Samuel Kim authored a review document discussing biomarkers for predicting immunotherapy response and resistance in glioblastoma. The document, last updated on May 5, 2026, is a 33.3 KB DOCX file hosted on figshare. It covers mechanistic and context-dependent biomarker signals, including PD-1/PD-L1, tumor mutational burden, MGMT methylation, interferon signaling, and immune cell populations.
Use Cases
- Identify potential biomarker candidates for patient stratification in immunotherapy trials based on the review of mechanistic and context-dependent signals.
- Design exploratory endpoints for biomarker discovery in clinical trials based on the discussion of body compartments like CSF, blood, and tissue.
- Develop nuanced biomarker signatures for machine learning models using the described categories of biomarkers.
- Evaluate the promise of radiographic biomarkers for monitoring immunotherapy response in glioblastoma patients.
Strengths
- The document is licensed under CC-BY-4.0, allowing for open sharing and reuse.
- It provides a focused review on a critical clinical challenge: predicting immunotherapy response in glioblastoma.
- The last update date of 2026-05-05 suggests recent consideration of the topic.
Limitations
- The dataset is a 33.3 KB DOCX file, indicating a limited scope likely containing a review article rather than raw data.
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment for data analysis tasks.
Provenance
- Source
- figshare
- Freshness
- Last updated 2026-05-05 05:23:45; freshness should be verified.