Title: Models for measuring metabolic chemical changes in the metastasis of high grade serous ovarian cancer: fallopian tube, ovary, and omentum
Ovarian cancer (OC) is the most lethal gynecologic malignancy and high grade serous ovarian cancer (HGSOC) is the most common and deadly subtype, accounting for 70–80% of OC deaths. HGSOC has a distinct pattern of metastasis as many believe it originates in the fallopian tube and then it metastasizes first to the ovary, and later to the adipose-rich omentum. Metabolomics has been heavily utilized to investigate metabolite changes in HGSOC tumors and metastasis. Generally, metabolomics studies have traditionally been applied to biospecimens from patients or animal models; a number of recent studies have combined metabolomics with innovative cell-culture techniques to model the HGSOC metastatic microenvironment for the investigation of cell-to-cell communication. The purpose of this review is to serve as a tool for researchers aiming to model the metastasis of HGSOC for metabolomics analyses. It will provide a comprehensive overview of current knowledge on the origin and pattern of metastasis of HGSOC and discuss the advantages and limitations of different model systems to help investigators choose the best model for their research goals, with a special emphasis on compatibility with different metabolomics modalities. It will also examine what is presently known about the role of small molecules in the origin and metastasis of HGSOC. more »« less
We investigated an in vitro model for mesothelial clearance, wherein ovarian cancer cells invade into a layer of mesothelial cells, resulting in mesothelial retraction combined with cancer cell disaggregation and spreading. Prior to the addition of tumor cells, the mesothelial cells had an elongated morphology, causing them to align with their neighbors into well-ordered domains. Flaws in this alignment, which occur at topological defects, have been associated with altered cell density, motion, and forces. Here we identified topological defects in the mesothelial layer, and showed how they affected local cell density by producing a net flow of cells inward or outward, depending on defect type. At locations of net inward flow, mesothelial clearance was impeded. Hence, the collective behavior of the mesothelial cells, as governed by the topological defects, affected tumor cell clearance and spreading. Importantly, our findings were consistent across multiple ovarian cancer cell types, suggesting a new physical mechanism that could impact ovarian cancer metastasis.
Jasuja, Haneesh; Solaymani Mohammadi, Farid; Kim, Jiha; Gaba, Anu; Katti, Dinesh R.; Katti, Kalpana S.
(, Journal of Tissue Engineering and Regenerative Medicine)
Stabler, Cherie L.
(Ed.)
The unavailability of reliable models for studying breast cancer bone metastasis is the major challenge associated with poor prognosis in advanced-stage breast cancer patients. Breast cancer cells tend to preferentially disseminate to bone and colonize within the remodeling bone to cause bone metastasis. To improve the outcome of patients with breast cancer bone metastasis, we have previously developed a 3D in vitro breast cancer bone metastasis model using human mesenchymal stem cells (hMSCs) and primary breast cancer cell lines (MCF-7 and MDAMB231), recapitulating late-stage of breast cancer metastasis to bone. In the present study, we have tested our model using hMSCs and patient-derived breast cancer cell lines (NT013 and NT023) exhibiting different characteristics. We investigated the effect of breast cancer metastasis on bone growth using this 3D in vitro model and compared our results with previous studies. The results showed that NT013 and NT023 cells exhibiting hormone-positive and triple-negative characteristics underwent mesenchymal to epithelial transition (MET) and formed tumors in the presence of bone microenvironment, in line with our previous results with MCF-7 and MDAMB231 cell lines. In addition, the results showed upregulation of Wnt-related genes in hMSCs, cultured in the presence of excessive ET-1 cytokine released by NT013 cells, while downregulation of Wnt-related genes in the presence of excessive DKK-1, released by NT023 cells, leading to stimulation and abrogation of the osteogenic pathway, respectively, ultimately mimicking different types of bone lesions in breast cancer patients.
Fleszar, Andrew J.; Walker, Alyssa; Kreeger, Pamela K.; Notbohm, Jacob
(, Integrative Biology)
Abstract Throughout the body, epithelial tissues contain curved features (e.g. cysts, ducts and crypts) that influence cell behaviors. These structures have varied curvature, with flat structures having zero curvature and structures such as crypts having large curvature. In the ovary, cortical inclusion cysts (CICs) of varying curvatures are found, and fallopian tube epithelial (FTE) cells have been found trapped within these cysts. FTE are the precursor for ovarian cancer, and the CIC niche has been proposed to play a role in ovarian cancer progression. We hypothesized that variations in ovarian CIC curvature that occur during cyst resolution impact the ability of trapped FTE cells to invade into the surrounding stroma. Using a lumen model in collagen gels, we determined that increased curvature resulted in more invasions of mouse FTE cells. To isolate curvature as a system parameter, we developed a novel technique to pattern concave curvatures into collagen gels. When FTE cells were seeded to confluency on curved substrates, increases in curvature increased the number of invading FTE cells and the invasion distance. FTE invasion into collagen substrates with higher curvature depended on matrix metalloproteinases (MMPs), but expression of collagen I degrading Mmps was not different on curved and flat regions. A finite-element model predicted that contractility and cell–cell connections were essential for increased invasion on substrates with higher curvature, while cell–substrate interactions had minimal effect. Experiments supported these predictions, with invasion decreased by blebbistatin, ethylene glycol-bis(β-aminoethyl ether)-N,N,N’,N’-tetraacetic acid (EGTA) or N-cadherin-blocking antibody, but with no effect from a focal adhesion kinase inhibitor. Finally, experimental evidence supports that cell invasion on curved substrates occurs in two phases—a cell–cell-dependent initiation phase where individual cells break away from the monolayer and an MMP-dependent phase as cells migrate further into the collagen matrix.
Das, Madhumita; Henry, Kymkecia; Armstrong, Djarie; Truman, Charle; Kendrick, Charlie; Saunders, Maya S; Anderson, Juan E; Lovett, Malcolm J; Stiffin, Rose; Huisso, Ayivi; et al
(, Cancer Research)
AACR
(Ed.)
Abstract Cancer is an intricate disease accountable for the deaths of over 10 million people per year in the United States of America. Several scientific studies showed that the cancer stem cell (CSC) markers have prognostic significance in various cancers and are crucial for designing anticancer drugs to lower cancer death. However, there was a lack of rapid, accurate identification, and analysis, of the prognostic cancer stem cell (CSC) biomarkers in numerous cancer patients. In our laboratory, we identified and analyzed prognostic lung cancer stem cell markers (LCSCs) by using the Immunofluorescence microtissue array (IMA) technique in different lung cancer patient’s tissue biopsy samples and observed that the increased expression of LCSCs principally, CD44 and CD80 in stage IIIA lung cancer tissues compared to normal lung biopsy tissues. We also investigated pancreatic cancer stem cell biomarkers (PAN CSCs) namely CD44 and CD80 with the IMA technique in pancreatic biopsy tissues. The CD44 fluorescence proved an increased expression in adenocarcinoma pancreatic cell tissues when compared to CD80. We also studied and analyzed the stage progression with ovarian cancer stem cell biomarkers (OCSCs) chiefly CD54 and CD44 using the IMA technique in ovarian cancer patients and normal biopsy tissues. The increased expression of CD44 and CD54 were observed in Stage III ovarian cancer tissues compared to normal ovarian tissue indicating the potential role of these OCSC’s biomarkers for the prognosis of ovarian cancer pathogenesis. Our results of prognostic cancer stem cell biomarkers of lung, pancreatic, and ovarian cancers have been analyzed by one-way ANOVA and bioinformatics software (Reactome, Cytoscape PSICQUIC services, STRING) to find underlying molecular mechanism of target gene regulation of increased expression of prognostic CSCs which may give a clue for the prevention and treatment of these cancers. Further research is warranted for these lung, pancreatic, and ovarian CSCs which could be valuable for clinical trials and drug discovery against these CSC biomarkers at early-stage development. Citation Format:Madhumita Das, Kymkecia Henry, Djarie Armstrong, Charle Truman, Charlie Kendrick, Maya S. Saunders, Juan E. Anderson, Malcolm J. Lovett, Rose Stiffin, Ayivi Huisso, Donrie Purcell, Marco Ruiz, Paulo Chaves, Jayanta Kumar Das. Immunofluorescence microtissue array (IMA) for detection of prognostic cancer stem cell biomarkers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7077.
Mukherjee, Apratim; Zhang, Haonan; Ladner, Katherine; Brown, Megan; Urbanski, Jacob; Grieco, Joseph P.; Kapania, Rakesh K.; Lou, Emil; Behkam, Bahareh; Schmelz, Eva M.; et al
(, Molecular Biology of the Cell)
Discher, Dennis
(Ed.)
Ovarian cancer is routinely diagnosed long after the disease has metastasized through the fibrous submesothelium. Despite extensive research in the field linking ovarian cancer progression to increasingly poor prognosis, there are currently no validated cellular markers or hallmarks of ovarian cancer that can predict metastatic potential. To discern disease progression across a syngeneic mouse ovarian cancer progression model, here we fabricated extracellular matrix mimicking suspended fiber networks: cross-hatches of mismatch diameters for studying protrusion dynamics, aligned same diameter networks of varying interfiber spacing for studying migration, and aligned nanonets for measuring cell forces. We found that migration correlated with disease while a force-disease biphasic relationship exhibited F-actin stress fiber network dependence. However, unique to suspended fibers, coiling occurring at the tips of protrusions and not the length or breadth of protrusions displayed the strongest correlation with metastatic potential. To confirm that our findings were more broadly applicable beyond the mouse model, we repeated our studies in human ovarian cancer cell lines and found that the biophysical trends were consistent with our mouse model results. Altogether, we report complementary high throughput and high content biophysical metrics capable of identifying ovarian cancer metastatic potential on a timescale of hours.
Lusk, Hannah, Burdette, Joanna E., and Sanchez, Laura M. Models for measuring metabolic chemical changes in the metastasis of high grade serous ovarian cancer: fallopian tube, ovary, and omentum. Retrieved from https://par.nsf.gov/biblio/10358702. Molecular Omics 17.6 Web. doi:10.1039/d1mo00074h.
Lusk, Hannah, Burdette, Joanna E., & Sanchez, Laura M. Models for measuring metabolic chemical changes in the metastasis of high grade serous ovarian cancer: fallopian tube, ovary, and omentum. Molecular Omics, 17 (6). Retrieved from https://par.nsf.gov/biblio/10358702. https://doi.org/10.1039/d1mo00074h
Lusk, Hannah, Burdette, Joanna E., and Sanchez, Laura M.
"Models for measuring metabolic chemical changes in the metastasis of high grade serous ovarian cancer: fallopian tube, ovary, and omentum". Molecular Omics 17 (6). Country unknown/Code not available. https://doi.org/10.1039/d1mo00074h.https://par.nsf.gov/biblio/10358702.
@article{osti_10358702,
place = {Country unknown/Code not available},
title = {Models for measuring metabolic chemical changes in the metastasis of high grade serous ovarian cancer: fallopian tube, ovary, and omentum},
url = {https://par.nsf.gov/biblio/10358702},
DOI = {10.1039/d1mo00074h},
abstractNote = {Ovarian cancer (OC) is the most lethal gynecologic malignancy and high grade serous ovarian cancer (HGSOC) is the most common and deadly subtype, accounting for 70–80% of OC deaths. HGSOC has a distinct pattern of metastasis as many believe it originates in the fallopian tube and then it metastasizes first to the ovary, and later to the adipose-rich omentum. Metabolomics has been heavily utilized to investigate metabolite changes in HGSOC tumors and metastasis. Generally, metabolomics studies have traditionally been applied to biospecimens from patients or animal models; a number of recent studies have combined metabolomics with innovative cell-culture techniques to model the HGSOC metastatic microenvironment for the investigation of cell-to-cell communication. The purpose of this review is to serve as a tool for researchers aiming to model the metastasis of HGSOC for metabolomics analyses. It will provide a comprehensive overview of current knowledge on the origin and pattern of metastasis of HGSOC and discuss the advantages and limitations of different model systems to help investigators choose the best model for their research goals, with a special emphasis on compatibility with different metabolomics modalities. It will also examine what is presently known about the role of small molecules in the origin and metastasis of HGSOC.},
journal = {Molecular Omics},
volume = {17},
number = {6},
author = {Lusk, Hannah and Burdette, Joanna E. and Sanchez, Laura M.},
}
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