Overview
Understanding the molecular mechanisms that drive Glioblastoma (GBM) could help unlock more effective therapies. To explore this further, NCI partnered with ESI to analyze proteins in blood samples taken pre- and post-treatment. Identifying specific proteomic patterns linked to GBM marks a critical step forward in personalizing treatment for GBM.
The Challenge
GBM, a particularly aggressive cancer, accounts for about 15% of all brain tumors in adults and is nearly always fatal. To find more effective treatments for GBM, NCI turned to their robust data sets from patients with GBM, which they’ve been collecting for nearly a decade. They wanted to explore new minimally invasive ways to understand treatment response, especially in early-stage patients, where timely intervention could improve survival rates. By unlocking the molecular mechanisms driving GBM, NCI hoped to inform the development of more effective and better targeted therapies for this deadly cancer.
The Solution
Working alongside our federal partners in NCI’s Center for Biomedical Informatics and Information Technology and the Radiation Oncology Branch at the Center for Cancer Research, ESI staff examined proteins associated with GBM to identify patterns that might help predict how patients will respond to treatment.
Using blood serum samples taken before and after combined chemotherapy and radiation treatment, our team analyzed protein levels to uncover distinct profiles linked to cancer progression.
In particular, we:
- Generated data with an aptamer-based approach (called SomaScan™ from SomaLogic) using samples collected from NCI’s clinical center.
- Identified proteins with different expression patterns before versus after treatment and mapped those patterns to the patients’ outcomes (i.e., high, medium, and low survival).
- Linked specific proteins to those different survival groups using Principal Components Analysis (PCA).
- Analyzed the data (using weighted gene correlation network analysis or WGCNA) to find trends in clinical features, such as tumor size or patient subgroups, associated with these proteins.
- Analyzed the data (using Gene Set Enrichment Analysis or GSEA) to see if we could find specific genetic pathways that were activated or deactivated after treatment.
The Results
This study was the first of its kind to identify changes in blood serum proteins associated with treatment in GBM patients.
Using NCI’s rich collection of GDM data, we were able to identify distinct differences in proteins that could be linked to:
- cancer progression,
- resistance to treatment,
- cancer recurrence, and
- overall likelihood of survival.
This work confirms the proteome’s usefulness not only for classifying glioma but also for probing the pathways that lead to cancer. Molecular changes such as those identified in this study offer oncologists a new way of predicting outcomes and monitoring brain cancer using a less-invasive blood test.
Further research will be needed to confirm and extend these results, so it will be some time before we know the full impact of this work. Nevertheless, ESI’s findings are vital for extracting information from both clinical and molecular data, collected over many years. The results of this study were published in Frontiers in Oncology.
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