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

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.