Data Sheet 1_Proteogenomic detection of tumor-specific somatic mutant proteins in urinary

A 2026 proof-of-concept study by Yuji Hakozaki investigating somatic mutant proteins as non-invasive biomarkers for bladder cancer. The research used a proteogenomic pipeline on matched tumor tissues, tissue-derived EVs, and urinary EVs from five patients. It identified 11,207 proteins in tumor tissues, 9,809 in tissue-derived EVs, and 5,828 in urinary EVs, with 39, 32, and 4 somatic mutant proteins detected respectively.

Use Cases

• Developing targeted mass spectrometry assays for mutant protein quantification based on the identified proteins LCP1_D321H, TKT_K102N, and PLCD1_R639H.
• Training machine learning models for recurrence risk prediction based on mutant protein levels associated with cystoscopic tumor burden.
• Building proteogenomic pipelines for somatic mutation detection in extracellular vesicles based on the described whole-exome sequencing and LC/MS methodology.
• Evaluating the specificity of urinary EV biomarkers for non-muscle invasive bladder cancer (NMIBC) monitoring based on the conceptual framework established.

Strengths

• Includes absolute quantification data for selected mutant proteins, supporting clinical feasibility assessment.
• Provides matched proteomic profiles across three specimen types (tumor tissue, tissue-derived EVs, urinary EVs) from five patients.
• Proteomic analyses identified over 5,000 proteins in urinary EVs, demonstrating depth of profiling.

Limitations

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

Provenance

Source

figshare

Collection Method

Whole-exome sequencing and deep proteomic profiling by LC/MS on matched samples from five bladder cancer patients.

Time Range

Data collection timeframe not specified in the input.

Freshness

Last updated 2026-04-15 04:36:57; freshness should be verified.

Geography

Geographic coverage not specified in the input.