Gold Biosensor + Smartphone = Portable Cancer Test System

One of the things most people fear most is being diagnosed with some form of cancer. One of the things most often broadcast about cancer, something everyone should know, is early detection greatly increases the possibility of survival. But for a lot of people, getting to regular checkups is a hassle, or, in some cases they can’t afford it, and/or it’s just not an available option where they live.

 

University of Buffalo (UB) researchers are also aware that early diagnosis of cancer greatly improves the odds of successful treatment. In response to this, a UB-led research team is creating a new cancer-spotting tool that health care providers could eventually use in areas that lack hospitals, clinics, and other treatment centers. Presented in two research papers published this year in the IEEE Journal of Selected Topics in Quantum Electronics and ACS Sensors, the instrument the UB team created employs a unique gold biosensor, which the research team created. When used with a smartphone or computer and some inexpensive tools, the system spots cancer biomarkers from a blood sample.

Sponsored by Anritsu Company

New VNA technologies enable mmWave broadband testing to 220 GHz, helping researchers and engineers to overcome test challenges and simplify mmWave testing.

Application development in the mmWave frequencies is growing. Broadband testing over hundreds of GHz of bandwidth is subject to repeatability/accuracy deficits, and engineers demand solutions to help overcome challenges and simplify mmWave testing.

 

The researchers tested the system by mounting the gold biosensor to a glass slide. Next, they applied blood samples from lung-cancer patients to the top of the biosensor, after which they shed LED light onto the sample.

 

According to the researchers, the cancer blood sample contains tiny organic particles called exosomes that contain lung cancer biomarkers. These biomarkers bind to the biosensor and cause the intensity of the light to change. By measuring the change of the light intensity before and after applying the blood sample, researchers can detect the biomarkers. This type of sensing is known as surface plasmon resonance, or SPR sensing.

 

In another experiment, the researchers mounted the biosensor to a smartphone’s camera. The system provided real-time imaging of exosomes containing epidermal growth factor receptor (EFGR), a protein commonly found in non-small cell lung cancer patients that can be used as a biomarker for screening and early detection.

 

Yun Wu

The system can detect another biomarker called programmed death-ligand 1 (PD-L1), a protein that stops the immune system from attacking cancer cells. Doctors measure PD-L1 levels in lung cancer patients to assess effectiveness of a checkpoint inhibitor treatment. Overall results show the system is comparable in sensing accuracy to common cancer diagnostic tests, such as enzyme-linked immunosorbent assay (ELISA). Yun Wu, PhD, assistant professor of biomedical engineering at UB, also a co-lead author of the studies points out, “Preliminary tests show our system is about as effective as the diagnostic tests that many hospitals use. We’re hoping to refine the system and get it into the hands of people who need it the most, because the earlier we detect cancer, the better the treatment outcomes are.”

 

Qiaoqiang Gan

Aside from its accurate diagnostic abilities, the system has the advantage of being small, easy to operate, and costs less than existing tools in common use. Qiaoqiang Gan, PhD, associate professor of electrical engineering in UB’s School of Engineering and Applied Sciences, and a co-lead author of the studies states “Smartphones and computers are increasingly common in places where basic health care is not. Our system takes advantage of that. We’ve designed a simple yet effective cancer screening system that we believe can eventually be deployed to areas that need it most.” For more details, visit the University at Buffalo.

Read more on

Suggested Articles

Video "experience" service by Revl doesn’t rely on an AI chip

Nvidia saw its stock drop by 16% from its high a week ago

AMD and Nvidia saw 6% drop, joining long list of losers