Tumor-Infiltrating T Cell Repertoire Across 29 Human Cancers

Over 600,000 complementarity determining region 3 (CDR3) sequences were inferred from 9,142 RNA-seq samples across 29 cancer types. The dataset was generated by researchers at Harvard University using a computational method to analyze tumor-infiltrating T-cells. It links T-cell diversity to tumor mutation load and identifies potential immunogenic antigens and somatic mutations.

Use Cases

• Predicting immunogenic cancer/testis antigens like SPAG5 and TSSK6 based on co-occurrence with T-cell clonotypes.
• Analyzing the association between T-cell receptor diversity and tumor mutation load across cancer types.
• Identifying potential immunogenic somatic mutations, such as PRAMEF4 F300V, based on their co-occurrence with specific CDR3 sequences.
• Comparing T-cell repertoire features, like CDR3 length distribution and variable gene usage, between tumors and healthy peripheral blood.

Strengths

• Includes data from 9,142 RNA-seq samples, providing a substantial scale for analysis.
• Covers 29 different cancer types, allowing for cross-cancer comparisons.
• Identified over 600,000 CDR3 sequences, with 15% being full-length.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.
• Data may reflect bias inherent to the samples aggregated on the paperswithcode platform.

Provenance

Source

Harvard University

Collection Method

Computational inference from publicly available RNA-seq samples.