AUTHOR=Yang Yang , Li Yaling , Qi Ruiqun , Zhang Lan 

TITLE=Development and Validation of a Combined Glycolysis and Immune Prognostic Model for Melanoma

JOURNAL=Frontiers in Immunology

VOLUME=12

YEAR=2021

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2021.711145

DOI=10.3389/fimmu.2021.711145

ISSN=1664-3224

ABSTRACT=<sec><title>Background</title><p>Glycolytic effects and immune microenvironments play important roles in the development of melanoma. However, reliable biomarkers for prognostic prediction of melanoma as based on glycolysis and immune status remain to be identified.</p></sec><sec><title>Methods</title><p>Glycolysis-related genes (GRGs) were obtained from the Molecular Signatures database and immune-related genes (IRGs) were downloaded from the ImmPort dataset. Prognostic GRGs and IRGs in the TCGA (The Cancer Genome Atlas) and GSE65904 datasets were identified. Least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression were used for model construction. Glycolysis expression profiles and the infiltration of immune cells were analyzed and compared. Finally, <italic>in vitro</italic> experiments were performed to assess the expression and function of these CIGI genes.</p></sec><sec><title>Results</title><p>Four prognostic glycolysis- and immune-related signatures (<italic>SEMA4D, IFITM1, KIF20A</italic> and <italic>GPR87</italic>) were identified for use in constructing a comprehensive glycolysis and immune (CIGI) model. CIGI proved to be a stable, predictive method as determined from different datasets and subgroups of patients and served as an independent prognostic factor for melanoma patients. In addition, patients in the high-CIGI group showed increased levels of glycolytic gene expressions and exhibited immune-suppressive features. Finally, <italic>SEMA4D</italic> and <italic>IFITM1</italic> may function as tumor suppressor genes, while <italic>KIF20A</italic> and <italic>GPR87</italic> may function as oncogenes in melanoma as revealed from results of <italic>in vitro</italic> experiments.</p></sec><sec><title>Conclusion</title><p>In this report we present our findings on the development and validation of a novel prognostic classifier for use in patients with melanoma as based on glycolysis and immune expression profiles.</p></sec>