Expression pattern of genes associated with tumor microenvironment in prostate cancer
G V Gerashchenko1, O V Grygoruk2, O A Kononenko3
1Institute of Molecular Biology and Genetics, NAS of Ukraine, Kyiv 03680, Ukraine.
Aim:
To assess relative expression (RE) levels of CAF-, TAM-specific, immune defense-associated genes in prostate tumors and to show correlation of RE with clinical, pathological and molecular characteristics, with the aim to define clinically significant specific alterations in a gene expression pattern.
Methods:
RE of 23 genes was analyzed by a quantitative polymerase chain reaction in 37 freshly frozen samples of prostate cancer tissues of a different Gleason score (GS) and at various tumor stages, compared with RE in 37 paired conventionally normal prostate tissue (CNT) samples and 20 samples of prostate adenomas.
Results:
Differences in RE were shown for 11 genes out of 23 studied, when tumor samples were compared with corresponding CNTs. 7 genes, namely ACTA2, CXCL14, CTGF, THY1, FAP, CD163, CCL17 were upregulated in tumors. 4 genes, namely CCR4, NOS2A, MSMB, IL1R1 were downregulated in tumors. 14 genes demonstrated different RE in TNA at different stages: CXCL12, CXCL14, CTGF, FAP, HIF1A, THY1, CCL17, CCL22, CCR4, CD68, CD163, NOS2A, CTLA4, IL1R1. RE changes of 9 genes - CXCL12, CXCL14, HIF1A, CCR4, CCL17, NOS2A, CTLA4, IL1R1, IL2RA - were found in tumors with different GS. Moreover, 9 genes showed differences in RE in TNA, dependently on the presence or absence of the TMPRSS2/ERG fusion and 7 genes showed differences in RE of groups with differential PTEN expression. Significant correlations were calculated between RE of 9 genes in adenocarcinomas and the stage, and GS; also, between RE of 2 genes and the fusion presence; and between RE of 4 genes and PTEN expression.
Conclusions:
Several gene expression patterns were identified that correlated with the GS, stage and molecular characteristics of tumors, i.e. presence of the TMPRSS2/ERG fusion and alterations in PTEN expression. These expression patterns can be used for molecular profiling of prostate tumors, with the aim to develop personalized medicine approaches. However, the proposed profiling requires a more detailed analysis and a larger cohort of patients with prostate tumor.
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