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.

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Formation of new synapses or maintenance of existing synapses requires the delivery of synaptic components from the soma to the nerve termini via axonal transport. One pathway that is important in synapse formation, maintenance and function of the Drosophila neuromuscular junction (NMJ) is the bone morphogenetic protein (BMP)-signaling pathway. Here we show that perturbations in axonal transport directly disrupt BMP signaling, as measured by its downstream signal, phospho Mad (p-Mad). We found that components of the BMP pathway genetically interact with both kinesin-1 and dynein motor proteins. Thick vein (TKV) vesicle motility was also perturbed by reductions in kinesin-1 or dynein motors. Interestingly, dynein mutations severely disrupted p-Mad signaling while kinesin-1 mutants showed a mild reduction in p-Mad signal intensity. Similar to mutants in components of the BMP pathway, both kinesin-1 and dynein motor protein mutants also showed synaptic morphological defects. Strikingly TKV motility and p-Mad signaling were disrupted in larvae expressing two human disease proteins; expansions of glutamine repeats (polyQ77) and human amyloid precursor protein (APP) with a familial Alzheimer's disease (AD) mutation (APPswe). Consistent with axonal transport defects, larvae expressing these disease proteins showed accumulations of synaptic proteins along axons and synaptic abnormalities. Taken together our results suggest that similar to the NGF-TrkA signaling endosome, a BMP signaling endosome that directly interacts with molecular motors likely exist. Thus problems in axonal transport occurs early, perturbs BMP signaling, and likely contributes to the synaptic abnormalities observed in these two diseases.

Objective The immune system is critical for controlling the progression of HPV cervical disease and the development of cancer. This study aimed to identify cervical cancer susceptibility alleles in candidate immune-modulating genes. Methods Our family-based study involved a cohort of 641 probands (women with ICC / CIN III) and their biologic parents or siblings (641 trios). In the discovery phase (stage 1), involving 288 of the trios, 81 tag single nucleotide polymorphisms (SNPs) in 11 immune-modulating genes (IFNG, IFNGR1, IFNGR2, JAK1, JAK2, STAT1, STAT6, IL12A, TNF, LTA and LTB) were evaluated on the GoldenGate platform. We used the combined dataset for a total of 641 trios (stage 2) and the Taqman platform to validate the SNPs that had proved significant in the discovery dataset. The transmission disequilibrium test was used to detect significant shifts in allelic transmissions in the datasets. Results Two SNPs in JAK2 and one SNP in STAT6 showed significant allelic association with cervical cancer in the stage 1 discovery dataset and were replicated in the larger joint analysis stage 2 dataset (JAK2 rs10815144, P = 0.0029 and rs12349785, P = 0.0058; and STAT6 rs3024971, P = 0.0127). An additional SNP in exon 19 of JAK2 (rs2230724) was also examined in the combined dataset due to its strong linkage disequilibrium (LD) with rs10815144. It was also significant (P=0.0335). Conclusions Our results suggest an association of SNPs in JAK2 and STAT6 with cervical cancer. This association should be investigated in additional cervical cancer populations.

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. 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 ( = 2 CIN1; = 2 CIN2; = 20 CIN3) and ICC ( = 37) samples. Pyrosequencing validated methylation changes at CpGs of interest in a larger sample cohort ( = 61 CIN3; 50 ICC). 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 of HPV 16 in ICC compared with CIN3. Global HPV methylation is significantly higher in ICC than CIN3, with gene methylation levels performing best for distinguishing CIN3 from ICC. Methylation levels at CpGs in the gene of HPV 16 (972, 978, 1870, and 1958) can distinguish between CIN3 and ICC. Higher methylation at specific CpGs may associate with increased likelihood of progression to ICC in HPV 16-positive CIN3 lesions..