Apoptosis and necrosis are the two major forms of cell death mechanisms. Both forms of cell death are involved in several physiological and pathological conditions and also in the elimination of cancer cells following successful chemotherapy. Large number of cellular and biochemical assays have evolved to determine apoptosis or necrosis for qualitative and quantitative purposes. A closer analysis of the assays and their performance reveal the difficulty in using any of these methods as a confirmatory approach, owing to the secondary induction of necrosis in apoptotic cells. This highlights the essential requirement of an approach with a real-time analysis capability for discriminating the two forms of cell death. This paper describes a sensitive live cell-based method for distinguishing apoptosis and necrosis at single-cell level. The method uses cancer cells stably expressing genetically encoded FRET-based active caspase detection probe and DsRed fluorescent protein targeted to mitochondria. Caspase activation is visualized by loss of FRET upon cleavage of the FRET probe, while retention of mitochondrial fluorescence and loss of FRET probe before its cleavage confirms necrosis. The absence of cleavage as well as the retention of mitochondrial fluorescence indicates live cells. The method described here forms an extremely sensitive tool to visualize and quantify apoptosis and necrosis, which is adaptable for diverse microscopic, flow cytometric techniques and high-throughput imaging platforms with potential application in diverse areas of cell biology and oncology drug screening.

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Oral cancer is a dreadful disease with a wide variation in geographical distribution. In order to identify some useful biomarkers for the disease prognosis, the present study assessed the influence of single nucleotide polymorphisms (SNPs) in cell cycle genes on survival in a well-annotated set of patients with oral squamous cell carcinoma (OSCC). The study examined 12 sequence variants or SNPs in selected cell cycle genes, with prognostic outcomes in 311 oral cancer patients. Our analysis showed that SNPs in cyclin D1:rs9344 and retinoblastoma:rs427686 genes showed a strong correlation with disease-free survival. In addition, the cumulative effect of these SNPs significantly and independently predicts the survival. Thus, the current study identified genotypes (SNP signature), which can be used as novel prognostic biomarkers to stratify patients based on disease-free survival and therefore maybe helpful in therapeutic decision-making.