Βιολογικές δοκιμασίες για τον προκλινικό έλεγχο νέων μορίων με αντικαρκινική δραστικότητα: το παράδειγμα ημισυνθετικών αναλόγων της ολευρωπεΐνης
DOI:
https://doi.org/10.60988/pj.v35i3.5Keywords:
ανάπτυξη νέων φαρμάκων, αντικαρκινική δράση, in silico έλεγχος, in vitro έλεγχος, in vivo έλεγχοςAbstract
Η τοξικότητα και η περιορισμένη αποτελεσματικότητα πολλών παραδοσιακών χημειοθεραπευτικών σκευασμάτων καθιστούν επιτακτική την ανάγκη ανεύρεσης νέων στόχων και την ανάπτυξη νέων φαρμάκων για τη θεραπεία του καρκίνου. Η ανάπτυξη νέων φαρμάκων με αντικαρκινική δραστικότητα αποτελεί μια επίπονη και χρονοβόρα διαδικασία και απαιτεί το συνδυασμό μιας πληθώρας in silico, in vitro, και in vivo τεχνικών και κλινικών δοκιμών. Η ραγδαία ανάπτυξη της πληροφορικής παρέχει τρομερές δυνατότητες και τα in silico προγράμματα χρησιμοποιούνται ευρέως για την ανακάλυψη νέων στόχων. Παράλληλα, με τις in vitro δοκιμασίες αξιολογούνται οι αλληλεπιδράσεις των πιθανών φαρμακευτικών ουσιών σε κυτταρικά συστήματα. Στο τελευταίο στάδιο του προκλινικού ελέγχου που αφορά τα in vivo μοντέλα, μελετάται η φαρμακοκινητική, η ασφάλεια και η αποτελεσματικότητα των υποψήφιων μορίων σε πειραματόζωα. Η συγκεκριμένη ανασκόπηση αποσκοπεί να παρουσιάσει μια σειρά από in silico, in vitro και in vivo τεχνικές που χρησιμοποιούνται στον προκλινικό έλεγχο για την αξιολόγηση της αντικαρκινικής δράσης ουσιών. Παρουσιάζονται οι πιο συνηθισμένες in silico προσεγγίσεις, καθώς και in vitro τεχνικές για τον έλεγχο της δραστικότητας των ουσιών, τον επαγόμενο τύπο κυτταρικού θανάτου, το βαθμό μεταβολής του κυτταρικού διπλασιασμού και των αλλαγών στον κυτταρικό κύκλο, κάποια in vivo μοντέλα για τον έλεγχο της ανάπτυξης του όγκου, αλλά και η αξιολόγηση της ενεργοποίησης του ανοσοποιητικού συστήματος ex vivo. Τέλος, παρουσιάζεται επιγραμματικά η πειραματική διαδικασία που ακολουθείται στη Μονάδα Κυτταρομετρίας Ροής του Τμήματος Βιολογίας σε συνεργασία με το Τμήμα Φαρμακευτικής του ΕΚΠΑ για την αξιολόγηση της αντικαρκινικής δράσης ενός νέου αναλόγου της ολευρωπεΐνης, παραθέτοντας ορισμένα αντιπροσωπευτικά αποτελέσματα.
References
Miller K. D., Siegel R. L., Lin C. C., Mariotto A. B., Kramer J. L., Rowland J. H., Stein D. S., Alteri R., Jemal A. Cancer treatment and survivorship statistics, 2016. CA: Cancer J. Clin. 66, 271–89, 2016.
Siegel R. L., Miller K. D., Jemal A. Cancer statistics, 2018. CA: Cancer J. Clin. 68, 7–30, 2018.
Global Cancer Observatory, Cancer Tomorrow. [online] 2020, Accessed December 5, 2022. Available from Internet: https://gco.iarc.fr/tomorrow/en/dataviz/isotype.
Siegel R. L., Miller K. D., Jemal A. Cancer statistics, 2016. CA: Cancer J. Clin. 66, 7–30, 2016.
Schnipper L. E., Davidson N. E., Wollins D. S., Tyne C., Blayney D. W., Blum D., Dicker A. P., Ganz P. A., Hoverman J. R., Langdon R., Lyman G. H., Meropol N. J., Mulvey T., Newcomer L., Peppercorn J., Polite B., Raghavan D., Rossi G., Saltz L., Schrag D., Smith T. J., Yu P. P., Hudis C. A., Schilsky R. L. American Society of Clinical Oncology Statement: A Conceptual Framework to Assess the Value of Cancer Treatment Options. J. Clin. Oncol. 33, 2563–77, 2015.
Su M., Zhang Q., Bai X., Wu C., Li Y., Mossialos E., Menshah G. A., Masoudi F. A., Lu J., Li X., Salas-Vega S., Zhang A., Lu Y., Nasir K., Krumholz H. M., Jiang L. Availability, cost, and prescription patterns of antihypertensive medications in primary health care in China: a nationwide cross-sectional survey. Lancet. 390, 2559–68, 2017.
Nosengo N. Can you teach old drugs new tricks? Nature. 534, 314–6, 2016.
Stone P. (2010). Pharmaceutical Products and Chemical Intermediates. Fourth Review: Advice Concerning the Addition of Certain Products to the Pharmaceutical Appendix to the HTS. USITC Publication 4181, pp. 13.
Carelle N., Piotto E., Bellanger A., Germanaud J., Thuillier A., Khayat D. Changing patient perceptions of the side effects of cancer chemotherapy. Cancer. 95, 155–63, 2002.
Zhang Z., Zhou L., Xie N., Nice E. C., Zhang T., Cui Y., Huang C. Overcoming cancer therapeutic bottleneck by drug repurposing. Sig. Transduct. Target Ther. 5, 2020.
Gordaliza M. Natural products as leads to anticancer drugs. Clin. Transl. Oncol. 9, 767–76, 2007.
Cragg G. M., Grothaus P. G., Newman D. J. Impact of natural products on developing new anti‐cancer agents. Chem. Rev. 109, 3012–43, 2009.
Cheng W. H., Cao B., Shang H., Niu C., Zhang L. M., Zhang Z. H., Tian D. L., Zhang S., Chen H., Zou, Z. M. Synthesis and evaluation of novel podophyllotoxin derivatives as potential antitumor agents. Eur. J. Med. Chem. 85, 498-507, 2014.
Rodrigues F. A., Bomfim I. S., Cavalcanti B. C., Pessoa C. O., Wardell J. L., Wardell S. M. S. V., Pinheiro A. C., Kaiser C. R., Nogueira T. C. M., Low J. N., Gomes L. R., de Souza M. V. Design, synthesis and biological evaluation of (E)-2-(2- arylhydrazinyl) quinoxalines, a promising and potent new class of anticancer agents. Bioorg. Med. Chem. Lett. 24, 934-9, 2014.
Kataoka T., Shima F. In Silico Drug Discovery Based on the Identification of a Novel “Druggable” Surface Pockets on the Ras Oncogene Products. [online] 2013, Accessed March 15, 2022.
Available from Internet: http://www.spring8.or.jp/en/news_publications/press_release/2013/
_2/.
Brandish P. E., Chiu C. S., Schneeweis J., Brandon N. J., Leech C. L., Kornienko O., Scolnick E. M., Strulovici B., Zheng W. A cell-based ultra-high-throughput screening assay for identifying inhibitors of D-amino acid oxidase. J. Biomol. Screen. 11, 481–7, 2006.
Segall M. D., Barber C. Addressing toxicity risk when designing and selecting compounds in early drug discovery. Drug Discov. Today. 19, 688–93, 2014.
Zhang K. Y. J., Milburn M. V., Artis D. R. Scaffold-based Drug Discovery, In: Jhoti H., Leach A. R. eds. Structure-based Drug Discovery, The Netherlands, Springer (2007) pp. 129-50.
Vidal D., Garcia-Serna R., Mestres J., Ligand-based approaches to in silico pharmacology, chemoinformatics and computational chemical biology. Springer. 672, 489–502, 2011.
Ezzat A., Wu M., Li X. L., Kwoh C. K. Computational prediction of drug–target interactions using chemogenomic approaches: an empirical survey. Brief Bioinform. 20, 1337–57, 2019.
Cichonska A., Ravikumar B., Parri E., Timonen S., Pahikkala T., Airola A., Wennerberg K., Rousu J., Aittokallio T. Computational-experimental approach to drug-target interaction mapping: a case study on kinase inhibitors. PLoS Comput. Biol. 13, 2017.
Agamah F. E., Mazandu G. K., Hassan R., Bope C. D., Thomford N. E., Ghansah A., Chimusa E. R. Computational/in silico methods in drug target and lead prediction. Brief Bioinform. 21, 1663–75, 2020.
Zheng S., Dharssi S., Wu M., Li J., Lu Z. Text mining for drug discovery. Method Mol. Biol. 1939, 231–52, 2019.
Rouillard A. D., Gundersen G. W., Fernandez N. F., Wang Z., Monteiro C. D., McDermott M. G., Ma’ayan A. The Harmonizome: a Collection of Processed Datasets Gathered to Serve and Mine Knowledge about Genes and Proteins. Database. 2016, 2016.
Ochoa D., Hercules A., Carmona M., Suveges D., Gonzalez-Uriarte A., Malangone C., Miranda A., Fumis L., Carvalho-Silva D., Spitzer M. Open Targets Platform: supporting systematic drug–target identification and prioritization. Nucleic Acids Res. 49, 1302–10, 2021.
Kim S., Chen J., Cheng T., Gindulyte A., He J., He S., Li Q., Shoemaker B. A., Thiessen P. A., Yu B. PubChem 2019 update: improved access to chemical data. Nucleic Acids Res. 47, 1102–09, 2019.
Norinder U., Bergstrom C. A. Prediction of ADMET properties. ChemMedChem. 1, 920–37, 2006.
Shaker B., Yu M. S., Lee J., Lee Y., Jung C., Na D. User guide for the discovery of potential drugs via protein structure prediction and ligand docking simulation. J. Microbiol. 58, 235–44, 2020.
Martin Y. C., Kofron J. L., Traphagen L. M. Do structurally similar molecules have similar biological activity? J. Med. Chem. 45, 4350–8, 2002.
Kim S., Thiessen P. A., Bolton E. E., Chen J., Fu G., Gindulyte A., Han L., He J., He S., Shoemaker B. A. PubChem substance and compound databases. Nucleic Acids Res. 44, 1202–13, 2016.
Sterling T., Irwin J. J. ZINC 15–ligand discovery for everyone. J. Chem. Inf. Model. 55, 2324–37, 2015.
Rognan D. Structure-based approaches to target fishing and ligand profiling. Mol. Inform. 29, 176–87, 2010.
Shaker B., Ahmad S., Lee J., Jung C., Na D. In silico methods and tools for Drug Discovery. Comput. Biol. Med. 137, 2021.
Kitchen D. B., Decornez H., Furr J. R., Bajorath J. Docking and scoring in virtual screening for drug discovery: methods and applications. Nat. Rev. Drug Discov. 3, 935–49, 2004.
Combs A. P. Structure-based drug design of new leads for phosphatase research. IDrugs. 10, 112–5, 2007.
Coumar M. S., Leou J. S., Shukla P., Wu J. S., Dixit A. K., Lin W. H., Chang C. Y., Lien T. W., Tan U. K., Chen C. H. Structure-based drug design of novel Aurora kinase A inhibitors: structural basis for potency and specificity. J. Med. Chem. 52, 1050–62, 2009.
Gohlke H., Klebe G. Approaches to the description and prediction of the binding affinity of small-molecule ligands to macromolecular receptors. Angew. Chem. Int. Ed. Engl. 41, 2644–76, 2002.
Kuntz I. D., Blaney J. M., Oatley S. J., Langridge R., Ferrin T. E. A geometric approach to macromolecule-ligand interactions. J. Mol. Biol. 161, 269–88, 1982.
Friesner R. A., Banks J. L., Murphy R. B., Halgren T. A., Klicic J. J., Mainz D. T., Repasky M. P., Knoll E. H., Shelley M., Perry J. K. Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J. Med. Chem. 47, 1739–49, 2004.
Grant B. J., Lukman S., Hocker H. J., Sayyah J., Brown J. H., McCammon J. A., Gorfe A. A. Novel allosteric sites on Ras for lead generation. PloS One. 6, 2011.
Nair P. C., Malde A. K., Drinkwater N., Mark A. E. Missing fragments: detecting cooperative binding in fragment-based drug design. ACS Med. Chem. Lett. 3, 322–6, 2012.
Venkatesh S., Lipper R. A. Role of the development scientist in compound lead selection and optimization. J. Pharm. Sci. 89, 145–54, 2000.
Viana Nunes A. M., das Chagas Pereira de Andrade F., Filgueiras L. A., de Carvalho Maia O. A., Cunha R. L. O. R, Rodezno S. V. A, Maia Filho A. L. M., de Amorim Carvalho F. A., Braz D. C., Mendes A. N. preADMET analysis and clinical aspects of dogs treated with the Organotellurium compound RF07: a possible control for canine visceral leishmaniasis? Environ. Toxicol. Pharmacol. 80, 2020.
Daina A., Michielin O., Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci. Rep. 7, 2017.
National Cancer Institute, Cell Lines in the In Vitro Screen. [online] 2015, Accessed March 15, 2023. Available from Internet: https://dtp.cancer.gov/discoverydevelopment/nci-60/ cell_list.htm.
Riss T. L., Moravec R. A., Niles A. L., Duellman S., Benink H. A., Worzella T. J., Minor L. Cell Viability Assays. 2013 May 1 [Updated 2016 Jul 1]. In: Markossian S. eds. Assay Guidance Manual [Online]. Bethesda (MD): Eli Lilly & Company and the National Center for Advancing Translational Sciences (2004). Available from Internet https://www.ncbi.nlm.nih.gov/books/
NBK144065/.
Berridge M. V., Tan A. S. Characterization of the cellular reduction of 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide (MTT): subcellular localization, substrate dependence, and involvement of mitochondrial electron transport in MTT reduction. Arch. Biochem. Biophys. 303, 474–82, 1993.
Gerlier D., Thomasset N. Use of MTT colorimetric assay to measure cell activation. J. Immunol. Meth. 94, 57–63, 1986.
Kamiloglu S., Sari G., Ozdal T., Capanoglu E. Guidelines for cell viability assays. Front. Nutr. 1, 332–49, 2020.
Skehan P., Storeng R., Scudiero D., Monks A., McMahon J., Vistica D., Warren J. T., Bokesch H., Kenney S., Boyd M. R. New colorimetric cytotoxicity assay for anticancer‐drug screening. J. Natl. Cancer Inst. 82, 1107–12, 1990.
Vichai V., Kirtikara K. Sulforhodamine B colorimetric assay for cytotoxicity screening. Nat. Protoc. 1, 1112, 2006
Decker T., Lohmann-Matthes M. L. A quick and simple method for the quantitation of lactate dehydrogenase release in measurements of cellular cytotoxicity and tumor necrosis factor (TNF) activity. J. Immunol. Meth. 115, 61–9, 1988.
Kumar P., Nagarajan A., Uchil P. D. Analysis of cell viability by the lactate dehydrogenase assay. Cold Spring Harb. Protoc. 6, 465– 8, 2018.
Strehler B. L., McElroy W. D. Assay of adenosine triphosphate. In Colwick S. P., Kaplan N. O. eds Methods in Enzymology, New York, Academic Press (1957) 3, 871–3.
Hannah R., Beck M., Moravec R., Riss T. CellTiter‐Glo™ Luminescent cell viability assay: a sensitive and rapid method for determining cell viability. Promega Cell Notes. 2, 11–3, 2001.
Lowe S. W., Lin A. W. Apoptosis in cancer. Carcinogenesis. 21, 485–95, 2000.
What is the difference between necrosis and apoptosis? Proteintech Group. [online] 2022, Accessed March 15, 2023. Available from Internet: https://www.ptglab.com/news/blog/what-is-the-difference-between-necrosis-and-apoptosis
Alberts B., Johnson A., Lewis J., Morgan D., Raff M., Roberts K., Walter P. (2018), Μοριακή Βιολογία του ΚΥΤΤΑΡΟΥ, Μετάφραση της 6ης Αμερικανικής Έκδοσης, Αθήνα, Εκδόσεις Utopia, pp. 976
Taatjes D. J., Sobel B. E., Budd R. C. Morphological and cytochemical determination of cell death by apoptosis. Histochem. Cell Biol. 129, 33–43, 2008.
Bottone M. G., Santin G., Aredia F., Bernocchi G., Pellicciari C., Scovassi, A. I. Morphological features of organelles during apoptosis: an overview. Cells. 2, 294–305, 2013.
Combs C. A. Fluorescence microscopy: a concise guide to current imaging methods. Curr. Protoc. Neurosci., Chapter 2, Unit 2.1, 2010.
Pringle J. R., Preston R. A., Adams A. E., Stearns T., Drubin D. G., Haarer B. K., Jones E. W. Fluorescence microscopy methods for yeast. Methods Cell Biol. 31, 357–435, 1989.
Renz M. Fluorescence microscopy – A historical and technical perspective. Cytometry Part A. 83, 767–9, 2013.
Berg, J. M., Tymoczko, J. L., Gatto, G. J., Stryer, L. (2017), Βιοχημεία, Μετάφραση της 8ης Αμερικανικής Έκδοσης- 3η Ελληνική Έκδοση, Αθήνα, Πανεπιστημιακές Εκδόσεις Κρήτης, pp. 87.
Adan A., Alizada G., Kiraz Y., Baran Y., Nalbant, A. Flow cytometry: basic principles and applications. Crit. Rev. Biotechnol. 37, 163–76, 2017.
Henel G., Schmitz J. L. Basic theory and clinical applications of flow cytometry. Lab. Med. 38, 428–36, 2007.
Vega-Perez J. M., Palo-Nieto C., Vega-Holm M., Góngora-Vargas P. Calderón-Montaño J. M., Burgos-Morón E., Lopez-Lazaro M., Iglesias-Guerra F. Aziridines from alkenyl-β-D-galactopyranoside derivatives: Stereoselective synthesis and in vitro selective anticancer activity. Eur. J. Med. Chem. 70, 380-92, 2013.
Pourahmad J., Salimi A. Isolated human peripheral blood mononuclear cell (PBMC), a cost-effective tool for predicting immunosuppressive effects of drugs and xenobiotics. Iran. J. Pharm. Res. 14, 979-80, 2015.
Samara P., Christoforidou N., Lemus C., Argyropoulou A., Ioannou K., Vougogiannopoulou K., Aligiannis N., Paronis E., Gaboriaud-Kolar N., Tsitsilonis O., Skaltsounis A. L. New semi-synthetic analogs of oleuropein show improved anticancer activity in vitro and in vivo. Eur. J. Med. Chem. 137, 11–29, 2017.
Workman P., Aboagye E. O., Balkwill F., Balmain A., Bruder G., Chaplin D. J., Double J. A., Everitt J., Farningham D. A. H., Glennie M. J., Kelland L. R., Robinson V., Stratford I. J., Tpzer G. M., Watson S., Wedge S. R., Eccles S. A., An Ad Hoc Committee of the National Cancer Research Institute. Guidelines for the welfare and use of animals in cancer research. Br. J. Cancer. 102, 1555–77, 2010.
House C. D., Hernandez L. F., Annunziata C. M. Recent Technological Advances in Using Mouse Models to Study Ovarian Cancer. Front. Oncol. 4, 26, 2014.
Κοκκινογένης Ε. Π., Δελή Μ., Παπακωστοπούλου Σ., Κότσαρη Μ., Ζουμπουρλής Π., Γουλιελμάκη Μ., Ζουμπουρλής Β. Ανασκόπηση των εφαρμογών των μοντέλων ποντικών στην έρευνα του καρκίνου. Arch. Hell. Med. 38, 166–76, 2021.
Brunner K. T., Mauel J., Cerottini J. C., Chapuis B. Quantitative assay of the lytic action of immune lymphoid cells on 51-Cr-labelled allogeneic target cells in vitro; inhibition by isoantibody and by drugs. Immunology. 14, 181–96, 1968.
Zaritskaya L., Shurin M. R., Sayers T. J., Malyguine A. M. New flow cytometric assays for monitoring cell-mediated cytotoxicity. Exp. Rev. Vaccines. 9, 601–16, 2010.
Trapani J. A., Smyth M. J. Functional significance of the perforin/ granzyme cell death pathway. Nat. Rev. Immunol. 2, 735–47, 2002.
Davis D. M., Dustin M. L., What is the importance of the immunological synapse? Trends Immunol. 25, 323–7, 2004.
Fridman W. H., Galon J., Pagès F., Tartout E., Sautès-Fridman C., Kroemer G. Prognostic and predictive impact of intra- and peritumoral immune infiltrates. Cancer Res. 71, 5601-5, 2011.
Fridman W. H., Pagès F., Sautès-Fridman C., Galon J. The immune contexture in human tumours: impact on clinical outcome. Nat. Rev. Cancer. 12, 298-306, 2012.
Fridman W. H., Dieu-Nosjean M. C., Pagès F., Cremer I., Damotte D., Sautès-Fridman C., Galon J. The Immune Microenvironment of Human Tumors: General Significance and Clinical Impact. Cancer Microenviron. 6, 117-22, 2013.
