Glioblastoma is a highly aggressive and malignant type of brain cancer with a poor prognosis, despite current treatment options of surgery, radiation therapy, and chemotherapy. Technical challenges, such as sample quality and availability, and challenges in analyzing and interpreting large amounts of data remain significant obstacles in omics sciences and precision medicine for glioblastoma.
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Understanding this could lead to better treatments, improved diagnostics, or a deeper grasp of how the human body works — benefiting patient care globally.
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