Description of an activity-based enzyme biosensor for lung cancer detection

BACKGROUND

Lung cancer is associated with the greatest cancer mortality as it typically presents with incurable distributed disease. Biomarkers relevant to risk assessment for the detection of lung cancer continue to be a challenge because they are often not detectable during the asymptomatic curable stage of the disease. A solution to population-scale testing for lung cancer will require a combination of performance, scalability, cost-effectiveness, and simplicity.

METHODS

One solution is to measure the activity of serum available enzymes that contribute to the transformation process rather than counting biomarkers. Protease enzymes modify the environment during tumor growth and present an attractive target for detection. An activity based sensor platform sensitive to active protease enzymes is presented. A panel of 18 sensors was used to measure 750 sera samples from participants at increased risk for lung cancer with or without the disease.

RESULTS

A machine learning approach is applied to generate algorithms that detect 90% of cancer patients overall with a specificity of 82% including 90% sensitivity in Stage I when disease intervention is most effective and detection more challenging.

CONCLUSION

This approach is promising as a scalable, clinically useful platform to help detect patients who have lung cancer using a simple blood sample. The performance and cost profile is being pursued in studies as a platform for population wide screening.

Ab initio structural dynamics of pure and nitrogen-containing amorphous carbon

Amorphous carbon (a-C) has attracted considerable interest due to its desirable properties, which are strongly dependent on its structure, density and impurities. Using ab initio molecular dynamics simulations we show that the sp2/sp3 content and underlying structural order of a-C produced via liquid quenching evolve at high temperatures and pressures on sub-nanosecond timescales. Graphite-like densities ([Formula: see text] 2.7 g/cc) favor the formation of layered arrangements characterized by sp2 disordered bonding resembling recently synthesized monolayer amorphous carbon (MAC), while at diamond-like densities ([Formula: see text] 3.3 g/cc) the resulting structures are dominated by disordered tetrahedral sp3 hybridization typical of diamond-like amorphous carbon (DLC). At intermediate densities the system is a highly compressible mixture of coexisting sp2 and sp3 regions that continue to segregate over 10's of picoseconds. The addition of nitrogen (20.3%) (a-CN) generates major system features similar with those of a-C, but has the unexpected effect of reinforcing the thermodynamically disfavored carbon structural motifs at low and high densities, while inhibiting phase separation in the intermediate region. At the same time, no nitrogen elimination from the carbon framework is observed above [Formula: see text] 2.8 g/cc, suggesting that nitrogen impurities are likely to remain embedded in the carbon structures during fast temperature quenches at high pressures.