Abstract
Genetic and epigenetic modifications are linked to the activation of oncogenes and inactivation of tumor suppressor genes. Likewise, the associated molecular alternations can best inform precision medicine for personalized tumor treatment. Therefore, performing characterization of genetic and epigenetic alternations at the molecular level represents a crucial step in early diagnosis and/or therapeutics of cancer. However, the prevailing methods for DNA analysis involve a series of tedious and complicated steps, in which important genetic and epigenetic information could be lost or altered. To provide a potential approach for non-invasive, direct, and efficient DNA analysis, herein, we present a promising strategy for label-free molecular profiling of serum DNA in its pristine form by fusing surface-enhanced Raman spectroscopy with machine learning on a superior plasmonic nanostructured platform. Using DNA methylation and single-point mutation as two case studies, the presented strategy allows a well-balanced sensitive and specific detection of epigenetic and genetic changes at the single-nucleotide level in serum. We envision the presented label-free strategy could serve as a versatile tool for direct molecular profiling in pristine forms of a wide range of biological markers and aid biomedical diagnostics as well as therapeutics.