The DOI matches its Crossref record; 82 of the 83 references it cites were found in a registry or an index.
Genetically Defined Syngeneic Mouse Models of Ovarian Cancer as Tools for the Discovery of Combination Immunotherapy
Open accessPublished version of a preprint
Abstract
Abstract Despite advances in immuno-oncology, the relationship between tumor genotypes and response to immunotherapy remains poorly understood, particularly in high-grade serous tubo-ovarian carcinomas (HGSC). We developed a series of mouse models that carry genotypes of human HGSCs and grow in syngeneic immunocompetent hosts to address this gap. We transformed murine-fallopian tube epithelial cells to phenocopy homologous recombination–deficient tumors through a combined loss of Trp53, Brca1, Pten, and Nf1 and overexpression of Myc and Trp53R172H, which was contrasted with an identical model carrying wild-type Brca1. For homologous recombination–proficient tumors, we constructed genotypes combining loss of Trp53 and overexpression of Ccne1, Akt2, and Trp53R172H, and driven by KRASG12V or Brd4 or Smarca4 overexpression. These lines form tumors recapitulating human disease, including genotype-driven responses to treatment, and enabled us to identify follistatin as a driver of resistance to checkpoint inhibitors. These data provide proof of concept that our models can identify new immunotherapy targets in HGSC. Significance: We engineered a panel of murine fallopian tube epithelial cells bearing mutations typical of HGSC and capable of forming tumors in syngeneic immunocompetent hosts. These models recapitulate tumor microenvironments and drug responses characteristic of human disease. In a Ccne1-overexpressing model, immune-checkpoint resistance was driven by follistatin. This article is highlighted in the In This Issue feature, p. 211
Overview
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
Verification
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?
In the citing paper
“Generation of multiple fallopian tube epithelial cell lines with combinations of common mutations in HGSOC (Tp53, Brca1, Brca2, Ccne1, Akt2, Brd4, Smarca4, Kras, Myc, Nf1, and Pten) using CRISPR/Cas9 recapitulated histopathological and clinical features observed in HGSOC patients, such as ascites and peritoneal metastases (Iyer et al., 2021).”
From Three-dimensional modelling of ovarian cancer: from cell lines to organoids for discovery and personalized medicine (2022) · cites this paper as Iyer et al., 2021
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
featureCounts: an efficient general purpose program for assigning sequence reads to genomic features
Liao, Y., Smyth, G. K., & Shi, W. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt656 · Cited by 27,219
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
Cancer immunotherapy using checkpoint blockade
Ribas, A., & Wolchok, J. D. (2018) · Science · doi:10.1126/science.aar4060 · Cited by 6,791
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., & Greenleaf, W. J. (2013) · Nature Methods · doi:10.1038/nmeth.2688 · Cited by 6,422
Molecular and cellular insights into T cell exhaustion
Wherry, E. J., & Kurachi, M. (2015) · Nature Reviews Immunology · doi:10.1038/nri3862 · Cited by 4,652
Wherry, E. J. (2011) · Nature Immunology · doi:10.1038/ni.2035 · Cited by 4,062 · cited 2×
“S3I), indicative once again of impaired effector T-cell functions (36, 37).”
BackgroundVignali, D. A. A., Collison, L. W., & Workman, C. J. (2008) · Nature Reviews Immunology · doi:10.1038/nri2343 · Cited by 3,463
Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells
Klein, A. M., Mazutis, L., Akartuna, I., Tallapragada, N., Veres, A., Li, V., Peshkin, L., Weitz, D. A., & Kirschner, M. W. (2015) · Cell · doi:10.1016/j.cell.2015.04.044 · Cited by 3,356
Maintenance Olaparib in Patients with Newly Diagnosed Advanced Ovarian Cancer
Moore, K., Colombo, N., Scambia, G., Kim, B.-G., Oaknin, A., Friedlander, M., Lisyanskaya, A., Floquet, A., Leary, A., Sonke, G. S., et al. (2018) · New England Journal of Medicine · doi:10.1056/nejmoa1810858 · Cited by 2,870
An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues
Corces, M. R., Trevino, A. E., Hamilton, E. G., Greenside, P. G., Sinnott-Armstrong, N. A., Vesuna, S., Satpathy, A. T., Rubin, A. J., Montine, K. S., Wu, B., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4396 · Cited by 2,496
Chemokines in the cancer microenvironment and their relevance in cancer immunotherapy
Nagarsheth, N., Wicha, M. S., & Zou, W. (2017) · Nature reviews. Immunology · doi:10.1038/nri.2017.49 · Cited by 2,251
The Nature of Myeloid-Derived Suppressor Cells in the Tumor Microenvironment
Kumar, V., Patel, S., Tcyganov, E., & Gabrilovich, D. I. (2016) · Trends in Immunology · doi:10.1016/j.it.2016.01.004 · Cited by 2,008
Ovarian Cancer Development and Metastasis
Lengyel, E. R. (2010) · American Journal Of Pathology · doi:10.2353/ajpath.2010.100105 · Cited by 1,702
KRAS Mutations and Primary Resistance of Lung Adenocarcinomas to Gefitinib or Erlotinib
Pao, W. J., Wang, T. Y., Riely, G. J., Miller, V. A., Pan, Q., Ladanyi, M., Zakowski, M. F., Heelan, R. T., Kris, M. G., & VARMUS, H. E. (2005) · PLoS Medicine · doi:10.1371/journal.pmed.0020017 · Cited by 1,517
Rethinking ovarian cancer II: reducing mortality from high-grade serous ovarian cancer
Bowtell, D. D. L., Böhm, S., Ahmed, A. A., Aspuria, P.-J. P., Bast, R. C., Beral, V., Berek, J. S., Birrer, M. J., Blagden, S. P., Bookman, M. A., et al. (2015) · Nature reviews. Cancer · doi:10.1038/nrc4019 · Cited by 1,395
TGF-β directly targets cytotoxic T cell functions during tumor evasion of immune surveillance
Thomas, D. A., & Massagué, J. (2005) · Cancer Cell · doi:10.1016/j.ccr.2005.10.012 · Cited by 1,355
Broz, M. L., Binnewies, M., Boldajipour, B., Nelson, A. E., Pollack, J. L., Erle, D. J., Barczak, A., Rosenblum, M. D., Daud, A., Barber, D. L., et al. (2014) · Cancer Cell · doi:10.1016/j.ccell.2014.09.007 · Cited by 1,207
T-cell exhaustion in the tumor microenvironment
Jiang, Y., Li, Y., & Zhu, B. (2015) · Cell Death and Disease · doi:10.1038/cddis.2015.162 · Cited by 1,197
TGF-β and immune cells: an important regulatory axis in the tumor microenvironment and progression
Yang, L., Pang, Y., & Moses, H. L. (2010) · Trends in Immunology · doi:10.1016/j.it.2010.04.002 · Cited by 1,023
Boeva, V., Popova, T. G., Kevin Bleakley, A., Chiche, P., Cappo, J., Schleiermacher, G., Janoueix‐Lerosey, I., Delattre, O., & Barillot, E. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr670 · Cited by 1,012
Essential role for nuclear PTEN in maintaining chromosomal integrity
Shen, W. H., Balajee, A. S., Wang, J., Wu, H., Eng, C., Pandolfi, P. P., & Yin, Y. (2007) · Cell · doi:10.1016/j.cell.2006.11.042 · Cited by 979
Homologous Recombination Deficiency: Exploiting the Fundamental Vulnerability of Ovarian Cancer
Konstantinopoulos, P. A., Ceccaldi, R., Shapiro, G. I., & D'Andrea, A. D. (2015) · Cancer Discovery · doi:10.1158/2159-8290.cd-15-0714 · Cited by 945
Sen, T., Rodriguez, B. L., Chen, L., Corte, C. M. D., Morikawa, N., Fujimoto, J., Cristea, S., Nguyen, T., Diao, L., Li, L., et al. (2019) · Cancer Discovery · doi:10.1158/2159-8290.cd-18-1020 · Cited by 902
Matulonis, U. A., Shapira‐Frommer, R., Santin, A. D., Lisyanskaya, A. S., Pignata, S., Vergote, I. B., Raspagliesi, F., Sonke, G. S., Birrer, M. J., Provencher, D. M., et al. (2019) · Annals of Oncology · doi:10.1093/annonc/mdz135 · Cited by 871
The Interplay of Immunotherapy and Chemotherapy: Harnessing Potential Synergies
Emens, L. A., & Middleton, G. (2015) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-15-0064 · Cited by 840
Abkevich, V., Timms, K. M., Hennessy, B. T., Potter, J., Carey, M. S., Meyer, L. A., Smith‐McCune, K., Broaddus, R. R., Lu, K. H., Chen, J., et al. (2012) · British Journal of Cancer · doi:10.1038/bjc.2012.451 · Cited by 817
Synthetic lethal targeting of PTEN mutant cells with PARP inhibitors
Mendes‐Pereira, A. M., Martin, S. A., Brough, R., McCarthy, A., Taylor, J. R., Kim, J., Waldman, T. A., Lord, C. J., & Ashworth, A. (2009) · EMBO Molecular Medicine · doi:10.1002/emmm.200900041 · Cited by 642
Strickland, K. C., Howitt, B. E., Shukla, S. A., Rodig, S. J., Ritterhouse, L. L., Liu, J. F., Garber, J. E., Chowdhury, D., Wu, C. J., D’Andrea, A. D., et al. (2016) · Oncotarget · doi:10.18632/oncotarget.7277 · Cited by 630
Perets, R., Wyant, G. A., Muto, K. W., Bijron, J. G., Poole, B. B., Chin, K. T., Chen, J. Y. H., Ohman, A. W., Stepule, C. D., Kwak, S., et al. (2013) · Cancer Cell · doi:10.1016/j.ccr.2013.10.013 · Cited by 596
Development of a Syngeneic Mouse Model for Events Related to Ovarian Cancer
Roby, K. F., Taylor, C. C., Sweetwood, J. P., Cheng, Y., Pace, J. L., Tawfik, O., Persons, D. L., Smith, P. G., & Terranova, P. F. (2000) · Carcinogenesis · doi:10.1093/carcin/21.4.585 · Cited by 593
Meeting the challenge of ascites in ovarian cancer: new avenues for therapy and research
Kipps, E., Tan, D. S. P., & Kaye, S. B. (2013) · Nature reviews. Cancer · doi:10.1038/nrc3432 · Cited by 575
PARP inhibition elicits STING-dependent antitumor immunity in brca1-deficient ovarian cancer
Ding, L., Kim, H.-J., Wang, Q., Kearns, M., Jiang, T., Ohlson, C. E., Li, B. B., Xie, S., Liu, J. F., Stover, E. H., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.11.054 · Cited by 572
SynergyFinder: a web application for analyzing drug combination dose–response matrix data
Ianevski, A., He, L., Aittokallio, T. A., & Tang, J. P. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx162 · Cited by 535
Characterization of the p53-Dependent Postmitotic Checkpoint following Spindle Disruption
Lanni, J. S., & Jacks, T. (1998) · Molecular and Cellular Biology · doi:10.1128/mcb.18.2.1055 · Cited by 493
Liu, X., Holstege, H. H., van der Gulden, H. M. L., Treur-Mulder, M., Zevenhoven, J., Velds, A., Kerkhoven, R. M., van Vliet, M. H., Wessels, L. F. A., Peterse, J. L., et al. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0702969104 · Cited by 476
Jiménez-Sánchez, A., Memon, D., Pourpe, S., Veeraraghavan, H., Li, Y., Vargas, H. A., Gill, M. B., Park, K. J., Zivanovic, O., Konner, J. A., et al. (2017) · Cell · doi:10.1016/j.cell.2017.07.025 · Cited by 456
Efficacy and Safety of Avelumab for Patients With Recurrent or Refractory Ovarian Cancer
Disis, M. L., Taylor, M. H., Kelly, K. L., Beck, J. T., Gordon, M. S., Moore, K. M., Patel, M. R., Chaves, J. M., Park, H., Mita, A. C., et al. (2019) · JAMA Oncology · doi:10.1001/jamaoncol.2018.6258 · Cited by 448
Genomic correlates of response to immune checkpoint blockade
Keenan, T. E., Burke, K. P., & Van Allen, E. M. (2019) · Nature Medicine · doi:10.1038/s41591-019-0382-x · Cited by 448
High-grade serous ovarian cancer arises from fallopian tube in a mouse model
Kim, J., Coffey, D. M., Creighton, C. J., Yu, Z., Hawkins, S. M., & Matzuk, M. M. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1117135109 · Cited by 400
PTEN: a new guardian of the genome
Yin, Y., & Shen, W. H. (2008) · Oncogene · doi:10.1038/onc.2008.241 · Cited by 395
ATR/CHK1 inhibitors and cancer therapy
Qiu, Z., Oleinick, N. L., & Zhang, J. (2017) · Radiotherapy and Oncology · doi:10.1016/j.radonc.2017.09.043 · Cited by 390
Wei, S. C., Anang, N.-A. A. S., Sharma, R., Andrews, M. C., Reuben, A., Levine, J. H., Cogdill, A. P., Mancuso, J. J., Wargo, J. A., Pe’er, D., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1821218116 · Cited by 359 · cited 1×
“We additionally investigated CTLA4 inhibition (51), which can inhibit Treg function (elevated in KPCA tumors) and can promote T-cell infiltration (low in KPCA tumors; Fig.”
BackgroundLessons from BRCA: the Tubal Fimbria Emerges as an Origin for Pelvic Serous Cancer
Crum, C. P., Drapkin, R., Kindelberger, D., Medeiros, F., Miron, A., & Lee, Y. (2007) · Clinical Medicine & Research · doi:10.3121/cmr.2007.702 · Cited by 342
Sztupinszki, Z. M., Dióssy, M., Krzystanek, M., Reiniger, L., Csabai, I., Favero, F., Birkbak, N. J., Eklund, A. C., Syed, A., & Szállási, Z. (2018) · npj Breast Cancer · doi:10.1038/s41523-018-0066-6 · Cited by 310
Immunogenomic profiling determines responses to combined PARP and PD-1 inhibition in ovarian cancer
Färkkilä, A., Gulhan, D., Casado, J., Jacobson, C. A., Nguyen, H. Q., Kochupurakkal, B. S., Maliga, Z., Yapp, C., Chen, Y., Schapiro, D., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15315-8 · Cited by 302
Mutation detection using Surveyor™ nuclease
Qiu, P., Shandilya, H., D'Alessio, J. M., O’Connor, K. C., Durocher, J. A., & Gerard, G. F. (2004) · BioTechniques · doi:10.2144/04364pf01 · Cited by 299
Modeling High-Grade Serous Ovarian Carcinogenesis from the Fallopian Tube
Karst, A. M., Levanon, K., & Drapkin, R. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1017300108 · Cited by 280
Jiménez-Sánchez, A., Cybulska, P., Mager, K. L., Koplev, S., Cast, O. M., Couturier, D., Memon, D., Selenica, P., Nikolovski, I., Mazaheri, Y., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0630-5 · Cited by 248
Zhang, S., Dolgalev, I., Zhang, T., Ran, H., Levine, D. A., & Neel, B. G. (2019) · Nature Communications · doi:10.1038/s41467-019-13116-2 · Cited by 245
Development of PARP and immune-checkpoint inhibitor combinations
Stewart, R. A., Pilié, P. G., & Yap, T. A. (2018) · Cancer Research · doi:10.1158/0008-5472.can-18-2652 · Cited by 239
Walton, J. B., Blagih, J., Ennis, D. P., Leung, E. Y. L., Dowson, S., Farquharson, M., Tookman, L. A., Orange, C., Athineos, D., Mason, S. M., et al. (2016) · Cancer Research · doi:10.1158/0008-5472.can-16-1272 · Cited by 236
Synthetic lethality between CCNE1 amplification and loss of BRCA1
Etemadmoghadam, D., Weir, B. A., Au‐Yeung, G., Alsop, K., Mitchell, G., George, J., Australian Ovarian Cancer Study Group, Davis, S. J., D’Andrea, A. D., Simpson, K. J., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1314302110 · Cited by 225
Lee, J., Nair, J. R., Zimmer, A. S., Lipkowitz, S., Annunziata, C. M., Merino, M. J., Swisher, E. M., Harrell, M. I., Trepel, J. B., Lee, M.-J., et al. (2018) · The Lancet Oncology · doi:10.1016/s1470-2045(18)30009-3 · Cited by 207
Giuntoli, R. L., Webb, T. J., Zoso, A., Rogers, O. C., Diaz-Montes, T. P., Bristow, R. E., & Oelke, M. (2009) · PubMed · Cited by 194
The Regulation and Functions of Activin and Follistatin in Inflammation and Immunity
Hedger, M. P., Winnall, W. R., Phillips, D. J., & de Kretser, D. M. (2011) · Vitamins and hormones · doi:10.1016/b978-0-12-385961-7.00013-5 · Cited by 182
Reinvigorating Exhausted T Cells by Blockade of the PD-1 Pathway
Lee, J., Ahn, E., Kissick, H. T., & Ahmed, R. (2015) · Forum on Immunopathological Diseases and Therapeutics · doi:10.1615/forumimmundisther.2015014188 · Cited by 172
The structure of myostatin:follistatin 288: insights into receptor utilization and heparin binding
Cash, J. N., Rejon, C. A., McPherron, A. C., Bernard, D. J., & Thompson, T. B. (2009) · The EMBO Journal · doi:10.1038/emboj.2009.205 · Cited by 166
Park, M.-J., Lee, S., Kim, E., Lee, E., Baek, J.-A., Park, S., Kwok, S., & Cho, M. (2018) · Scientific Reports · doi:10.1038/s41598-018-21856-2 · Cited by 165
Activin-A in the regulation of immunity in health and disease
Morianos, I., Papadopoulou, G., Semitekolou, M., & Xanthou, G. (2019) · Journal of Autoimmunity · doi:10.1016/j.jaut.2019.102314 · Cited by 153
Au‐Yeung, G., Lang, F., Azar, W. J., Mitchell, T. J., Jarman, K. E., Lackovic, K., Aziz, D., Cullinane, C. M., Pearson, R. B., Mileshkin, L., et al. (2016) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-16-0620 · Cited by 147
Integrated genomic analyses of ovarian carcinoma
The Cancer Genome Atlas Research Network (2011) · Nature · doi:10.1038/nature10166 · Cited by 129
The bright and the dark sides of activin in wound healing and cancer
Antsiferova, M. A., & Werner, S. (2012) · Journal of Cell Science · doi:10.1242/jcs.094789 · Cited by 113
Gu, L., Deng, Z. J., Roy, S., & Hammond, P. T. (2017) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-16-2186 · Cited by 99
High‐grade serous carcinomas arise in the mouse oviduct via defects linked to the human disease
Zhai, Y., WU, R. T., Kuick, R. D., Sessine, M. S., Schulman, S., Green, M., Fearon, E. R., & Cho, K. R. (2017) · The Journal of Pathology · doi:10.1002/path.4927 · Cited by 95
O’Connor, L. O., Rulten, S. L., Cranston, A. N., Odedra, R., Brown, H., Jaspers, J. E., Jones, L., Knights, C., Evers, B., Ting, A. K. T., et al. (2016) · Cancer Research · doi:10.1158/0008-5472.can-15-3240 · Cited by 93
Zhang, S., Iyer, S., Ran, H., Dolgalev, I., Gu, S. S., Wei, W., Foster, C., Loomis, C. A., Olvera, N., Dao, F., et al. (2020) · Cancer Discovery · doi:10.1158/2159-8290.cd-20-0455 · Cited by 89
Opportunities in immunotherapy of ovarian cancer
Coukos, G., Tanyi, J. L., & Kandalaft, L. E. (2016) · Annals of Oncology · doi:10.1093/annonc/mdw084 · Cited by 77
Kampan, N., Madondo, M., McNally, O., Stephens, A. N., Quinn, M., & Plebanski, M. (2017) · Frontiers in Immunology · doi:10.3389/fimmu.2017.01482 · Cited by 73
High Serum Levels of Follistatin in Patients with Ovarian Cancer
Ren, P., Chen, F.-F., Liu, H.-Y., Cui, X.-L., Sun, Y., Guan, J.-L., Liu, Z.-H., Liu, J.-G., & Wang, Y.-N. (2012) · Journal of International Medical Research · doi:10.1177/147323001204000306 · Cited by 57
Higher metastatic efficiency of KRas G12V than KRas G13D in a colorectal cancer model
Álamo, P., Gallardo, A., Nicolantonio, F. D., Pavón, M. Á., Casanova, I., Trías, M., Mangues, M. A., Pousa, A. L., Villaverde, A., Vázquez, E., et al. (2014) · The FASEB Journal · doi:10.1096/fj.14-262303 · Cited by 50
Clinical and therapeutic implications of follistatin in solid tumours
SHI, L., RESAUL, J., OWEN, S., YE, L., & JIANG, W. G. (2016) · Cancer Genomics & Proteomics · doi:10.21873/cgp.20005 · Cited by 47
Saatcioglu, H. D., Kano, M., Horn, H., Zhang, L., Samore, W. R., Nagykery, N. G., Meinsohn, M.-C., Hyun, M., Suliman, R., Poulo, J., et al. (2019) · eLife · doi:10.7554/elife.46349 · Cited by 46
Janat-Amsbury, M. M., Yockman, J. W., Anderson, M. L., Kieback, D., & Kim, S. W. (2006) · PubMed · Cited by 43
Precious GEMMs: emergence of faithful models for ovarian cancer research
Stückelberger, S., & Drapkin, R. (2018) · The Journal of Pathology · doi:10.1002/path.5065 · Cited by 28
Cárdenas, H., Jiang, G., Pepin, J. T., Parker, J. B., Condello, S., Nephew, K. P., Nakshatri, H., Chakravarti, D., Liu, Y., & Matei, D. E. (2019) · npj Precision Oncology · doi:10.1038/s41698-019-0103-4 · Cited by 27
Fazzini, M., Vallejo, G., Colman‐Lerner, A., Trigo, R., Campo, S., Barañao, J. L., & Saragüeta, P. (2005) · Journal of Cellular Physiology · doi:10.1002/jcp.20533 · Cited by 22
RNA‐Peptide nanoplexes drug DNA damage pathways in high‐grade serous ovarian tumors
Dreaden, E. C., Kong, Y. W., Quadir, M., Correa, S., Suárez-López, L., Barberio, A. E., Hwang, M. K., Shi, A. C., Oberlton, B., Gallagher, P. N., et al. (2018) · Bioengineering & Translational Medicine · doi:10.1002/btm2.10086 · Cited by 17
Current Preclinical Models of Ovarian Cancer
Tisato, E. K. V. (2015) · Journal of Carcinogenesis & Mutagenesis · doi:10.4172/2157-2518.1000220 · Cited by 13
Kaneko, H. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-801028-0.00189-6 · Cited by 2
Flagged first, then by citations
1 of the 83 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Targeting replication stress in cancer therapy
da Costa, A. A. B. A., Chowdhury, D., Shapiro, G. I., D’Andrea, A. D., & Konstantinopoulos, P. A. (2022) · Nature Reviews Drug Discovery · doi:10.1038/s41573-022-00558-5 · Cited by 380
Ovarian cancer mutational processes drive site-specific immune evasion
Vázquez-Garćıa, I., Uhlitz, F., Ceglia, N., Lim, J. L., Wu, M. K. Y., Mohibullah, N., Niyazov, J., Ruiz, A. E. B., Boehm, K. M., Bojilova, V., et al. (2022) · Nature · doi:10.1038/s41586-022-05496-1 · Cited by 329
Molecular mechanisms of platinum‑based chemotherapy resistance in ovarian cancer (Review)
Yang, L., Xie, H., Li, Y., Wang, X., Liu, X., & Mai, J. (2022) · Oncology Reports · doi:10.3892/or.2022.8293 · Cited by 327
Immunobiology of high-grade serous ovarian cancer: lessons for clinical translation
Kandalaft, L. E., Laniti, D. D., & Coukos, G. (2022) · Nature reviews. Cancer · doi:10.1038/s41568-022-00503-z · Cited by 190
Molecular, cellular and systemic aspects of epithelial ovarian cancer and its tumor microenvironment
Schoutrop, E., Moyano‐Galceran, L., Lheureux, S., Mattsson, J., Lehti, K., Dahlstrand, H. M., & Magalhaes, I. (2022) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2022.03.027 · Cited by 181
Metadata
- Authors
- Iyer, S., Zhang, S., Yucel, S., Horn, H., Smith, S. G., Reinhardt, F., Hoefsmit, E., Assatova, B., Casado, J., Meinsohn, M.-C., Barrasa, M. I., Bell, G. W., Pérez-Villatoro, F., Huhtinen, K., Hynninen, J., Oikkonen, J., Galhenage, P. M., Pathania, S., Hammond, P. T., Neel, B. G., Farkkila, A., Pépin, D., & Weinberg, R. A.
- Affiliations
- Whitehead Institute for Biomedical Research (US)
- NYU Langone Health (US)
- Broad Institute (US)
- Massachusetts Institute of Technology (US)
- 1Whitehead Institute for Biomedical Research, Cambridge, Massachusetts.
- University of Helsinki (FI)
- Harvard University (US)
- 6Research Program in Systems Oncology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- University of Turku (FI)
- University of Massachusetts Boston (US)
- Corresponding author
- Pépin, David
- Weinberg, Robert A.
- ORCID
- Iyer, Sonia
- Zhang, Shuang
- Horn, Heiko
- Smith, Sean G.
- Assatova, Bimarzhan
- Casado, Julia
- Meinsohn, Marie-Charlotte
- Barrasa, M. Inmaculada
- Bell, George W.
- Pérez-Villatoro, Fernando
- Huhtinen, Kaisa
- Hynninen, Johanna
- Oikkonen, Jaana
- Galhenage, Pamoda M.
- Pathania, Shailja
- Hammond, Paula T.
- Neel, Benjamin G.
- Farkkila, Anniina
- Pépin, David
- Weinberg, Robert A.
- Venue
- Cancer Discovery
- Published
- 2021-02-01
- Volume
- 11
- Issue
- 2
- Pages
- 384-407
- ISSN
- 2159-8274 (ISSN-L)
- 2159-8290
- PMC
- PMC8344888
- OpenAlex
- W3097756289
- Cited by
- 136
- References
- 83
- Citations by year
- 2026: 20 · 2025: 33 · 2024: 24 · 2023: 21 · 2022: 22 · 2021: 13
- FWCI
- 12.99
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cancer Discovery (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- UTUPub (University of Turku) (submittedVersion)
- Funders
- NIH (R01 CA0784561, P01 CA080111)
- Ovarian Cancer Research Program (W81XWH-17-1-0212)
- US Army Medical Research (21702-5014)
- Topics
- Health Sciences › Medicine › Oncology › Ovarian cancer diagnosis and treatment
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › BRCA gene mutations in cancer
- Keywords
- high-grade serous ovarian cancer, syngeneic mouse model, genetically engineered mouse models, combination immunotherapy, immunotherapy resistance, immune checkpoint inhibitors, follistatin, homologous recombination deficiency, BRCA1, PTEN, neurofibromatosis type 1, c-Myc, cyclin E1, KRAS G12V, BRD4, SMARCA4, tumor microenvironment, immunotherapy response prediction
- MeSH terms
- Immune Checkpoint Inhibitors, Animals, Disease Models, Animal, Drug Therapy, Combination, Fallopian Tube Neoplasms, Female, Mice, Transgenic, Ovarian Neoplasms, Cystadenocarcinoma, Serous
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