Non-invasive early detection of cancer four years before conventional diagnosis using a blood test

Abstract

Early detection has the potential to reduce cancer mortality, but an effective screening test must demonstrate asymptomatic cancer detection years before conventional diagnosis in a longitudinal study. In the Taizhou Longitudinal Study (TZL), 123,115 healthy subjects provided plasma samples for long-term storage and were then monitored for cancer occurrence. Here we report the preliminary results of PanSeer, a noninvasive blood test based on circulating tumor DNA methylation, on TZL plasma samples from 605 asymptomatic individuals, 191 of whom were later diagnosed with stomach, esophageal, colorectal, lung or liver cancer within four years of blood draw. We also assay plasma samples from an additional 223 cancer patients, plus 200 primary tumor and normal tissues. We show that PanSeer detects five common types of cancer in 88% (95% CI: 80-93%) of post-diagnosis patients with a specificity of 96% (95% CI: 93-98%), We also demonstrate that PanSeer detects cancer in 95% (95% CI: 89-98%) of asymptomatic individuals who were later diagnosed, though future longitudinal studies are required to confirm this result. These results demonstrate that cancer can be non-invasively detected up to four years before current standard of care.

Conflict of interest statement

J.G., A.G., Q.H., J.M., X.L., L.C., Z.Z., H.N., Z.L., Z.X., H.S., J.D., C.M., and R.L. are employees of Singlera Genomics. Y.G. and R.L. are board members of Singlera Genomics. J.G., A.G., and R.L. are inventors on a patent (US62/657,544) held by Singlera Genomics that covers basic aspects of the library preparation method used in this paper. K.Z. is a co-founder, equity holder, and paid consultant of Singlera Genomics. The terms of these arrangements are being managed by the University of California–San Diego in accordance with its conflict of interest policies. X.C., M.L., Z.Y., X.Y., Y.J., T.Z., C.S., X.Z., M.F., X.W., Y.Y., J.Z., J.W., S.Y., W.Y., and L.J. declare no competing interests.

Figures

Fig. 1. Summary of the Taizhou longitudinal study (TZL).

The flowchart shows recruitment, baseline survey, sample collection, and cohort follow-up for TZL. Qualified pre-diagnosis patients and healthy participants were selected from the TZL cohort and qualified post-diagnosis patients were selected from local Taizhou hospital biobanks; 328 samples were processed but later excluded due to not meeting inclusion criteria or failing quality control metrics.

Fig. 2. Performance of PanSeer.

All presented results used only the test set samples. Dots represent the logistic regression (LR) score. a Receiver operator characteristic curves (ROC) and area under the curve (AUC) values for PanSeer. The red star shows the cutoff value derived from the training set. Separate curves are shown for post-diagnosis samples and pre-diagnosis samples (divided by years before diagnosis). b LR scores for PanSeer samples by years before diagnosis. c LR scores for PanSeer samples by cancer stage for post-diagnosis samples. d LR scores for PanSeer samples by tissue of origin for post-diagnosis samples. e LR scores for PanSeer samples by cancer stage at diagnosis for pre-diagnosis samples. f LR scores for PanSeer samples by tissue of origin for pre-diagnosis samples.

Fig. 3. Performance of PanSeer using only tissue-concordant genomic regions.

All presented results used only the test set samples, and only utilized target regions showing concordant hyper/hypo-methylation between training set cancer plasma samples and cancer tissue samples. Dots represent the logistic regression (LR) score. a Receiver operator characteristic curves (ROC) and area under the curve (AUC) values. The red star shows the cutoff value derived from the training set. Separate curves are shown for post-diagnosis samples and pre-diagnosis samples (divided by years before diagnosis). b LR scores by years before diagnosis.