26-05-2025
UP biologists use mathematical model to detect early signs of metastasis in breast cancer patients
UP biologists use mathematical model to detect early signs of metastasis in breast cancer patients (Photo from Dr. Michael Velarde)
Biologists from the University of the Philippines Diliman have developed a mathematical model that can detect lymphovascular invasion (LVI), an early indicator of metastasis, in breast cancer patients even before a surgical operation.
'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,' said Michael Velarde, one of the authors of the study, in a news release by the UP College of Science.
LVI is the condition when cancer cells invade the lymphatic and blood vessels which enables them to travel to other body parts. When cancer cells spread to other organs, the process is called metastasis.
Tumor must first be surgically removed to detect possible LVI by examining the tissue surrounding it.
The scientists determined whether LVI+ breast tumors contain a unique gene signature that could facilitate earlier detection.
'Here, we conducted an integrative analysis of the gene profile between LVI+ and LVI− primary breast tumors from various sources, including published data and our own research, using both microarray and RNA-seq data,' the study's abstract read.
The study discovered that the majority of breast cancer patients in the sample also did not respond to anti-cancer drugs, such as doxorubicin and anthracyclines, given before the tumor removal operations.
The scientists found that certain genes involved in breaking down anti-cancer drugs, called the UGT1 and CYP genes, are more abundant in patients with LVI. Hence, the drugs are becoming less effective because they are easily broken down.
'An elastic net regression model containing 13 of these uridine 5'-diphospho-glucuronosyltransferases and cytochrome P450 genes can predict LVI status with 92% accuracy,' the abstract read.
'This suggests a potential link to drug resistance, which was further confirmed by the finding that patients with LVI+ tumors had a significantly lower clinical response rate than individuals with LVI− tumors.'
However, Velarde said that the regression model they used is still in its early stages of development. But the scientists plan to further validate their results by testing the gene signatures of large groups of cancer patients in the Philippines.
'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,' said Velarde.
Other biologists behind the study are Allen Joy Corachea, Regina Joyce Ferrer, Lance Patrick Ty, and Madeleine Morta.
According to the UPD College of Science, the country has recorded over 33,000 new breast cancer patients in 2022. In the same year, more than 11,000 died, making it the second leading cancer-related death after lung cancer. —Vince Angelo Ferreras/LDF, GMA Integrated News
