Gene expression programs of lactic acidosis in human cancers

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DESCRIPTION (provided by applicant): One challenge in cancer research is how to translate the findings obtained with cell culture in vitro to the complex behaviors of human cancers in vivo. We previously identified a hypoxia gene signature in cultured cells to allow us infer the level of hypoxia pathway activities in many human cancers to identify patients with strong hypoxia response. By relating in vitro cell culture models to their in vivo cancer counterparts via the common language of "gene signature", we found we can recognize the molecular programs in human cancers reflecting defined perturbations in culture to explore their prognostic significance and phenotypic characteristics. Tumor microenvironments play critical roles in determining tumor behaviors and treatment responses and are featured by hypoxia and lactic acidosis. Although lactic acidosis is reported to be associated with tumor aggression and poor clinical outcomes, we know little about how cells respond to lactic acidosis, their prognostic significance in human cancers and best ways to identify tumors with this feature. In this proposal, we will use global gene expression in cell culture and human cancers to understand the role lactic acidosis in human cancers. We will first determine the transcriptional responses to lactic acidosis in various cultured cells to define "gene signatures" reflecting lactic acidosis. The possibility of abolishing this response by inhibiting Acid-Sensing Ion Channel (ASICs) or hypoxia-inducible factor (HIF) proteins will be tested. Secondly, the gene expression pattern associated with high lactate levels in tumors will be determined based on gene expression analysis of human cancers with measured lactate levels. The lactic acidosis gene signatures, obtained either in cell culture or tumors, will be used as molecular gauges to determine the level of lactic acidosis response in tumors based on gene expression. The prognostic significances of these gene signatures will be further tested in many other gene expression studies and the composition of molecular pathways lactic acidosis tumors will also be identified with advanced bioinformatics. To allow us to identify lactic acidosis cancers with high clinical risks, we will select molecular markers based on our gene expression studies. The spatial distribution of marker expression in tumor tissues will be compared to hypoxia markers (CA9) and measured tumor physiology parameters. Their prognostic values of these candidate markers will be further determined on multiple cancer tissue microarrays.