New mathematical algorithms might help diagnose
cancer
|
Hany Farid (left), Bruce Donald
(seated), and Ryan Lilien have developed an algorithm named Q5
that uses data from a mass spectrometer to distinguish between
healthy and diseased blood. (photo by Joe Mehling
'69) |
February 04, 2004. Dartmouth
researchers have developed an algorithm that might someday be used
to analyze blood for diagnostic purposes. Using data from a mass
spectrometer, a device that generates a molecular fingerprint of
biological samples, the Dartmouth team's calculations can
distinguish healthy blood from diseased blood.
This study by Ryan Lilien, a
Dartmouth M.D./Ph.D. student, Hany Farid, Assistant
Professor of Computer Science , and Bruce Donald, the Foley
Professor of Computer Science, appeared in the Journal of
Computational Biology in December 2003.
"Our algorithm, named Q5, works on the assumption
that the molecular composition of the blood changes between healthy
and disease states," says Donald, the senior researcher on the
project. "The goal of our work is to develop minimally invasive
diagnostic methods with high predictive accuracy, and this is a
promising first step."
Mathematical computations are routinely developed,
varied and refined to analyze mass spectrometry data. Q5 uses
mathematical techniques called Principal Component Analysis (PCA)
and Linear Discriminant Analysis (LDA) to differentiate between the
mass spectra of healthy and diseased blood samples. Q5 learns with
each sample it tests, resulting in better accuracy. The algorithm
compares the molecular fingerprint of each sample to identify
features that differ between the healthy and disease states.
"Our algorithm detected ovarian cancer with
virtually 100% accuracy and prostate cancer with approximately 95%
accuracy," explains Lilien, the lead author on the paper. "Q5
analyzes the mass spec data and offers control over the threshold
between healthy and disease classification. Although we only tested
against ovarian and prostate cancer, we think it's possible that Q5
may be used to test for other cancers and diseases."
The researchers explain that there is much still
to be learned from the different types of information within a
sample of blood, and Q5 is one means of extracting new and important
data.
"Most exciting to us, unlike previous mass spec
disease diagnosis methods, Q5 provides clues about the molecular
identities of abnormal proteins and peptides, which often cause
disease. These altered proteins can serve as biomarkers, helping
doctors make diagnosis and also helping researchers design better
targeted drugs," says Donald.
This research is funded by the National Institutes of Health, the National Science Foundation, the John Simon Guggenheim Foundation, and
an Alfred P. Sloan
Fellowship.