The Virtual Patient: The Analytical Challenge

Ruedi Aebersold, Ph.D

Institute of Molecular Systems Biology, ETH-Zrich; Faculty of Science, University of Zrich SystemsX.ch

JOINT STATEMENT BY PRESIDENT CLINTON AND PRIME MINISTER TONY BLAIR

PRESIDENT CLINTON ANNOUNCES THE COMPLETION OF THE FIRST SURVEY OF THE ENTIRE HUMAN GENOME Hails Public and Private Efforts Leading to This Historic Achievement

June 26, 2000 Today.!

Press release US. Govt.

....announced that the international Human Genome Project and Celera Genomics Corporation have both completed an initial sequencing of the human genome -- the genetic blueprint for human beings.He congratulated the scientists working in both the public and private sectors on this landmark achievement, which promises to lead to a new era of molecular medicine, an era that will bring new ways to prevent,diagnose, treat and cure disease.!

Now, scientists will be able to use the working draft of the human genome to:!

* Alert patients that they are at risk for certain diseases. !

* Reliably predict the course of disease. !

Precisely diagnose disease and ensure the most effective treatment is used. !

Developing new treatments at the molecular level.!

Press release US. Govt.

GENOTYPE PHENOTYPE LINK (CA 2000)

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Genome Phenotype

GENOTYPE PHENOTYPE LINK (CA 2012)

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Genome Phenotype Environm

ent,

Epigenome

Genotype Phenotype Prediction

To predict phenotype from genotype we need:

Complete genomic sequence Knowledge of perturbations and

epigenome Algorithm how the cell/body computes a

response to perturbations (Systems Biology)

Postulate

Accurate, quantitative measurements of the acute state (molecular phenotype) of a patient substitute for the present lack of understanding (perturbations,

algorithm)

Acute State Measurement

When the subjective symptoms are more or less well defined and known, the physician collects objective physical signs of illnesses by doing or ordering the:

Physical examination

Laboratory tests (PSA, CEA, CA125, HDL.)

Radiological or CT imaging

Source: Denis Hochstrasser

NETWORK AS LINK BETWEEN GENOME AND PHENOTYPE

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Genome

Protein Network

Phenotype Environm

ent,

Epigenome

The Virtual Patient and the Acute Network State

Measure network nodes (and edges): Longitudinally Comprehensively Quantitatively accurate Reproducibly at high Throughput

A

A snapshot of the molecular state of patient, in situ and remotely

The Virtual Patient: The Vision

A

Genomics: Identify risk factors and predispositions Identify high risk populations

Acute network state measurements: Quantify the acute state by longitudinal measurements in risk groups Quantify network state to assess therapeutic efficacy Quantify re setting of perturbed networks

Generating complete proteome map via SWATH-MS (Sequential Window Acquisition of all THeoretical Mass Spectra)

Principle: Generate digital record for all objects and relate them with digital map

Gillet et al, 2012

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min 10 20 30 40 50 60 70 80 90 100 110

Swath Acquisition Mass Spectrometry: Principle

Digital record of all proteins and a permanent record

Recording time:

Targeted Proteomics of Protein Networks

Contained in list Not on list

486 proteins of reconstructed prostate protein network by: - Literature mining - mRNA profiling - in silico

prediction (genome)

Mapped onto KEGG Pathways in Cancer

CollaboraRon: Chris Sander group MSKCC

Protein Network: whole cell lysate: SWATH / SRM

In situ measurements of whole cell lysate: - SWATH - S/MRM

Virtually the whole network quanRfiable;

NETWORK AS LINK BETWEEN GENOME AND PHENOTYPE

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Genome

Protein Network

Phenotype Environm

ent,

Epigenome

Testable Predictions

1. The ensemble of cancer mutations cluster around related functional modules

2. The functional modules affected by the ensemble of cancer mutations are related to the cancer phenotype

3. The functional modules affected by the ensemble of cancer mutations is detectable in situ (tissue) and remotely (blood)

RELATION OF CAPS AND GENOMIC MUTATIONS IN OC

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FuncRonal mutaRons and epigeneRcally silenced genes in OC

Reactome funcRonal interacRon network (RFIN)

Cancer-associated proteins

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GENOMIC MUTATIONS IN OVARIAN CANCER (OC)

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Frequency of non-silent mutaRons in serous ovarian cancers

Only 18 mutaRons occur in 10 or more paRents

Non-silent mutaRons

Num

ber of paR

ents

Bell et al. Integrated genomic analyses of ovarian carcinoma. Nature (2011) vol. 474 (7353) pp. 609-615

121 funRonal mutaRons and 167 epigeneRcally silenced genes in OC

PHENOTYPIC LIST OF CANCER-ASSOCIATED PROTEINS (CAPS)

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Cancer associated proteins (CAPs): Molecular phenotypes

Polanski et al. A list of candidate cancer biomarkers for targeted proteomics. Biomark Insights (2007) vol. 1 pp. 1-48

1261 proteins with differenRal abundance in various human cancers

Plasma proteins: 274

Tissue proteins: 542

mRNA: 656

RELATION OF CAPS AND GENOMIC MUTATIONS IN OC

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Genomic mutaRons

Cancer-associated proteins

Other interacRng proteins

Subnetwork of funcRonally mutated genes and epigeneRcally silenced

genes in ovarian cancer is enriched for cancer-associated proteins

(p-value < 1e-17)

Hfenhain et al. A mass spectrometric map for reproducible quanRficaRon of cancer-associated proteins in body fluids. Under revision

NETWORK PREDICTED PROTEINS DETECTED REMOTELY

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QuanRficaRon of OVA1 proteins and 21 network predicted proteins by SRM in plasma of ovarian cancer paRents (n = 64) and paRents with benign ovarian tumors (n = 16)

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