The majority of patients with epithelial ovarian cancer are diagnosed at a late stage when the peritoneal metastases exist; however, there is little knowledge of the metastatic process in this disease setting. In this study, we report the identification of the long noncoding RNA LINC00092 as a nodal driver of metastatic progression mediated by cancer-associated fibroblasts (CAF). Prometastatic properties of CAFs and were found to associate with elevated expression of the chemokine CXCL14. In clinical specimens, elevated levels of CXCL14 in CAFs also correlated with poor prognosis. Notably, CXCL14-high CAFs mediated upregulation of LINC00092 in ovarian cancer cells, the levels of which also correlated with poor prognosis in patients. Mechanistic studies showed that LINC00092 bound a glycolytic enzyme, the fructose-2,6-biphosphatase PFKFB2, thereby promoting metastasis by altering glycolysis and sustaining the local supportive function of CAFs. Overall, our study uncovered a positive feedback loop in the metabolism of CXCL14-positive CAFs and ovarian cancer cells that is critical for metastatic progression. .

BackgroundOvarian cancer constitutes one of the most lethal gynecologic malignancies for females. Currently, early detection strategies and therapeutic options for ovarian cancer are far from satisfactory, leading to high diagnosis rates at late stages and disease relapses. New avenues of therapy are needed that target key processes in ovarian cancer progression. While a variety of non-coding RNAs have been proven to regulate ovarian cancer metastatic progression, the functional roles of RNA-binding proteins (RBPs) in this process are less well defined.ResultsIn this study, we identify that the RBP sorbin and SH3 domain containing 2 (SORBS2) is a potent suppressor of ovarian cancer metastatic colonization. Mechanistic studies show that SORBS2 binds the 3′ untranslated regions (UTRs) of WFDC1 (WAP four-disulfide core domain 1) and IL-17D (Interleukin-17D), two secreted molecules that are shown to act as metastasis suppressors. Enhanced expression of either WFDC1 or IL-17D potently represses SORBS2 depletion-mediated cancer metastasis promotion. By enhancing the stability of these gene transcripts, SORBS2 suppresses ovarian cancer invasiveness and affects monocyte to myeloid-derived suppressor cell and M2-like macrophage polarization, eliciting a tumor-suppressive immune microenvironment.ConclusionsOur data illustrate a novel post-transcriptional network that links cancer progression and immunomodulation within the tumor microenvironment through SORBS2-mediated transcript stabilization.Electronic supplementary materialThe online version of this article (10.1186/s13059-018-1412-6) contains supplementary material, which is available to authorized users.

Epithelial ovarian cancer (EOC) is one of the most common gynecological cancers, with diagnosis often at a late stage. Metastasis is a major cause of death in patients with EOC, but the underlying molecular mechanisms remain obscure. Here, we utilized an integrated approach to find potential key transcription factors involved in ovarian cancer metastasis and identified STAT4 as a critical player in ovarian cancer metastasis. We found that activated STAT4 was overexpressed in epithelial cells of ovarian cancer and STAT4 overexpression was associated with poor outcome of ovarian cancer patients, which promoted metastasis of ovarian cancer in both in vivo and in vitro. Although STAT4 mediated EOC metastasis via inducing epithelial-to-mesenchymal transition (EMT) of ovarian cancer cells in vivo, STAT4 failed to induce EMT directly in vitro, suggesting that STAT4 might mediate EMT process via cancer-stroma interactions. Further functional analysis revealed that STAT4 overexpression induced normal omental fibroblasts and adipose- and bone marrow-derived mesenchymal stem cells to obtain cancer-associated fibroblasts (CAF)-like features via induction of tumor-derived Wnt7a. Reciprocally, increased production of CAF-induced CXCL12, IL6 and VEGFA within tumor microenvironment could enable peritoneal metastasis of ovarian cancer via induction of EMT program. In summary, our study established a model that STAT4 promotes ovarian cancer metastasis via tumor-derived Wnt7a-induced activation of CAFs.

Metastases constitute the greatest causes of deaths from cancer. However, no effective therapeutic options currently exist for cancer patients with metastasis. Estrogen receptor β (ERβ), as a member of the nuclear receptor superfamily, shows potent tumor-suppressive activities in many cancers. To investigate whether modulation of ERβ could serve as a therapeutic strategy for cancer metastasis, we examined whether the selective ERβ agonist LY500307 could suppress lung metastasis of triple-negative breast cancer (TNBC) and melanoma. Mechanistically, while we observed that LY500307 potently induced cell death of cancer cells metastasized to lung in vivo, it does not mediate apoptosis of cancer cells in vitro, indicating that the cell death-inducing effects of LY500307 might be mediated by the tumor microenvironment. Pathological examination combined with flow cytometry assays indicated that LY500307 treatment induced significant infiltration of neutrophils in the metastatic niche. Functional experiments demonstrated that LY500307-treated cancer cells show chemotactic effects for neutrophils and that in vivo neutrophil depletion by Ly6G antibody administration could reverse the effects of LY500307-mediated metastasis suppression. RNA sequencing analysis showed that LY500307 could induce up-regulation of IL-1β in TNBC and melanoma cells, which further triggered antitumor neutrophil chemotaxis. However, the therapeutic effects of LY500307 treatment for suppression of lung metastasis was attenuated in murine models, due to failure to induce antitumor neutrophil infiltration in the metastatic niche. Collectively, our study demonstrated that pharmacological activation of ERβ could augment innate immunity to suppress cancer metastatic colonization to lung, thus providing alternative therapeutic options for cancer patients with metastasis.

BackgroundThe current TNM staging system plays a central role in lung adenocarcinoma (LUAD) prognosis. However, it may not adequately stratify the risk of tumor recurrence. With the aid of gene expression profiling, we identified 31 lncRNAs whose expressions in tumor tissues could be used as a risk indicator for the guidance of lung cancer therapy. This exploratory analysis may shed new light on identification of potential prognostic factors.Materials and methodsA survival prediction scoring model was developed from the data that are publicly available in The Cancer Genome Atlas (TCGA) LUAD RNA Sequencing dataset. Multivariate Cox regression analysis and Kaplan–Meier analysis were performed on a cohort of 254 stage I lung carcinoma patients with survival records.ResultsOur model indicates that the panels comprising 31 lncRNAs are highly associated with overall survival (OS): 18.9% (95% CI: 10.4%–34.5%) and 89.5% (95% CI: 80.7%–99.2%) for the high- and low-risk group, respectively. The specificity and sensitivity of the model are verified, which show that the area under receiver operating characteristic curve yields 0.881, meaning our model has good accuracy and it is feasible for further applications.ConclusionThe 31-lncRNA model might be able to predict OS in patients with LUAD with high accuracy. Its further applications in biomolecular experiments using clinical samples with independent cohorts of patients are needed to verify the results.