Diagnostic Technologies for Early Cancer Detection

Diagnostic Technologies for Early Cancer Detection


We develop nanosensor technologies to accurately identify cancer at the earliest stages. Early detection improves the chances that cancer treatments will be effective. We are building implantable sensor technologies to facilitate the real-time monitoring, to enable the detection of cancer biomarkers at the earliest possible timepoints. Some of these sensors can even interface with wearable devices.

We are also developing sensor technologies that use artificial intelligence to detect many biomarkers simultaneously, to improve sensitivity and specificity.

These technologies could monitor people with heightened risk for cancers, or in successfully treated patients who have a high risk of recurrence. In people who are undergoing treatment, the sensors could signal immediately whether a biomarker is going up or down and, when needed, alert a doctor to switch to a different course of therapy. We are pursuing the translation of these sensor platforms from the laboratory to the clinic.


A Sensor Sniffs for Cancer, Using Artificial Intelligence

To Detect Ovarian Cancer Early, Researchers Look to Nanotechnology

Science Meets Art to Build a Paintable Diagnostic Test for Cancer

Detective Work: How Implantable Nanosensors Could Monitor Cancer Activity


M Kim, C Chen, P Wang, JJ Mulvey, Y Yang, C Wun, M Antman-Passig, H-B Luo, S Cho, K Long-Roche, LV Ramanathan, A Jagota, M Zheng, Y Wang, DA Heller*. “Machine-Learning-Based Detection of an Ovarian Cancer Disease Fingerprint from Serum via Quantum Defect-Modified Carbon Nanotube Arrays.” Nature Biomedical Engineering (2022).

Z Yaari, Y Yang, E Apfelbaum, C Cupo, A Settle, Q Cullen, W Cai, K Long Roche, DA Levine, M Fleisher, LV Ramanathan, M Zheng, A Jagota, DA Heller*. “A Perception-Based Machine-Perception Nanosensor Platform to Detect Cancer Biomarkers.” Science Advances (2021) In press.

J Budhathoki-Uprety, J Shah, JA Korsen, AE Wayne, TV Galassi, JR Cohen, JD Harvey, PV Jena, LV Ramanathan, EA Jaimes, DA Heller*. “Synthetic Molecular Recognition Nanosensor Paint for Microalbuminuria.” Nature Communications 10 (2019) 3605. 

RM Williams, C Lee, TV Galassi, JD Harvey, R Leicher, M Sirenko, M Dorso, J Shah, N Olvera, F Dao, DA Levine,DA Heller*. “Non-Invasive Ovarian Cancer Biomarker Detection via an Optical Nanosensor Implant.” Science Advances 4 (2018) eaaq1090.

JD Harvey, PV Jena, HA Baker, GH Zerze, RM Williams, TV Galassi, D Roxbury, J Mittal, DA Heller: “A Carbon Nanotube Reporter of miRNA Hybridization Events In Vivo.” Nature Biomedical Engineering 1 (2017) 0041