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Background: The tumor microenvironment (TME) is critical to every aspect of cancer biology. Organotypic tumor slice cultures (TSCs) preserve the original TME and have demonstrated utility in predicting drug sensitivity, but the association between clinicopathologic parameters and in vitro TSC behavior has not been well-defined., Methods: One hundred and eight fresh tumor specimens from liver resections at a tertiary academic center were procured and precisely cut with a Vibratome to create 250 μm × 6 mm slices. These fixed-dimension TSCs were grown on polytetrafluoroethylene inserts, and their metabolic activities were determined by a colorimetric assay. Correlation between baseline activities and clinicopathologic parameters was assessed. Tissue CEA mRNA expression was determined by RNAseq., Results: By standardizing the dimensions of a slice, we found that adjacent tumor slices have equivalent metabolic activities, while those derived from different tumors exhibit >30-fold range in baseline MTS absorbances, which correlated significantly with the percentage of tumor necrosis based on histologic assessment. Extending this to individual cancers, we were able to detect intra-tumoral heterogeneity over a span of a few millimeters, which reflects differences in tumor cell density and Ki-67 positivity. For colorectal cancers, tissue CEA expression based on RNAseq of tumor slices was found to correlate with clinical response to chemotherapies., Conclusions: We report a standardized method to assess and compare human cancer growth ex vivo across a wide spectrum of tumor samples. TSC reflects the state of tumor behavior and heterogeneity, thus providing a simple approach to study of human cancers with an intact TME., Competing Interests: Conflicts of Interest: The authors have no conflicts of interest to declare., (2020 Annals of Translational Medicine. All rights reserved.)

With the widespread adoption of molecular profiling in clinical oncology practice, many physicians are faced with making therapeutic decisions based upon isolated genomic alterations. For example, epidermal growth factor receptor tyrosine kinase inhibitors (TKIs) are effective in EGFR-mutant non-small cell lung cancers (NSCLC) while anti-EGFR monoclonal antibodies are ineffective in Ras-mutant colorectal cancers. The matching of mutations with drugs aimed at their respective gene products represents the current state of "precision" oncology. Despite the great expectations of this approach, only a fraction of cancers responds to 'targeted' interventions, and many early responders will ultimately develop resistance to these agents. The underwhelming success of mutation-driven therapies across all cancer types is not due to an inability to detect genetic changes in tumors; rather a deficit in functional insight into the genomic alterations that give rise to each cancer. The Achilles heel of precision oncology thus remains the lack of a robust functional understanding of an individual cancer genome that then allows prediction of the best therapy and resultant outcome for that patient. Current practice focuses on one 'actionable' mutation at a time, while solid cancers typically possess many mutations that involve different cellular sub-populations within a tumor. No method or platform currently exists to guide the interpretation of these complex data, nor to accurately predict response to treatment. This problem is particularly germane to primary liver cancers (PLC), for which only a handful of targeted therapies have been introduced. Here, we will review strategies aimed at overcoming some of these challenges in precision oncology, using liver cancer as an example., Competing Interests: Conflicts of Interest: The authors have no conflicts of interest to declare.