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Modern Approaches to Testing Drug Sensitivity of Patients’ Tumors (Review)

Modern Approaches to Testing Drug Sensitivity of Patients’ Tumors (Review)

Druzhkova I.N., Shirmanova M.V., Kuznetsova D.S., Lukina М.М., Zagaynova Е.V.
Key words: medical oncology; individualized cancer therapy; cancer treatment selection; molecular genetic tumor testing; drug testing in vitro.
2020, volume 12, issue 4, page 91.

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Drug therapy is still one of the basic techniques used to treat cancers of different etiology. However, tumor resistance to drugs is a pressing problem limiting drug treatment efficacy. It is obvious for both modern fundamental and clinical oncology that there is the need for an individual approach to treating cancer taking into account the biological properties of a tumor when prescribing chemo- and targeted therapy. One of the promising strategies is to increase the antitumor therapy efficacy by developing predictive tests, which enable to evaluate the sensitivity of a particular tumor to a specific drug or a drug combination before the treatment initiation and, thus, make individual therapy selection possible.

The present review considers the main approaches to drug sensitivity assessment of patients’ tumors: molecular genetic profiling of tumor cells, and direct efficiency testing of the drugs on tumor cells isolated from surgical or biopsy material. There were analyzed the key directions in research and clinical studies such as: the search for predictive molecular markers, the development of methods to maintain tumor cells or tissue sections viable, i.e. in a condition maximum close to their physiological state, the development of high throughput systems to assess therapy efficiency. Special attention was given to a patient-centered approach to drug therapy in colorectal cancer.

  1. DeVita V.T.  Jr., Chu E. A history of cancer chemotherapy. Cancer Res 2008; 68(21): 8643–8653, https://doi.org/10.1158/0008-5472.CAN-07-6611.
  2. Schirrmacher V. From chemotherapy to biological therapy: a review of novel concepts to reduce the side effects of systemic cancer treatment (review). Int J Oncol 2019; 54(2): 407–419.
  3. Chabner B.A., Roberts T.G. Jr. Timeline: chemotherapy and the war on cancer. Nat Rev Cancer 2005; 5(1): 65–72, https://doi.org/10.1038/nrc1529.
  4. Fedyanin M.Yu., Gladkov O.A., Gordeev S.S., Rykov I.V., Tryakin A.A., Chernykh M.V. Practical recommendations for the treatment of colorectal cancer. Zlokachestvennye opukholi: prakticheskie rekomendatsii RUSSCO #3s2 2018; 8: 325–362.
  5. Fedyanin M.Yu., Gladkov O.A., Gordeev S.S., Rykov I.V., Tryakin A.A. Practical recommendations for the treatment of colorectal cancer and rectosigmoid compounds. Zlokachestvennye opukholi: prakticheskie rekomendatsii RUSSCO #3s2 2018; 8: 289–324.
  6. Padma V.V. An overview of targeted cancer therapy. Biomedicine (Taipei) 2015; 5(4): 19, https://doi.org/10.7603/s40681-015-0019-4.
  7. Goossens N., Nakagawa S., Sun X., Hoshida Y. Cancer biomarker discovery and validation. Transl Cancer Res 2015; 4(3): 256–269, https://doi.org/10.3978/j.issn.2218-676X.2015.06.04.
  8. Michor F., Polyak K. The origins and implications of intratumor heterogeneity. Cancer Prev Res (Phila) 2010; 3(11): 1361–1364, https://doi.org/10.1158/1940-6207.CAPR-10-0234.
  9. Visvader J.E. Cells of origin in cancer. Nature 2011; 469(7330): 314–322, https://doi.org/10.1038/nature09781.
  10. Stanta G., Bonin S. Overview on clinical relevance of intra-tumor heterogeneity. Front Med (Lausanne) 2018; 5: 85, https://doi.org/10.3389/fmed.2018.00085.
  11. Wang X., Zhang H., Chen X. Drug resistance and combating drug resistance in cancer. Cancer Drug Resist 2019; 2: 141–160, https://doi.org/10.20517/cdr.2019.10.
  12. Hammond W.A., Swaika A., Mody K. Pharmacologic resistance in colorectal cancer: a review. Ther Adv Med Oncol 2016; 8(1): 57–84, https://doi.org/10.1177/1758834015614530.
  13. Sommerová L., Michalová E., Hrstka R. New approaches for chemosensitivity testing in malignant diseases. Clin Onkol 2018; 31(2): 117–124, https://doi.org/10.14735/amko2018117.
  14. Moiseyenko V.M., Moiseyenko F.V., Yanus G.A., Kuligina E.S., Sokolenko A.P., Bizin I.V., Kudriavtsev A.A., Aleksakhina S.N., Volkov N.M., Chubenko V.A., Kozyreva K.S., Kramchaninov M.M., Zhuravlev A.S., Shelekhova K.V., Pashkov D.V., Ivantsov A.O., Venina A.R., Sokolova T.N., Preobrazhenskaya E.V., Mitiushkina N.V., Togo A.V., Iyevleva A.G., Imyanitov E.N. First-line cetuximab monotherapy in KRAS/NRAS/BRAF mutation-negative colorectal cancer patients. Clin Drug Investig 2018; 38(6): 553–562, https://doi.org/10.1007/s40261-018-0629-1.
  15. Yanus G.A., Belyaeva A.V., Ivantsov A.O., Kuligina E.S., Suspitsin E.N., Mitiushkina N.V., Aleksakhina S.N., Iyevleva A.G., Zaitseva O.A., Yatsuk O.S., Gorodnova T.V., Strelkova T.N., Efremova S.A., Lepenchuk A.Yu., Ochir-Garyaev A.N., Paneyah M.B., Matsko D.E., Togo A.V., Imyanitov E.N. Pattern of clinically relevant mutations in consecutive series of Russian colorectal cancer patients. Med Oncol 2013; 30(3): 686, https://doi.org/10.1007/s12032-013-0686-5.
  16. Sexton R.E., Mpilla G., Kim S., Philip P.A., Azmi A.S. Ras and exosome signaling. Semin Cancer Biol 2019; 54: 131–137, https://doi.org/10.1016/j.semcancer.2019.02.004.
  17. Vladimirova L.Yu., Abramova N.A., Storozhakova A.E. Targeted anti-EGFR monoclonal antibody therapy for colorectal cancer. Zlokachestvennye opuholi 2016; 4-S1: 87–91.
  18. Oliner K., Douillard J.Y., Siena S., Tabernero J., Burkes R.L., Hamblet M.E.B., Bodoky G., Cunningham D., Jassem J., Rivera F., Kocáková I., Ruff P., Blasinska-Morawiec M., Smakal M., Williams R.T., Rong A., Wiezorek J.S., Sidhu R., Patterson S.D. Analysis of KRAS/NRAS and BRAF mutations in the phase III PRIME study of panitumumab (pmab) plus FOLFOX versus FOLFOX as first-line treatment (tx) for metastatic colorectal cancer (mCRC). J Clin Oncol 2013; 35(15): 3511, https://doi.org/10.1200/jco.2013.31.15_suppl.3511.
  19. Schwartzberg L.S., Rivera F., Karthaus M., Fasola G., Canon J.-L., Go H.Y.Y. PEAK (study 20070509): a randomized phase II study of mFOLFOX6 with either panitumumab (pmab) or bevacizumab (bev) as first-line (tx) in patients (pts) with unresectable wild type (WT) KRAS metastatic colorectal cancer (mCRC). J Clin Oncol 2013; 31(4): 446, https://doi.org/10.1200/jco.2013.31.4_suppl.446.
  20. Van Cutsem E., Lenz H.J., Köhne C.H., Heinemann V., Tejpar S., Melezínek I., Beier F., Stroh C., Rougier P., van Krieken J.H., Ciardiello F. Fluorouracil, leucovorin, and irinotecan plus cetuximab treatment and RAS mutations in colorectal cancer. J Clin Oncol 2015; 33(7): 692–700, https://doi.org/10.1200/JCO.2014.59.4812.
  21. De Roock W., Claes B., Bernasconi D., Schutter J.D., Beismans B., Founzilas G., Kalogeras K.T., Kotoula V., Papamichael D., Laurent-Puig P., Penault-Llorca F., Rougier P., Vincenzi B., Santini D., Tonini G., Cappuzzo F., Frattini M., Molinari F., Saletti P., De Dosso S., Martini M., Bardelli A., Siena S., Sartore-Bianchi A., Tabernero J., Macarulla T., Di Fiore F., Gangloff A.O., Ciardiello F., Pfeiffer P., Qvortrup C., Hansen T.P., Van Cutsem E., Piessevaux H., Lambrechts D., Delorenzi M., Tejpar S. Effects of KRAS, BRAF, NRAS, and PIK3CA mutations on the efficacy of cetuximab plus chemotherapy in chemotherapy-refractory metastatic colorectal cancer: a retrospective consortium analysis. Lancet Oncol 2010; 1(8): 753–762, https://doi.org/10.1016/S1470-2045(10)70130-3.
  22. Di Nicolantonio F., Martini M., Molinari F., Sartore-Bianche A., Arena S., De Dosso P.S., Mazzucchelli L., Frattini M., Siena S., Bardelli A. Wild-type BRAF is required for response to panitumumab or cetuximab in metastatic colorectal cancer. J Clin Oncol 2008; 26(35): 5705–5712, https://doi.org/10.1200/JCO.2008.18.0786.
  23. Fedyanin M.Yu., Tryakin A.A., Tjulandin S.A. Promises for treating colon cancer patients with BRAF gene mutation. Onkologicheskaa koloproktologia 2014; 3: 9–16.
  24. Tariq K., Tariq K., Ghias K., Ghias K. Colorectal cancer carcinogenesis: a review of mechanisms. Biol Med 2016; 13(1): 120–135, https://doi.org/10.20892/j.issn.2095-3941.2015.0103.
  25. Fedyanin M.Y., Tryakin A.A., Tjulandin S.A. Role of microsatellite instability in colon cancer. Onkologicheskaa koloproktologia 2012; 3: 19–25.
  26. Roth A., Tejpar S., Delorenzi M., Yan P., Fiocca R., Klingbiel D., Dietrich D., Biesmans B., Bodoky G., Barone C., Aranda E., Nordlinger B., Cisar L., Labianca R., Cunningham D., Van Cutsem E., Bosman F. Prognostic role of KRAS and BRAF in stage II and III resected colon cancer: results of the translational study on the PETACC-3, EORTC 40993, SAKK 60-00 trial. J Clin Oncol 2009; 28: 466–474, https://doi.org/10.1200/JCO.2009.23.3452.
  27. Heinemann V., Rivera F., O’Neil B.H., Stintzing S., Koukakis R., Terwey J.H., Douillard J.Y. A study-level meta-analysis of efficacy data from head-to-head first-line trials of epidermal growth factor receptor inhibitors versus bevacizumab in patients with RAS wild-type metastatic colorectal cancer. Eur J Cancer 2016; 67: 11–20, https://doi.org/10.1016/j.ejca.2016.07.019.
  28. Price T., Kim T.W., Li J., Cascinu S., Ruff P., Suresh A.S., Thomas A., Tjulandin S., Guan X., Peeters M. Final results and outcomes by prior bevacizumab exposure, skin toxicity, and hypomagnesaemia from ASPECCT: randomized phase 3 non-inferiority study of panitumumab versus cetuximab in chemorefractory wild-type KRAS exon 2 metastatic colorectal cancer. Eur J Cancer 2016; 68: 51–59, https://doi.org/10.1016/j.ejca.2016.08.010.
  29. Imjanitov E.N. Standard and potential predictive markers for gastrointestinal tumors. Prakticheskaja onkologija 2012; 13(4): 219–228.
  30. Lenz H.J. Pharmacogenomics and colorectal cancer. Adv Exp Med Biol 2006; 587: 211–231, https://doi.org/10.1007/978-1-4020-5133-3_18.
  31. Lurje G., Manegold P.C., Ning Y., Pohl A., Zhang W., Lenz H.J. Thymidylate synthase gene variations: predictive and prognostic markers. Mol Cancer Ther 2009; 8(5): 1000–1007, https://doi.org/10.1158/1535-7163.MCT-08-0219.
  32. Ye D.J., Zhang J.M. Research development of the relationship between thymidine phosphorylase expression and colorectal carcinoma. Cancer Biol Med 2013; 10(1): 10–15, https://doi.org/10.7497/j.issn.2095-3941.2013.01.002.
  33. Yoon Y.S., Kim J.C. Recent applications of chemosensitivity tests for colorectal cancer treatment. World J Gastroenterol 2014; 20(44): 16398–16408, https://doi.org/10.3748/wjg.v20.i44.16398.
  34. Ikeguchi M., Arai Y., Maeta Y., Ashida K., Katano K., Wakatsuki T. Topoisomerase I expression in tumors as a biological marker for CPT11 chemosensitivity in patients with colorectal cancer. Surg Today 2011; 41(9): 1196–1199, https://doi.org/10.1007/s00595-011-4546-7.
  35. Arriagada R., Bergman B., Dunant A., Le Chevalier T., Pignon J.P., Vansteenkiste J.; International Adjuvant Lung Cancer Trial Collaborative Group. Cisplatin-based adjuvant chemotherapy in patients with completely resected non-small-cell lung cancer. N Engl J Med 2004; 350(4): 351–360, https://doi.org/10.1056/NEJMoa031644.
  36. Jensen N.F., Smith D.H., Nygård S.B., Rømer M.U., Nielsen K.V., Brünner N. Predictive biomarkers with potential of converting conventional chemotherapy to targeted therapy in patients with metastatic colorectal cancer. Scand J Gastroenterol 2012; 47(3): 340–355, https://doi.org/10.3109/00365521.2012.640835.
  37. Smith A., Farrah K. Gene expression profiling tests for breast cancer: a rapid qualitative review. Ottawa (ON): Canadian Agency for Drugs and Technologies in Health; 2019. URL: https://www.ncbi.nlm.nih.gov/books/NBK545134.
  38. Yang Q., Feng M., Ma X., Li H., Xie W. Gene expression profile comparison between colorectal cancer and adjacent normal tissues. Oncology Letters 2017; 14(5): 6071–6078, https://doi.org/10.3892/ol.2017.6915.
  39. Sun L.C., Qian H.X. Screening for implicated genes in colorectal cancer using whole genome gene expression profiling. Molecular Medicine Reports 2018; 17(6): 8260–8268, https://doi.org/10.3892/mmr.2018.8862.
  40. Rygaard J., Povlsen C.O. Heterotransplantation of a human malignant tumor to “Nude” mice. Acta Pathol Microbiol Scand 1969; 77: 758–760.
  41. Tentler J.J., Tan A.C., Weekes C.D., Jimeno A., Leong S., Pitts T.M., Arcaroli J.J., Messersmith W.A., Eckhardt S.G. Patient-derived tumour xenografts as models for oncology drug development. Nat Rev Clin Oncol 2012; 9(6): 338–350, https://doi.org/10.1038/nrclinonc.2012.61.
  42. Lawson D.A., Bhakta N.R., Kessenbrock K., Prummel K.D., Yu Y., Takai K., Zhou A., Eyob H., Balakrishnan S., Wang C.Y., Yaswen P., Goga A., Werb Z. Single-cell analysis reveals a stem-cell program in human metastatic breast cancer cells. Nature 2015; 526(7571): 131–135, https://doi.org/10.1038/nature15260.
  43. Xiao T., Li W., Wang X., Xu H., Yang J., Wu Q., Huang Y., Geradts J., Jiang P., Fei T., Chi D., Zang C., Liao Q., Rennhack J., Andrechek E., Li N., Detre S., Dowsett M., Jeselsohn R.M., Liu X.S., Brown M. Estrogen-regulated feedback loop limits the efficacy of estrogen receptor-targeted breast cancer therapy. Proc Natl Acad Sci U S A 2018; 115(31): 7869–7878, https://doi.org/10.1073/pnas.1722617115.
  44. Reyal F., Guyader C., Decraene C., Lucchesi C., Auger N., Assayag F., De Plater L., Gentien D., Poupon M.F., Cottu P., De Cremoux P., Gestraud P., Vincent-Salomon A., Fontaine J.J., Roman-Roman S., Delattre O., Decaudin D., Marangoni E. Molecular profiling of patient-derived breast cancer xenografts. Breast Cancer Res 2012; 14(1): R11, https://doi.org/10.1186/bcr3095.
  45. Zhao X., Liu Z., Yu L., Zhang Y., Baxter P., Voicu H., Gurusiddappa S., Luan J., Su J.M., Leung H.C., Li X.N. Global gene expression profiling confirms the molecular fidelity of primary tumor-based orthotopic xenograft mouse models of medulloblastoma. Neuro Oncol 2012; 14(5): 574–583, https://doi.org/10.1093/neuonc/nos061.
  46. Misale S., Bozic I., Tong J., Peraza-Penton A., Lallo A., Baldi F., Lin K.H., Truini M., Trusolino L., Bertotti A., Di Nicolantonio F., Nowak M.A., Zhang L., Wood K.C., Bardelli A. Vertical suppression of the EGFR pathway prevents onset of resistance in colorectal cancers. Nat Commun 2015; 6: 8305, https://doi.org/ https://doi.org/10.1038/ncomms9305.
  47. Evans K.W., Yuca E., Akcakanat A., Scott S.M., Arango N.P., Zheng X., Chen K., Tapia C., Tarco E., Eterovic A.K., Black D.M., Litton J.K., Yap T.A., Tripathy D., Mills G.B., Meric-Bernstam F. A population of heterogeneous breast cancer patient-derived xenografts demonstrate broad activity of PARP inhibitor in BRCA1/2 wild-type tumors. Clin Cancer Res 2017; 23(21): 6468–6477, https://doi.org/10.1158/1078-0432.CCR-17-0615.
  48. Topp M.D., Hartley L., Cook M., Heong V., Boehm E., McShane L., Pyman J., McNally O., Ananda S., Harrell M., Etemadmoghadam D., Galletta L., Alsop K., Mitchell G., Fox S.B., Kerr J.B., Hutt K.J., Kaufmann S.H.; Australian Ovarian Cancer Study; Swisher E.M., Bowtell D.D., Wakefield M.J., Scott C.L. Molecular correlates of platinum response in human high-grade serous ovarian cancer patient-derived xenografts. Mol Oncol 2014; 8(3): 656–668, https://doi.org/10.1016/j.molonc.2014.01.008.
  49. Nunes M., Vrignaud P., Vacher S., Richon S., Lievre A., Cacheux W., Weiswald L.B., Massonnet G., Chateau-Joubert S., Nicolas A., Dib C., Zhang W., Watters J., Bergstrom D., Roman-Roman S., Bièche I., Dangles-Marie V. Evaluating patient-derived colorectal cancer xenografts as preclinical models by comparison with patient clinical data. Cancer Res 2015; 75(8): 1560–1566, https://doi.org/10.1158/0008-5472.CAN-14-1590.
  50. George E., Kim H., Krepler C., Wenz B., Makvandi M., Tanyi J.L., Brown E., Zhang R., Brafford P., Jean S., Mach R.H., Lu Y., Mills G.B., Herlyn M., Morgan M., Zhang X., Soslow R., Drapkin R., Johnson N., Zheng Y., Cotsarelis G., Nathanson K.L., Simpkins F. A patient-derived-xenograft platform to study BRCA-deficient ovarian cancers. JCI Insight 2017; 2(1): e89760, https://doi.org/10.1172/jci.insight.89760.
  51. Hidalgo M., Bruckheimer E., Rajeshkumar N.V., Garrido-Laguna I., De Oliveira E., Rubio-Viqueira B., Strawn S., Wick M.J., Martell J., Sidransky D. A pilot clinical study of treatment guided by personalized tumorgrafts in patients with advanced cancer. Mol Cancer Ther 2011; 1(8): 1311–1316, https://doi.org/10.1158/1535-7163.MCT-11-0233.
  52. Stebbing J., Paz K., Schwartz G.K., Wexler L.H., Maki R., Pollock R.E., Morris R., Cohen R., Shankar A., Blackman G., Harding V., Vasquez D., Krell J., Zacharoulis S., Ciznadija D., Katz A., Sidransky D. Patient-derived xenografts for individualized care in advanced sarcoma. Cancer 2014; 120(13): 2006–2015, https://doi.org/10.1002/cncr.28696.
  53. Rubio-Viqueira B., Jimeno A., Cusatis G., Zhang X., Iacobuzio-Donahue C., Karikari C., Shi C., Danenberg K., Danenberg P.V., Kuramochi H., Tanaka K., Singh S., Salimi-Moosavi H., Bouraoud N., Amador M.L., Altiok S., Kulesza P., Yeo C., Messersmith W., Eshleman J., Hruban R.H., Maitra A., Hidalgo M. An in vivo platform for translational drug development in pancreatic cancer. Clin Cancer Res 2006; 12(15): 4652–4661, https://doi.org/10.1158/1078-0432.CCR-06-0113.
  54. Zhang X., Claerhout S., Prat A., Dobrolecki L.E., Petrovic I., Lai Q., Landis M.D., Wiechmann L., Schiff R., Giuliano M., Wong H., Fuqua S.W., Contreras A., Gutierrez C., Huang J., Mao S., Pavlick A.C., Froehlich A.M., Wu M.F., Tsimelzon A., Hilsenbeck S.G., Chen E.S., Zuloaga P., Shaw C.A., Rimawi M.F., Perou C.M., Mills G.B., Chang J.C., Lewis M.T. A renewable tissue resource of phenotypically stable, biologically and ethnically diverse, patient-derived human breast cancer xenograft models. Cancer Res 2013; 73(15): 4885–4897, https://doi.org/10.1158/0008-5472.CAN-12-4081.
  55. Lang H., Béraud C., Bethry A., Danilin S., Lindner V., Coquard C., Rothhut S., Massfelder T. Establishment of a large panel of patient-derived preclinical models of human renal cell carcinoma. Oncotarget 2016; 7(37): 59336–59359, https://doi.org/10.18632/oncotarget.10659.
  56. Moro M., Bertolini G., Caserini R., Borzi C., Boeri M., Fabbri A., Leone G., Gasparini P., Galeone C., Pelosi G., Roz L., Sozzi G., Pastorino U. Establishment of patient derived xenografts as functional testing of lung cancer aggressiveness. Sci Rep 2017; 7(1): 6689, https://doi.org/10.1038/s41598-017-06912-7.
  57. Park H.S., Lee J.D., Kim J.Y., Park S., Kim J.H., Han H.J., Choi Y.A., Choi A.R., Sohn J.H., Kim S.I. Establishment of chemosensitivity tests in triple-negative and BRCA-mutated breast cancer patient-derived xenograft models. PLoS One 2019; 14(12): e0225082, https://doi.org/10.1371/journal.pone.0225082.
  58. Kamiyama H., Rauenzahn S., Shim J.S., Karikari C.A., Feldmann G., Hua L., Kamiyama M., Schuler F.W., Lin M.T., Beaty R.M., Karanam B., Liang H., Mullendore M.E., Mo G., Hidalgo M., Jaffee E., Hruban R.H., Jinnah H.A., Roden R.B., Jimeno A., Liu J.O., Maitra A., Eshleman J.R. Personalized chemotherapy profiling using cancer cell lines from selectable mice. Clin Cancer Res 2013; 19(5): 1139–1146, https://doi.org/10.1158/1078-0432.CCR-12-2127.
  59. Mitra A., Mishra L., Li S. Technologies for deriving primary tumor cells for use in personalized cancer therapy. Trends Biotechnol 2013; 31(6): 347–354, https://doi.org/10.1016/j.tibtech.2013.03.006.
  60. Hidalgo M., Amant F., Biankin A.V., Budinska E., Byrne A.T., Caldas C., Clarke R.B., de Jong S., Jonkers J., Mælandsmo G.M., Roman-Roman S., Seoane J., Trusolino L., Villanueva A. Patient-derived xenograft models: an emerging platform for translational cancer research. Cancer Discov 2014; 4(9): 998–1013, https://doi.org/10.1158/2159-8290.CD-14-0001.
  61. Dangles-Marie V., Pocard M., Richon S., Weiswald L.-B., Assayag F., Saulnier P., Judde J.G., Janneau J.L., Auger N., Validire P., Dutrillaux B., Praz F., Bellet D., Poupon M.F. Establishment of human colon cancer cell lines from fresh tumors versus xenografts: comparison of success rate and cell line features. Cancer Res 2007; 67(1): 398, https://doi.org/10.1158/0008-5472.CAN-06-0594.
  62. Weiswald L.B., Richon S., Massonnet G., Guinebretière J.M., Vacher S., Laurendeau I., Cottu P., Marangoni E., Nemati F., Validire P., Bellet D., Bièche I., Dangles-Marie V. A short-term colorectal cancer sphere culture as a relevant tool for human cancer biology investigation. Br J Cancer 2013; 108(8): 1720–1731, https://doi.org/10.1038/bjc.2013.132.
  63. Senthebane D.A., Jonker T., Rowe A., Thomford N.E., Munro D., Dandara C., Wonkam A., Govender D., Calder B., Soares N.C., Blackburn J.M., Iqbal P.M., Dzobo K. The role of tumor microenvironment in chemoresistance: 3D extracellular matrices as accomplices. Int J Mol Sci 2018; 19(10): 2861, https://doi.org/10.3390/ijms19102861.
  64. Kobayashi H., Tanisaka K., Kondo N., Mito Y., Koezuka M., Yokouchi H., Higashiyama M., Kodama K., Doi O., Yamada M. Development of new in vitro chemosensitivity test using collagen gel droplet embedded culture and its clinical usefulness. Gan To Kagaku Ryoho 1995; 22(13): 1933–1939.
  65. Tanigawa N., Yamaue H., Ohyama S., Sakuramoto S., Inada T., Kodera Y., Kitagawa Y., Omura K., Terashima M., Sakata Y., Nashimoto A., Yamaguchi T., Chin K., Nomura E., Lee S.W., Takeuchi M., Fujii M., Nakajima T. Exploratory phase II trial in a multicenter setting to evaluate the clinical value of a chemosensitivity test in patients with gastric cancer (JACCRO-GC 04, Kubota memorial trial). Gastric Cancer 2016; 19(2): 350–360, https://doi.org/10.1007/s10120-015-0506-z.
  66. Sounni N.E., Noel A. Targeting the tumor microenvironment for cancer therapy. Clin Chem 2013; 59(1): 85–89, https://doi.org/10.3390/ijms20040840.
  67. Pauli C., Hopkins B.D., Prandi D., Shaw R., Fedrizzi T., Sboner A., Sailer V., Augello M., Puca L., Rosati R., McNary T.J., Churakova Y., Cheung C., Triscott J., Pisapia D., Rao R., Mosquera J.M., Robinson B., Faltas B.M., Emerling B.E., Gadi V.K., Bernard B., Elemento O., Beltran H., Demichelis F., Kemp C.J., Grandori C., Cantley L.C., Rubin M.A. Personalized in vitro and in vivo cancer models to guide precision medicine. Cancer Discov 2017; 7(5): 462–477, https://doi.org/10.1158/2159-8290.CD-16-1154.
  68. Clevers H. Modeling development and disease with organoids. Cell 2016; 165(7): 1586–1597, https://doi.org/10.1016/j.cell.2016.05.082.
  69. van de Wetering M., Francies H.E., Francis J.M., Bounova G., Iorio F., Pronk A., van Houdt W., van Gorp J., Taylor-Weiner A., Kester L., McLaren-Douglas A., Blokker J., Jaksani S., Bartfeld S., Volckman R., van Sluis P., Li V.S., Seepo S., Sekhar Pedamallu C., Cibulskis K., Carter S.L., McKenna A., Lawrence M.S., Lichtenstein L., Stewart C., Koster J., Versteeg R., van Oudenaarden A., Saez-Rodriguez J., Vries R.G., Getz G., Wessels L., Stratton M.R., McDermott U., Meyerson M., Garnett M.J., Clevers H. Prospective derivation of a living organoid biobank of colorectal cancer patients. Cell 2015; 161(4): 933–945, https://doi.org/10.1016/j.cell.2015.03.053.
  70. Sato T., Stange D.E., Ferrante M., Vries R.G., Van Es J.H., Van den Brink S., Van Houdt W.J., Pronk A., Van Gorp J., Siersema P.D., Clevers H. Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma, and Barrett’s epithelium. Gastroenterology 2011; 141(5): 1762–1772, https://doi.org/10.1053/j.gastro.2011.07.050.
  71. Astolfi M., Péant B., Lateef M.A., Rousset N., Kendall-Dupont J., Carmona E., Monet F., Saad F., Provencher D., Mes-Masson A.M., Gervais T. Micro-dissected tumor tissues on chip: an ex vivo method for drug testing and personalized therapy. Lab Chip 2016; 16(2): 312–325, https://doi.org/10.1039/c5lc01108f.
  72. Dohmen A.J.C., Sanders J., Canisius S., Jordanova E.S., Aalbersberg E.A., van den Brekel M.W.M., Neefjes J., Zuur C.L. Sponge-supported cultures of primary head and neck tumors for an optimized preclinical model. Oncotarget 2018; 9(38): 25034–25047, https://doi.org/10.18632/oncotarget.25244.
  73. Naipal K.A., Verkaik N.S., Sánchez H., van Deurzen H.M., den Bakker M.A., Hoeijmakers J.H.J., Kanaar R., Vreeswijk M.P., Jager A., van Gent D.C. Tumor slice culture system to assess drug response of primary breast cancer. BMC Cancer 2016; 16: 78, https://doi.org/10.1186/s12885-016-2119-2.
  74. Meijer T.G., Naipal C.A.T., Jager A., van Gent D.C. Ex vivo tumor culture systems for functional drug testing and therapy response prediction. Future Sci OA 2017; 3(2): FSO190, https://doi.org/10.4155/fsoa-2017-0003.
  75. Roelants C., Pillet C., Franquet Q., Sarrazin C., Peilleron N., Giacosa S., Guyon L., Fontanell A., Fiard G., Long J.A., Descotes J.L., Cochet C., Filhol O. Ex-vivo treatment of tumor tissue slices as a predictive preclinical method to evaluate targeted therapies for patients with renal carcinoma. Cancers (Basel) 2020; 12(1): 232, https://doi.org/10.3390/cancers12010232.
  76. Unger F.T., Bentz S., Krger J., Rosenbrock C., Schaller J., Pursche K., Schaller A., Juhl H., David K.A. Precision cut cancer tissue slices in anti-cancer drug testing. Mol Pathophysiol 2015; 4: 108–121, https://doi.org/10.5455/jmp.20151023055556.
  77. Roife D., Dai B., Kang Y., Perez M.V.R., Pratt M., Li X., Fleming J.B. Ex vivo testing of patient-derived xenografts mirrors the clinical outcome of patients with pancreatic ductal adenocarcinoma. Clin Cancer Res 2016; 22(24): 6021–6030, https://doi.org/10.1158/1078-0432.CCR-15-2936.
  78. Zhang Y., Huang W., Yang Q., Zhang H., Zhu X., Zeng M., Zhou X., Wang Z., Li W., Jing H., Zhang X., Shi Y., Hu H., Yan H., Li Z., Zhai B. Cryopreserved biopsy tissues of rectal cancer liver metastasis for assessment of anticancer drug response in vitro and in vivo. Oncol Rep 2020; 43(2): 405–414, https://doi.org/10.3892/or.2019.7450.
  79. Valente K.P., Khetani S., Kolahchi A.R., Sanati-Nezhad A., Suleman A., Akbari M. Microfluidic technologies for anticancer drug studies. Drug Discov Today 2017; 22(11): 1654–1670, https://doi.org/10.1016/j.drudis.2017.06.010.
  80. Novak R., Didier M., Calamari E., Ng C.F., Choe Y., Clauson S.L., Nestor B.A., Puerta J., Fleming R., Firoozinezhad S.J., Ingber D.E. Scalable fabrication of stretchable, dual channel, microfluidic organ chips. J Vis Exp 2018; 140: 58151, https://doi.org/10.3791/58151.
  81. Lee I.C. Cancer-on-a-chip for drug screening. Curr Pharm Des 2018; 24(45): 5407–5418, https://doi.org/10.2174/1381612825666190206235233.
  82. Kumar V., Varghese S. Ex vivo tumor-on-a-chip platforms to study intercellular interactions within the tumor microenvironment. Adv Healthc Mater 2019; 8(4): e1801198, https://doi.org/10.1002/adhm.201801198.
  83. Shim S., Belanger M.C., Harris A.R., Munson J.M., Pompano R.R. Two-way communication between ex vivo tissues on a microfluidic chip: application to tumor-lymph node interaction. Lab Chip 2019; 19(6): 1013–1026, https://doi.org/10.1039/c8lc00957k.
  84. Barrile R., van der Meer A.D., Park H., Fraser J.P., Simic D., Teng F., Conegliano D., Nguyen J., Jain A., Zhou M., Karalis K., Ingber D.E., Hamilton G.A., Otieno M.A. Organ-on-chip recapitulates thrombosis induced by an anti-CD154 monoclonal antibody: translational potential of advanced microengineered systems. Clin Pharmacol Ther 2018; 104(6): 1240–1248, https://doi.org/10.1002/cpt.1054.
  85. Dhiman N., Kingshott P., Sumer H., Sharma C.S., Rath S.N. On-chip anticancer drug screening — recent progress in microfluidic platforms to address challenges in chemotherapy. Biosens Bioelectron 2019; 137: 236–254, https://doi.org/10.1016/j.bios.2019.02.070.
  86. Hassell B.A., Goyal G., Lee E., Sontheimer-Phelps A., Levy O., Chen C.S., Ingber D.E. Human organ chip models recapitulate orthotopic lung cancer growth, therapeutic responses, and tumor dormancy in vitro. Cell Rep 2017; 21(2): 508–516, https://doi.org/10.1016/j.celrep.2017.09.043.
  87. Choi Y., Hyun E., Seo J., Blundell C., Kim H.C., Lee E., Lee S.H., Moon A., Moon W.K., Huh D. A microengineered pathophysiological model of early-stage breast cancer. Lab Chip 2015; 15(16): 3350–3357, https://doi.org/10.1039/c5lc00514k.
  88. Shah A.T., Demory Beckler M., Walsh A.J., Jones W.P., Pohlmann P.R., Skala M.C. Optical metabolic imaging of treatment response in human head and neck squamous cell carcinoma. PLoS One 2014; 9(3): e90746, https://doi.org/10.1371/journal.pone.0090746.
  89. Huang S., Heikal A.A., Webb W.W. Two-photon fluorescence spectroscopy and microscopy of NAD(P)H and flavoprotein. Biophys J 2002; 82(5): 2811–2825, https://doi.org/10.1016/S0006-3495(02)75621-X.
  90. Lukina M.M., Shirmanova M.V., Sergeeva T.F., Zagaynova Е.V. Metabolical imaging for the study of oncological processes (review). Sovremennye tehnologii v medicine 2016; 8(4): 113–121, https://doi.org/10.17691/stm2016.8.4.16.
  91. Lukina M.M., Dudenkova V.V., Ignatova N.I., Druzhkova I.N., Shimolina L.E., Zagaynova E.V., Shirmanova M.V. Metabolic cofactors NAD(P)H and FAD as potential indicators of cancer cell response to chemotherapy with paclitaxel. Biochim Biophys Acta Gen Subj 2018; 1862(8): 1693–1700, https://doi.org/10.1016/j.bbagen.2018.04.021.
  92. Lukina M.M., Dudenkova V.V., Shimolina L.E., Snopova L.B., Zagaynova E.V., Shirmanova M.V. In vivo metabolic and SHGi for monitoring of tumor response to chemotherapy. Cytometry A 2019; 95(1): 47–55, https://doi.org/10.1002/cyto.a.23607.
  93. Alam S.R., Wallrabe H., Svindrych Z., Chaudhary A.K., Christopher K.G., Chandra D., Periasamy A. Investigation of mitochondrial metabolic response to doxorubicin in prostate cancer cells: an NADH, FAD and tryptophan FLIM assay. Sci Rep 2017; 7(1): 10451, https://doi.org/10.1038/s41598-017-10856-3.
  94. Sharick J., Walsh C.M., Sprackling C.M., Pasch C.A., Pham D.L., Esbona K., Choudhary A., Garcia-Valera R., Burkard M.E., McGregor S.M., Matkowskyj K.A., Parikh A.A., Meszoely I.M., Kelley M.C., Tsai S., Deming D.A., Skala M.C. Metabolic heterogeneity in patient tumor-derived organoids by primary site and drug treatment. Front Oncol 2020; 10: 553, https://doi.org/10.3389/fonc.2020.00553.
  95. Cree I.A. Chemosensitivity and chemoresistance testing in ovarian cancer. Curr Opin Obstet Gynecol 2009; 21(1): 39–43, https://doi.org/10.1097/GCO.0b013e32832210ff.
  96. Bosserman L.D., Rajurkar S.P., Rogers K., Davidson D.C., Chernick M., Hallquist A., Malouf D., Presant C.A. Correlation of drug-induced apoptosis assay results with oncologist treatment decisions and patient response and survival. Cancer 2012; 118(19): 4877–4883, https://doi.org/10.1002/cncr.27444.
  97. Jamal B.T., Grillone G.A., Jalisi S. Chemoresponse assay in head and neck cancer patients: a three-year follow up. J Clin Diagn Res 2017; 11(5): XC01–XC03, https://doi.org/10.7860/JCDR/2017/24802.9816.
Druzhkova I.N., Shirmanova M.V., Kuznetsova D.S., Lukina М.М., Zagaynova Е.V. Modern Approaches to Testing Drug Sensitivity of Patients’ Tumors (Review). Sovremennye tehnologii v medicine 2020; 12(4): 91, https://doi.org/10.17691/stm2020.12.4.11


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