Glioma Grading Clinical and Mutation Features from TCGA-LGG and TCGA-GBM Projects

23 features characterize patient records for glioma grading, including 20 frequently mutated genes and 3 clinical demographics. The dataset was constructed from The Cancer Genome Atlas (TCGA) LGG and GBM projects by Tasci, E., Zhuge, Y., Kaur, H., Camphausen, K., & Krauze, A. V. The prediction task is to classify tumors as Lower-Grade Glioma (LGG) or Glioblastoma Multiforme (GBM).

Use Cases

• Binary classification of glioma grade (LGG vs. GBM) based on mutation and clinical features mentioned in the description
• Feature selection to identify an optimal subset of genes and demographics for cost-effective diagnosis
• Research into the relationship between specific gene mutations and glioma tumor grade

Strengths

• Includes 20 molecular features for the most frequently mutated genes in glioma
• Contains 3 clinical features concerning patient demographics
• Preprocessing removed 23 instances with missing or 'not reported' values for key features

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• Last update date is unknown; freshness unverified

Provenance

Source

The Cancer Genome Atlas (TCGA) Project - NCI

Collection Method

Constructed from TCGA-LGG and TCGA-GBM brain glioma projects.

Time Range

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Freshness

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Geography

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