Shiladitya Sengupta

Predicting clinical response to anticancer drugs remains a major challenge in cancer treatment. Emerging reports indicate that the tumour microenvironment and heterogeneity can limit the predictive power of current biomarker-guided strategies for chemotherapy. Here we report the engineering of personalized tumour ecosystems that contextually conserve the tumour heterogeneity, and phenocopy the tumour microenvironment using tumour explants maintained in defined tumour grade-matched matrix support and autologous patient serum. The functional response of tumour ecosystems, engineered from 109 patients, to anticancer drugs, together with the corresponding clinical outcomes, is used to train a machine learning algorithm; the learned model is then applied to predict the clinical response in an independent validation group of 55 patients, where we achieve 100% sensitivity in predictions while keeping specificity in a desired high range. The tumour ecosystem and algorithm, together termed the CANScript technology, can emerge as a powerful platform for enabling personalized medicine.

Understanding the emerging models of adaptive resistance is key to overcoming cancer chemotherapy failure. Using human breast cancer explants, in vitro cell lines, mouse in vivo studies and mathematical modelling, here we show that exposure to a taxane induces phenotypic cell state transition towards a favoured transient CD44(Hi)CD24(Hi) chemotherapy-tolerant state. This state is associated with a clustering of CD44 and CD24 in membrane lipid rafts, leading to the activation of Src Family Kinase (SFK)/hemopoietic cell kinase (Hck) and suppression of apoptosis. The use of pharmacological inhibitors of SFK/Hck in combination with taxanes in a temporally constrained manner, where the kinase inhibitor is administered post taxane treatment, but not when co-administered, markedly sensitizes the chemotolerant cells to the chemotherapy. This approach of harnessing chemotherapy-induced phenotypic cell state transition for improving antitumour outcome could emerge as a translational strategy for the management of cancer.

In the present study, we report the novel application of polyhydroxylated fullerenes (fullerenols) in cancer drug delivery. The facile synthetic procedure for generating multiple hydroxyl groups on the fullerene cage offers scope for high drug loading in addition to conferring hydrophilicity. Doxorubicin, a first line cancer chemotherapeutic, was conjugated to fullerenols through a carbamate linker, achieving ultrahigh loading efficiency. The drug-fullerenol conjugate was found to be relatively stable in phosphate buffer saline but temporally released the active drug when incubated with tumor cell lysate. The fullerenol-doxorubicin conjugate suppressed the proliferation of cancer cell-lines in vitro through a G2-M cell cycle block, resulting in apoptosis. Furthermore, in an in vivo murine tumor model, fullerenol-doxorubicin exhibited comparable antitumor efficacy as free drug without the systemic toxicity of free doxorubicin. Additionally, we demonstrate that the fullerenol platform can be extended to other chemotherapeutic agents, such as the slightly water-soluble cisplatin, and can emerge as a new paradigm in the management of cancer.