Dr Michelle Hill
The University of Queensland Diamantina Institute
“Turning scientific discoveries into better treatments...”
The University of Queensland Diamantina Institute (UQDI) was established on
1st January 2007 as the sixth research institute of The University of Queensland.
The location of UQDI on the Princess Alexandra Hospital campus is key to the
institute’s mission, “to translate scientific discoveries into better treatments”.
UQDI is now part of Translational
Research Institute (TRI), a state-
of-the-art facility housing four
research institutes to promote
better collaborative innovation.
TRI houses 650+ researchers and
is the first of it’s kind in Australia,
allowing biopharmaceuticals and
treatments to be discovered,
produced, clinically tested and
manufactured in the one location.
Research at UQDI
Immune-related diseases
• Rheumatoid arthritis
• Type 1 diabetes
• Infection & immunity
Cancer
• Skin cancers
• Head & Neck cancer
• Cancer vaccine & immunotherapy
Genomics & Proteomics technology
• Susceptibility genes, disease etiology
• Biomarkers
Omics in translational biomarker research
Biomarker
• Measurable attribute that can be used to indicate or predict physiological status
– Blood pressure
– Imaging
– Metabolite/chemicals (e.g. blood glucose)
– Genomic (mutation or expression level)
– Protein (e.g. PSA)
Simon 2011 EMBO Mol Med 3, 429
Genomic
Proteomic
Metabolomic
Imaging
Genomic
Pharmacogenomic
Proteomic
Metabolomic
Imaging
Prognostic
Theragnostic
Predictive
Annual PubMed records for
‘diagnostic biomarkers’
(Moschos 2012 Bioanalysis)
Approved In vitro
diagnostics (IVD)
In vitro diagnostic (IVD)
“reagents, instruments, and systems intended for use in the diagnosis of disease or other conditions, including a determination of the state of health, in order to cure, mitigate, treat or prevent disease...”
(FDA guideline, Title 21 of Code of Federal Regulations)
Classification based on:
• Intended use – what the test measures (biomarkers)
• Indications for use – why a patient would be tested
Approval requires:
• Preclinical evaluation – demonstrates accurate and
reproducible measurements
• Clinical performance – shows that the device provides the
expected results in a defined patient population for intended use
Mansfield et al. 2005 J Mol Diag
Bridges over the valley of death: From biomarker to IVD
• Clearly defined clinical intended use
• Sufficient preliminary evidence from multiple cohorts
• Select/develop suitable clinical assays
• Design appropriate clinical trial for regulatory approval
Vidal et al. 2012 Clin Proteomics
Multidisciplinary & multi-centre:
Clinical – sample collection with controlled standard procedures
Technology – establish standard measurement conditions
Informatics & Statistics – consistent rigorous analysis
Team decision making – when to drop biomarkers
National Cancer Institute Early Detection Research Network
(EDRN)
2001-2003
biomarker development paradigm,
standardize collection and banking of non-invasive
biosamples with comprehensive clinical data
2006-2008
Prospective Specimen Collection Retrospective
Blinded Evaluation (PRoBE) design for
phase 2 and 3 biomarker validation trials
1998-2000
inception & inauguration
2003-2005
establish partnerships,
collaborative projects,
bioinformatics tools
2008- present
delivery of clinically useful
biomarkers:
300+ passed phase 2
(300+ did not)
1450+ publications
28+ patents, 14+ licences
Adapted from Srivastava 2013 Clin Chem
EDRN five phase biomarker development paradigm
Phase 1 • Preclinical discovery: Distinction between normal and cancer
Phase 2
• Preclinical verification: Reproducibility of markers
• Development of suitable clinical assay: Portability of assay format
Phase 3
• Preclinical validation: Evaluation of sensitivity & specificity for clinical indication
Phase 4 • Clinical evaluation: Estimation of false positive and false negative rates
Phase 5 • Disease Control: Evaluation of overall benefits & risks of the test
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2001-2003
biomarker development paradigm,
standardize collection and banking of non-invasive
biosamples with comprehensive clinical data
2006-2008
Prospective Specimen Collection Retrospective
Blinded Evaluation (PRoBE) design for
phase 2 and 3 biomarker validation trials
1998-2000
inception & inauguration
2003-2005
establish partnerships,
collaborative projects,
bioinformatics tools
2008- present
delivery of clinically useful
biomarkers:
300+ passed phase 2
(300+ did not)
1450+ publications
28+ patents, 14+ licences
Adapted from Srivastava 2013 Clin Chem
National Cancer Institute Early Detection Research Network
(EDRN)
Omics discovery $$$$
Clinical assay $
EDRN five phase biomarker development paradigm
Phase 1
• Preclinical discovery: Distinction between normal and cancer
Phase 2
• Preclinical verification: Reproducibility of markers
• Development of suitable clinical assay: Portability of assay format
Phase 3
• Preclinical validation: Evaluation of sensitivity & specificity for clinical indication
Phase 4
• Clinical evaluation: Estimation of false positive and false negative rates
Phase 5
• Disease Control: Evaluation of overall benefits & risks of the test
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Moschos 2012 Bioanalysis 4, 2499
Less than ¼ of new molecular in vitro
diagnostics approved by US FDA since
1995 use nucleic acid biomarkers
Which Omics for biomarker discovery?
Moschos 2012 Bioanalysis 4, 2499
Assay capable of predicting drug dose, efficacy or safety risk of a drug
Companion diagnostic
Manjili et al. 2012 Future Onc 8, 703
In vitro diagnostic multivariate index assay (IVDMIA)
An IVD that measures 2 or more independent variables in
parallel, and a scoring algorithm
Moschos 2012 Bioanalysis 4, 2499
Why proteins?
• Simple, specific and sensitive assay with antibodies
• Proteome but not genome rapidly modulated by
disease/treatment : disease detection vs disease risk
• Can be actively released or shed from cells
• Body fluid detection desirable over tissues because:
- less invasive, allows repeated sampling - reduced sampling error (tumour heterogeneity)
- ability to detect microenvironmental changes (increase
specificity or sensitivity)
Less than ¼ of new
molecular in vitro
diagnostics approved
by US FDA since 1995
use nucleic acid
biomarkers
Anderson & Anderson 2002 MCP
Comparative proteomics in blood is challenging!
Strategies for body fluid protein biomarker discovery
• Depletion of abundant proteins
• Target sub-proteome
– Glycoproteins
– Exosome/microvesicles (small circulating vesicles, also contain DNA and RNA)
Glycosylation changes of circulating proteins as biomarker
• Glycosylation changes implicated in cancer pathogenesis
- Change in glycosylation machinery in the cancer cell
- Neo-expression in stromal cells, which has a different profile of
glycosyltransferases
• Lectins as affinity reagent which binds to specific glycan structures: readily
adaptable for clinical assay
• Glycosylation changes more specific than changes in protein, e.g. AFP-L3 test for
fucosylated form of a-fetoprotein
Lectin Abbrev. Ligand moiety Related cancers
Aleuria aurantia lectin AAL Core fucosylation Liver, lung, breast, colon,
pancreatic, esophageal etc.
Helix pomatia agglutinin HPA GalNAc Breast cancer
Elderberry lectin SNA α2-6-linked sialic acid Pancreatic cancer
Lectin-magnetic bead array-coupled mass spectrometry (LeMBA-MS) for glyco-biomarker discovery
GlycoSelect database biomarker selection pipeline for LeMBA-MS
Data entry/storage Lectin-protein pairs
Analysis
1. Patient selection
2. Normalize to internal standard
3. Sample outlier detection
4. Identify on/off changes using group
difference tool
5. Ranking of quantitative changes
using sPLS-DA
(sparse Partial Least Squares regression-
Discriminant Analysis,
Le Cao et al. 2011 BMC Bioinformatics)
David Chen, Kim-Anh Le Cao
Phase 1 discovery for oesophageal adenocarcinoma (EAC)
Goal: Obtain a list of differentially glycosylated serum proteins in oesophageal
adenocarcinoma (EAC) by comparing with matched samples from the pre-cancer
condition Barrett’s oesophagus (BE) and controls.
Multidisciplinary team
PhD student ( Alok Shah)
Epidemiologist & biological samples
(David Whiteman, Australian Cancer
Study, PROBE-NET)
Oncology surgeon (Andrew Barbour)
Informatics (David Chen)
Biostatistics (Kim-Anh Le Cao)
Nanotechnology for diagnostic device
(Matt Trau)
Discovery cohort
Phase 1 discovery LeMBA-MS/MS outcomes
Phase 1
• Preclinical discovery: Distinction between normal and cancer
Phase 2
• Preclinical verification: Reproducibility of markers
• Development of suitable clinical assay: Portability of assay format
Phase 3
• Preclinical validation: Evaluation of sensitivity & specificity for clinical indication
Phase 4
• Clinical evaluation: Estimation of false positive and false negative rates
Phase 5
• Disease Control: Evaluation of overall benefits & risks of the test
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Summary
• Clinical utility of biomarkers when translated into IVD.
• Discovery and development requires multi-disciplinary, multi-institutional team.
• Omics technologies with rigorous statistical assessment essential in biomarker discovery.