Could a Blood Test Offer an Additional Screening Option for Women With Dense Breasts?
Background
Dense breast tissue can obscure cancers on mammograms and is itself associated with increased breast cancer risk. Supplemental screening with MRI, contrast-enhanced mammography (CEM), or ultrasound can detect additional cancers but may involve false alarms, unnecessary procedures, higher costs, or limited access.
Researchers are investigating blood-based tests that identify cancer-associated proteins rather than relying on breast images. One investigational approach uses automated mass spectrometry and machine learning to analyze thousands of circulating proteins for patterns associated with breast cancer. Whether such testing could improve screening remains uncertain.
Study Description
Horrmann and colleagues evaluated the test, developed by Astrin Biosciences, using previously collected blood samples from women with confirmed, untreated breast cancer (stages 0–IV) and healthy controls. After quality checks, 1,242 samples remained: 845 for model training and 397 for validation. Researchers used automated laboratory processing and mass spectrometry to measure approximately 7,000 proteins per sample using less than 1 milliliter of plasma.
Separately, investigators simulated supplemental screening in 100,000 women with dense breasts to estimate potential outcomes when the blood test followed a negative mammogram. The test was not evaluated in a prospective screening population.
Key Findings
- Accuracy in stored samples: The test correctly distinguished most blood samples from women with breast cancer from those of healthy controls.¹
- Detection across stages and tumor types: Sensitivity was relatively high for early-stage cancers and several tumor subtypes, including invasive lobular carcinoma, although some groups contained few patients.²
- Cancer-associated protein signals: Researchers identified protein patterns associated with biological pathways involved in breast cancer development and progression.3
- Potential supplemental screening benefit: A computer simulation predicted fewer missed cancers when the blood test was added after a negative mammogram, but these benefits have not been demonstrated in clinical screening.4
Interpretation/Implications
The findings provide preliminary evidence that detailed blood-protein analysis can distinguish women with diagnosed breast cancer from healthy controls. This approach is of particular interest for women with dense breasts because, unlike mammography, blood-based testing does not rely on X-ray images, where dense tissue can obscure cancers. Researchers envision its potential use as a triage test following a negative mammogram, rather than as a replacement for mammography. In this proposed approach, women with negative blood test results might avoid additional MRI examinations, while those with positive results would undergo MRI to locate a suspected cancer and determine whether biopsy is needed.
However, the study does not establish that the test can detect cancers missed by mammography or reduce unnecessary imaging in clinical practice. Breast density was not recorded, so performance specifically in women with dense breasts could not be assessed. Furthermore, a positive blood test cannot identify the location of a suspected cancer and would require additional imaging and potentially biopsy. These findings should not change current screening recommendations.
Limitations
This retrospective study used stored blood samples from women already known to have cancer or to be healthy, rather than women undergoing routine screening. Importantly, the findings concerning dense breasts were based entirely on simulation rather than observed clinical outcomes. A positive blood test without a corresponding imaging finding could also create uncertainty and anxiety, an issue not evaluated in this study.
Large, independent prospective studies in diverse screening populations are necessary to determine whether the test can detect otherwise missed cancers, establish real-world false-positive rates, and assess how results could be incorporated safely into existing screening workflows. The test is marketed as a laboratory-developed test but has not received FDA clearance or approval.
Detailed Results
1 Overall accuracy: In the validation group, sensitivity was 92.6% (187/202; 95% CI: 88.1–95.4%), specificity was 92.3% (180/195; 95% CI: 87.7–95.3%), and the area under the curve (AUC), a measure of overall test discrimination, was 0.975 (95% CI: 0.961–0.987).
2 Detection by cancer stage and tumor subtype: Sensitivity was 85.7% (12/14) for stage 0, 88.6% (62/70) for stage I, and 96.9% (95/98) for stage II, with no statistically significant trend across stages 0–III (P=.204). By tumor subtype, sensitivity was 100% (20/20) for invasive lobular carcinoma, 94.8% (145/153) for invasive ductal carcinoma, and 90.9% (10/11) for ductal carcinoma in situ (DCIS).
3 Protein patterns: Analysis identified enrichment of cancer-associated biological pathways, including epithelial-to-mesenchymal transition and PI3K-AKT signaling.
4 Simulated screening outcomes: In a hypothetical population of 100,000 women with dense breasts, mammography alone was estimated to miss 431 cancers (95% CI: 347–521), compared with 31 (95% CI: 15–54) when universal supplemental blood testing was modeled. The combined mammography–blood test strategy was estimated to produce 16,591 false-positive results. These figures represent modeled predictions, not actual screening outcomes.