Genomic structures and regulation patterns at HPV integration sites in cervical cancer.

Human papillomavirus (HPV) integration has been implicated in transforming HPV infection into cancer, but its genomic consequences have been difficult to study using short-read technologies. To resolve the dysregulation associated with HPV integration, we performed long-read sequencing on 63 cervical cancer genomes. We identified six categories of integration events based on HPV-human genomic structures. Of all HPV integrants, defined as two HPV-human breakpoints bridged by an HPV sequence, 24% contained variable copies of HPV between the breakpoints, a phenomenon we termed heterologous integration. Analysis of DNA methylation within and in proximity to the HPV genome at individual integration events revealed relationships between methylation status of the integrant and its orientation and structure. Dysregulation of the human epigenome and neighboring gene expression in cis with the HPV-integrated allele was observed over megabase-ranges of the genome. By elucidating the structural, epigenetic, and allele-specific impacts of HPV integration, we provide insight into the role of integrated HPV in cervical cancer.

Multi-omics mapping of human papillomavirus integration sites illuminates novel cervical cancer target genes.

BACKGROUND: Integration of human papillomavirus (HPV) into the host genome is a dominant feature of invasive cervical cancer (ICC), yet the tumorigenicity of cis genomic changes at integration sites remains largely understudied. METHODS: Combining multi-omics data from The Cancer Genome Atlas with patient-matched long-read sequencing of HPV integration sites, we developed a strategy for using HPV integration events to identify and prioritise novel candidate ICC target genes (integration-detected genes (IDGs)). Four IDGs were then chosen for in vitro functional studies employing small interfering RNA-mediated knockdown in cell migration, proliferation and colony formation assays. RESULTS: PacBio data revealed 267 unique human-HPV breakpoints comprising 87 total integration events in eight tumours. Candidate IDGs were filtered based on the following criteria: (1) proximity to integration site, (2) clonal representation of integration event, (3) tumour-specific expression (Z-score) and (4) association with ICC survival. Four candidates prioritised based on their unknown function in ICC (BNC1, RSBN1, USP36 and TAOK3) exhibited oncogenic properties in cervical cancer cell lines. Further, annotation of integration events provided clues regarding potential mechanisms underlying altered IDG expression in both integrated and non-integrated ICC tumours. CONCLUSIONS: HPV integration events can guide the identification of novel IDGs for further study in cervical carcinogenesis and as putative therapeutic targets.

Identification and validation of a prognostic proteomic signature for cervical cancer.

OBJECTIVE: To date, The Cancer Genome Atlas (TCGA) has provided the most extensive molecular characterization of invasive cervical cancer (ICC). Analysis of reverse phase protein array (RPPA) data from TCGA samples showed that cervical cancers could be stratified into 3 clusters exhibiting significant differences in survival outcome: hormone, EMT, and PI3K/AKT. The goals of the current study were to: 1) validate the TCGA RPPA results in an independent cohort of ICC patients and 2) to develop and validate an algorithm encompassing a small antibody set for clinical utility. METHODS: Subjects consisted of 2 ICC patient cohorts with accompanying RPPA and clinical-pathologic data: 155 samples from TCGA (TCGA-155) and 61 additional, unique samples (MCW-61). Using data from 173 common RPPA antibodies, we replicated Silhouette clustering analysis in both ICC cohorts. Further, an index score for each patient was calculated from the survival-associated antibodies (SAAs) identified using Random survival forests (RSF) and the Cox proportional hazard regression model. Kaplan-Meier survival analysis and the log-rank test were performed to assess and compare cluster or risk group survival outcome. RESULTS: In addition to validating the prognostic ability of the proteomic clusters reported by TCGA, we developed an algorithm based on 22 unique antibodies (SAAs) that stratified women with ICC into low-, medium-, or high-risk survival groups. CONCLUSIONS: We provide a signature of 22 antibodies which accurately predicted survival outcome in 2 separate groups of ICC patients. Future studies examining these candidate biomarkers in additional ICC cohorts is warranted to fully determine their clinical potential.

Genetic variations in human papillomavirus and cervical cancer outcomes.

Cervical cancer is driven by persistent infection of human papillomavirus (HPV), which is influenced by HPV type and intratypic variants, yet the impact of HPV type and intratypic variants on patient outcomes is far less understood. Here, we examined the association of cervical cancer stage and survival with HPV type, clade, lineage, and intratypic variants within the HPV E6 locus. Of 1,028 HPV-positive cases recruited through the CerGE study, 301 were in-situ and 727 were invasive cervical cancer (ICC), with an average post-diagnosis follow-up of 4.8 years. HPV sequencing was performed using tumor-isolated DNA to assign HPV type, HPV 16 lineage, clade, and intratypic variants within the HPV 16 E6 locus, of which nonsynonomous variants were functionally annotated by molecular modeling. HPV 18-related types were more prevalent in ICC compared to in-situ disease and associated with significantly worse recurrence-free survival (RFS) compared to HPV 16-related types. The HPV 16 Asian American lineage D3 and Asian lineage A4 associated more frequently with ICC than with in situ disease and women with an intratypic HPV 16 lineage B exhibited a trend toward worse RFS than those with A, C, or D lineages. Participants with intratypic E6 variants predicted to stabilize the E6-E6AP-p53 complex had worse RFS. Variants within the highly immunogenic HPV 16 E6 region (E14-I34) were enriched in ICC compared to in-situ lesions but were not associated with survival. Collectively, our results suggest that cervical cancer outcome is associated with HPV variants that affect virus-host interactions.

Correction: Identification of a serum-induced transcriptional signature associated with metastatic cervical cancer.

[This corrects the article DOI: 10.1371/journal.pone.0181242.].

Identification of a serum-induced transcriptional signature associated with metastatic cervical cancer.

OBJECTIVE: Tumor cells that escape local tissue control can convert inflammatory cells from tumor suppressors to tumor promoters. Moreover, soluble immune-modulating factors secreted from the tumor environment can be difficult to identify in patient serum due to their low abundance. We used an alternative strategy to infer a metastatic signature induced by sera of cervical cancer patients. METHODS: Sera from patients with local and metastatic cervical cancer were used to induce a disease-specific transcriptional signature in cultured, healthy peripheral blood mononuclear cells (PBMCs). An empirical Bayesian method, EBarrays, was used to identify differentially expressed (DE) genes with a target false discovery rate of <5%. Ingenuity Pathway Analysis (IPA) software was used to detect the top molecular and cellular functions associated with the DE genes. IPA and in silco analysis was used to pinpoint candidate upstream regulators, including cancer-related microRNAs (miRNAs). RESULTS: We identified enriched pathways in the metastatic cervical group related to immune surveillance functions, such as downregulation of engulfment, accumulation, and phagocytosis of hematopoietic cells. The predicted top upstream genes were IL-10 and immunoglobulins. In silco analysis identified miRNAs predicted to drive the transcriptional signature. Two of the 4 miRNAs (miR-23a-3p and miR-944) were validated in a cohort of women with local and metastatic cervical cancer. CONCLUSIONS: This study supports the use of a cell-based assay that uses PBMC "reporters" to predict biologically relevant factors in patient serum. Further, disease-specific transcriptional signatures induced by patient sera have the potential to differentiate patients with local versus metastatic disease.

Targeted, Deep Sequencing Reveals Full Methylation Profiles of Multiple HPV Types and Potential Biomarkers for Cervical Cancer Progression.

Background: Invasive cervical cancer (ICC) and its premalignant phase (cervical intraepithelial neoplasia; CIN1-3) are distinguished by gynecologic and pathologic examination, yet no current methodologies can predict precancerous lesions that are destined to progress to ICC. Thus, development of reliable assays to assess patient prognosis is much needed.Methods: Human papillomavirus (HPV) DNA methylation is significantly altered in cervical disease. Using an HPV enrichment approach and next-generation DNA sequencing, methylation status was characterized in a case-case comparison of CIN (n = 2 CIN1; n = 2 CIN2; n = 20 CIN3) and ICC (n = 37) samples. Pyrosequencing validated methylation changes at CpGs of interest in a larger sample cohort (n = 61 CIN3; 50 ICC).Results: Global viral methylation, across HPV types, was significantly higher in ICC than CIN3. Average L1 gene methylation in 13 different HPV types best distinguished CIN3 from ICC. Methylation levels at individual CpG sites as a quantitative classifier achieved a sensitivity and specificity of >95% for detecting ICC in HPV 16 samples. Pyrosequencing confirmed significantly higher methylation of these CpGs in E1 of HPV 16 in ICC compared with CIN3.Conclusions: Global HPV methylation is significantly higher in ICC than CIN3, with L1 gene methylation levels performing best for distinguishing CIN3 from ICC. Methylation levels at CpGs in the E1 gene of HPV 16 (972, 978, 1870, and 1958) can distinguish between CIN3 and ICC.Impact: Higher methylation at specific E1 CpGs may associate with increased likelihood of progression to ICC in HPV 16-positive CIN3 lesions. Cancer Epidemiol Biomarkers Prev; 26(4); 642-50. ©2017 AACR.

The lncRNA PVT1 Contributes to the Cervical Cancer Phenotype and Associates with Poor Patient Prognosis.

The plasmacytoma variant translocation 1 gene (PVT1) is an lncRNA that has been designated as an oncogene due to its contribution to the phenotype of multiple cancers. Although the mechanism by which PVT1 influences disease processes has been studied in multiple cancer types, its role in cervical tumorigenesis remains unknown. Thus, the present study was designed to investigate the role of PVT1 in cervical cancer in vitro and in vivo. PVT1 expression was measured by quantitative PCR (qPCR) in 121 invasive cervical carcinoma (ICC) samples, 30 normal cervix samples, and cervical cell lines. Functional assays were carried out using both siRNA and LNA-mediated knockdown to examine PVT1's effects on cervical cancer cell proliferation, migration and invasion, apoptosis, and cisplatin resistance. Our results demonstrate that PVT1 expression is significantly increased in ICC tissue versus normal cervix and that higher expression of PVT1 correlates with poorer overall survival. In cervical cancer cell lines, PVT1 knockdown resulted in significantly decreased cell proliferation, migration and invasion, while apoptosis and cisplatin cytotoxicity were significantly increased in these cells. Finally, we show that PVT1 expression is augmented in response to hypoxia and immune response stimulation and that this lncRNA associates with the multifunctional and stress-responsive protein, Nucleolin. Collectively, our results provide strong evidence for an oncogenic role of PVT1 in cervical cancer and lend insight into potential mechanisms by which PVT1 overexpression helps drive cervical carcinogenesis.