The Use of Blood Tests in Breast Cancer

For Detection and Treatment

Dr. Emanuel Petricoin

George Mason University

Center for Applied Proteomics and Molecular Medicine

Manassas, VA

703-993-864- phone

703-993-4288- fax

epetrico@gmu.edu

Duffy et al:

•Conclusions: The main disadvantages of existing serum markers for breast cancer

are a lack of sensitivity for low-volume disease and a lack of specificity.

Consequently, the available markers are of no value in either screening or

diagnosing early breast cancer. Although of little use for early diagnosis, however,

CA 15-3 may be the first independent circulating prognostic marker described for

breast cancer.

•Preoperative CA 15-3 concentrations may thus be combined with established

prognostic factors for use in deciding which lymph node-negative breast cancer

patients should receive adjuvant chemotherapy.

•Currently, one of the most widely used applications of tumor markers in breast

cancer is in the follow-up of patients with diagnosed disease. In the absence of data

from a large randomized trial, however, the clinical value of this practice is unclear.

•Finally, CA 15-3 and other markers are potentially useful in monitoring therapy in

advanced disease, particularly in patients who cannot be assessed by standard

modalities.

• None of the available markers is increased in all patients with breast cancer even in

the presence of advanced disease. For those patients with advanced disease

who do not have increased CA 15-3 concentrations, other markers, such as CEA,

TPA, TPS, or the shed form of HER-2, may be considered for monitoring purposes.

• The available markers are most sensitive for detecting distant metastases and are of

little value in diagnosing locoregional recurrences.

• The magnitude of change between successive marker concentrations that

constitutes a critical change is not clear.

• Paradoxical patterns of tumor marker concentrations after initiation of chemotherapy

may occur. For example, transient alterations in marker concentrations can occur after

the commencement of chemotherapy

• Certain benign diseases may give rise to increased marker concentrations. Thus,

chronic active hepatitis, liver cirrhosis, sarcoidosis, hypothyroidism, and megablastic

anemia have all been reported to increase CA 15-3 concentrations.

Conclusions:

We have performed feature-selection and classification techniques to identify blood

serum proteins that are indicative of breast cancer in premenopausal women.

The best features to detect breast cancer were MIF, MMP-9, and MPO.

While the proteins could distinguish normal tissue from cancer and normal tissue from

benign lesions, they could not distinguish benign from malignant lesions.

… it is likely that these proteins play a role in the inflammatory response to a lesion,

whether benign or malignant, rather than in a role specific for cancer.

While the current set of proteins show moderate ability for detecting breast cancer,

their true usefulness in a screening program remains to be seen in their integration

with imaging-based screening practices.

EDRN’s Mission

• To implement biomarker research through systematic, evidence-based discovery, development and validation of biomarkers for:

• cancer risk assessment,

• early detection,

• diagnosis and

• prognosis of cancer

Biomarker Development Pipeline

BDL CVC BRL

Objectives

• Provides a National Infrastructure to support a “vertical”

collaborative approach to move promising

biomarker/technology to clinical validation

• Established guidelines and criteria for the validation

• Developing and instituting quality assurance regimens,

Standard Operating Procedures, etc.

•

• Conduct early clinical and epidemiological studies to

evaluate predictive value of biomarkers

• Foster Public- Private Partnership

Prior to EDRN

Fragmented studies, with discoveries using convenience samples

Results of studies not generalizable

Lack of Standard Operating Procedures for sample collection and study designs

Studies compromised by chance, bias and confounders Lack of evidence for the claimed clinical use

After EDRN

Clinically annotated samples for discovery

Roadmap for biomarker discovery and validation using EDRN five-phase

guidelines and PRoBE design

Well designed multi-center, multi-discipline validation study to minimize chance,

bias, confounders

Well-designed Standard Reference Sample Sets to quickly evaluate biomarkers

for intended clinical uses

Adoption of EDRN-developed guidelines and concept of validation throughout the

biomarker research community

Adoption of EDRN-developed study-design evaluation criteria by the biomarker community and the NIH study sections

Meeting Objectives

National Infrastructure

Detection/ Biomarker

Assay

Discovery Refine/

Adapt for Clin

Use

Clinical

Validation

Clinical Translation

Blood

proPSA

FDA approved

Urine

PCA3

FDA approved

Urine/TMA assay for

T2S:Erg fusion for Prostate

Cancer

CLIA in process

FISH to detect T2S:Erg

fusion for Prostate Cancer

In CLIA Lab

Aptamer-based markers for

Lung Cancer

In CLIA Lab

Proteomic Panel for Lung

Cancer

In CLIA Lab

OVA1TM for Ovarian Cancer FDA Approved

SOPs for Blood (Serum,

Plasma), Urine, Stool,

Frequently used by biomarker

research community

Vimentin Methylation Marker

for Colon Cancer

In CLIA Lab

ROMA Algorithm for CA125

and HE4 Tests for Pelvic

Mass Malignancies

FDA Approved

Blood/DCP and AFP-L3 for

Hepatocellular Carcinoma

FDA Approved

Blood GP73 Together with AFP-L3 used in China

for monitoring/risk assessment of

cirrhotic patients for HCC

Meeting Objectives

Adoption of Clinical Assays

Biomarker Discovery

Technical Barriers

• Biomarkers exist in very low concentration: Significantly below the detection limits of mass spectrometry

• Obscured by abundant resident blood proteins such as albumin

• Rapidly degraded by enzymes post collection

• Hard to validate: Lack of antibodies specific for candidate biomarkers

The Center for

Applied Proteomics

and Molecular

Medicine

Proteomics Tools for

Clinical Medicine

Anderson, N.L., Anderson, N.G. (2002 ) Mol. Cell. Proteomics. 1, 845-867.

1%

Blood Protein Biomarker Discovery

An Overwhelming Analytical Challenge

- 22 proteins constitute 99% blood protein mass - Biomarkers likely are low abundance proteins - No analytical method has sufficient dynamic range

PSA

Preferred MS method to discover biomarker proteins (in blood)?

- Targeted Proteomics - Selective protein sampling, enrichment, fractionation

- Combine biological hypothesis and new technology

Dynamic Range

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Tissue microenvironment Circulation

Endothelial basement membrane

Endothelial cells

Fibroblast

Tumor cell

Proteinase

Immune cell

Biomarker protein

LMW Proteins and Fragments

Proteinase

Biomarker Cascades Generated In the Tissue

Microenvironoment

• Products of cell-cell cell-ECM interactions

• Enzymatic cascades; specific cleavage products

• Proteins shed during cell metabolism and death

Novel technology to overcome biomarker technical barriers

“Smart” Core Shell Affinity Bait Nanoporous Particles

• Three independent functions within minutes, in one step, in solution: – a) Molecular size sieving

– b) Affinity capture of all solution phase target molecules

– c) Complete protection of harvested proteins from enzymatic degradation

• Amplify the effective concentration of very low abundance molecules

The Center for

Applied Proteomics

and Molecular

Medicine

Proteomics Tools for

Clinical Medicine

• Particles can be produced in large quantities

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5 ml

50 ml

In-solution harvesting

Smart particles amplify the

biomarker concentration

Nanoparticles in vacutainer blood collection tubes

100 fold amplification

New Biomarker Discovery-Verification Workflow

Raw serum

Thermo LTQ-Orbitrap

Hybrid Mass Spectrometer

Elute the tryspin protein digestion

+ + + + . . . . . . Electrospray

ionization

d. C18 RP-HPLC

gradient elution

e. LC/MS-MS

Analysis

a. Collect proteins/peptides

with MW<10kDa

b. No digestion or Lys-C digestion

+ . . . . . . c. C18 RP-HPLC

gradient elution Thermo LTQ-ETD

Mass Spectrometer

+

Objective: Identify

native serum

protein fragments –

Peptidomics

Electrospray

ionization

MRM

Thermo Quantum

Triple Quad Mass Spectrometer

VERIFICATION

T1a Breast Cancer > Benign Control

Gelsolin isoforms a and b

2 peptides

Development and initial validation of a metabolite profile for the early detection

of breast cancer recurrence.

J Clin Oncol 30: 2012 (suppl 30; abstr 5)

Author(s):

Daniel Raftery et al

Metabolite profiles of 116 serial serum samples from 20 recurring patients and 141

serial samples from 36 breast cancer survivors with no evidence of disease (NED).

Multivariate analysis was used to identify 11 metabolite markers that were used to

build a model with high accuracy (AUROC >0.88 using 10 fold cross validation) with a

sensitivity of 68% and specificity of 94%.

Strikingly, over 55% of the patients could be correctly predicted to have recurrence on

average 13 months before clinical diagnosis, representing a large improvement over

the current diagnostic assays CA 27.29 and CA 15-3 (Cancer Res. 2010; 70, 8309-

18)..

The profile was tested using a separate validation set of 96 patient samples run

identically. The performance was similar to the training set with a sensitivity of 65%

and specificity of 93%. Recurrence detection was approximately 11 months ahead of

clinical diagnosis (based on imaging for symptomatic patients) and about 2 years

ahead of CA 27-29 alone.

RESEARCH FUNDING

THANK YOU!!!!!!!!!!