Supplementary Figures 1-9 from Nuclear Factor of Activated T-cell Activity Is Associated with Metastatic Capacity in Colon Cancer
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posted on 2023-03-30, 22:47 authored by Manish K. Tripathi, Natasha G. Deane, Jing Zhu, Hanbing An, Shinji Mima, Xiaojing Wang, Sekhar Padmanabhan, Zhiao Shi, Naresh Prodduturi, Kristen K. Ciombor, Xi Chen, M. Kay Washington, Bing Zhang, R. Daniel BeauchampSupplementary Figures 1-9. All supplementary data for publication as referenced in the manuscript
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ARTICLE ABSTRACT
Metastatic recurrence is the leading cause of cancer-related deaths in patients with colorectal carcinoma. To capture the molecular underpinnings for metastasis and tumor progression, we performed integrative network analysis on 11 independent human colorectal cancer gene expression datasets and applied expression data from an immunocompetent mouse model of metastasis as an additional filter for this biologic process. In silico analysis of one metastasis-related coexpression module predicted nuclear factor of activated T-cell (NFAT) transcription factors as potential regulators for the module. Cells selected for invasiveness and metastatic capability expressed higher levels of NFATc1 as compared with poorly metastatic and less invasive parental cells. We found that inhibition of NFATc1 in human and mouse colon cancer cells resulted in decreased invasiveness in culture and downregulation of metastasis-related network genes. Overexpression of NFATc1 significantly increased the metastatic potential of colon cancer cells, whereas inhibition of NFATc1 reduced metastasis growth in an immunocompetent mouse model. Finally, we found that an 8-gene signature comprising genes upregulated by NFATc1 significantly correlated with worse clinical outcomes in stage II and III colorectal cancer patients. Thus, NFATc1 regulates colon cancer cell behavior and its transcriptional targets constitute a novel, biologically anchored gene expression signature for the identification of colon cancers with high risk of metastatic recurrence. Cancer Res; 74(23); 6947–57. ©2014 AACR.Usage metrics
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BiomarkersCancer PreventionBiological mechanisms in preventionCarcinogenesisAnimal models of carcinogenesisRisk assessmentComputational MethodsGene expression profilingGastrointestinal CancersColorectal cancerGene TechnologiesMicroarraysGenome BiologyFunctional genomicsProgression, Invasion & MetastasisMetastasis
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