Outline

•  Treehouse genomic analysis of pediatric tumors

•  Motivation

•  Gene expression outlier analysis

•  Outlier analysis of diffuse intrinsic pontine glioma

•  Outlier gene identification in DIPG cohort

•  Validation in DIPG cell lines

Outline

GadGetz,BroadIns/tute

PediatriccancersAdultcancersassociatedwithcarcinogen

Pediatric cancers are different: fewer and distinct mutations than found in adult cancers

- Adult cancer genomes often have many (order of 100 or more) mutations - Pediatric cancer genomes often have few (order of 10 or fewer) mutations

Can genomics point to more treatments for children with cancer?

•  Treehouse genomic analysis of pediatric tumors

•  Motivation

•  Gene expression outlier analysis

•  Outlier analysis of diffuse intrinsic pontine glioma

•  Outlier gene identification in DIPG cohort

•  Validation in DIPG cell lines

Outline

Focus on RNA expression

•  Hypothesis: RNA gene expression can be used as

a proxy for protein & pathway activity

Focus on RNA expression

•  Hypothesis: RNA gene expression can be used as

a proxy for protein & pathway activity

•  Many cancer pathways already have adult drugs developed to target them

Focus on RNA expression

•  Hypothesis: RNA gene expression can be used as

a proxy for protein & pathway activity

•  Many cancer pathways already have adult drugs developed to target them

•  Can we find abnormal activity of cancer pathways in pediatric tumors?

livercarcinoma

prostateadenocarcinoma

kidneycarcinomabreastcarcinoma

thyroidcarcinoma

ovariancystadenocarcinoma

glioma

glioblastoma

11,000+ tumors 78 tumor types

Treehouse cancer compendium

TumorMap:LaurenSanders,TeresaSwatloski,YuliaNewton

Expression level of gene in other cancers

Gene expressed at an abnormally high level “up outlier”

Gene expressed at an abnormally

low level “down outlier”

Treehouse gene expression outlier analysis

Outlieranalysis:1)Lessonslearnedfromtheapplica2onofwhole-genomeanalysistothetreatmentofpa2entswithadvancedcancersColdSpringHarbMolCaseStud.2015Oct;1(1):a000570.2)Evolu2onofanadenocarcinomainresponsetoselec2onbytargetedkinaseinhibitorsGenomeBiol.2010;11(8):R82.

Two Types of Outlier Analysis Pan-cancer analysis The sample is compared to the pan-cancer compendium of 11,000+ other tumor samples Pan-disease analysis The sample is compared to only the samples from the tumor types most similar to the sample itself

Treehouse gene expression outlier analysis

•  Treehouse genomic analysis of pediatric tumors

•  Motivation

•  Gene expression outlier analysis

•  Outlier analysis of diffuse intrinsic pontine glioma

•  Outlier gene identification in DIPG cohort

•  Validation in DIPG cell lines

Outline

Diffuse Intrinsic Pontine Glioma (DIPG)

•  Affects 200-300 children in the US per year •  Surgical resection is impossible, chemotherapy has been

ineffective, and radiation therapy is only palliative

•  Few recurrent mutations; and those that are recurrent are not clinically actionable

•  Can gene outlier analysis identify clinically actionable over-expressed genes in DIPG?

Outlier analysis identifies known overexpressed genes in a subset of DIPG

PNOCdata:AdamResnick,MikePrados,SabineMueller

PNOCdata:AdamResnick,MikePrados,SabineMueller

Outlier analysis identifies known overexpressed genes in a subset of DIPG

Outlier analysis of DIPG identifies known overexpressed genes: PIK3C2A & PTCH1

PIK3C2Aexpression PTCH1expression

PTCH1overexpressioninDIPG:Compara2veMul2dimensionalMolecularAnalysesofPediatricDiffuseIntrinsicPon2neGliomaRevealsDis2nctMolecularSubtypes,ActaNeuropathol.2014Jun;127(6):881–895.PIK3C2AoverexpressioninDIPG:Mesenchymaltransi2onandPDGFRAamplifica2on/muta2onarekeydis2nctoncogeniceventsinpediatricdiffuseintrinsicpon2negliomas,PLoSOne.2012;7(2):e30313

PNOCdata:AdamResnick,MikePrados,SabineMueller

HMGCR–hydroxy-methylglutarylCoAreductaseHARS–his/dyl-tRNAsynthetase

Outlier analysis of DIPG identifies two novel overexpressed genes

•  Treehouse genomic analysis of pediatric tumors

•  Motivation

•  Gene expression outlier analysis

•  Outlier analysis of diffuse intrinsic pontine glioma

•  Outlier gene identification in DIPG cohort

•  Validation in DIPG cell lines

Outline

Outlier analysis of DIPG cell lines

PNOCdata:AdamResnick,MikePrados,SabineMueller

HMGCR–hydroxy-methylglutarylCoAreductaseHARS–his/dyl-tRNAsynthetase

Carnosine HARSac/vity

Simvasta/n HMGCRac/vity

CanthedrugcrosstheBBB?

Yes

Yes

Carnosine HARSac/vity

Simvasta/n HMGCRac/vity

CanthedrugcrosstheBBB?

Yes

Yes

CourtesyofDr.SameerAgnihotri,UniversityofPi`sburgh

Viability assays: DIPG cell lines

CourtesyofDr.SameerAgnihotri,UniversityofPi`sburgh

Viability assays: normal brain cells

NormalHumanAstrocytes NormalNeuralStemCells

Gene expression outlier analysis

•  Identification of potential therapeutic targets in DIPG patient tumors

•  Target validation in DIPG cell lines revealed decreased viability

Next steps

•  Pathway analysis: Cholesterol biosynthesis pathway

•  Evaluate outlier analysis in larger cohort of DIPG cell lines

Conclusions & Next Steps

UCSC Treehouse Team

Olena Morozova Isabel Bjork Holly Beale Jacob Pfeil

Ellen Kephart Ann Durbin

Sofie Salama David Haussler

University of Pittsburgh Sameer Agnihotri

Acknowledgements

PNOC Consortium Sabine Mueller Michael Prados Adam Resnick

Funding