Detect cancer signals from a single blood draw.

METAseq was developed on 24,325 blood samples (plasma and serum) drawn from multiple independent research cohorts. It detects cancer-associated circulating microRNA patterns and estimates the most likely tissue of origin across 14 cancer types.

Understanding sensitivity and specificity in cancer detection

Specificity is the probability the test correctly says "no signal" in a cancer-free person. At 99% specificity, roughly 1 in 100 healthy individuals will receive a false positive — triggering unnecessary follow-up. MCED tests run at high specificity because the cost of a false positive in a well person is high.

Sensitivity is the probability the test detects a cancer signal when cancer is present. METAseq detected 89.2% of cancers overall at 99% specificity in a held-out case-control evaluation (8,767 confirmed cancer samples). Detection rate varies by cancer type. A negative result does not rule out cancer.

For context, the leading commercial MCED test (Galleri, GRAIL) reports approximately 50% sensitivity at ~99.5% specificity. Important: these figures come from a retrospective case-control study design, not a prospective screening trial. Case-control studies typically show higher sensitivity than real-world screening because cases are enriched and often diagnosed at symptomatic stages. Prospective validation in a screening population is planned and may result in materially different performance estimates.

Training cohort and detection sensitivity by cancer type — held-out cohort · 99% specificity · case-control design

Sensitivity varies across cancer types and is influenced by both biological factors and sample size in the training cohort. Melanoma has the smallest training set (n=273) and lowest held-out sensitivity; interpretation should account for this. Tissue-of-origin top-3 accuracy 97.5% (10×10 cross-validation). Prospective validation is planned.