AUTHOR=Zhang Peng , Wu Xiaofang , Basu Moushumi , Dong Chen , Zheng Pan , Liu Yang , Sandler Anthony David 

TITLE=MYCN Amplification Is Associated with Repressed Cellular Immunity in Neuroblastoma: An In Silico Immunological Analysis of TARGET Database

JOURNAL=Frontiers in Immunology

VOLUME=Volume 8 - 2017

YEAR=2017

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2017.01473

DOI=10.3389/fimmu.2017.01473

ISSN=1664-3224

ABSTRACT=Purpose	RNA and DNA sequencing data are traditionally used to discern intrinsic cellular pathways in cancer pathogenesis, their utility for investigating the tumor microenvironment has not been fully explored.  This study explores the use of sequencing data to investigate immunity within the tumor microenvironment.
Experimental design 	Here we use immune cell fraction estimation analysis to determine the immune profiles in the microenvironment of neuroblastoma based on RNAseq data in the TARGET database. The correlation between immune cell transcripts and prognosis in pediatric neuroblastoma is also investigated.  
Results	 In silico analysis revealed a strong inverse correlation between MYCN amplification and leukocyte infiltration. This finding was validated by immunohistochemistry analysis in tumor samples. Moreover, the abundance of CD4 T cells strongly associated with better patient survival regardless of MYCN gene amplification, while those of CD8 T cells, NK or B cells do not.  Based on characteristic cytokine expression of CD4 subsets in tumors, the Th2 rather than Th1 levels were associated with better prognosis.  
Conclusion		We found that the in silico analysis of TARGET database reflected tumor immunity and was validated by the immuno-histochemical tumor data. Our results reveal the association of MYCN amplification with repressed cellular immunity and the potential prognostic value of infiltrating CD4 T cell transcripts in pediatric neuroblastoma. This analysis illustrates the potential role of MYCN in neuroblastoma as a regulator of immune privilege and characterizes the power of in silico analysis for delineating cancer immunology and risk stratification.