DNA Methylation Analysis Improves Risk Assessment of Childhood Leukemia for Personalizing Treatment

For T-cell acute lymphoblastic leukemia (T-ALL), a specific subtype of leukemia, treatment typically involves chemotherapy over a two-year period, sometimes followed by a bone marrow transplant. While these treatments are largely effective—today, nearly 90% of children diagnosed with T-ALL survive—there are severe side effects. These include nausea, fatigue, increased susceptibility to infections, and hair loss. Long-term risks also exist, such as heart issues, cognitive impairments, fertility problems, and an elevated risk of developing other cancers. The likelihood of relapse varies among T-ALL patients, but current diagnostic methods are insufficient for accurately assessing the risk of relapse. As a result, many children undergo more intensive treatments out of caution, which can expose them to even more side effects than necessary. Now, advancements in diagnostic methods offer the potential to make leukemia treatment more precise, minimizing side effects while optimizing outcomes.

Methylation, an epigenetic process, involves the addition of chemical groups to a DNA sequence, regulating the expression of specific genes. This process is essential for the unique characteristics and properties of different cell types, as the methylation pattern varies across the genome. Disruption of the methylation pattern can lead to tumor development, making it a key factor in understanding cancer. Essentially, DNA methylation patterns serve as a molecular fingerprint that offers valuable insights into the properties of cancer cells. A new study led by Umeå University (Umeå, Sweden) has shown that analyzing the methylation patterns in the DNA of leukemia cells can improve risk assessment, allowing for more tailored treatment plans. The study examined diagnostic samples from 348 children with T-ALL who received treatment between 2008 and 2020.

Using advanced array technology and bioinformatics, the researchers analyzed around 850,000 DNA methylation positions in the genome. Their findings suggest that examining methylation patterns at the time of diagnosis can enhance risk stratification, ensuring that only those who need the most intensive treatment receive it. Additionally, the method can identify patients who do not respond well to current treatments, signaling the need for alternative therapeutic approaches. The researchers also looked at the gene expression and genetic alterations in leukemia cells to understand how different methylation patterns influence treatment strategies. Future studies will continue this work with the goal of refining treatment approaches. The team has also developed an epigenetic platform that facilitates DNA methylation array analysis for both research and diagnostic purposes, enhancing the capabilities of advanced epigenetic research and clinical diagnostics.

“Our results show that DNA methylation analysis may be a viable way to individualize treatment according to the type of leukemia, with the hope of a better quality of life," said Professor Sofie Degerman at Umeå University, who led the study with participating researchers from several countries. "We are continuing our research to investigate the possibility of including DNA methylation analysis in clinical diagnostics for patients with T-ALL."

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