Sequential Molecular and Cellular Events during Neoplastic Progression: A Mouse Syngeneic Ovarian Cancer Model

Roberts, Paul C.; Mottillo, Emilio P.; Baxa, Andrea C.; Heng, Henry H.Q.; Doyon-Reale, Nicole; Grégoire, Lucie; Lancaster, Wayne D.; Rabah, Raja; Schmelz, Eva M.

doi:10.1593/neo.05358

Cited by 79 publications

(128 citation statements)

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“…Our results are in accordance with several reports suggesting that strong differences exist between early and advanced ovarian cancer in terms of overall survival, treatment response and tumour behaviour (25)(26)(27)(28)(29). In addition, we found a difference between A carrier frequencies in early and advanced stages of the disease (P=0.008), suggesting that stage I/II and III/IV ovarian tumours have distinct cell populations.…”

Section: Discussionsupporting

confidence: 92%

CXCL12 chemokine genotypes as predictive biomarkers of ovarian cancer outcome

Coelho

Pereira²,

Nogal³

et al. 2008

Mol Med Rep

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Abstract. Ovarian cancer is an aggressive disease with high mortality. The CXCL12 chemokine has been associated with the development of this neoplasia. The aim of this study was to evaluate the genetic influence of the CXCL12-3'A polymorphism as a prognostic/predictive factor in ovarian cancer patients treated with platinum/paclitaxel chemotherapy. The mean survival rates for early stages (I/II) of the disease were statistically different according to patient genotype (96 months for GG and 57 months for A carrier genotypes; p=0.017). The mean progression-free interval was statistically lower in patients with early stages (I/II) of the tumour carrying the A allele (55 months) than in those carrying the GG genotype (91 months; P=0.009). The CXCL12-3'A polymorphism leads to a poorer response to chemotherapy with cisplatin/paclitaxel, and diminishes the mean survival rate and the progression-free interval in patients with ovarian cancer. CXCL12-3'A may therefore serve as an important predictive biomarker for the determination of outcome in ovarian cancer. IntroductionOvarian cancer is the sixth most common type of cancer and ranks seventh as the most frequent cause of cancer-related death in women (4.0% of cases and 4.2% deaths) (1). At diagnosis, the majority of ovarian cancers have already progressed to stage III or IV, which results in poor long-term patient survival and quality of life (2). Standard treatment involves cytoreductive surgery followed by systemic platinumbased chemotherapy (3). Paclitaxel combinations with either cisplatin or carboplatin are first-line chemotherapy regimens, each combination producing similar responses (4). This therapy results in variable efficacy rates, with frequent recurrences at even early stages of the disease, and with most tumours eventually becoming resistant to chemotherapy (5).The biological mechanisms responsible for chemotherapy resistance remain unclear, but it is now widely accepted that the apoptotic capacity of cancer cells is pivotal in determining response to chemotherapeutic targets (6). Phosphatidylinositol 3-kinase (PI3K)/Akt (serine/threonine kinase subfamily) is a major cell survival pathway, and several targets of Akt, such as proapoptotic protein BAD and caspase-9, have roles in the regulation of apoptosis; phosphorylation by Akt inhibits their function (7).Akt overexpression or activation is correlated with poor prognosis in several tumour types, including gastric and hepatocellular carcinoma, breast and pancreatic cancer and melanoma (8). Previous studies have proposed that PI3K/Akt activation in ovarian cancer cells promotes resistance to cisplatin-induced apoptosis, serving as a mediator in chemoresistance (6,7). This activation may occur due to a variety of stimuli in different types of tumours. It has been suggested that one such stimulus is the chemokine CXCL12 (9-12).The chemokine receptor CXCR4 and its sole ligand, SDF-1/CXCL12 (stromal cell-derived factor-1), play important roles in inflammation and hematopoiesis by acting as chemoattractants for...

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Section: Discussionsupporting

confidence: 92%

CXCL12 chemokine genotypes as predictive biomarkers of ovarian cancer outcome

Coelho

Pereira²,

Nogal³

et al. 2008

Mol Med Rep

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“…42,43 The MOSE-L FFLv used in this study is a highly aggressive cell type generated by intraperitoneal injection of tumorigenic MOSE cells (MOSE-L) into syngeneic mice and recovery of cells in the ascites; injection of MOSE-L FFLv results in rapidly developing tumors, 44,45 therefore suggesting TIC character. 46 For the purpose of this study, cells were cultured in DMEM (Sigma Aldrich, St. Louis, MO) supplemented with 4% of FBS (Atlanta Biologicals, Flowery Branch, GA) and 100 lg/ml each of penicillin and streptomycin (Life Technologies, Carlsbad, CA) at 37 C in a humidified incubator with 5% CO 2 .…”

Section: Cell Preparationmentioning

confidence: 99%

Enhanced contactless dielectrophoresis enrichment and isolation platform via cell-scale microstructures

et al. 2016

Self Cite

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We designed a new microfluidic device that uses pillars on the same order as the diameter of a cell (20 lm) to isolate and enrich rare cell samples from background. These cell-scale microstructures improve viability, trapping efficiency, and throughput while reducing pearl chaining. The area where cells trap on each pillar is small, such that only one or two cells trap while fluid flow carries away excess cells. We employed contactless dielectrophoresis in which a thin PDMS membrane separates the cell suspension from the electrodes, improving cell viability for off-chip collection and analysis. We compared viability and trapping efficiency of a highly aggressive Mouse Ovarian Surface Epithelial (MOSE) cell line in this 20 lm pillar device to measurements in an earlier device with the same layout but pillars of 100 lm diameter. We found that MOSE cells in the new device with 20 lm pillars had higher viability at 350 V RMS , 30 kHz, and 1.2 ml/h (control 77%, untrapped 71%, trapped 81%) than in the previous generation device (untrapped 47%, trapped 42%). The new device can trap up to 6 times more cells under the same conditions. Our new device can sort cells with a high flow rate of 2.2 ml/h and throughput of a few million cells per hour while maintaining a viable population of cells for off-chip analysis. By using the device to separate subpopulations of tumor cells while maintaining their viability at large sample sizes, this technology can be used in developing personalized treatments that target the most aggressive cancerous cells. V C 2016 AIP Publishing LLC. [http://dx

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“…Here, we used fibronectin as the ECM component that allows the ovarian and mesothelial cells to adhere to the glass-bottom culture dishes, however, other ECM components can be used including collagen and laminin. Furthermore, other cell types that are found under the basement membrane, including fibroblasts, can be added to this experimental system, to assess the role of these cell types in mesothelial clearance 9,19,20 . Lastly, interactions of other types of tumor cells (e.g.…”

Section: Movie 3 Control Ovca433 Spheroids (Red) Invading Into a Mesmentioning

confidence: 99%

<em>In vitro</em> Mesothelial Clearance Assay that Models the Early Steps of Ovarian Cancer Metastasis

Davidowitz

Iwanicki

Brugge

2012

JoVE

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Ovarian cancer is the fifth leading cause of cancer related deaths in the United States 1 . Despite a positive initial response to therapies, 70 to 90 percent of women with ovarian cancer develop new metastases, and the recurrence is often fatal 2 . It is, therefore, necessary to understand how secondary metastases arise in order to develop better treatments for intermediate and late stage ovarian cancer. Ovarian cancer metastasis occurs when malignant cells detach from the primary tumor site and disseminate throughout the peritoneal cavity. The disseminated cells can form multicellular clusters, or spheroids, that will either remain unattached, or implant onto organs within the peritoneal cavity 3 (Figure 1, Movie 1).All of the organs within the peritoneal cavity are lined with a single, continuous, layer of mesothelial cells [4][5][6] (Figure 2). However, mesothelial cells are absent from underneath peritoneal tumor masses, as revealed by electron micrograph studies of excised human tumor tissue sections 3,5-7 (Figure 2). This suggests that mesothelial cells are excluded from underneath the tumor mass by an unknown process.Previous in vitro experiments demonstrated that primary ovarian cancer cells attach more efficiently to extracellular matrix than to mesothelial cells 8 , and more recent studies showed that primary peritoneal mesothelial cells actually provide a barrier to ovarian cancer cell adhesion and invasion (as compared to adhesion and invasion on substrates that were not covered with mesothelial cells) 9,10 . This would suggest that mesothelial cells act as a barrier against ovarian cancer metastasis. The cellular and molecular mechanisms by which ovarian cancer cells breach this barrier, and exclude the mesothelium have, until recently, remained unknown.Here we describe the methodology for an in vitro assay that models the interaction between ovarian cancer cell spheroids and mesothelial cells in vivo ( Figure 3, Movie 2). Our protocol was adapted from previously described methods for analyzing ovarian tumor cell interactions with mesothelial monolayers [8][9][10][11][12][13][14][15][16] , and was first described in a report showing that ovarian tumor cells utilize an integrin -dependent activation of myosin and traction force to promote the exclusion of the mesothelial cells from under a tumor spheroid 17 . This model takes advantage of time-lapse fluorescence microscopy to monitor the two cell populations in real time, providing spatial and temporal information on the interaction. The ovarian cancer cells express red fluorescent protein (RFP) while the mesothelial cells express green fluorescent protein (GFP). RFP-expressing ovarian cancer cell spheroids attach to the GFP-expressing mesothelial monolayer. The spheroids spread, invade, and force the mesothelial cells aside creating a hole in the monolayer. This hole is visualized as the negative space (black) in the GFP image. The area of the hole can then be measured to quantitatively analyze differences in clearance activity between cont...

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Sequential Molecular and Cellular Events during Neoplastic Progression: A Mouse Syngeneic Ovarian Cancer Model

Cited by 79 publications

References 46 publications

CXCL12 chemokine genotypes as predictive biomarkers of ovarian cancer outcome

CXCL12 chemokine genotypes as predictive biomarkers of ovarian cancer outcome

Enhanced contactless dielectrophoresis enrichment and isolation platform via cell-scale microstructures

<em>In vitro</em> Mesothelial Clearance Assay that Models the Early Steps of Ovarian Cancer Metastasis

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