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Ovarian Cancer Early Diagnosis Project
A collaboration with Professor Touradj Solouki, PhD, of the University
of Maine
Study Recruitment: Women
with ovarian cancer, endometriosis, or polycystic ovarian syndrome
now needed. Click here for study eligibility.
INTRODUCTION
Is there meaningful information contained within a person's breath?
Could this information lead to early detection of ovarian cancer? In
partnership with Touradj Solouki, associate professor of chemistry at
the University of Maine, the Pine Street Foundation seeks to answer these
questions by using two of the most sensitive and sophisticated scent
detection devices on the planet: a type of mass spectrometer and a dog's
nose.
We are thrilled to announce
that this project has recently been awarded a federal research grant
by the Congressionally Directed Medical Research Program and we'll
be launching this next phase of our groundbreaking canine scent detection
work soon.
We will focus specifically on detecting ovarian cancer through analysis
of exhaled breath, leading the way towards a truly noninvasive way to
diagnose ovarian cancer. A major step forward in this study is that breath
analysis will be conducted both with trained dogs here at the Pine Street
Foundation as well as with sophisticated analytical chemistry at the
laboratories of Dr. Solouki in Maine.
PUBLIC ABSTRACT:
Early Detection of Epithelial Ovarian Cancer Using Exhaled Breath
Markers:
GC/FT-ICR Mass Spectrometry and Canine Olfaction
BACKGROUND WORK
Epithelial ovarian cancer is the fifth leading cause of cancer death
in women. Early diagnosis is the most important step toward reducing
morbidity and mortality from epithelial ovarian cancer (e.g., from less
than 10% in late stage cancer to greater than 90% survival rate for early
detection). Although some women with early stage ovarian cancer experience
symptoms, research has shown that early signs may be misleading. Furthermore,
the best current method to test for ovarian cancer, a combination of
a blood test called CA-125 and ultrasound of the lower abdomen, is also
not an accurate indicator of early-stage disease.
Our preliminary results suggest that human exhaled breath condensate
(EBC) may provide an important source of biomarkers for early detection
of ovarian cancer. We have explored exhaled breath condensate analysis
using a biological method (trained dogs in California labs). In careful
double-blinded conditions, we have tested the ability of trained dogs
to distinguish ovarian cancer cases from controls using samples of exhaled
breath condensate with accuracy of over 97%. In addition, we have acquired
preliminary data from chemical methods involving Gas Chromatography/Fourier
transform Ion Cyclotron Resonance Mass Spectrometry (GC/FT-ICR MS analyses
in Maine labs). Preliminary results strongly suggest that there is a
tangible prospect to identify potentially unique biomarkers from exhaled
breath condensate for early detection of ovarian cancer. Currently, we
hold the GC/MS world record for mass resolving power; this unique ability
to distinguish very similar molecules from each other, coupled with the
unrivaled capability of FT-ICR MS for accurate mass measurement and identification
of minor components in a complex mixture, allows sample "fingerprinting" at
the highest level of confidence currently achievable. We believe that
these two biological and chemical sensing methods, examined in combination,
will allow us to develop a new "breathalyzer" type
test for early detection of ovarian cancer from
WHAT WE HOPE TO FIND
We believe that, using our approach, patients with epithelial ovarian
cancer can be distinguished from both healthy women and women who have
other abdominal disorders, endometriosis or polycystic ovarian syndrome
controls. It is anticipated that exhaled breath condensate analysis can
predict whether a woman's ovarian
cancer will recur after treatment or become resistant to treatment.
HOW WE PROPOSE TO DO THIS
Our primary aim is to identify exhaled breath condensate biomarker(s)
that can be used to distinguish ovarian cancer patients from healthy
controls at the molecular level. To accomplish this aim, we will first
obtain exhaled breath condensate from both epithelial ovarian cancer
cases (between biopsy and initiation of therapy) and healthy controls.
We will then analyze the collected samples using sophisticated FT-ICR
technology (equipped with electron impact [EI], chemical ionization [CI],
and electrospray [ESI] ionization sources), followed by statistical data
analysis. Our secondary aim is to train five dogs to discriminate between
the exhaled breath condensate of epithelial ovarian cancer patients and
healthy controls, using our previously established and published methods.
We will use samples of exhaled breath condensate from the same cases
and controls, described in the primary aim. Dogs will be trained to indicate
the cancer patient samples by sitting directly in front of the cancer
sample only, and sniffing but ignoring the samples from healthy controls.
Having trained the dogs on a "training
set" of epithelial ovarian cancer cases
and healthy controls, we will then test this approach with a new set
of cases and controls, using a controlled double-blind testing design.
We will apply both of the above methods, chemical analysis and canine
scent detection, to distinguish epithelial ovarian cancer patients from
controls with polycystic ovarian syndrome and endometriosis.
Finally, in order to test the prognostic capability of these exhaled
breath condensate analyses, we will continue to follow epithelial ovarian
cancer cases until recurrence, death, or end of the proposed studies.
DESIGN
The proposed
project will incorporate a case-control design in which we will compare
cases and controls. In order to control for potential confounding
by inflammation, which can be associated both with epithelial cancer
and other non-malignant diseases such as polycystic ovarian syndrome
and endometriosis, we will also collect data on CA-125, level of physical
activity, body mass index, and concurrent chronic obstructive pulmonary
disease, periodontal disease, rheumatoid arthritis, asthma, rhinitis,
diabetes, renal disease, and cardiovascular disease.
RELEVANCE AND INNOVATION
Our team will be the first to use analysis of ECB (both by chemical and
biological means), for early detection of epithelial ovarian cancer.
The proposed approach is a truly non-invasive diagnostic method. There
is a strong short-term potential to extend the proposed procedures
to identify biomarkers for early detection of other types of cancers
and human diseases. A long-term objective is to exploit our research
findings to develop portable devices for early detection of ovarian
cancer.
WE WILL NEED YOUR HELP
Although we will receive funds to begin this important research project,
your donations towards the following will greatly help:
Research Assistant Salaries: $12,000
Recruitment Coordinator Salaries: $12,000
Research Supplies: $575
Research Equipment: $11,984
Hospital Center Data Coordinators: $30,000
Training Site Costs: $16,800
Ethical Review Board Fees: $5,400
TOTAL: $88,759
Your tax-deductible gift, regardless of size, will really make a difference! Learn
more about the ways you can give online by clicking here.
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