Batch Effect Adjustment to Lower the Drug Attrition Rate of MCF-7 Breast Cancer Cells Exposed to Silica Nanomaterial-Derived Scaffolds

Abstract

Drug attrition rate is the calculation or measure of the clinical efficacy of a candidate drug on a screen platform for a specific period. Determining the attrition rate of a prospective cancer drug is a reliable way of testing the clinical efficacy. A low attrition rate in the last phase of a preclinical trial increases the success of a drug discovery process. It has been reported that the attrition rates of antineoplastic drugs are much higher than for other therapeutic drugs. Among the factors identified for the high attrition rates in antineoplastic drugs are the nature of the screen-based platforms involving human-derived xenografts, extracellular matrix-derived scaffold systems, and the synthetic scaffolds, which all have propensity to proliferate tumor cells at faster rates than in vivo primary tumors. Other factors that affect the high attrition rates are induced scaffold toxicity and the use of assays that are irrelevant, yet affect data processing. These factors contribute to the wide variation in data and systematic errors. As a result, it becomes imperative to filter batch variations and to standardize the data. Importantly, understanding the interplay between the biological milieu and scaffold connections is also crucial. Here the cell viability of MCF-7 (breast cancer cell line) cells exposed to different scaffolds were screened before cisplatin dosing using the calculated p-values. The statistical significance (p-value) of data was calculated using the one-way analysis of variance, with the p-value set as: 0 < p < 0.06. In addition, the half-maximal inhibitory concentration (IC50) of the different scaffolds exposed to MCF-7 cells were calculated with the probit extension model and cumulative distribution (%) of the extension data. The chemotherapeutic dose (cisplatin, 56 mg/m2) reduced the cell viability of MCF-7 cells to 5% within 24 h on the scaffold developed from silica nanoparticles (SNPs) and polyethylene glycol (PEG) formulation (SNP:PEG) mixtures with a ratio of 1:10, respectively.