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Efficient DNA mutation detection methods are required for diagnosis, personalized therapy development, and prognosis assessment for diseases such as cancer. To address this issue, we proposed a straightforward approach by combining active plasmonic nanostructures, surface-enhanced Raman spectroscopy (SERS), and polymerase chain reaction (PCR) with a statistical tool to identify and classify BRAF wild type (WT) and V600E mutant genes. The nanostructures provide enhanced sensitivity, while PCR offers high specificity toward target DNA. A series of positively charged plasmonic nanostructures including gold/silver nanospheres, nanoshells, nanoflowers, and nanostars were synthesized with a one-pot strategy and characterized. By changing the shape of nanostructures, we are able to vary the surface plasmon resonance from 551 to 693 nm. The gold/silver nanostar showed the highest SERS activity, which was employed for DNA mutation detection. We reproducibly analyzed as few as 100 copies of target DNA sequences using gold/silver nanostars, thus demonstrating the high sensitivity of the direct SERS detection. By means of statistical analysis (principal component analysis-linear discriminant analysis), this method was successfully applied to differentiate the WT and V600E mutant both from whole genome DNA lysed from cell line and from cell-free DNA collected from cell culture media. We further proved that this assay is capable of specifically amplifying and accurately classifying a real plasma sample. Thus, this direct SERS strategy combined with the active plasmonic nanostructures has the potential for wide applications as an alternative tool for sensitively monitoring and evaluating important clinical nucleotide biomarkers.