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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