Urinary Proteomics for Endometrial Cancer Biomarkers, 40 Participants

Khalid Akkour published a proteomics dataset on figshare in April 2026. It contains label-free quantitative mass spectrometry data from urine samples of 40 women, including 20 endometrial cancer patients and 20 controls. The study identified 193 differentially expressed proteins and three potential biomarkers.

Use Cases

• Identify candidate urinary biomarkers for endometrial cancer based on 193 differentially expressed proteins.
• Validate biomarker performance using receiver operating curve analysis metrics like AUC.
• Investigate molecular pathways in endometrial cancer, such as Fc gamma receptor-dependent phagocytosis and complement activation.
• Compare proteomic profiles between cancer and control groups using multivariate statistical methods like PCA and OPLS-DA.

Strengths

• Data is from a controlled clinical study with 40 participants matched for age.
• Analysis identified 193 proteins with significant differences (117 upregulated, 76 downregulated).
• Three specific biomarkers (GLUD1, Iduronate 2-sulfatase, histidine-rich glycoprotein) were highlighted with high AUC values.

Limitations

• Row count and column-level documentation are unknown, requiring manual inspection after download.
• The dataset is small (17.9 KB), suggesting limited scope.
• Data may reflect geographic bias inherent to recruitment from King Khalid University Hospital.

Provenance

Source

King Khalid University Hospital, King Saud University.

Collection Method

Untargeted label-free LC-MS/MS mass spectrometry on urine samples.

Freshness

Last updated 2026-04-09 05:15:43.