Gene network reconstruction reveals cell cycle and antiviral genes as major drivers of cervical cancer

Abstract

Although human papillomavirus was identified as an aetiological factor in cervical cancer, the key human gene drivers of this disease remain unknown. Here we apply an unbiased approach integrating gene expression and chromosomal aberration data. In an independent group of patients, we reconstruct and validate a gene regulatory meta-network, and identify cell cycle and antiviral genes that constitute two major subnetworks upregulated in tumour samples. These genes are located within the same regions as chromosomal amplifications, most frequently on 3q. We propose a model in which selected chromosomal gains drive activation of antiviral genes contributing to episomal virus elimination, which synergizes with cell cycle dysregulation. These findings may help to explain the paradox of episomal human papillomavirus decline in women with invasive cancer who were previously unable to clear the virus.

Conflict of interest statement

COMPETING FINANCIAL INTERESTS

The authors declared no competing financial interests.

Figures

Figure 1. Chromosomal aberrations regulating expression of genes from frequent chromosomal gain or loss

(a) Heat map of the 1268 genes differentially expressed between cervical tumor and normal tissue samples in the five data sets used for the meta-analysis of gene expression microarray data. red-upregulated, green-downregulated, grey-missing value. (b) Frequency of gain (FqG, red) or loss (FqL, green) in the genome detected in the meta-analysis of comparative genomic hybridization studies using cervical cancer samples. (c) Distribution of the delta values (FqG − FqL) for the 1268 genes. Chromosomal regions with delta values > 0.32 or < −0.2 were considered to be regions of frequent gains or losses, respectively. Bar graph shows the number of up- (Up) or down-regulated (Dn) genes in each region. There is an association between gene expression and chromosomal aberrations for the genes in the regions of frequent gains and losses (p < 0.0001; Fisher exact test).

Figure 2. Gene regulatory network reconstructed using the differentially expressed genes in cervical cancer

Dots are genes (red, up-regulated; green, down-regulated); lines indicate presence of correlation between genes. The three identified sub-networks indicated by circles were named after Gene Ontology terms they represent as Cell Cycle, Antiviral (equivalent to GO term “response to virus”), and Epithelial differentiation.

Figure 3. Hierarchy in the cell cycle and antiviral sub-networks

(a) Sub-network 1- Cell Cycle. (b) Sub-network 2- Antiviral. The sub-networks 1 and 2 have genes located in the regions of frequent DNA gain and were organized hierarchically with the regulator genes on the top and the target genes below them. (c) Testing the hierarchy of the sub-networks by perturbagens analysis using the Connectivity Map (http://www.broadinstitute.org/cmap). Twenty acting and 20 non-acting perturbagens were tested in each group of genes (regulators, targets and other sub-network), in the sub-network 1 and sub-network 2. Enrichment score (or connectivity score) is a measure of how perturbagens influence a gene expression signature where high positive score means significant induction (designated by **p < 0.0001 and *p < 0.001; Mann-Whitney Test).

Figure 4. Reproducibility of the meta-analysis in a new patient dataset

(a) Correlation between frequency of gain in the meta-analysis and in validation dataset for the 36 regulator genes from the cell cycle and antiviral sub-networks (r = 0.8; p < 0.0001; spearman rank correlation). (b) Gene expression data of 82 patients were used to build a network from the genes that comprised the meta-network. Red nodes are up-regulated genes, blue nodes are down-regulated genes, white and black edges represent positive and negative correlations, respectively. Three sub-networks are indicated. (c) Chromosomal gains increase expression of key driver genes. Expression level of each of the six genes in patients with gains, losses or no change in the corresponding chromosomal region. Each symbol represents an individual tumor. NAT13, LAMP3, p<0.01; others, p<0.001 for comparison of ‘gain’ vs. ‘none’. (d) Chromosomal gains in the key driver genes regions regulate expression of their respective target genes. Driver genes are indicated on x axis. Each dot represents ratio for individual target genes that are calculated by dividing average expression of a target gene in tumors with gains by its expression in tumors with no gains.

Figure 5. Drivers of cell cycle and antiviral sub-networks are located in the same regions of frequent gains

(a) Frequency of patients with chromosomal gains containing the driver genes from the Cell cycle and Antiviral sub-networks together and separately in the patients from meta-analysis and from validation dataset (p<0.0001, p<0.002, Chi-squared test respectively). (b) An integrative network reconstructed with data on chromosomal aberrations and gene expression correlation using the driver genes of cell cycle and antiviral sub-networks. All correlations in this network were positive. (c) Distribution of number of frequent chromosomal aberrations (gains) present in the same tumor. The regions used for this analysis were those containing regulator genes (1q, 1p, 3q, 5p, 8q, 17q, 19q, 20q). For b and c, n=97 patients from the validation dataset.

Figure 6. Antiviral sub-network genes are regulated by LAMP3

(a) Expression of genes from the antiviral sub-network in an in vitro culture W12 before and during elimination of episomal HPV in the presence of integrated HPV in the study of Pett et al. (data retrieved from GSE4289). (b) Knock down of LAMP3 by siRNA leads to down-regulation of many antiviral IFN-dependent genes. HeLa cells were pre-treated with control or LAMP3 siRNA overnight, then 1 ng/ml IFN-alpha was added for 3 or 4 days and gene expression was assessed. Log intensity values are represented by colors: orange - high expression, blue – low expression.

Figure 7. A revised model of cervical carcinogenesis

Persistent high risk HPV infection may result in the integration of virus into host genome leading to the increased genomic instability and aberrations, however, the expression of E6/E7 oncogenes is still under control of E2 if the episomal virus is around. If the chromosomal aberrations (gains) occur in the regions containing antiviral genes, they will induce the elimination of inhibitory episomal E2 , release of E6/E7 that will block suppressors of cell cycle (p53, retinoblastoma). The same chromosomal gains contain drivers of cell cycle that directly induce cell proliferation. The two processes act synergistically allowing the dysplastic cell to become a malignant tumor.