A Pan-Cancer Signature Catalog to Classify Tumor Mixtures:

Application to Recognition of Metastatic Disease in Prostate Cancer

Kiley GraimUC Santa Cruz

Motivation

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TCGA has many high quality primary tumor samples,

but metastasis kills

Which primaries will metastasize?

Image courtesy of wikimedia commons

3 Possible Scenarios

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Primary Subtype Metastatic Subtype

If true, may use signature as an early sign of aggressive disease.

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Do a restricted subset of primary subtypes share gene expression signatures with metastatic disease?

Multiple Datasets to Define Primary and Metastatic Gene Expression Signatures• n Dataset #

Normal# Primary # Metastatic # Genes

Cai (2011) 0 22 29 10,523Chandran (2007) 0 10 21 14,997

Grasso (2012) 28 59 32 15,830GTEx (2014) 42 0 0 13,256

Monzon (2007) 52 65 25 9,383Taylor (2010) 29 131 19 19,923

TCGA 21 246 0 20,500Joint 172 533 126 4,895

4831 Samples (659 Tumor)

Removal of Batch and Dataset Effects

• << new before/after combat PCA plots >>• << add indicat

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Before After

Batch effect removal via COMBAT (R package ‘sva’)

Removal of Batch and Dataset Effects

• << new before/after combat PCA plots >>• << add indicat

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Before After

Batch effect removal via COMBAT (R package ‘sva’)

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4 Primary Subtypes Identified from

Multiple Datasets (Including TCGA)

K = 4

Subtype 1 vs. Not

Subtype 2 vs. Not

Subtype 3 vs. Not

Subtype 4 vs. Not

Primary Subtype Predictors• Multinomial elastic

net to predict primary subtypes

• Trained using primary data

• Leave-one-out cross-validation

• Apply to metastatic samples

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Samples

SubtypeNot Subtype

How Robust Are the Predictors?

Balanced Success Rate = 0.991 9

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K = 3

3 Met Subtypes Identified from

Multiple Datasets (None TCGA)

Predicted Primary Cluster 11

The Majority of Mets Are Predicted to Be Primary Subtype 2

Met-like primaries

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Met-Like Primaries Have Higher Gleason and Higher Tumor Grade

pval = 0.0e-3

FDR = 0.0e-3

pval = 0.0e-3

FDR = 0.0e-3

Met-like primaries

Predisposition for Movement and Metastasis

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pval = 0.0e-3

FDR = 0.0e-3

pval = 0.0e-3

FDR = 0.0e-3

MILI_PSEUDOPODIA_HAPTOTAXIS_UP BIDUS_METASTASIS_UP

Are There Networks that Distinguish Met-like Primaries from the Others?

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PathMark Overview of Distinguishing Networks of Met-Like Primaries

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Proliferation-Related Subnetwork

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MYB/MYC Subnetwork

Acknowledgements

Yulia Newton Adrian Bivol Robert Baertsch Artem Sokolov Christina Yau (Buck Institute) Joshua M. Stuart

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Subtype Pipeline

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TCGA

Taylor

Joint primaries, mets, normals

CombatBatch effectadjusted joint

MetsPrimaries

ConsensusClustering

Normalizedjoint

ExponentialNormalization

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