Ovarian tumor is a highly metastatic disease but no effective strategies

Ovarian tumor is a highly metastatic disease but no effective strategies to target this metastatic process currently are known. ZNF304 promotes multiple proto-oncogenic pathways important for cell survival migration and invasion. ZNF304 transcriptionally regulates β1 integrin which subsequently regulates Src/focal adhesion kinase and paxillin and prevents anoikis. In vivo delivery of ZNF304 siRNA by a novel dual assembly nanoparticle led to sustained gene silencing for 14 days increased anoikis and reduced tumor growth in orthotopic mouse models of ovarian cancer. Taken together ZNF304 is a novel transcriptional regulator of β1 integrin promotes cancer cell survival and protects against anoikis in ovarian cancer. Introduction Ovarian carcinoma (OC) has the highest mortality rate among gynecologic malignancies. In the United States in 2014 over 21 0 women will be diagnosed with OC and more than 14 0 women will die 1. The most common histological subtype is high-grade serous OC (HGSOC) and the poor survival rate associated with this subtype is due primarily to the advanced stage of disease and widespread metastases at the time of diagnosis. The rapid spread of HGSOC is based on its propensity to seed the peritoneal cavity leading to ascites formation and metastases 2 3 this highlights the need for a deeper understanding of the molecular mechanisms that regulate OC growth and progression. To identify new therapeutic targets and strategies we carried out an integrative analysis of The Cancer Genome Atlas (TCGA) HGSOC dataset and gene profiles of ovarian and breast tumors to identify genes that are important for cancer metastasis. Among the genes identified zinc finger protein 304 (ZNF304) was found to be the most highly associated with overall survival in HGSOC patients. ZNF304 is a transcription factor that belongs to the C2H2 zinc finger family. The member genes of this family represent the largest class of transcription factors in humans and indeed one of the largest gene families in mammals 4. ZNF304 can be upregulated by activated Kirsten rat sarcoma viral oncogene homolog (KRAS) in KRAS-positive colorectal cancer cells and binds at the promoters of INK4-ARF and other CpG island methylator phenotype genes in colorectal cancer cells and in human embryonic stem cells 5. However the role of ZNF304 in metastasis and its downstream effectors are not well understood. Here we aimed to unravel the mechanisms by which Regorafenib (BAY 73-4506) ZNF304 promotes cancer metastasis and Regorafenib (BAY 73-4506) to evaluate its Regorafenib (BAY 73-4506) role as a potential therapeutic target. Results ZNF304 in human HGSOC We first carried out an integrative computational analysis to identify genes that are important for cancer metastasis and that are upregulated in ovarian cancer (OC). Since N-cadherin has been reported to play a critical role in invasion and anoikis resistance of cancer cells 6 7 we first identified gene signatures in tumors with high N-cadherin expression in TCGA HGSOC dataset. Of 16 869 Rabbit polyclonal to DUSP26. genes that were upregulated in OC 493 genes had a positive correlation with tumoral N-cadherin expression (Figure 1A). Of these 493 genes ciliary neurotrophic factor receptor (were upregulated in invasive ovarian and breast Regorafenib (BAY 73-4506) tumor epithelium compared with normal ovarian 8and breast epithelium9 respectively. Figure 1 Significance of zinc finger protein 304 (ZNF304) expression in human ovarian carcinoma (OC). Abbreviations: N-cad N-cadherin; CNTFR Regorafenib (BAY 73-4506) ciliary neurotrophic factor receptor; MAGED1 melanoma antigen family D 1 NR2F2 nuclear receptor subfamily 2 group … We then assessed the effect of tumoral expression on patient survival for these 4 genes using TCGA HGSOC dataset (Supplementary Figure 1). For each gene we randomly split the entire OC patient population into training (2/3 of cases) and validation cohorts (1/3 of cases). In both cohorts Regorafenib (BAY 73-4506) patients were divided into sextiles according to mRNA expression and the first and last sextiles were contrasted. Importantly the relationships between overall survival and known prognostic factors such as age or residual disease were examined in both the training and the validation cohorts using a Cox proportional hazards model. Only was a significant factor in this analysis (Figure 1B and 1C). In contrast (Training and validation sets; Supplementary Figure 1A and 1B respectively) (Training and validation sets; Supplementary Figure 1C and 1D respectively) and (Training and validation sets; Supplementary Figure 1E and 1F respectively) expression levels were not correlated.