Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Genetics and Genomics

Transcriptome analysis of newly established carboplatin-resistant ovarian cancer cell model reveals genes shared by drug resistance and drug-induced EMT

British Journal of Cancer volume 128, pages 1344–1359 (2023)Cite this article

Subjects

Abstract

Background

In ovarian cancer (OC) therapy, even initially responsive patients develop drug resistance.

Methods

Here, we present an OC cell model composed of variants with differing degrees of acquired resistance to carboplatin (CBP), cross-resistance to paclitaxel, and CBP-induced metastatic properties (migration and invasion). Transcriptome data were analysed by two approaches identifying differentially expressed genes and CBP sensitivity-correlating genes. The impact of selected genes and signalling pathways on drug resistance and metastatic potential, along with their clinical relevance, was examined by in vitro and in silico approaches.

Results

TMEM200A and PRKAR1B were recognised as potentially involved in both phenomena, also having high predictive and prognostic values for OC patients. CBP-resistant MES-OV CBP8 cells were more sensitive to PI3K/Akt/mTOR pathway inhibitors Rapamycin, Wortmannin, SB216763, and transcription inhibitor Triptolide compared with parental MES-OV cells. When combined with CBP, Rapamycin decreased the sensitivity of parental cells while Triptolide sensitised drug-resistant cells to CBP. Four PI3K/Akt/mTOR inhibitors reduced migration in both cell lines.

Conclusions

A newly established research model and two distinct transcriptome analysis approaches identified novel candidate genes enrolled in CBP resistance development and/or CBP-induced EMT and implied that one-gene targeting could be a better approach than signalling pathway inhibition for influencing both phenomena.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Characterisation of MES-OV and MES-OV CBP variants regarding their sensitivity to CBP and TAX, EMT phenotype, and metastatic potential.
Fig. 2: Functional analysis of MIR99AHG, DNER, TMEM200A, and SERPINE2 in CBP resistance, drug-induced metastatic potential, and their possible clinical application.
Fig. 3: Functional analyses of PRKAR1B, HES7, WDR46, and FBLN5 in CBP resistance and drug-induced metastatic potential.
Fig. 4: Functional analysis of inhibitors in CBP resistance and drug-induced metastatic potential.

Similar content being viewed by others

Data availability

All data supporting the findings of this study are included within the article and its Supplementary Information files (and Reporting summary). Also, the data will be shared upon reasonable request to the corresponding author from colleagues who want to analyse in deep our findings.

References

  1. Reid BM, Permuth JB, Sellers TA. Epidemiology of ovarian cancer: a review. Cancer Biol Med. 2017;14:9–32.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Desai A, Xu J, Aysola K, Qin Y, Okoli C, Hariprasad R, et al. Epithelial ovarian cancer: an overview. World J Transl Med. 2014;3:1–8.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Brozovic A, Ambriović-Ristov A, Osmak M. The relationship between cisplatin-induced reactive oxygen species, glutathione, and BCL-2 and resistance to cisplatin. Crit Rev Toxicol. 2010;40:347–59.

    Article  CAS  PubMed  Google Scholar 

  4. Tchounwou PB, Dasari S, Noubissi FK, Ray P, Kumar S. Advances in our understanding of the molecular mechanisms of action of cisplatin in cancer therapy. J Exp Pharmacol. 2021;13:303–28.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Mosca L, Ilari A, Fazi F, Assaraf YG, Colotti G. Taxanes in cancer treatment: activity, chemoresistance and its overcoming. Drug Resist Updat. 2021;54:100742.

    Article  CAS  PubMed  Google Scholar 

  6. Mellor HR, Snelling S, Hall MD, Modok S, Jaffar M, Hambley TW, et al. The influence of tumour microenvironmental factors on the efficacy of cisplatin and novel platinum(IV) complexes. Biochem Pharmacol. 2005;70:1137–46.

    Article  CAS  PubMed  Google Scholar 

  7. Fang F, Cardenas H, Huang H, Jiang G, Perkins SM, Zhang C, et al. Genomic and epigenomic signatures in ovarian cancer associated with resensitization to platinum drugs. Cancer Res. 2018;78:631–44.

    Article  CAS  PubMed  Google Scholar 

  8. Kamble PR, Breed AA, Pawar A, Kasle G, Pathak BR. Prognostic utility of the ovarian cancer secretome: a systematic investigation. Arch Gynecol Obstet. 2022;306:639–62.

    Article  CAS  PubMed  Google Scholar 

  9. Wu W, Wang Q, Yin F, Yang Z, Zhang W, Gabra H, et al. Identification of proteomic and metabolic signatures associated with chemoresistance of human epithelial ovarian cancer. Int J Oncol. 2016;49:1651–65.

    Article  CAS  PubMed  Google Scholar 

  10. Theiry JP. Epithelial-mesenchymal transitions in tumour progression. Nat Rev Cancer. 2002;2:442–54.

    Article  Google Scholar 

  11. Brozovic A. The relationship between platinum drug resistance and epithelial–mesenchymal transition. Arch Toxicol. 2017;91:605–19.

    Article  CAS  PubMed  Google Scholar 

  12. Brozovic A, Duran GE, Wang YC, Francisco EB, Sikic BI. The miR-200 family differentially regulates sensitivity to paclitaxel and carboplatin in human ovarian carcinoma OVCAR-3 and MES-OV cells. Mol Oncol. 2015;9:1678–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Yang J, Antin P, Berx G, Blanpain C, Brabletz T, Bronner M, et al. Guidelines and definitions for research on epithelial–mesenchymal transition. Nat Rev Mol Cell Biol. 2020;21:341–52.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Moisan F, Francisco EB, Brozovic A, Duran GE, Wang YC, Chaturvedi S, et al. Enhancement of paclitaxel and carboplatin therapies by CCL2 blockade in ovarian cancers. Mol Oncol. 2014;8:1231–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. von Mering C, Jensen LJ, Snel B, Hooper SD, Krupp M, Foglierini M, et al. STRING: known and predicted protein–protein associations, integrated and transferred across organisms. Nucleic Acids Res. 2004;33:D433–7.

    Article  PubMed Central  Google Scholar 

  16. Kuleshov MV, Jones MR, Rouillard AD, Fernandez NF, Duan Q, Wang Z, et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 2016;44:W90–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Xie Z, Bailey A, Kuleshov MV, Clarke DJB, Evangelista JE, Jenkins SL, et al. Gene set knowledge discovery with Enrichr. Curr Protoc. 2021;1:e90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Chen EY, Tan CM, Kou Y, Duan Q, Wang Z, Meirelles GV, et al. Enrichr: Interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics. 2013;14:128.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Fekete JT, Ősz Á, Pete I, Nagy GR, Vereczkey I, Győrffy B. Predictive biomarkers of platinum and taxane resistance using the transcriptomic data of 1816 ovarian cancer patients. Gynecol Oncol. 2020;156:654–61.

    Article  CAS  PubMed  Google Scholar 

  20. Fekete JT, Győrffy B. ROCplot.org: Validating predictive biomarkers of chemotherapy/hormonal therapy/anti-HER2 therapy using transcriptomic data of 3,104 breast cancer patients. Int J Cancer. 2019;145:3140–51.

    Article  CAS  PubMed  Google Scholar 

  21. Lin G, Chai J, Yuan S, Mai C, Cai L, Murphy RW, et al. VennPainter: a tool for the comparison and identification of candidate genes based on Venn diagrams. PLoS One. 2016;11:e0154315.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Lee HH, Bellat V, Law B. Chemotherapy induces adaptive drug resistance and metastatic potentials via phenotypic CXCR4-expressing cell state transition in ovarian cancer. PLoS One. 2017;12:e0171044.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Harris AR, Esparza S, Azimi MS, Cornelison R, Azar FN, Llaneza DC, et al. Platinum chemotherapy induces lymphangiogenesis in cancerous and healthy tissues that can be prevented with adjuvant anti-VEGFR3 therapy. Front Oncol. 2022;12:801764.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Volk-Draper L, Hall K, Griggs C, Rajput S, Kohio P, DeNardo D, et al. Paclitaxel therapy promotes breast cancer metastasis in a TLR4-dependent manner. Cancer Res. 2014;74:5421–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Volmer L, Koch A, Matovina S, Dannehl D, Weiss M, Welker G, et al. Neoadjuvant chemotherapy of patients with early breast cancer is associated with increased detection of disseminated tumor cells in the bone marrow. Cancers (Basel). 2022;14:635–48.

    Article  CAS  PubMed  Google Scholar 

  26. Zyl B, van, Tang D, Bowden NA. Biomarkers of platinum resistance in ovarian cancer: what can we use to improve treatment. Endocr Relat Cancer. 2018;25:303–18.

    Article  Google Scholar 

  27. Januchowski R, Sterzyńska K, Zawierucha P, Ruciński M, Świerczewska M, Partyka M, et al. Microarray-based detection and expression analysis of new genes associated with drug resistance in ovarian cancer cell lines. Oncotarget. 2017;8:49944–58.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Weidle UH, Birzele F, Kollmorgen G, Rueger R. Mechanisms and targets involved in dissemination of ovarian cancer. Cancer Genomics Proteom. 2016;13:407–23.

    Article  CAS  Google Scholar 

  29. Ricci F, Brunelli L, Affatato R, Chilà R, Verza M, Indraccolo S, et al. Overcoming platinum-acquired resistance in ovarian cancer patient-derived xenografts. Ther Adv Med Oncol. 2019;11:1758835919839543.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Ye Q, Liu K, Shen Q, Li Q, Hao J, Han F, et al. Reversal of multidrug resistance in cancer by multi-functional flavonoids. Front Oncol. 2019;9:487–502.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Hassan MK, Waly AA, Elsayed W, Keshk S, Allam WR, El-khamisy SF. Integrative microRNA and gene expression analysis identifies new epigenetically regulated microRNAs mediating taxane resistance in ovarian cancer. Sci Rep. 2021;11:562–78.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Szenajch J, Szabelska-Beręsewicz A, Świercz A, Zyprych-Walczak J, Siatkowski I, Góralski M, et al. Transcriptome remodeling in gradual development of inverse resistance between paclitaxel and cisplatin in ovarian cancer cells. Int J Mol Sci. 2020;21:9218–48.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Van Den Berg PR, Budnik B, Slavov N & Semrau S. Dynamic post-transcriptional regulation during embryonic stem cell differentiation. bioRxiv [Preprint] 2017. Available from: https://doi.org/10.1101/123497.

  34. Vogel C, Marcotte EM. Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat Rev Genet. 2012;13:227–32.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Jolly MK, Boareto M, Huang B, Jia D, Lu M, Onuchic JN, et al. Implications of the hybrid epithelial/mesenchymal phenotype in metastasis. Front Oncol. 2015;5:155–74.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Pastushenko I, Blanpain C. EMT transition states during tumor progression and metastasis. Trends Cell Biol. 2019;29:212–26.

    Article  CAS  PubMed  Google Scholar 

  37. Strauss R, Li ZY, Liu Y, Beyer I, Persson J, Sova P, et al. Analysis of epithelial and mesenchymal markers in ovarian cancer reveals phenotypic heterogeneity and plasticity. PLoS One. 2011;6:e16186.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Alves CL, Elias D, Lyng MB, Bak M, Ditzel HJ. SNAI2 upregulation is associated with an aggressive phenotype in fulvestrant-resistant breast cancer cells and is an indicator of poor response to endocrine therapy in estrogen receptor-positive metastatic breast cancer. Breast Cancer Res. 2018;20:60–72.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Huang RYJ, Wong MK, Tan TZ, Kuay KT, Ng AHC, Chung VY, et al. An EMT spectrum defines an anoikis-resistant and spheroidogenic intermediate mesenchymal state that is sensitive to e-cadherin restoration by a src-kinase inhibitor, saracatinib (AZD0530). Cell Death Dis. 2013;4:e915.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Greaves M, Maley CC. Clonal evolution in cancer. Nature. 2012;481:306–13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Schmit K, Michiels C. TMEM proteins in cancer: a review. Front Pharmacol. 2018;9:1345–58.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Marx S, Dal Maso T, Chen JW, Bury M, Wouters J, Michiels C, et al. Transmembrane (TMEM) protein family members: poorly characterized even if essential for the metastatic process. Semin Cancer Biol. 2020;60:96–106.

    Article  CAS  PubMed  Google Scholar 

  43. Drougat L, Settas N, Ronchi CL, Bathon K, Calebiro D, Maria AG, et al. Genomic and sequence variants of protein kinase A regulatory subunit type 1β (PRKAR1B) in patients with adrenocortical disease and Cushing syndrome. Genet Med J Am Coll Med Genet. 2021;23:174–82.

    CAS  Google Scholar 

  44. Elsayed AM, Bayraktar E, Amero P, Salama SA, Abdelaziz AH, Ismail RS, et al. PRKAR1B-AS2 long noncoding RNA promotes tumorigenesis, survival, and chemoresistance via the PI3K/AKT/mTOR pathway. Int J Mol Sci. 2021;22:1–25.

    Article  Google Scholar 

  45. Liu G, Ouyang X, Gong L, Yao L, Liu S, Li J, et al. E2F3 promotes liver cancer progression under the regulation of circ-PRKAR1B. Mol Ther Nucleic Acids. 2021;26:104–13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Cui Y, Yang S, Fu X, Feng J, Xu S, Ying G. High levels of KAP1 expression are associated with aggressive clinical features in ovarian cancer. Int J Mol Sci. 2015;16:363–77.

    Article  Google Scholar 

  47. Hu M, Fu X, Cui Y, Xu S, Xu Y, Dong Q, et al. Expression of KAP1 in epithelial ovarian cancer and its correlation with drug-resistance. Int J Clin Exp Med. 2015;8:17308–20.

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Li B, Dou SX, Yuan JW, Liu YR, Li W, Ye F, et al. Intracellular transport is accelerated in early apoptotic cells. Proc Natl Acad Sci USA. 2018;115:12118–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Manders DB, Kishore HA, Gazdar AF, Keller PW, Tsunezumi J, Yanagisawa H, et al. Dysregulation of fibulin-5 and matrix metalloproteases in epithelial ovarian cancer. Oncotarget. 2018;9:14251–67.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Li R, Wu H, Jiang H, Wang Q, Dou Z, Ma H, et al. FBLN5 is targeted by microRNA-27a-3p and suppresses tumorigenesis and progression in high-grade serous ovarian carcinoma. Oncol Rep. 2020;44:2143–51.

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Chuang HW, Hsia KT, Liao J, Bin, Yeh CC, Kuo WT, et al. Serpine2 overexpression is associated with poor prognosis of urothelial carcinoma. Diagnostics. 2021;11:1928–39.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Mao M, Wang W. SerpinE2 promotes multiple cell proliferation and drug resistance in osteosarcoma. Mol Med Rep. 2016;14:881–7.

    Article  CAS  PubMed  Google Scholar 

  53. Yang Y, Xin X, Fu X, Xu D. Expression pattern of human SERPINE2 in a variety of human tumors. Oncol Lett. 2018;15:4523–30.

    PubMed  PubMed Central  Google Scholar 

  54. Møller HD, Ralfkjær U, Cremers N, Frankel M, Pedersen RT, Klingelhöfer J, et al. Role of fibulin-5 in metastatic organ colonization. Mol Cancer Res MCR. 2011;9:553–63.

    Article  PubMed  Google Scholar 

  55. Albig AR, Schiemann WP. Fibulin-5 function during tumorigenesis. Futur Oncol. 2005;1:23–35.

    Article  CAS  Google Scholar 

  56. Lin N, Sato T, Ito A. Triptolide, a novel diterpenoid triepoxide from Tripterygium wilfordii Hook. f., suppresses the production and gene expression of pro-matrix metalloproteinases 1 and 3 and augments those of tissue inhibitors of metalloproteinases 1 and 2 in human synovial. Arthritis Rheum. 2001;44:2193–2200.

    Article  CAS  PubMed  Google Scholar 

  57. Vispé S, DeVries L, Créancier L, Besse J, Bréand S, Hobson DJ, et al. Triptolide is an inhibitor of RNA polymerase I and II-dependent transcription leading predominantly to down-regulation of short-lived mRNA. Mol Cancer Ther. 2009;8:2780–90.

    Article  PubMed  Google Scholar 

  58. Liu J, Zhang L, Zhang X, Xing X. Rapamycin enhanced the antitumor efficacy of oxaliplatin in cisplatin-resistant ovarian cancer cells A2780cis both in vitro and in vivo. J Chemother. 2015;27:358–64.

    Article  CAS  PubMed  Google Scholar 

  59. Guo Q, Nan XX, Yang JR, Yi L, Liang BL, Wei YB, et al. Triptolide inhibits the multidrug resistance in prostate cancer cells via the downregulation of MDR1 expression. Neoplasma. 2013;60:598–604.

    Article  CAS  PubMed  Google Scholar 

  60. Schlosshauer PW, Li W, Lin KT, Chan JLK, Wang LH. Rapamycin by itself and additively in combination with carboplatin inhibits the growth of ovarian cancer cells. Gynecol Oncol. 2009;114:516–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Zhong Y, Le F, Cheng J, Luo C, Zhang X, Wu X, et al. Triptolide inhibits JAK2/STAT3 signaling and induces lethal autophagy through ROS generation in cisplatin-resistant SKOV3/DDP ovarian cancer cells. Oncol Rep. 2021;45:1–10.

    Article  Google Scholar 

  62. Le F, Yang L, Han Y, Zhong Y, Zhan F, Feng Y, et al. TPL inhibits the invasion and migration of drug-resistant ovarian cancer by targeting the PI3K/AKT/NF-κB-signaling pathway to inhibit the polarization of M2 TAMs. Front Oncol. 2021;11:704001.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Wang R, Ma X, Su S, Liu Y. Triptolide antagonized the cisplatin resistance in human ovarian cancer cell line A2780/CP70 via hsa-mir-6751. Future Med Chem. 2018;10:1947–55.

    Article  CAS  PubMed  Google Scholar 

  64. Zhong YY, Chen HP, Tan BZ, Yu HH, Huang XS. Triptolide avoids cisplatin resistance and induces apoptosis via the reactive oxygen species/nuclear factor-κB pathway in SKOV3PT platinum-resistant human ovarian cancer cells. Oncol Lett. 2013;6:1084–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Tian Y, Li P, Xiao Z, Zhou J, Xue X, Jiang N, et al. Triptolide inhibits epithelial-mesenchymal transition phenotype through the p70S6k/GSK3/β-catenin signaling pathway in taxol-resistant human lung adenocarcinoma. Genet Med. 2021;10:1007–19.

    CAS  Google Scholar 

  66. Huang G, Hu H, Zhang Y, Zhu Y, Liu J, Tan B, et al. Triptolide sensitizes cisplatin-resistant human epithelial ovarian cancer by inhibiting the phosphorylation of AKT. J Cancer. 2019;10:3012–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Liu R, Chen Y, Liu G, Li C, Song Y, Cao Z, et al. PI3K/AKT pathway as a key link modulates the multidrug resistance of cancers. Cell Death Dis. 2020;11:1–12.

    Article  CAS  Google Scholar 

  68. Huang X, Li Z, Zhang Q, Wang W, Li B, Wang L, et al. Circular RNA AKT3 upregulates PIK3R1 to enhance cisplatin resistance in gastric cancer via miR-198 suppression. Mol Cancer. 2019;18:1–20.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Professor Gerhard Fritz (University of Düsseldorf, Germany) and Professor Maja T. Tomicic (University Medical Center of the Johannes Gutenberg University of Mainz) for critical reading of the manuscript and helpful suggestions regarding its improvement and outlook, Graduate Engineer Marina Šutalo (Ruđer Bošković Institute, Croatia) for technical assistance, Mrs. Carla Edwards for language editing and members of the Centre for Information and Media Technology at Heinrich-Heine-University Düsseldorf who provided the computational infrastructure and support.

Funding

These materials are based on the work financed by the Croatian Science Foundation (CSF, project numbers IP-2016-06-1036 and DOK-2018-01-8086), COST Action 17104, and Croatian League against Cancer.

Author information

Authors and Affiliations

  1. Division of Molecular Biology, Ruđer Bošković Institute, Bijenička cesta 54, Zagreb, Croatia

    Juran Kralj, Margareta Pernar Kovač & Anamaria Brozovic

  2. Department of Biochemistry and Molecular Biology, Faculty of Pharmacy and Biochemistry, University of Zagreb, Ante Kovačića 1, Zagreb, Croatia

    Sanja Dabelić

  3. Selvita, Hondlova ulica 2, 10000, Zagreb, Croatia

    Darija Stupin Polančec

  4. Genomics and Transcriptomics Laboratory at the Biological and Medical Research Center (BMFZ), Heinrich-Heine-University Düsseldorf, Universitätsstraße 1, Düsseldorf, Germany

    Thorsten Wachtmeister & Karl Köhrer

Authors
  1. Juran Kralj
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Margareta Pernar Kovač
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sanja Dabelić
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Darija Stupin Polančec
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Thorsten Wachtmeister
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Karl Köhrer
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Anamaria Brozovic
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

AB and JK designed the study. JK, MPK, SD, DSP and TW performed the experiments. AB, JK and KK provided conceptual advice. JK and AB wrote the manuscript. AB secured the funding.

Corresponding author

Correspondence to Anamaria Brozovic.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kralj, J., Pernar Kovač, M., Dabelić, S. et al. Transcriptome analysis of newly established carboplatin-resistant ovarian cancer cell model reveals genes shared by drug resistance and drug-induced EMT. Br J Cancer 128, 1344–1359 (2023). https://doi.org/10.1038/s41416-023-02140-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41416-023-02140-1

This article is cited by

Search

Advanced search

Quick links