Search

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]