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Abstract Oral squamous cell carcinoma (OSCC) is a malignant tumour of Head and Neck Cancer (HNC). The recent therapeutic approaches used to treat cancer have adverse side effects. The natural agents exhibiting anticancer activities are generally considered to have a robust therapeutic potential. Curcuminoids, one of the major active compounds of the turmeric herb, are used as a therapeutic agent for several diseases including cancer. In this study, the cytotoxicity of curcuminoids was investigated against OSCC cell line HNO97. Our data showed that curcuminoids significantly inhibits the proliferation of HNO97 in a time and dose-dependent manner (IC50=35 μM). Cell cycle analysis demonstrated that curcuminoids increased the percentage of G2/M phase cell populations in the treated groups. Treating HNO97 cells with curcuminoids led to cell shrinking and increased detached cells, which are the typical appearance of apoptotic cells. Moreover, flow cytometry analysis revealed that curcuminoids significantly induced apoptosis in a time-dependent manner. Furthermore, as a response to curcuminoids treatment, comet tails were formed in cell nuclei due to the induction of DNA damage. Curcuminoids treatment reduced the colony formation capacity of HNO97 cells and induced morphological changes. Overall, these findings demonstrate that curcuminoids can in vitro inhibit HNC proliferation and metastasis and induce apoptosis.

Abstract Bulbine natalensis and Chorophytum comosum are potential medicinal source for the treatment of cancers. Chronic myeloid leukaemia is a hematopoietic stem cells disorder treated by tyrosine kinase inhibitors but often cause recurrence of the leukaemia after cessation of therapy, hence require alternative treatment. This study determines the anti-cancer effect of leaf, root and bulb methanolic and aqueous extracts of B. natalensis and C. comosum in chronic human myelogenous leukaemia (K562) cell line by MTT, Hoechst bis-benzimide nuclear and annexin V stain assays. The root methanolic extract of B. natalensis and C. comosum showed a high cytotoxicity of 8.6% and 16.7% respectively on the K562 cell line at 1,000 μg/ml concentration. Morphological loss of cell membrane integrity causing degradation of the cell and fragmentation were observed in the root methanolic extract of both plants. A high apoptosis (p < 0.0001) was induced in the K562 cells by both leaf and root extracts of the C. comosum compared to the B. natalensis. This study shows both plants possess apoptotic effect against in vitro myelogenous leukaemia which contributes to the overall anti-cancer properties of B. natalensis and C. comosum to justify future therapeutic applications against chronic myelogenous leukaemia blood cancer.

Abstract When applying the improved composition of the solution used during endoscopic mucosal resection (EMR), we observed unexpectedly large and quantitatively significant differences in adenoma response vs. healthy tissue of the surrounding GIT tract, namely, the selective reaction enhancing the adenoma volume and differentiated colour. The in vitro experiments on the model neoplasia cell line HCT116 suggest that the robust differences in the response of starving cells can be traced down principally to tetrastarch digestion and the enhanced metabolic rate of neoplastic cells. The neoplastic tissue grows into several intestine layers so that submucosal injection of iso-oncotic tetrastarch compound leads to degradation of starch and production of oncotic molecules in submucosa transported by facilitated transport into the neoplastic tissue. The colour distinction is due to concentration differences of the reporting dye between three separated compartments, further enhancing the utility of the contrasting mixture. The diffusion dynamics shall be tuneable by optimizing starch composition, improving desirable pharmacokinetics.

ABSTRACT Computational drug sensitivity models have the potential to improve therapeutic outcomes by identifying targeted drug components that are likely to achieve the highest efficacy for a cancer cell line at hand at a therapeutic dose. State of the art drug sensitivity models use regression techniques to predict the inhibitory concentration of a drug for a tumor cell line. This regression objective is not directly aligned with either of these principal goals of drug sensitivity models: We argue that drug sensitivity modeling should be seen as a ranking problem with an optimization criterion that quantifies a drug’s inhibitory capacity for the cancer cell line at hand relative to its toxicity for healthy cells. We derive an extension to the well-established drug sensitivity regression model PaccMann that employs a ranking loss and focuses on the ratio of inhibitory concentration and therapeutic dosage range. We find that the ranking extension significantly enhances the model’s capability to identify the most effective anticancer drugs for unseen tumor cell profiles based in on in-vitro data.