Quantitative HER2 Protein Assay Data for Breast Cancer Patient Stratification

A 2026 study by Junmei Hao presents a quantitative HER2 protein assay dataset for invasive breast cancer. The data includes protein lysate measurements from 225 patient specimens (106 training, 119 validation) to evaluate a new assay method against traditional immunohistochemistry. Results include an inter-rater ICC of 0.877 for the new method and an AUC of 0.9477 for distinguishing HER2-low from HER2 0 status.

Use Cases

• Validate a quantitative HER2 assay against pathologist consensus based on protein quantification data.
• Establish a clinical cutoff for HER2 status stratification based on the identified 0.2746 nmole/g threshold.
• Compare assay consistency using inter-rater reliability metrics like Intraclass Correlation Coefficient.
• Train machine learning models for patient stratification using quantitative protein levels as features.

Strengths

• Includes data from 225 patient specimens split into training and validation cohorts.
• Reports high assay consistency with an inter-rater ICC of 0.877 (95% CI: 0.840-0.908).
• Demonstrates strong discriminatory power with an AUC of 0.9477 (p<0.005) in ROC analysis.
• Provides a specific quantitative cutoff (0.2746 nmole/g) for clinical stratification.

Limitations

• Row count and column-level documentation are unknown, limiting suitability assessment.
• Data is contained in a 146.4 KB DOCX file, suggesting limited raw data scope.
• Geographic and demographic coverage of the patient cohorts is unspecified.

Provenance

Source

figshare, author Junmei Hao.

Collection Method

Protein lysates were extracted from FFPE slices of consecutive resection specimens from invasive breast cancer patients.

Freshness

Last updated 2026-04-27 04:14:35.