UP-developed model may detect early signs of metastasis in breast cancer patients
MANILA, Philippines — Researchers from the University of the Philippines (UP) and Philippine Genome Center have developed a mathematical model that is “promising” in terms of detecting early signs of metastasis in breast cancer patients.
In a statement released to the media on Monday, UP revealed that the recently developed mathematical model of their biologists can detect lymphovascular invasion (LVI) in breast cancer patients even before surgery.
LVI serves as an early indicator of metastasis for doctors. Currently, it can solely be detected by “examining tissue surrounding the tumor that has been surgically removed.”
“Now, biologists from the [UP] have developed a mathematical model that can detect LVI in breast cancer patients even before surgical treatment,” the UP statement read.
It added that the researchers’ study likewise revealed links between LVI and drug resistance, which helps explain why breast cancer patients with LVI respond poorly to anticancer drugs.
Early detection, better strategies
“If we can detect LVI earlier, doctors could personalize patient treatment and improve their outcomes. This could help avoid ineffective treatments and focus on strategies that work better for aggressive breast cancer,” corresponding author Dr. Michael Velarde of the UP- Diliman College of Science Institute of Biology (UPD-CS IB) said.
Aside from Velarde, likewise involved in the research / study are Allen Joy Corachea, Regina Joyce Ferrer, Lance Patrick Ty, and Madeleine Morta of UPD-CS IB, as well as the researchers from the Philippine Genome Center and UP Manila.
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The authors observed from the clinical data of 625 breast cancer patients at the Philippine General Hospital, along with publicly available data, that “the majority of patients with LVI also responded poorly to the anticancer drugs.”
“They further confirmed the link between LVI and drug resistance by collecting tumor samples and growing them in a lab into organoids – small, organ-like structures that mimic real organs. Their tests revealed that LVI-positive organoids were indeed less receptive to anticancer drugs compared to LVI-negative ones,” the statement said.
“They discovered that certain genes involved in breaking down anticancer drugs, called the UGT1 and CYP genes, are more abundant in patients with LVI. When these genes are more abundant, the drugs are broken down more quickly, reducing their effectiveness. As a result, patients with high activity of UGT1 and CYP genes are more likely to have tumors that survive chemotherapy and eventually metastasize,” it further explained.
With the said insights, the researchers developed a regression model that analyzed the expression patterns of the UGT1 and CYP genes, as it reportedly predicted accurately LVI status at the time of biopsy and before surgery 92% of the time.
Accessible to Filipinos
“Importantly, our approach can be implemented in the Philippines using locally available genomic technologies, making earlier detection and tailored treatment more accessible to Filipino patients,” Velarde said.
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Despite the promising results, he noted that the model is still in its early stages of development and is “not yet ready to replace current methods for diagnosing LVI.”
More studies needed
“More validation studies are needed before this can be used in clinics,” Velarde said.
He also said that they are planning to validate their results by testing the gene signatures of larger groups of breast cancer patients in the Philippines.
Aside from this, the authors further seek to investigate how UGT1 and CYP genes are related to LVI in order to identify drug combinations that work better for LVI-positive patients.
“Our goal is to develop a practical test that can be used in Philippine hospitals to guide doctors in choosing the best treatment for each patient,” said Velarde.
Breast cancer is the most common type of cancer among women in the Philippines. In 2022, over 33,000 new cases were recorded. More than 11,000 also reportedly died in the said year, making it the second leading cause of cancer-related mortality in the country, next to lung cancer.
