UC Berkeley

COVID-19 and lung cancer are two diseases that have enormous negative impacts on human health worldwide. COVID-19 has killed more than 3.9 million people globally, and the emergence and spread of new variants continue to necessitate strict restrictions on movement among, and within, many countries, thus inflicting significant psychological and economic damage. Lung cancer has nearly as significant an impact: in 2020, an estimated 1.8 million people died of lung cancer, more than any other cancer. Both COVID-19 and lung cancer can be diagnosed and monitored by detecting disease biomarkers in biofluids.

COVID-19 is typically diagnosed with RT-qPCR tests that detect SARS-CoV-2, the enveloped virus that causes the disease, based on the presence of viral RNA. While sensitive, these tests have several shortcomings, including being resource-intensive and susceptible to amplifying residual genomic fragments, even after a patient has recovered. Therefore, we developed a streamlined method to detect only intact SARS-CoV-2, the presence of which is a better indicator than viral RNA that a patient is contagious.

To detect intact virus, we make use of two properties of SARS-CoV-2: its encapsulation in a lipid bilayer membrane and its presentation of Spike protein. Our method is based on 1) labeling SARS-CoV-2 with exogenous single-stranded DNA oligonucleotides (ssDNA oligo); 2) capturing the labeled particles on paramagnetic beads coated with ACE2, the primary protein on human cells to which the SARS-CoV-2 binds; and 3) performing qPCR on the ssDNA oligo labels, which will produce a signal that increases linearly with SARS-CoV-2 count. We developed and validated this method using two models of SARS-CoV-2: liposomes displaying Spike protein (spike-liposomes) and Spike-pseudotyped lentivirus. We found the output signal to be highly responsive to the number of spike-liposomes in a sample over four orders of magnitude, and we demonstrated the detection of just 10,000 spike-liposomes or 100 pfu Spike-pseudotyped lentivirus and the specific detection of Spike-pseudotyped lentivirus in a background of proteins and vesicles in cell culture supernatant.

Another type of lipid bilayer nanoparticle, extracellular vesicles (EVs), are 30-150 nm in diameter, released from virtually all cells, contain proteins and nucleic acids from their cell of origin, and are found in all biofluids. By detecting EVs displaying lung cancer-associated surface proteins, lung cancer could be diagnosed via a non- or minimally-invasive liquid biopsy. We developed two methods to detect specifically lung tumor-derived EVs: the first is based on oligo tagging of the lipid bilayer membrane of EVs, and the second is based on measuring the size increase of microbeads when tumor-derived EVs are captured.

To detect tumor-derived EVs, we adapted the oligo labeling method used to detect SARS-CoV-2. Specifically, our method is based on 1) labeling all EVs with ssDNA oligos; 2) capturing specifically tumor-derived EVs on paramagnetic beads coated with antibodies for lung tumor-associated surface proteins; and 3) performing qPCR on the ssDNA oligo labels, which will produce a signal that increases linearly with tumor-derived EV count. We demonstrated the specific detection of spiked tumor-derived EVs in human serum and the potential for quantifying EVs nondestructively by cleaving the oligo labels from the EV surface using a restriction enzyme prior to qPCR.

As an alternative method to detect tumor-derived EVs, we applied the principle of node-pore sensing (NPS), in which a segmented microfluidic channel is paired with ultra-sensitive electronics to measure nano-scale differences in the size of microbeads. Using this method, we were able to detect an increase in the mean size of beads functionalized with antibodies for lung tumor-associated surface markers when tumor-derived EVs bound specifically. We present the design, development, and characterization of an NPS platform - including a microfluidic device, instrumentation, and data analysis pipeline - that is capable of detecting EVs displaying specific surface markers. Using this platform, we demonstrated the specific detection of tumor-derived EVs from cell culture supernatant.

Both cholesterol-oligo tagging and NPS are promising methods for detecting tumor-derived EVs or enveloped viruses in biofluids for routine lung cancer or viral screening.