High-throughput 3-dimensional Culture of Epithelial Ovarian Cancer Cells as Preclinical Model of Disease
Open accessAbstract
// Victoria Heredia-Soto 1, 2 , Andrés Redondo 3, 4, 5 , Alberto Berjón 1, 6 , María Miguel-Martín 1 , Esther Díaz 4 , Roberto Crespo 4 , Alicia Hernández 7 , Laura Yébenes 1, 6 , Alejandro Gallego 3 , Jaime Feliu 2, 3, 4, 5, 8 , David Hardisson 1, 5, 6, 9 and Marta Mendiola 1, 2, 9 1 Molecular Pathology and Therapeutic Targets Research Lab, Instituto de Investigación del Hospital Universitario La Paz, IdiPAZ, Hospital Universitario La Paz, HULP, Madrid 28046, Spain 2 Centro de Investigación Biomédica en Red de Cáncer, CIBERONC. Instituto de Salud Carlos III, Madrid 28029, Spain 3 Department of Medical Oncology, Hospital Universitario La Paz, HULP, Madrid 28046, Spain 4 Translational Oncology Research Lab, IdiPAZ, Hospital Universitario La Paz, HULP, Madrid 28046, Spain 5 School of Medicine, Universidad Autónoma de Madrid, UAM, Madrid 28029, Spain 6 Department of Pathology, Hospital Universitario La Paz, HULP, Madrid 28046, Spain 7 Department of Gynecology and Obstetrics, Hospital Universitario La Paz, HULP, Madrid 28046, Spain 8 Cátedra UAM-AMGEN, Universidad Autónoma de Madrid, Campus de Cantoblanco, Madrid 28049, Spain 9 Molecular Pathology Section, Instituto de Genética Molecular y Médica, INGEMM, Hospital Universitario La Paz, HULP, Madrid 28046, Spain Correspondence to: Marta Mendiola, email: marta.mendiola@idipaz.es David Hardisson, email: david.hardisson@salud.madrid.org Keywords: ovarian cancer; epithelial mesenchymal transition; 3D cell culture model Received: August 18, 2017 Accepted: March 19, 2018 Published: April 24, 2018 ABSTRACT Background: Recent reports have identified distinct genomic patterns in ovarian carcinoma, including proliferative and mesenchymal-like groups, with worse outcome. The exact mechanisms driving the onset and progression of these tumors are still poorly understood. Additionally, researchers are concerned about the correct subtype stratification of the available cell line models, and the exploration of alternatives to monolayer culture. Identification of biomarkers to stratify cell lines, characterization of important processes as epithelial-mesenchymal transition (EMT), and the use of three-dimensional (3D) cultures as alternative models could be useful for cell line classification. Methods and Results: In this work, we present a descriptive analysis of 16 commonly used ovarian cancer cell lines. We have studied their morphology in 2- and 3D culture, and their response to cisplatin, observing in the majority of them an increased resistance in 3D. We have also performed an immunohistochemical analysis for proliferation marker Ki-67, and EMT related markers to establish phenotypes. Epithelial cells tend to show higher proliferative rates, and mesenchymal cells show an increase in EMT related markers, especially when cultured in 3D conditions. Conclusions: We have stated the complex heterogeneity of ovarian cancer models, resembling primary tumors, agreeing with the argument that the cell line model for in vitro experiments must be carefully chosen. Our results also support that tridimensional culture could be a very helpful alternative in ovarian cancer research. Regarding EMT, a very important process for the development of this disease, some related biomarkers might be further characterized for their role in this disease development.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Formation of single large spheroids (>500 μm diameter) enables the formation of a hypoxic core, and drug, oxygen and metabolite gradients that mimic solid tumor physiology.
“Formation of single large spheroids (>500 μm diameter) enables the formation of a hypoxic core, and drug, oxygen and metabolite gradients that mimic solid tumor physiology (Vinci et al., 2012; Heredia-Soto et al., 2018).”
From Three-dimensional modelling of ovarian cancer: from cell lines to organoids for discovery and personalized medicine (2022) · cites this paper as Heredia-Soto et al., 2018
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
The basics of epithelial-mesenchymal transition
Kalluri, R., & Weinberg, R. A. (2009) · Journal of Clinical Investigation · doi:10.1172/jci39104 · Cited by 10,196 · see citing works
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., et al. (2012) · Nature · doi:10.1038/nature11003 · Cited by 7,950 · see citing works
Integrated genomic analyses of ovarian carcinoma
Perou, C. M. (2019) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · doi:10.17615/hvp3-wg08 · Cited by 7,927 · see citing works
Novel Molecular Subtypes of Serous and Endometrioid Ovarian Cancer Linked to Clinical Outcome
Tothill, R. W., Tinker, A. V., George, J., Brown, R. E., Fox, S. B., Lade, S., Johnson, D., Trivett, M. K., Etemadmoghadam, D., Locandro, B., et al. (2008) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-08-0196 · Cited by 1,472 · see citing works
Rethinking ovarian cancer: recommendations for improving outcomes
Vaughan, S., Coward, J. I. G., Bast, R. C., Berchuck, A., Berek, J. S., Brenton, J. D., Coukos, G., Crum, C. P., Drapkin, R., Etemadmoghadam, D., et al. (2011) · Nature reviews. Cancer · doi:10.1038/nrc3144 · Cited by 1,470 · see citing works
Evaluating cell lines as tumour models by comparison of genomic profiles
Domcke, S., Sinha, R., Levine, D. A., Sander, C., & Schultz, N. D. (2013) · Nature Communications · doi:10.1038/ncomms3126 · Cited by 1,426 · see citing works
Vinci, M., Gowan, S., Boxall, F., Patterson, L., Zimmermann, M., Court, W., Lomas, C., Mendiola, M., Hardisson, D., & Eccles, S. A. (2012) · BMC Biology · doi:10.1186/1741-7007-10-29 · Cited by 1,024 · see citing works
The Dualistic Model of Ovarian Carcinogenesis
Kurman, R. J., & Shih, I. (2016) · American Journal Of Pathology · doi:10.1016/j.ajpath.2015.11.011 · Cited by 933 · see citing works
Tan, T. Z., Miow, Q. H., Miki, Y., Noda, T., Mori, S., Huang, R. Y., & Thiery, J. P. (2014) · EMBO Molecular Medicine · doi:10.15252/emmm.201404208 · Cited by 792 · see citing works
Loessner, D., Stok, K. S., Lutolf, M. P., Hutmacher, D. W., Clements, J. A., & Rizzi, S. C. (2010) · Biomaterials · doi:10.1016/j.biomaterials.2010.07.064 · Cited by 602 · see citing works
Ovarian Cancer Metastasis: Integrating insights from disparate model organisms
Naora, H., & Montell, D. J. (2005) · Nature reviews. Cancer · doi:10.1038/nrc1611 · Cited by 538 · see citing works
Yemelyanova, A. V., VANG, R. S., Kshirsagar, M. P., Lü, D., Marks, M. A., Shih, I., & Kurman, R. J. (2011) · Modern Pathology · doi:10.1038/modpathol.2011.85 · Cited by 515 · see citing works
Pathogenesis of Ovarian Cancer
Kurman, R. J., & Shih, I. (2008) · International Journal of Gynecological Pathology · doi:10.1097/pgp.0b013e318161e4f5 · Cited by 460 · see citing works
The genesis and evolution of high-grade serous ovarian cancer
Bowtell, D. D. L. (2010) · Nature reviews. Cancer · doi:10.1038/nrc2946 · Cited by 441 · see citing works
Ovarian Cancer Cell Line Panel (OCCP): Clinical Importance of In Vitro Morphological Subtypes
Beaufort, C. M., Helmijr, J. C. A., Piskorz, A. M., Hoogstraat, M., Ruigrok-Ritstier, K., Besselink, N., Murtaza, M., van IJcken, W. F. J., Heine, A. A. J., Smid, M., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0103988 · Cited by 403 · see citing works
Haslehurst, A., Koti, M., Dharsee, M., Nuin, P. A. S., Evans, K., Geraci, J., Childs, T. J., Chen, J., Li, J., Weberpals, J. I., et al. (2012) · BMC Cancer · doi:10.1186/1471-2407-12-91 · Cited by 402 · see citing works
Prognostic and Therapeutic Relevance of Molecular Subtypes in High-Grade Serous Ovarian Cancer
Konecny, G. E., Wang, C., Hamidi, H., Winterhoff, B. J. N., Kalli, K. R., Dering, J., Ginther, C., Chen, H., Dowdy, S. C., Cliby, W. A., et al. (2014) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/dju249 · Cited by 399 · see citing works
Optimized p53 immunohistochemistry is an accurate predictor of TP53 mutation in ovarian carcinoma
Köbel, M., Piskorz, A., Lee, S., Lui, S., Page, C. L., Marass, F., Rosenfeld, N., Mes‐Masson, A., & Brenton, J. D. (2016) · The Journal of Pathology Clinical Research · doi:10.1002/cjp2.53 · Cited by 389 · see citing works
Lee, J. M., Mhawech-Fauceglia, P. Y., Lee, N., Parsanian, L. C., Lin, Y. G., Gayther, S. A., & Lawrenson, K. (2013) · Laboratory Investigation · doi:10.1038/labinvest.2013.41 · Cited by 302 · see citing works
Characterization and properties of nine human ovarian adenocarcinoma cell lines.
Langdon, S. P., Lawrie, S. S., Hay, F. G., Hawkes, M. M., McDonald, A. W., Hayward, I. P., Schol, D. J., Hilgers, J., Leonard, R. C., & Smyth, J. F. (1988) · PubMed · Cited by 269 · see citing works
Curcio, E., Salerno, S., Barbieri, G., Bartolo, L. D., Drioli, E., & Bader, A. (2007) · Biomaterials · doi:10.1016/j.biomaterials.2007.08.033 · Cited by 262 · see citing works
Type-Specific Cell Line Models for Type-Specific Ovarian Cancer Research
Anglesio, M. S., Wiegand, K. C., Melnyk, N., Chow, C., Salamanca, C. M., Prentice, L., Senz, J., Yang, W., Spillman, M. A., Cochrane, D. R., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0072162 · Cited by 248 · see citing works
Sodek, K. L., Ringuette, M. J., & Brown, T. J. (2009) · International Journal of Cancer · doi:10.1002/ijc.24188 · Cited by 248 · see citing works
Köbel, M., Kalloger, S. E., Carrick, J., Huntsman, D. D., Haider, A. A., Oliva, E., Ewanowich, C. A., Soslow, R. A., & Gilks, C. B. (2008) · The American Journal of Surgical Pathology · doi:10.1097/pas.0b013e3181788546 · Cited by 230 · see citing works
An Immunohistochemical Algorithm for Ovarian Carcinoma Typing
Köbel, M., Rahimi, K., Rambau, P., Naugler, C. T., Page, C. L., Meunier, L., de Ladurantaye, M., Lee, S., Leung, S. C. Y., Goode, E. L., et al. (2016) · International Journal of Gynecological Pathology · doi:10.1097/pgp.0000000000000274 · Cited by 221 · see citing works
Cole, A. J., Dwight, T., Gill, A. J., Dickson, K.-A., Zhu, Y., Clarkson, A., Gard, G. B., Maidens, J., Valmadre, S., Clifton-Bligh, R. J., et al. (2016) · Scientific Reports · doi:10.1038/srep26191 · Cited by 208 · see citing works
Epithelial–Mesenchymal Transition in Ovarian Carcinoma
Davidson, B., Trope, C. G., & Reich, R. (2012) · Frontiers in Oncology · doi:10.3389/fonc.2012.00033 · Cited by 174 · see citing works
The Changing View of High-Grade Serous Ovarian Cancer
Berns, E. M. J. J., & Bowtell, D. D. L. (2012) · Cancer Research · doi:10.1158/0008-5472.can-11-3911 · Cited by 170 · see citing works
The multiple facets of drug resistance: one history, different approaches
Niero, E. L. D. O., Rocha-Sales, B., Lauand, C., Cortez, B. A., de Souza, M. M., Teixeira, P. R., Urabayashi, M. S., Martens, A. A., Neves, J. H., & Machado‐Santelli, G. M. (2014) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/1756-9966-33-37 · Cited by 135 · see citing works
Characterization of a functional C3A liver spheroid model
Gaskell, H., Sharma, P., Colley, H. E., Murdoch, C., Williams, D. P., & Webb, S. D. (2016) · Toxicology Research · doi:10.1039/c6tx00101g · Cited by 131 · see citing works
Integrated genomic analyses of ovarian carcinoma
The Cancer Genome Atlas Research Network (2011) · Nature · doi:10.1038/nature10166 · Cited by 129 · see citing works
Attenuating the p53 Pathway in Human Cancers: Many Means to the Same EndPreprint
Wasylishen, A. R., & Lozano, G. (2016) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a026211 · Cited by 128 · see citing works
Tumor Spheroid-Based Migration Assays for Evaluation of Therapeutic Agents
Vinci, M., Box, C., Zimmermann, M., & Eccles, S. A. (2013) · Methods in molecular biology · doi:10.1007/978-1-62703-311-4_16 · Cited by 108 · see citing works
Microtissue size and hypoxia in HTS with 3D cultures
Asthana, A., & Kisaalita, W. S. (2012) · Drug Discovery Today · doi:10.1016/j.drudis.2012.03.004 · Cited by 94 · see citing works
Wang, C., Armasu, S. M., Kalli, K. R., Maurer, M. J., Heinzen, E. P., Keeney, G. L., Cliby, W. A., Oberg, A. L., Kaufmann, S. H., & Goode, E. L. (2017) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-17-0246 · Cited by 91 · see citing works
Kessel, S. L., Cribbes, S., Déry, O., Kuksin, D., Sincoff, E., Qiu, J., & Chan, L. L. (2016) · SLAS TECHNOLOGY · doi:10.1177/2211068216652846 · Cited by 90 · see citing works
Alkema, N. G., Wisman, G. B. A., van der Zee, A. G. J., van Vugt, M. A. T. M., & de Jong, S. (2015) · Drug Resistance Updates · doi:10.1016/j.drup.2015.11.005 · Cited by 80 · see citing works
Measurement of oxygen diffusion distance in tumor cubes using a fluorescent hypoxia probe
Olive, P. L., Vikse, C. M., & Trotter, M. J. (1992) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/0360-3016(92)90840-e · Cited by 77 · see citing works
Létourneau, I. J., Quinn, M. C. J., Wang, L.-L., Portelance, L., Caceres, K., Cyr, L., Delvoye, N., Meunier, L., de Ladurantaye, M., Shen, Z. Z., et al. (2012) · BMC Cancer · doi:10.1186/1471-2407-12-379 · Cited by 72 · see citing works
Chen, J., Wang, J., Chen, D., Yang, J., Yang, C., Zhang, Y., Zhang, H., & Dou, J. (2013) · BMC Cell Biology · doi:10.1186/1471-2121-14-7 · Cited by 69 · see citing works
Allen, H. J., Porter, C. W., Gamarra, M., Piver, S. M., & Johnson, E. A. (2008) · Experimental Cell Biology · doi:10.1159/000163419 · Cited by 57 · see citing works
Dong, Y., Stephens, C. R., Walpole, C., Swedberg, J. E., Boyle, G. M., Parsons, P. G., McGuckin, M. A., Harris, J. M., & Clements, J. A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057056 · Cited by 54 · see citing works
In vitro three‐dimensional modelling of human ovarian surface epithelial cells
Lawrenson, K., Benjamin, E. O., Turmaine, M., Jacobs, I. J., Gayther, S. A., & Dafou, D. (2009) · Cell Proliferation · doi:10.1111/j.1365-2184.2009.00604.x · Cited by 48 · see citing works
Two-Dimensional vs. Three-Dimensional In Vitro Tumor Migration and Invasion Assays
Zimmermann, M., Box, C., & Eccles, S. A. (2013) · Methods in molecular biology · doi:10.1007/978-1-62703-311-4_15 · Cited by 46 · see citing works
Kessel, S. L., Cribbes, S., Bonasu, S., Rice, W., Qiu, J., & Chan, L. L. (2017) · Cytometry Part A · doi:10.1002/cyto.a.23143 · Cited by 30 · see citing works
Paullin, T., Powell, C. D., Menzie, C., Hill, R. G., Cheng, F., Martyniuk, C. J., & Westerheide, S. D. (2017) · PLoS ONE · doi:10.1371/journal.pone.0182930 · Cited by 30 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Surendran, V., Rutledge, D., Colmon, R., & Chandrasekaran, A. (2021) · Biofabrication · doi:10.1088/1758-5090/abe1cf · Cited by 99 · see citing works
Yee, C., Dickson, K.-A., Muntasir, M. N., Ma, Y., & Marsh, D. J. (2022) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2022.836984 · Cited by 66 · see citing works
Griseti, E., Merbahi, N., & Golzio, M. (2020) · Cancers · doi:10.3390/cancers12030721 · Cited by 63 · see citing works
Three-Dimensional 3D Culture Models in Gynecological and Breast Cancer Research
Salinas-Vera, Y. M., Valdés, J., Pérez‐Navarro, Y., Mandujano-Lázaro, G., Marchat, L. A., Ramos‐Payán, R., Núñez-Olvera, S. I., Pérez‐Plasencia, C., & López‐Camarillo, C. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.826113 · Cited by 64 · see citing works
Ciucci, A., Buttarelli, M., Fagotti, A., Scambia, G., & Gallo, D. (2022) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-022-04395-y · Cited by 43 · see citing works
Polymeric Hydrogels for In Vitro 3D Ovarian Cancer Modeling
Braccini, S., Tacchini, C., Chiellini, E., & Puppi, D. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23063265 · Cited by 42 · see citing works
Stojanovska, V., Arnold, S., Bauer, M., Voss, H., Fest, S., & Zenclussen, A. C. (2022) · Cells · doi:10.3390/cells11182884 · Cited by 32 · see citing works
Establishment and characterization of an in vitro 3D ovarian cancer model for drug screening assays
Tofani, L. B., Abriata, J. P., Luiz, M. T., Marchetti, J. M., & Swiech, K. (2020) · Biotechnology Progress · doi:10.1002/btpr.3034 · Cited by 33 · see citing works
ADAM17 Inhibition Increases the Impact of Cisplatin Treatment in Ovarian Cancer Spheroids
Hedemann, N., Herz, A., Schiepanski, J. H., Dittrich, J., Sebens, S., Dempfle, A., Feuerborn, J., Rogmans, C., Tribian, N., Flörkemeier, I., et al. (2021) · Cancers · doi:10.3390/cancers13092039 · Cited by 30 · see citing works
Matriptase drives dissemination of ovarian cancer spheroids by a PAR-2/PI3K/Akt/MMP9 signaling axis
Pawar, N. R., Buzza, M. S., Duru, N., Strong, A. A., & Antalis, T. (2023) · The Journal of Cell Biology · doi:10.1083/jcb.202209114 · Cited by 30 · see citing works
Giusti, I., Poppa, G., D’Ascenzo, S., Esposito, L., Vitale, A. R., Calvisi, G., & Dolo, V. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms231911782 · Cited by 27 · see citing works
Carboplatin sensitivity in epithelial ovarian cancer cell lines: The impact of model systems
Patra, B., Lateef, M. A., Brodeur, M. N., Fleury, H., Carmona, E., Péant, B., Provencher, D. M., Mes‐Masson, A., & Gervais, T. (2020) · PLoS ONE · doi:10.1371/journal.pone.0244549 · Cited by 26 · see citing works
Gao, J., Jung, M., Williams, R. T., Hui, D., Russell, A. J., Naim, A. J., Kamili, A., Clifton, M., Bongers, A., Mayoh, C., et al. (2022) · Cancers · doi:10.3390/cancers14081878 · Cited by 20 · see citing works
Heredia-Soto, V., López‐Guerrero, J. A., Redondo, A., & Mendiola, M. (2020) · European Journal of Cancer Supplements · doi:10.1016/j.ejcsup.2019.11.003 · Cited by 18 · see citing works
Target cell adhesion limits macrophage phagocytosis and promotes trogocytosis
Rollins, K., Fiaz, S., Datta, I., & Morrissey, M. A. (2025) · The Journal of Cell Biology · doi:10.1083/jcb.202502034 · Cited by 16 · see citing works
Gupta, P., Miller, A. F., Olayanju, A., Madhuri, T. K., & Velliou, E. G. (2022) · Cancers · doi:10.3390/cancers14051274 · Cited by 17 · see citing works
Świerczewska, M., Nowacka, M., Stasiak, P., Iżycki, D., Sterzyńska, K., Płóciennik, A., Nowicki, M. O., & Januchowski, R. (2025) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2024.117804 · Cited by 14 · see citing works
de Souza-Araújo, C. N., Tonetti, C. R., Cardoso, M. R., Andrade, L. A. L. D. A., da Silva, R. F., Fernandes, L. G. R., & Guimarães, F. (2020) · Cells · doi:10.3390/cells9030635 · Cited by 12 · see citing works
Mendoza, M. F. M., Mendoza, E. N., Padilla, A. L., Choquenaira-Quispe, C., Guimarães, C. D. J., Pereira, J. V. D. M., Nepomuceno, F. W. A. B., dos Santos, I. L., Pessoa, C., de Moraes, M. O., et al. (2024) · Journal of Toxicology and Environmental Health Part B · doi:10.1080/10937404.2024.2407452 · Cited by 11 · see citing works
Three Dimensional Models of Endocrine Organs and Target Tissues Regulated by the Endocrine System
Luca, E., Zitzmann, K., Bornstein, S. R., Kugelmeier, P., Beuschlein, F., Nölting, S., & Hantel, C. (2023) · Cancers · doi:10.3390/cancers15184601 · Cited by 10 · see citing works
Cortesi, M., Warton, K., & Ford, C. E. (2024) · PeerJ · doi:10.7717/peerj.17603 · Cited by 8 · see citing works
Mokbel, N. E., Goyeneche, A. A., Prakash, R., Forgie, B. N., Abdalbari, F. H., Zeng, X. Z., Tessier‐Cloutier, B., Leung, S. O. A., & Telleria, C. M. (2024) · Biochemistry and Biophysics Reports · doi:10.1016/j.bbrep.2024.101838 · Cited by 4 · see citing works
Antitumoral Effect of Plocabulin in High Grade Serous Ovarian Carcinoma Cell Line Models
Heredia-Soto, V., Escudero, J., Miguel, M. P. D., Ruiz, P., Gallego, A., Berjón, A., Hernández, A., Martínez, M., Zheng, S., Tang, J. P., et al. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.862321 · Cited by 3 · see citing works
Mendiola, M., Saarela, J., Escudero, J., Heredia-Soto, V., Potdar, S., Rodriguez-Marrero, S., Miguel, M. P. D., Pozo‐Kreilinger, J. J., Berjón, A., Ortiz-Cruz, E. J., et al. (2024) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2024.116397 · Cited by 3 · see citing works
Sevinyan, L., Gupta, P., Velliou, E. G., & Madhuri, T. K. (2022) · Cancers · doi:10.3390/cancers14225628 · Cited by 2 · see citing works
Models of ovarian cancer to test new agents
Sodi, V. L., Craig, A. D., Peri, S., & Connolly, D. C. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-819840-7.00012-1
Ovarian cancer: Current status of preclinical research
Kharbithai, R., Prasad, S., Pathak, H. K., & Sharma, H. K. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-31656-2.00014-1
Scrocciolani, C., Caserio, L., Grillo, S., Ottavi, F., Masi, I., Jacchetti, E., Vangosa, F. B., Raimondi, M. T., Colosimo, B. M., Rosanò, L., et al. (2026) · ACS Applied Bio Materials · doi:10.1021/acsabm.6c00299 · Cited by 1 · see citing works
Ahmad, S., Nagar, G., Yadav, N., Singh, S., Shrivastava, A., & Singh, R. K. (2026) · Cells · doi:10.3390/cells15191826
Engineering a Functional Angiogenesis-Enabled and Ovarian Cell-Specific Tumor Microenvironment Chip
Oktem, E., Ma, S.-Y., Chang, A. K.-W., Hsu, C.-H., & Jain, A. (2026) · Cellular and Molecular Bioengineering · doi:10.1007/s12195-026-00951-9
- Authors
- Heredia-Soto, V., Redondo, A., Berjón, A., Miguel-Martín, M., Díaz, E., Crespo, R., Hernández, A., Yébenes, L., Gallego, A., Feliu, J., Hardisson, D., & Mendiola, M.
- Affiliations
- Hospital Universitario La Paz (ES)
- Centro de Investigación Biomédica en Red de Cáncer, CIBERONC. Instituto de Salud Carlos III, Madrid 28029, Spain
- ORCID
- Venue
- Oncotarget
- Publisher
- Impact Journals, LLC
- Published
- 2018-04-24
- Volume
- 9
- Issue
- 31
- Pages
- 21893-21903
- ISSN
- 1949-2553 (ISSN-L)
- PMC
- PMC5955171
- OpenAlex
- W2801664145
- Cited by
- 33
- References
- 45
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 4 · 2023: 2 · 2022: 10 · 2021: 2 · 2020: 9
- FWCI
- 2.95
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Oncotarget (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, other-oa)
- Hispana (submittedVersion)
- Biblos-e Archivo (Universidad Autónoma de Madrid) (submittedVersion, public-domain)
- Funders
- Fundación Mutua Madrileña
- Centro de Investigación Biomédica en Red de Cáncer
- Instituto de Salud Carlos III (PNI-D+i 2008–2011, 2008-2011)
- European Regional Development Fund
- Topics
- Health Sciences › Medicine › Reproductive Medicine › Ovarian cancer diagnosis and treatment
- Physical Sciences › Engineering › Biomedical Engineering › 3D Printing in Biomedical Research
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Keywords
- epithelial ovarian cancer, 3D cell culture, preclinical models, epithelial-mesenchymal transition, tumor microenvironment, cancer stem cells, tumor spheroids, drug screening, drug resistance, chemoresistance, drug repurposing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
