Table 1_Proteogenomic detection of tumor-specific somatic mutant proteins in urinary extra

5,828 proteins were identified in urinary extracellular vesicles from five patients with bladder cancer. The dataset, created by Yuji Hakozaki and last updated in April 2026, contains results from a proteogenomic strategy that detected 4 somatic mutant proteins in urinary EVs, linking their levels to tumor burden.

Use Cases

• Developing targeted mass spectrometry assays based on identified mutant proteins like LCP1_D321H, TKT_K102N, and PLCD1_R639H.
• Training models to correlate protein quantification data with clinical tumor burden metrics.
• Building a mutation-informed protein database for proteogenomic analysis of bladder cancer.
• Validating the detection of tumor-specific somatic mutant proteins in extracellular vesicles as a liquid biopsy concept.

Strengths

• Data includes absolute quantification results for selected mutant proteins.
• Proteomic analyses identified 5,828 proteins in urinary extracellular vesicles.
• Matched sample sets from tumor tissues, tissue-derived EVs, and urinary EVs enable comparative analysis.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data is from a proof-of-concept study with a small cohort of five patients.

Provenance

Source

figshare

Collection Method

Proteogenomic pipeline using whole-exome sequencing and deep LC/MS proteomic profiling on matched tumor tissues, tissue-derived EVs, and urinary EVs.

Time Range

null

Freshness

Last updated 2026-04-15 04:36:55; freshness should be verified.

Geography

null