Beschreibung:
e17076 Background: Cancer is a genetic disease. However, because of the randomness of mutations, less than 20% of patients have known driver mutations and it is estimated that in the United States, less than 5% of patients benefit from genome-driven targeted therapy. [1] Thus, treatment for millions of cancer patients is still today a hit or miss experiment. Therefore, we have developed a developed a genome-free and mechanism agnostic 3D micro-tumor platform (SAGE Direct Test™) to help oncologists and patients alike to directly identify the treatment that is most effective for an individual patient. Methods: The SAGE Direct Test™ works as follows with actionable results within 1 week: Disaggregation of the patient’s tumor tissue and recreation of 3D microtumors that resemble the tumor biology and heterogeneity of the patient’s primary tumor biopsy. Exposure of those 3D microtumors to a panel of potential treatment options. Measuring the metabolic or image-based response of such 3D microtumors, for example as EC50. Results: We created hundreds of 3D micro-tumors from biopsies of 7 ovarian cancer patients. Not surprisingly, when these microtumors were exposed to various cytotoxic chemotherapies such as cisplatin, paclitaxel or gemcitabine or targeted therapies such as erlotinib or crizotinib, the median EC50 varied significantly from drug to drug. However, for any given drug, the EC50 varied significantly from patient to patient, with an interquartile range spreading often by more than one order of magnitude. Values in the table are standardized means with their standard deviations. Conclusions: We have developed a 3D micro-tumor model that can measure the sensitivity of a patient’s cancer biopsy tissue within one week. Furthermore, we found that the sensitivities of those 3D microtumors differed significantly from patient to patient. These results have not yet established a correlation between this 3D micro-tumor model and patients’ tumor responses, which is one of the next steps towards establishing clinical utility for the millions of patients where genomic testing remains non-informative. [Table: see text]