Decoding Cancer’s Pastโ to Predict its Future: A New Approach to Tumor Evolution
Researchers at IDIBAPSโ in Barcelona are pioneering aโ new method toโฃ understand cancer development by decipheringโข patterns withinโ DNA methylation – chemical modifications toโ DNA that don’t change the sequence itself, but can โalter gene expression. Initially dismissed as “background noise,” these patterns are now being revealed as a โขrich source ofโ information about a tumor’s history.
The team, led by researcher Martรญn-Subero, hasโ developed a methodology utilizing artificial intelligence to interpret theseโค methylation patterns. By applyingโ mathematical models, they’ve been able to reconstruct the evolutionary trajectory of tumors from a study of โค2,000 samples. This allows them to determine when a โtumor began to โขgrow, its growth rate, and the degree of diversity within its cells.
“What we discardedโ before, now we have found that it is indeed a gold mine, gives us information thatโ was hidden into the eyes of the whole world,” โฃMartรญn-Subero explains. โ
This “secret history” revealed โby methylation patterns has potential clinical implications.โ The researchers โhave created a tool to anticipate how a cancer will evolve, potentially predicting future aggressiveness and the timing of necessary treatment, even for slower-progressing cancers like chronic lymphocytic leukemia.
While promising, the research is still in its early โstages.Manel Esteller, a โresearch professor at the โฃjosep carreras โคLeukemia Institute, emphasizes the need for โฃfurther experimental validation before clinical implementation. He notes that existing DNA methylation analysis techniques alreadyโ combine biologicalโ verification with advanced algorithms to achieve similar results, especially in leukemia.
Though, Alejo Rodrรญguez Fraticelli, โan ICREA researcherโข at the Institut de Recerca Biomรจdica deโข Barcelona (IRB), highlightsโฃ the low cost of the newly developed technique as a meaningful advantage. He believes โคtheโฃ ability to โuse epigenetic information as “molecular barcodes” to track disease progression at a โlow cost is a true innovation.
Martรญn-Subero acknowledges that the methodology โฃisn’t yet ready for widespread clinical use, โขrequiring a company to translate the research into a practical request. โStill, he stresses its cost-effectiveness and its potential to fundamentally improve our โunderstanding of cancer biology. โค”If โฃwe know the โpast of cancer, we can advance โขto your future and make a โคbetter management of โclinical resourcesโค for a better treatment and better patient prognosis estimate,” he concludes.
