There is evidence to suggest that the next generation of cancer screening tests may employ not just one, but a small panel of less than ten biomarkers, that together add statistical power to the detection of specific cancers. While immunoassays such as ELISA are well established for antigen-based biomarker detection, the fidelity of the assay is primarily governed by the disassociation constant, Kd, of the antibody-antigen complex. If the antigen concentration is significantly below the Kd, then the binding kinetics are slow and read-out precision of the antigen-antibody complex is degraded by noise. We are proposing a general approach for improving the performance of immunoassays. The approach is based on a nano/microfluidic device that controllably concentrates biomarkers to the vicinity of the Kd. Provided the amplification (or gain) of the concentrator is adjustable, the dynamic range and detection limit of the immunoassay will ultimately be governed by the properties of the concentrator and not the Kd. We have developed and validated a nanochannel-based preconcentrator that increases sample concentration linearly with time and can enhance the initial sample concentration by approximately 10/7 in an hour. Since the total volume of the concentrate is 10-100 pL, we are proposing to integrate the preconcentrator with a detector of similar volume in order to avoid dilution. The detector is conceptually similar to ELISA;however, the read-out of the antigen-antibody binding is based on the direct detection of biomarker mass with picogram resolution within a 10 pL volume. Thus, we anticipate that the combined concentrator and SMR detection system will allow a specific biomarker to be detected at a resolution near 1 pg/mL. In order to enhance the predictive power of biomarkers for cancer, we will profile the abundance of four different biomarkers from a single sample with an integrated system. The system will be batch fabricated by conventional foundry-level micromachining processes to enable widespread and low-cost distribution for point-of-care applications.
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