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Background: Despite our efforts to develop effective treatment paradigms, the overall success rates of most of the anti-cancer therapies for aggressive cancers remain very low. There is an urgent need to develop novel therapeutics to meet the present challenges. In recent years, several plant derived chemicals showed promising return as antineoplastic agents. Objective: Here, we evaluate the anticancer effects of one well known phytochemical Lupeol on a panel of aggressive cancer types in preclinical platforms. Methods: Melanoma (B16- F10), breast cancer (MDA MB- 231), Cisplatin resistant laryngeal cancer cell line HEp-2c, oral cancer cell line UPCI: SCC131 and prostate cancer (PC-3) cell lines were treated with different doses of Lupeol for 24 and 48 hours. Cytotoxic effects of these agents were measured by different endpoint assays. Matrigel tube formation, Limiting Dilution (LD) and sphere formation assay along with alteration in CD133 expression were performed. The expression status of Ephrin A2 and its downstream molecules were examined in aggressive mouse melanoma solid tumor in vivo. We also established the key findings in a patient derived ex vivo explant model (CANScript TM) for human breast and HNSCC tumors. Results: Viability (MTT) assay showed significant IC50 value for each cell lines treated with Lupeol followed by CFU assay. Concurrently, induction of apoptosis was found to be prominent in treatment arm. We also observed down regulation of CD133 expression and disrupted tube formation in all cell lines that together ascertain their ability to inhibit vasculogenic mimicry (VM). The ability of Lupeol to interfere with cancer stem cell (CSC) like properties was also evident where sphere formation and LD profile demonstrated alteration in the CSC pools for majority. The machinery of these effects suggested its link with Ephrin A2 and its downstream elements driving VM in melanoma in vivo tumour model. Further validation of these data in patient derived CANScript ex vivo setting where efficacy of this drug was tested on the patient tumors clinically progressed on standard of care (SOC). Discussion and conclusion: Together, these data suggest the promising roles of phytochemical in treating diverse cancer indications at aggressive or late stages of the diseases where existing paradigms frequently show limited efficacy. [ABSTRACT FROM AUTHOR]

Basis: Our learning from the limited trajectory of biomarker guided and genomic assay based response prediction to inform clinical action ability of cancers led to the strategic rethinking of developing and validating robust and individualized platform (CANScript) that make prediction based on multiple phenotypic inputs. Methods: Accelerated CANScript Enabled Personalized Treatment (ACCEPT) is an investigator initiated study aiming to predict response to anticancer drugs at clinic. Surgically resected tumors from primary breast cancer patients (n=30) were cultured in slices and treated with Epirubicin, Cyclophosphamide and 5FU in CANScript platform for three days in presence of autologous growth factors, immune milieu and indication specific matrix support where patient tumor microenvironment was extensively preserved. The outcome was measured by integrating both pathological (tumor content, viability, proliferation and induction of apoptosis) and kinetic endpoints (cell viability and metabolism) into a single data trained M score algorithm as described (Majumder B et al., Nature Commun, 2015, Brijwani N et al., Scientific Reports, 2017). After 6 cycles of therapy, following surgery, patients were clinically evaluated for response based on multiple criteria including radiological examination. This short-term clinical response was compared with CANScript driven response prediction. Results: Out of 25 evaluable patients, outcome is available for ten patients (40%) till today. Data indicate that CANScript derived predictive scores for responders and non-responders were highly correlated with clinical observation. For all six clinical non-responders, CANScript guided outcome was found to be matched with clinical outcome. Similarly, for rest 4 patients, while CANScript predicted response, 3 patients showed clinical response. These preliminary data from an ongoing study are encouraging and more patients will be enrolled and follow up data will be collected. Conclusion: Phenotypic assay based platform technologies are emerging as a new frontier of individual response prediction based on the complex and dynamic interplay of tumor and stroma including immune network. CANScript guided prediction of response showed encouraging results to understand the response of drugs at clinic, would offer further opportunity to incorporate phenotypic inputs for informed treatment decision in an adjuvant setting. [ABSTRACT FROM AUTHOR]

Basis: Our learning from the limited trajectory of biomarker guided and genomic assay based response prediction to inform clinical action ability of cancers led to the strategic rethinking of developing and validating robust and individualized platform (CANScript) that make prediction based on multiple phenotypic inputs. Methods: Accelerated CANScript Enabled Personalized Treatment (ACCEPT) is an investigator initiated study aiming to predict response to anticancer drugs at clinic. Surgically resected tumors from primary breast cancer patients (n=30) were cultured in slices and treated with Epirubicin, Cyclophosphamide and 5FU in CANScript platform for three days in presence of autologous growth factors, immune milieu and indication specific matrix support where patient tumor microenvironment was extensively preserved. The outcome was measured by integrating both pathological (tumor content, viability, proliferation and induction of apoptosis) and kinetic endpoints (cell viability and metabolism) into a single data trained M score algorithm as described (Majumder B et al., Nature Commun, 2015, Brijwani N et al., Scientific Reports, 2017). After 6 cycles of therapy, following surgery, patients were clinically evaluated for response based on multiple criteria including radiological examination. This short-term clinical response was compared with CANScript driven response prediction. Results: Out of 25 evaluable patients, outcome is available for ten patients (40%) till today. Data indicate that CANScript derived predictive scores for responders and non-responders were highly correlated with clinical observation. For all six clinical non-responders, CANScript guided outcome was found to be matched with clinical outcome. Similarly, for rest 4 patients, while CANScript predicted response, 3 patients showed clinical response. These preliminary data from an ongoing study are encouraging and more patients will be enrolled and follow up data will be collected. Conclusion: Phenotypic assay based platform technologies are emerging as a new frontier of individual response prediction based on the complex and dynamic interplay of tumor and stroma including immune network. CANScript guided prediction of response showed encouraging results to understand the response of drugs at clinic, would offer further opportunity to incorporate phenotypic inputs for informed treatment decision in an adjuvant setting. [ABSTRACT FROM AUTHOR]