Abstract
Background
Ovarian cancer is one of the most common diseases of the female reproductive system. The aim of this study was the investigation of the antitumor cisplatin effect on ascitic fluid tumor cells in the ovarian cancer experimental model by digital cytomorphometry and cell bioinformatic analysis.
Methods
Female Wistar rats were inoculated by ovarian cancer strain. After ovarian cancer transplantation rats were divided into two groups: control group—without cisplatin treatment, the experimental group—under cisplatin treatment. The ascitic fluid was taken on the 9-th day after tumor cell inoculation. Digital cytomorphometric and cytobioinformatic analysis were used to study ascitic fluid cancer cell morphofunctional changes under cisplatin treatment.
Results
Digital cytomorphometric characteristics of rat ovarian cancer ascitic cells were obtained. Tumor cells were classified into four groups according to their geometric size: small, medium, large, “gigantic”. The algorithm and the computer program based on tumor cell morphometric characteristics were created to calculate such cell bioinformatic characteristic as information redundancy coefficient R. Three parameters were determined as the criteria of cisplatin effect on cancer cells: cell number, nuclear/cytoplasmic ratio, R-value.
Conclusions
Data obtained suggest that cisplatin reduces the total cell number, the nuclear/cytoplasmic ratio and R-value thus indicates a decrease in cellular resistance and adaptive potential. The digital cytomorphometry and bioinformatics could be recommended as a testing system in the experimental or clinical study.
Similar content being viewed by others
References
Bespalov VG, Kireeva GS, Belyaeva OA, Senchik KY, Stukov AN, Maydin MA, et al. Experimental study of antitumor activity and effects on leukocyte count of intraperitoneal administration and hyperthermic intraperitoneal chemoperfusion (HIPEC) with dioxadet in a rat model of ovarian cancer. J Chemother. 2016;28(3):203–9. https://doi.org/10.1179/1973947815Y.0000000040.
Belashov AV, Zhikhoreva AA, Bespalov VG, Novik VI, Zhilinskaya NT, Semenova IV, et al. Refractive index distributions in dehydrated cells of human oral cavity epithelium. J Opt Soc Am A Opt Image Sci Vis. 2017;34(12):2538–43. https://doi.org/10.1364/JOSAB.34.002538.
Zhikhoreva AA, Belashov AV, Bespalov VG, Romanov VA, Semenov AL, Zhilinskaya NT, et al. Detection of morphological changes in cisplatin-treated ovarian cancer cells by digital holographic microscopy. Paper presented at the International Conference Laser Optics (ICLO), St.Petersburg, Russia, 4–8 June 2018. 577–577. https://doi.org/10.1109/LO.2018.8435576
Zhikhoreva AA, Belashov AV, Bespalov VG, Semenov AL, Semenova IV, Tochilnikov GV, et al. Morphological changes in ovarian carcinoma cells of Wistar rats induced by chemotherapy with Cisplatin and Dioxadet. Biomed Opt Express. 2018;9(11):5817–27. https://doi.org/10.1364/BOE.9.005817.
Gamal Din A, Badawi M, Abdel Aal S, Ibrahim N, Morsy F. DNA cytometry and nuclear morphometry in ovarian benign, borderline and malignant tumors. Maced J Med Sci. 2015;3(4):537–44. https://doi.org/10.3889/oamjms.2015.104.
Yan Z, Liu Y, Wei Y, Zhao Ning, Zhang Q, Wu C, et al. The functional consequences and prognostic value of dosage sensitivity in ovarian cancer. Mol Biosyst 2017; 13 (2): 380–391. https://doi.org/10.1039/c6mb00625f
Xinyan Z, Tomi A, Li Y, Zhang X, Akinyemiju T, Ojesina AI, Szychowski JM, Liu N, et al. A two stage approach for combining gene expression and mutation with clinical data improves survival prediction in myeloplastic syndromes and ovarian cancer. JBG. 2016. 1(1): 1–11. https://doi.org/10.18454/jbg.2016.1.1.2
Nast CC, Lemley KV, Hodgin JB, Bagnasco S, Avila-Casado C, Hewitt SM, et al. Morphology in the digital age: integrating high-resolution description of structural alterations with phenotypes and genotypes. Semin Nephrol. 2015;35(3):266–78. https://doi.org/10.1016/j.semnephrol.2015.04.006.
Parmar D, Sawke N, Sawke G. Diagnostic application of computerized nuclear morphometric image analysis in fine needle aspirates of breast lesions. Saudi J Health Sci. 2015;4:51–5. https://doi.org/10.4103/2278-0521.151409.
Boruah D, Deb P, Srinivas V, Mani NS. Morphometric study of nuclei and microvessels in gliomas and its correlation with grades. Microvasc Res. 2014;93:52–61. https://doi.org/10.1016/j.mvr.2014.03.002.
Natarajan S, Mahajan S, Boaz K, George T. Prediction of lymph node metastases by preoperative nuclear morphometry in oral squamous cell carcinoma: a comparative image analysis study. Indian J Cancer. 2010;47(4):406–11. https://doi.org/10.4103/0019-509X.73580.
Isaeva N, Savin E, Subbotina T, Yashin A. Bioinformatsionnyy analiz tyazhesti morfologicheskikh izmeneniy v pecheni pri razlichnykh patologicheskikh protsessakh. Mezhdunarodnyy zhurnal prikladnykh i fundamental’nykh issledovaniy. 2013;10:315–6 ((in Russian)).
Zhilinskaia N, Bazarnova J, Shleikin A, Peshuk L, Galenko O. Using of bioinformatics and computer morphometry in study of Fusarium spp. causing potato dry rot. Ukr Food J. 2016;5(3):515–22.
Zhilinskaia NT, Bazarnova JG, Politaeva NA. The using of bioinformatics in microbiological research. Paper presented at the IX International Congress Biotechnology: State of the Art and Perspectives. Moscow, Russia, 20–22 February, 2017. Congress Proceedings (vol. 2): 300–302. https://doi.org/https://doi.org/10.1080/02656736.2017.1375161
Bespalov VG, Alvovsky IK, Tochilnikov GV, Stukov AN, Vyshinskaya EA, Semenov AL, et al. Comparative efficacy evaluation of catheter intraperitoneal chemotherapy, normothermic and hyperthermic chemoperfusion in a rat model of ascitic ovarian cancer. Int J Hyperthermia. 2018;34(5):545–50. https://doi.org/10.1080/02656736.2017.1375161.
Avtandilov GG, Barsukov VS. Information analysis of immune and endocrine organs. Morphological changes in the course of infection. Zentralbl Pathol. 1992; 138 (5): 345–349
Avtandilov GG. Information characteristic of morphology of the adaptational norm, disadaptation, and pathology under the aspect of diagnostic microscopy. Gegenbaurs Morphol Jahrb. 1989;135:169–71.
Mendaçolli PJ, Brianezi G, Schmitt JV, Marques ME, Miot HA. Nuclear morphometry and chromatin textural characteristics of basal cell carcinoma. An Bras Dermatol. 2015;90(6):874–8. https://doi.org/10.1590/abd1806-4841.20154076.
Nivia M, Sunil SN, Rathy R, Anikumar TV. Comparative cytomorphometric analysis of oral mucosal cells in normal, tobacco users, oral leukoplakia and oral squamous cell carcinoma. J Cytol. 2015; 32(4): 253–260. https://doi.org/10.4103/0970-9371.171241
Boruah D, Bhatia JK, Rai A, Srinivas V, Nijhawan VS. Correlation of microvessel parameters in invasive ductal carcinoma of the breast and fibroadenomas: a morphometric study. Ann Diagn Pathol. 2016;25:72–8. https://doi.org/10.1016/j.anndiagpath.2016.09.014.
Wong R. Apoptosis in cancer: from pathogenesis to treatment. J Exp Clin Cancer Res. 2011; https://doi.org/10.1186/1756-9966-30-87
Kroemer G, El-Deiry WS, Golstein P, Peter ME, Vaux D, Vandenabeele P, et al. Classification of cell death: recommendations of the Nomenclature Committee on Cell Death and Differentiation. Cell Death Differ. 2005;12:1463–7. https://doi.org/10.1038/sj.cdd.4401724.
Zhang XF, Gurunathan S. Combination of salinomycin and silver nanoparticles enhances apoptosis and autophagy in human ovarian cancer cells: an effective anticancer therapy. Int J Nanomedicine. 2016;11:3655–75. https://doi.org/10.2147/IJN.S111279.
O’Sullivan-Coyne G, O’Sullivan GC, O’Donovan TR, Piwocka K, McKenna SL. Curcumin induces apoptosis-independent death in oesophageal cancer cells. Br J Cancer. 2009;101(9):1585–95. https://doi.org/10.1038/sj.bjc.6605308.
Sung WW, Lin YM, Wu PR, Yen H-H, Lai H-W, Su T-C, et al. High nuclear/cytoplasmic ratio of Cdk1 expression predicts poor prognosis in colorectal cancer patients. BMC Cancer; 2014. 14. https://doi.org/https://doi.org/10.1186/1471-2407-14-951
Ardeleanu V, Nechita A, Frâncu LL, Georgescu C. Nuclear morphometry and proliferative activity evaluation in the gastrointestinal stromal tumors. Rom J Morphol Embryol. 2014;55:319–233.
Mahovlić V, Ovanin-Rakić A, Skopljanac-Macina L, Barišić A, Rajhvajn S, Juric D, et al. Digital morphometry of cytologic aspirate endometrial samples. Coll Antropol. 2010;34:45–51.
Zhang ML, Guo AX, VandenBussche CJ. Morphologists overestimate the nuclear-to-cytoplasmic ratio. Cancer Cytopathol. 2016;124:669–77. https://doi.org/10.1002/cncy.21735.
Hasegawa K, Suetsugu A, Nakamura M, Matsumoto T, Aoki H, Kunisada T, et al. Imaging Nuclear-Cytoplasmic Dynamics in Primary and Metastatic Colon Cancer in Nude Mice. Anticancer Res. 2016;36:2113–7.
Malatesta M, Perdoni F, Santin G, Battistelli S, Muller S, Biggiogera M. Hepatoma tissue culture (HTC) cells as a model for investigating the effects of low concentrations of herbicide on cell structure and function. Toxicol In Vitro. 2008;22(8):1853–60. https://doi.org/10.1016/j.tiv.2008.09.006.
Boruah D, Manu V, Aung Hein T, Nijhawan VS. Utility of nuclear morphometry in serous ovarian carcinoma and its correlation with grades. J Interdiscip Histopathol. 2017;5(3):69–74. https://doi.org/10.5455/jihp.20170607073657.
Kashyap A, Jain M, Shukla S, Andley M. Study of nuclear morphometry on cytology specimens of bening and malignant breast lesions: a study of 122 cases. J Cytol. 2017;34(1):10–5. https://doi.org/10.4103/0970-9371.197591.
Krishnappa I, Parthiban R, Sharma A, Rani P. Significance of nuclear morphometry as a diagnostic tool in fine-needle aspirates of breast masses. Indian J Pathol Oncol. 2018; 5(4):592–597. https://doi.org/10.18231/2394-6792.2018.0114
Voeikov R, Abakumova T, Grinenko N, Melnikov P, Bespalov V, Stukov A, et al. Dioxadet-loaded nanogels as a potentional formulation for glioblastoma treatment. J Pharm Investig. 2017;47(1):75–83. https://doi.org/10.1007/s40005-016-0294-4.
Helms V. Principles of computational cell biology: from protein complexes to cellular networks. 2nd ed. New York: Wiley-Blackwell; 2019.
Farhat D, Léon S, Ghayad SE, Gadot N, Icard P, Le Romancer M, et al. Lipoic acid decreases breast cancer cell proliferation by inhibiting IGF-1R via furin downregulation. Br J Cancer. 2020. https://doi.org/10.1038/s41416-020-0729-6.
Feuerecker B, Pirsig S, Seidl C, Aichler M, Feuchtinger A, Bruchelt G, et al. Lipoic acid inhibits cell proliferation of tumor cells in vitro and in vivo. Cancer Biol Ther. 2012;13(14):1425–35. https://doi.org/10.4161/cbt.22003.
Kishimoto T, Yoshikawa Y, Yoshikawa K, Komeda S. Different effects of cisplatin and transplatin on the higher-order structure of DNA and gene expression. Int J Mol Sci. 2020;21(1):34. https://doi.org/10.3390/ijms21010034.
Acknowledgements
This work was partially financially supported by the Ministry of Science and Higher Education of the Russian Federation, Grant RFMEFI58117X0020.
Author information
Authors and Affiliations
Contributions
Conception and design of the work: Vladimir Bespalov. Acquisition: Alexander Semenov. Analysis: Grigory Tochilnikov, Elena Ermakova. Interpretation of data for the work: Nadezhda Zhilinskaya, Nadezhda Barakova. Drafting the work: Valerii Alexandrov. Revising for important intellectual content: Denis Baranenko. Final approval of the version to be published: Nadezhda Zhilinskaya.
Corresponding author
Ethics declarations
Conflict of interest
Authors declared that they have no conflict of interest.
Statement of human and animal rights
This article does not contain any studies with human participants performed by any of the authors. Maintenance and care of all animals were carried out according to the ethical principles established by the European Convention for the protection of vertebrate animals, used for experimental and other scientific purposes (accepted in Strasbourg 18.03.1986 and confirmed in Strasbourg 15.06.2006), and approved by Local ethical committee of the N.N. Petrov National Medical Research Center of Oncology.
Rights and permissions
About this article
Cite this article
Zhilinskaya, N.T., Bespalov, V.G., Semenov, A.L. et al. Cisplatin effect on digital cytomorphometric and bioinformatic tumor cell characteristics in rat ovarian cancer model–a preliminary study. Pharmacol. Rep 73, 642–649 (2021). https://doi.org/10.1007/s43440-020-00199-8
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s43440-020-00199-8