Searching across hundreds of databases

Our searching services are busy right now. Your search will reload in five seconds.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.

Search

Type in a keyword to search

On page 1 showing 1 ~ 5 papers out of 5 papers

Sphingosine kinase 1 is required for TGF-β mediated fibroblastto- myofibroblast differentiation in ovarian cancer.

  • Jessica A Beach‎ et al.
  • Oncotarget‎
  • 2016‎

Sphingosine kinase 1 (SPHK1), the enzyme that produces sphingosine 1 phosphate (S1P), is known to be highly expressed in many cancers. However, the role of SPHK1 in cells of the tumor stroma remains unclear. Here, we show that SPHK1 is highly expressed in the tumor stroma of high-grade serous ovarian cancer (HGSC), and is required for the differentiation and tumor promoting function of cancer-associated fibroblasts (CAFs). Knockout or pharmacological inhibition of SPHK1 in ovarian fibroblasts attenuated TGF-β-induced expression of CAF markers, and reduced their ability to promote ovarian cancer cell migration and invasion in a coculture system. Mechanistically, we determined that SPHK1 mediates TGF-β signaling via the transactivation of S1P receptors (S1PR2 and S1PR3), leading to p38 MAPK phosphorylation. The importance of stromal SPHK1 in tumorigenesis was confirmed in vivo, by demonstrating a significant reduction of tumor growth and metastasis in SPHK1 knockout mice. Collectively, these findings demonstrate the potential of SPHK1 inhibition as a novel stroma-targeted therapy in HGSC.


Metformin induces distinct bioenergetic and metabolic profiles in sensitive versus resistant high grade serous ovarian cancer and normal fallopian tube secretory epithelial cells.

  • Melissa Hodeib‎ et al.
  • Oncotarget‎
  • 2018‎

Metformin is a widely used agent for the treatment of diabetes and infertility, however, it has been found to have anti-cancer effects in a variety of malignancies including high grade serous ovarian cancer (HGSC). Studies describing the mechanisms by which metformin affects HGSC are ongoing, but detailed analysis of its effect on the cellular metabolism of both HGSC cells and their precursor, normal fallopian tube secretory epithelial cells (FTSECs), is lacking. We addressed the effects of metformin and the more potent biguanide, phenformin, on HGSC cell lines and normal immortalized FTSECs. Cell proliferation assays identified that FTSECs and a subset of HGSC cell lines are relatively resistant to the anti-proliferative effects of metformin. Bioenergetic and metabolomic analyses were used to metabolically differentiate the metformin-sensitive and metformin-resistant cell lines. Bioenergetically, biguanides elicited a significant decrease in mitochondrial respiration in all HGSC cells and FTSECs. However, biguanides had a greater effect on mitochondrial respiration in metformin sensitive cells. Metabolomic analysis revealed that metformin and phenformin generally induce similar changes in metabolic profiles. Biguanide treatment led to a significant increase in NADH in FTSECs and HGSC cells. Interestingly, biguanide treatment induced changes in the levels of mitochondrial shuttle metabolites, glycerol-3-phopshate (G3P) and aspartate, specifically in HGSC cell lines and not in FTSECs. Greater alterations in G3P or aspartate levels were also found in metformin sensitive cells relative to metformin resistant cells. These data identify bioenergetic and HGSC-specific metabolic effects that correlate with metformin sensitivity and novel metabolic avenues for possible therapeutic intervention.


Glucose deprivation elicits phenotypic plasticity via ZEB1-mediated expression of NNMT.

  • Justyna Kanska‎ et al.
  • Oncotarget‎
  • 2017‎

Glucose is considered the primary energy source for all cells, and some cancers are addicted to glucose. Here, we investigated the functional consequences of chronic glucose deprivation in serous ovarian cancer cells. We found that cells resistant to glucose starvation (glucose-restricted cells) demonstrated increased metabolic plasticity that was dependent on NNMT (Nicotinamide N-methyltransferase) expression. We further show that ZEB1 induced NNMT, rendered cells resistant to glucose deprivation and recapitulated metabolic adaptations and mesenchymal gene expression observed in glucose-restricted cells. NNMT depletion reversed metabolic plasticity in glucose-restricted cells and prevented de novo formation of glucose-restricted colonies. In addition to its role in glucose independence, we found that NNMT was required for other ZEB1-induced phenotypes, such as increased migration. NNMT protein levels were also elevated in metastatic and recurrent tumors compared to matched primary carcinomas, while normal ovary and fallopian tube tissue had no detectable NNMT expression. Our studies define a novel ZEB1/NNMT signaling axis, which elicits mesenchymal gene expression, as well as phenotypic and metabolic plasticity in ovarian cancer cells upon chronic glucose starvation. Understanding the causes of cancer cell plasticity is crucial for the development of therapeutic strategies to counter intratumoral heterogeneity, acquired drug resistance and recurrence in high-grade serous ovarian cancer (HGSC).


Characterization of fusion genes in common and rare epithelial ovarian cancer histologic subtypes.

  • Madalene A Earp‎ et al.
  • Oncotarget‎
  • 2017‎

Gene fusions play a critical role in some cancers and can serve as important clinical targets. In epithelial ovarian cancer (EOC), the contribution of fusions, especially by histological type, is unclear. We therefore screened for recurrent fusions in a histologically diverse panel of 220 EOCs using RNA sequencing. The Pipeline for RNA-Sequencing Data Analysis (PRADA) was used to identify fusions and allow for comparison with The Cancer Genome Atlas (TCGA) tumors. Associations between fusions and clinical prognosis were evaluated using Cox proportional hazards regression models. Nine recurrent fusions, defined as occurring in two or more tumors, were observed. CRHR1-KANSL1 was the most frequently identified fusion, identified in 6 tumors (2.7% of all tumors). This fusion was not associated with survival; other recurrent fusions were too rare to warrant survival analyses. One recurrent in-frame fusion, UBAP1-TGM7, was unique to clear cell (CC) EOC tumors (in 10%, or 2 of 20 CC tumors). We found some evidence that CC tumors harbor more fusions on average than any other EOC histological type, including high-grade serous (HGS) tumors. CC tumors harbored a mean of 7.4 fusions (standard deviation [sd] = 7.4, N = 20), compared to HGS EOC tumors mean of 2.0 fusions (sd = 3.3, N = 141). Few fusion genes were detected in endometrioid tumors (mean = 0.24, sd = 0.74, N = 55) or mucinous tumors (mean = 0.25, sd = 0.5, N = 4) tumors. To conclude, we identify one fusion at 10% frequency in the CC EOC subtype, but find little evidence for common (> 5% frequency) recurrent fusion genes in EOC overall, or in HGS subtype-specific EOC tumors.


Investigation of factors affecting the efficacy of 3C23K, a human monoclonal antibody targeting MISIIR.

  • Sarah E Gill‎ et al.
  • Oncotarget‎
  • 2017‎

MISIIR is a potential target for ovarian cancer (OC) therapy due to its tissue-specific pattern of expression. 3C23K is a novel therapeutic monoclonal anti-MISIIR antibody designed to recruit effector cells and promote cell death through ADCC (antibody dependent cell-mediated cytotoxicity). Our objective was to determine the tolerability and efficacy of 3C23K in OC patient-derived xenografts (PDX) and to identify factors affecting efficacy. Quantitative RT-PCR, immunohistochemistry (IHC), and flow cytometry were used to categorize MISIIR expression in established PDX models derived from primary OC patients. We selected two high expressing models and two low expressing models for in vivo testing. One xenograft model using an MISIIR over-expressing SKOV3ip cell line (Z3) was a positive control. The primary endpoint was change in tumor size. The secondary endpoint was final tumor mass. We observed no statistically significant differences between control and treated animals. The lack of response could be secondary to a number of variables including the lack of known biomarkers of response, the low membrane expression of MISIIR, and a limited ability of 3C23K to induce ADCC in PDX models. Further study is needed to determine the magnitude of ovarian cancer response to 3C23K and also if there is a threshold surface expression to predict response.


  1. SciCrunch.org Resources

    Welcome to the FDI Lab - SciCrunch.org Resources search. From here you can search through a compilation of resources used by FDI Lab - SciCrunch.org and see how data is organized within our community.

  2. Navigation

    You are currently on the Community Resources tab looking through categories and sources that FDI Lab - SciCrunch.org has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.

  3. Logging in and Registering

    If you have an account on FDI Lab - SciCrunch.org then you can log in from here to get additional features in FDI Lab - SciCrunch.org such as Collections, Saved Searches, and managing Resources.

  4. Searching

    Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:

    1. Use quotes around phrases you want to match exactly
    2. You can manually AND and OR terms to change how we search between words
    3. You can add "-" to terms to make sure no results return with that term in them (ex. Cerebellum -CA1)
    4. You can add "+" to terms to require they be in the data
    5. Using autocomplete specifies which branch of our semantics you with to search and can help refine your search
  5. Save Your Search

    You can save any searches you perform for quick access to later from here.

  6. Query Expansion

    We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.

  7. Collections

    If you are logged into FDI Lab - SciCrunch.org you can add data records to your collections to create custom spreadsheets across multiple sources of data.

  8. Facets

    Here are the facets that you can filter your papers by.

  9. Options

    From here we'll present any options for the literature, such as exporting your current results.

  10. Further Questions

    If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.

Publications Per Year

X

Year:

Count: