The Origins of Gastric Cancer From Gastric Stem Cells: Lessons From Mouse Models

Mitochondrial biomarkers predict tumor progression and poor overall survival in gastric cancers: Companion diagnostics for personalized medicine

Here, we employed a bioinformatics approach to identify novel molecular determinants to predict tumor progression and overall survival in gastric cancer patients. In particular, we directly assessed whether nuclear-derived mRNA species encoding proteins involved in mitochondrial protein translation and OXPHOS are able to successfully predict clinical outcome in gastric cancer. As such, using in silico validation, we have now established the prognostic value of these mitochondrial biomarkers, in a defined population of gastric cancer patients. In this context, we interrogated 5 year follow-up data collected from a group of N = 359 gastric cancer patients. Importantly, in this group of cancer patients, Ki67 and PCNA (conventional markers of cell proliferation) were associated with tumor progression, as might be expected. Using this simplified informatics approach, we identified ∼75 new individual mitochondrial gene probes that effectively predicted tumor progression, with hazard-ratios (HR) of up to 2.22 (p < 2.1e-10). These mitochondrial mRNA transcripts included heat shock proteins/chaperones, membrane proteins, anti-oxidants, enzymes involved in genome maintenance, as well as mitochondrial ribosomal proteins (MRPs) and numerous members of the OXPHOS complexes. In addition, we combined 8 mitochondrial protein transcripts (NDUFS5, VDAC3, ATP5O, IMMT, MRPL28, COX5B, MRPL52, PRKDC), to generate a compact gastric mitochondrial gene signature, associated with a HR of 2.77 (p = 1.4e-14). As a result of this analysis and validation, we strongly suggest that proteins involved in mitochondrial protein translation and OXPHOS should be considered as targets for new drug discovery, for the treatment of gastric cancers. The mitochondrial markers we identified here could also be used as companion diagnostics, to predict clinical outcomes, as well as the patient response to therapy. This should allow a more successful and personalized approach to gastric cancer diagnosis and therapy.

Porcine Esophageal Submucosal Gland Culture Model Shows Capacity for Proliferation and Differentiation

BACKGROUND & AIMS

Although cells comprising esophageal submucosal glands (ESMGs) represent a potential progenitor cell niche, new models are needed to understand their capacity to proliferate and differentiate. By histologic appearance, ESMGs have been associated with both overlying normal squamous epithelium and columnar epithelium. Our aim was to assess ESMG proliferation and differentiation in a 3-dimensional culture model.

METHODS

We evaluated proliferation in human ESMGs from normal and diseased tissue by proliferating cell nuclear antigen immunohistochemistry. Next, we compared 5-ethynyl-2'-deoxyuridine labeling in porcine ESMGs in vivo before and after esophageal injury with a novel in vitro porcine organoid ESMG model. Microarray analysis of ESMGs in culture was compared with squamous epithelium and fresh ESMGs.

RESULTS

Marked proliferation was observed in human ESMGs of diseased tissue. This activated ESMG state was recapitulated after esophageal injury in an in vivo porcine model, ESMGs assumed a ductal appearance with increased proliferation compared with control. Isolated and cultured porcine ESMGs produced buds with actively cycling cells and passaged to form epidermal growth factor-dependent spheroids. These spheroids were highly proliferative and were passaged multiple times. Two phenotypes of spheroids were identified: solid squamous (P63+) and hollow/ductal (cytokeratin 7+). Microarray analysis showed spheroids to be distinct from parent ESMGs and enriched for columnar transcripts.

CONCLUSIONS

Our results suggest that the activated ESMG state, seen in both human disease and our porcine model, may provide a source of cells to repopulate damaged epithelium in a normal manner (squamous) or abnormally (columnar epithelium). This culture model will allow the evaluation of factors that drive ESMGs in the regeneration of injured epithelium. The raw microarray data have been uploaded to the National Center for Biotechnology Information Gene Expression Omnibus (accession number: GSE100543).