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Nanopore-Based DNA Computing Detects Cancer at Subfemtomolar Concentrations

By Brittany Wade 

July 20, 2022 | Cholangiocarcinoma, or bile duct cancer, is a complex and rapidly progressing disease often deemed terminal at the time of diagnosis. The race to develop early diagnostic methods to improve patient outcomes and prevent costly and invasive surgical biopsies has been underway for quite some time. 

Liquid biopsies–testing procedures that look for cancer cells in biological fluids such as blood–have quickly become a preferred diagnostic method given their non-invasive nature and relatively low cost. Still, with aggressive diseases such as intrahepatic cholangiocarcinoma, there was a growing need to detect cancers even earlier and with greater precision.  

A research team at the Tokyo University of Agriculture and Technology (TUAT) expounded on traditional liquid biopsies by incorporating nanopore-based DNA computing technology to detect subpicomolar–less than one-trillionth of a mole per liter–concentrations of cancerous genetic material.  

Before this experiment, picomolar levels were considered the detection limit for similar methods. Detecting such low concentrations means scientists can diagnose cancer in its initial stages, resulting in better prognoses. 

DNA-Based Diagnostics 

As customary with liquid biopsies, plasma samples were collected from cholangiocarcinoma patients. Each specimen naturally contained a group of molecules of particular interest: microRNAs (miRNAs). MicroRNAs are small, single-stranded, non-coding genetic molecules that bind DNA and regulate gene expression. Scientists favor miRNA as target biomarkers because they are cancer-specific and expressed in early stages. 

DNA computing is a powerful diagnostic method for liquid biopsies, as they run mathematical computations with nucleic acids rather than silicon chips. “DNA computing uses the biochemical reactions of the information-encoding DNA molecules to solve problems based on formal logic, in the same way that normal computers do,” said Ryuji Kawano, TUAT Professor and corresponding author, in a press release.  

Though DNA computing offers numerous benefits, conventional biological computing cannot occur without additional procedures like gel electrophoresis, fluorescence detection, and polymerase chain reaction amplification. By pursuing a nanopore-based approach, the team eliminated unnecessary methodologies. They also increased detection speed, decreased costs, and detected oncologic genetic material at astonishingly low concentrations. 

High-Specificity Nanopore Analysis 

In the case of cholangiocarcinoma, nanopore-based DNA computing can detect five miRNA (miR-193, miR-106a, miR-15a, miR-374, and miR-224) bile duct cancer expression patterns. As published in the Journal of the American Chemical Society, the team created a custom DNA-miRNA complex–also called a hybridized computational molecule–to be decoded by a nanopore: a protein pore the size of a nanometer (DOI: 10.1021/jacsau.2c00117). 

“In this case, a diagnostic DNA molecule was designed to be able to bind five different kinds of miRNA associated with bile duct cancer. In the process of binding the miRNA molecules, the diagnostic DNA converts the expression pattern of the miRNAs into the information contained in the form of a nucleic acid structure,” explains Kawano. 

When the hybridized molecule passes through the nanopore, miRNA unwinds–or “unzips”–from the DNA and halts the amplitude and duration of the electrical current flowing through the pore. Those electrical disruptions are measured and used to define the passing miRNA molecules.  

The team successfully detected as small as attomolar (10–18 M/L) concentrations of cholangiocarcinoma miRNA using clinical samples and subfemtomolar (10–15 M/L) concentrations without any adjustments to the basic nanopore analysis procedure. For reference, a picomole–the previous standard–is 10–12 M. With unprecedented detection levels, the TUAT team is pushing the limits of technology and emphasizing its role in the power of precision oncology. 

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