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These figures contain extensions of data that would not fit in the primary manuscript but are important for a complete understanding of the work. These include analysis of other data sets, correlations between genomic profiling our stromal subtyping and information on bioinformatics and animal models.

Treatment of metastatic gastric cancer typically involves chemotherapy and monoclonal antibodies targeting HER2 (ERBB2) and VEGFR2 (KDR). However, reliable methods to identify patients who would benefit most from a combination of treatment modalities targeting the tumor stroma, including new immunotherapy approaches, are still lacking. Therefore, we integrated a mouse model of stromal activation and gastric cancer genomic information to identify gene expression signatures that may inform treatment strategies. We generated a mouse model in which VEGF-A is expressed via adenovirus, enabling a stromal response marked by immune infiltration and angiogenesis at the injection site, and identified distinct stromal gene expression signatures. With these data, we designed multiplexed IHC assays that were applied to human primary gastric tumors and classified each tumor to a dominant stromal phenotype representative of the vascular and immune diversity found in gastric cancer. We also refined the stromal gene signatures and explored their relation to the dominant patient phenotypes identified by recent large-scale studies of gastric cancer genomics (The Cancer Genome Atlas and Asian Cancer Research Group), revealing four distinct stromal phenotypes. Collectively, these findings suggest that a genomics-based systems approach focused on the tumor stroma can be used to discover putative predictive biomarkers of treatment response, especially to antiangiogenesis agents and immunotherapy, thus offering an opportunity to improve patient stratification. Cancer Res; 76(9); 2573–86. ©2016 AACR.

These figures contain extensions of data that would not fit in the primary manuscript but are important for a complete understanding of the work. These include analysis of other data sets, correlations between genomic profiling our stromal subtyping and information on bioinformatics and animal models.

This file contains details too lengthy to put in the primary manuscript file as well as methods for supplemental data

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In this chapter, we present the methodology currently used in our laboratory to generate a starPEG-MMP (starPEG)- and heparin maleimide HM06 (heparin)-based 3D cell culture system, in a hydrogel, that can be used to study human neuronal development and Alzheimer's disease (AD) pathology. A 3D cell culture system can mimic the in vivo cellular environment better than a 2D format, in which these cells exhibit neural network formation, electrophysiological activity, tissue-specific extracellular matrix (ECM) deposition, and neurotransmitter responsiveness. When treated with amyloid beta-42 (Aβ42) peptides, this system recapitulates many of the pathological effects of AD, including reduced neural stem cell proliferation, impaired neuronal network formation, dystrophic axonal ends, synaptic loss, failure to deposit ECM, elevated tau hyperphosphorylation, and formation of neurofibrillary tangles. Culturing human primary cortical astrocyte (pHA)- or induced pluripotent stem cell (iPSC)-derived human neural stem cells in this biohybrid hydrogel system has led to the discovery of novel regulatory pathways underlying neurodegenerative pathology in different phases of AD.