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Background  The tumour microenvironment comprises a network of immune response and vascularization factors. From this network, we identified immunological and vascularization gene expression clusters and the correlations between the clusters. We subsequently determined which factors were correlated with patient survival in cervical carcinoma.    Methods  The expression of 42 genes was investigated in 52 fresh frozen squamous cervical cancer samples by qRT-PCR. Weighted gene co-expression network analysis and mixed-model analyses were performed to identify gene expression clusters. Correlations and survival analyses were further studied at expression cluster and single gene level.    Results  We identified four immune response clusters: ‘T cells’ ( CD3E / CD8A / TBX21 / IFNG / FOXP3 / IDO1 ), ‘Macrophages’ ( CD4 / CD14 / CD163 ), ‘Th2’ ( IL4 / IL5 / IL13 / IL12 ) and ‘Inflammation’ ( IL6 / IL1B / IL8 / IL23 / IL10 / ARG1 ) and two vascularization clusters: ‘Angiogenesis’ ( VEGFA / FLT1 / ANGPT2 /  PGF / ICAM1 ) and ‘Vessel maturation’ ( PECAM1 / VCAM1 / ANGPT1 / SELE / KDR / LGALS9 ). The ‘T cells’ module was correlated with all modules except for ‘Inflammation’, while ‘Inflammation’ was most significantly correlated with ‘Angiogenesis’ (p < 0.001). High expression of the ‘T cells’ cluster was correlated with earlier TNM stage (p = 0.007). High  CD3E  expression was correlated with improved disease-specific survival (p = 0.022), while high  VEGFA  expression was correlated with poor disease-specific survival (p = 0.032). Independent predictors of poor disease-specific survival were  IL6  (hazard ratio = 2.3, p = 0.011) and a high  IL6 / IL17  ratio combined with low  IL5  expression (hazard ratio = 4.2, p = 0.010).    Conclusions  ‘Inflammation’ marker  IL6 , especially in combination with low levels of  IL5  and  IL17 , was correlated with poor survival. This suggests that  IL6  promotes tumour growth, which may be suppressed by a Th17 and Th2 response. Measuring  IL6, IL5  and  IL17  expression may improve the accuracy of predicting prognosis in cervical cancer.

Correlations between immune response and vascularization qRT-PCR gene expression clusters in squamous cervical cancer