Researchers identify possible imaging
method to stratify breast cancer without biopsy
Scientists from the Kimmel Cancer Center at Jefferson
have discovered a possible way for malignant breast tumors to be identified, without
the need for a biopsy. The findings were published online ahead of print in the
Journal of Nuclear Medicine.
Current imaging modalities miss up to 30% of breast cancers
and cannot distinguish malignant tumors from benign tumors, thus requiring invasive
biopsies.
"The challenge has been to develop an imaging agent that will target a specific,
fingerprint biomarker that visualizes malignant breast lesions early and reliably,"
said Mathew Thakur, Ph.D., professor of Radiology at Jefferson Medical College
of Thomas Jefferson University and director of Radiopharmaceutical Research and
Nuclear Medicine Research.
Dr. Thakur and colleagues studied an agent called 64Cu-TP3805,
which is used to evaluate tumors via PET imaging. 64Cu-TP3805 detects breast cancer
by finding a biomarker called VPAC1, which is overexpressed as the tumor develops.
The researchers compared the images using that agent
with images using the "gold standard" imaging agent, 18F-FDG. They used
MMTVneu mice, which are mice that develop breast tumors spontaneously, like humans.
The mice first received a PET scan using the 18F-FDG. Then they received a CT
scan, and then they received another PET scan using 64Cu-TP3805.
Ten tumors were detected on the mice. Four tumors were
detected using both 18F-FDG and 64Cu-TP3805, and four additional tumors were found
with 64Cu-TP3805 only. All eight of these tumors overexpressed the VPAC1 oncogene
on tumor cells and were malignant by histology. The remaining two tumors were
benign and were detected only with 18F-FDG. They did not express the VPAC1 oncogene,
and thus were not detected by the 64Cu-TP3805.
"If this ability of 64Cu-TP3805 holds up in humans,
then in the future, PET scans with 64Cu-TP3805 will significantly contribute to
the management of breast cancer," Dr. Thakur said.
Other Jefferson researchers involved in the study include
Devakumar Devadhas, Ph.D.; Kaijun Zhang, Ph.D.; Richard G. Pestell, M.D., Ph.D.;
Chenguang Wang, Ph.D.; Peter McCue, M.D.; and Eric Wickstrom, Ph.D.
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