From 3D Cell Culture System to Personalized Medicine in Osteosarcoma

Osteosarcoma is the most common primary malignant tumor of bone, which occurs most often in children and young adults between the ages of 10 and 20 during a growth spurt, while with a second peak in incidence in those over the age of 50 [1,2]. Localized osteosarcoma presenting in up to 80% of patients is amenable to cure, however, the outcome for patients with metastases, commonly in lung and other bones, is dismal unless surgery of metastases is feasible [3,4]. Although the surgical resection of the primary tumor is the mainstay treatment for osteosarcoma, the overall survival of patients treated with surgery alone remains low [5]. Neoadjuvant and adjuvant chemotherapies (cisplatin, doxorubicin and ifosfamide, or high-dose methotrexate) incorporated into many treatment protocols followed by surgical resection of disease triple the 5-year survival rate to 65-70% in patients with localized tumor [6-9]. However, due to the undetectable microscopic metastases at the time of presentation, up to 35% of these patients who have been successfully resected, eventually develop metastases [10,11]. Finally, the long-term outcomes for patients with metastases or relapsed osteosarcoma remained unfortunately unchanged over the past 30 years, with an overall 5-year survival rate of ~ 20% [12,13].

Osteosarcoma is not a common cancer with a worldwide incidence of 3.4 cases per million people per year [5,14]. Thus, the rarity of the disease itself is one of the obstacles to develop and conduct large scale clinical trials for osteosarcoma with novel therapeutic agents despite international collaborative efforts, both in children and adult patients. During the last two decades, intensive genome-wide genetic and epigenetic studies have been performed in osteosarcoma to understand the mechanisms for progression and metastasis [7,8,15]. Potential therapeutic targets including tumor suppressors, oncogenes, as well as histone demethylase and non-coding RNAs have been reported as their expressions are dysregulated in tumor tissues or cell lines [16-25]. However, few of these targets have been validated for phase I clinical trials due to the highly complicated genetic and epigenetic heterogeneity in osteosarcoma. Therefore, a better pre-clinical drug screening system is urgently required.

From 2D cell culture models to 3D cell culture models

Since last several decades, in vitro cell-based assays have been widely employed in the drug discovery process, because they are simple, fast, versatile, easily reproducible and cost-effective as compared to animal models. Most of these cell culture-based drug screening assays are 2D monolayers of cells grown in plastic plates adapted for cell attachment and growth. Although these 2D cell models are still effectively used in some drug pre-clinical screening, more and more evidence reveal that they are not good models for certain diseases such as cancer, because lack of tissue-specific architecture, they cannot reflect the complex microenvironment for cells encountered in tumor [26,27].

Carcinogenesis is a complex and dynamic process including initiation, progression, and metastasis that also involves the tumor microenvironment (TME). The TME is composed of extracellular matrix (ECM), stromal cells (such as fibroblasts, myofibroblasts, neuroendocrine cells, adipose cells and immune-inflammatory cells), and lymphatic vascular networks [28,29]. It is reported to play an important role to direct functional differentiation of organs and dictate proper tissue function and structure [30]. Thus, to elucidate the TME becomes a critical key to understand tumor progression and metastasis and to screen anti-cancer agents. For that purpose, 3D cell culture models have been developed since the last decade and have been demonstrated to model the dynamic cellcell and cell-ECM interactions, and mimic the natural TME [31-33].

3D osteosarcoma cell culture systems

Several different methods have been reported to successfully form 3D osteosarcoma cell culture [34]. In general, in vitro 3D osteosarcoma cell cultures are formed with or without special scaffold.

The main purpose of using biocompatible scaffolds are to help cell adhesion without modification [35]. The natural scaffolds used in 3D cell culture systems are typical components of ECM such as collagen, elastin, laminin, fibrin, gelatin, matrigel or hydrogels [36]. These biodegradable materials are derived from natural sources, like chitosan, silk, alginate, hyaluronic acid, heparin and chondroitin sulfate, and can promote cell interaction properties, adhesion and signaling. In addition, a synthetic scaffold, polyethylene glycol diacrylate (PEGDA) hydrogel, has also been used to encapsulate tumor cells [37].

As for scaffold-free systems, different techniques have been developed to favor spontaneous cell aggregation. In order to prevent cell monolayer formation to adhesive surface, liquid overlay technique has been used to form cell spheroids with special low and ultralow binding plates or traditional cell culture plates precoated with either agar/agarose or poly-HEMA [38-43]. Another most used and suitable system is called “hanging drop” technique. The conventional “hanging drop” technique contains two steps: droplets of fluid containing suspended cells are deposited on the non-adhesive lid of cell plates, then the lid is inverted over the plate [44]. With the gravity, the cells precipitate to the bottom of the drop and form the spheroid in each drop. More recently, commercialized Gravity Plus 3D culture plates make the “hanging drop” easier and more reliable and convenient, permitting long term analysis of 3D cultures following different treatment [45,46].

3D cell culture, a path to personalized treatment in osteosarcoma

Current in vitro 3D cell culture techniques indeed reveal physio pathological state of TMEs closer to the reality, and the data obtained are comparable to the in vivo models. Several reports have demonstrated that a higher chemoresistance was observed in 3D osteosarcoma cell spheroids as compared to the conventional 2D monolayer cultures, which is due to a reduction in drug permeability to the much more densified core of osteosarcoma spheroids, and is also associated with the TME which plays a physical barrier function [38,45,47]. These observations are highly consistent with the development of chemoresistance in osteosarcoma patients upon chemotherapy [48], which indicate that the osteosarcoma spheroids could effectively be used to evaluate the sensitivity of novel therapeutic targets to current chemotherapy.

Although prominent results have been obtained with spheroid models, they are mainly focused on the interaction between cancer cells and the ECM which could not completely reflect the complexity and heterogeneity of osteosarcoma TME. Importantly, one in vitro 3D vascularized tumor model has been established by combining the 3D osteosarcoma spheroids with the 2D endothelial cells and successfully created a vascular network [46]. Osteosarcoma is considered as a highly vascularized bone tumor with early metastatic dissemination through intra-tumoral blood vessels [49].

This promising vascularized spheroid model could be useful to screen novel targets against tumor vascularization and metastasis.

Inflammatory microenvironment could also promote the development of tumors via promoting angiogenesis and metastasis, subverting adaptive immune responses, and altering responses to hormones and chemotherapeutic agents [50,51]. The expression of several pro-inflammatory cytokines or chemokines have been shown to be increased in 3D osteosarcoma spheroids [41,46,52-55]. However, no immune-inflammatory cells have been yet introduced to the present 3D osteosarcoma spheroid models. Therefore, more complex 3D osteosarcoma cell culture models, including tumor cells, fibroblasts, endothelial and immune-inflammatory cells, should be developed to simulate the physio pathological microenvironment in osteosarcoma.

With the exponentially increased genomic information in the last decade and the new diagnostic and research approaches, such as 3D cell culture models, the term personalized medicine is now used to tailor therapy with the best response and highest safety margin to ensure better patient outcome (Figure 1) [56]. Although challenges are still presented for personalized medicine in osteosarcoma, today’s 3D cell culture models are the first step towards the automatic, high throughput and standardized 3D spheroid or organoid platforms for pre-clinical drug screening systems dedicating to personalized medicine.

Figure 1:Global approach from 3D cell culture system to personalized medicine in Osteosarcoma. Strategy: After Incisional or liquid biopsy, cells are cultivated in 3D well-organized spheroids (organoids) and then several chemotherapy drugs can be screened. The best candidate will be selected to treat the patient.

The authors would like to thank “La Fondation des gueules cassées” for the financial support.

1. Mirabello L, Troisi RJ, Savage SA (2009) International osteosarcoma incidence patterns in children and adolescents, middle ages and elderly persons. Int J Cancer 125(1): 229-234.
2. Botter SM, Neri D, Fuchs B (2014) Recent advances in osteosarcoma. Curr Opin Pharmacol 16: 15-23.
3. Hegyi M, Semsei AF, Jakab Z, Antal I, Kiss J, et al. (2011) Good prognosis of localized osteosarcoma in young patients treated with limb-salvage surgery and chemotherapy. Pediatr Blood Cancer 57(3): 415-422.
4. Longhi A, Errani C, De Paolis M, Mercuri M, Bacci G (2006) Primary bone osteosarcoma in the pediatric age: state of the art. Cancer Treat Rev 32(6): 423-436.
5. Geller DS, Gorlick R (2010) Osteosarcoma: a review of diagnosis, management and treatment strategies. Clin Adv Hematol Oncol 8(10): 705-718.
6. Jaffe N, Frei E, Traggis D, Bishop Y (1974) Adjuvant methotrexate and citrovorum-factor treatment of osteogenic sarcoma. N Engl J Med 291(19): 994-997.
7. Kansara M, Teng MW, Smyth MJ, Thomas DM (2014) Translational biology of osteosarcoma. Nat Rev Cancer 14(11): 722-735.
8. Morrow JJ, Khanna C (2015) Osteosarcoma genetics and epigenetics: emerging biology and candidate therapies. Crit Rev Oncog 20(3-4): 173- 197.
9. Collins M, Wilhelm M, Conyers R, Herschtal A, Whelan J, et al. (2013) Benefits and adverse events in younger versus older patients receiving neoadjuvant chemotherapy for osteosarcoma: findings from a metaanalysis. J Clin Oncol 31(18): 2303-2312.
10. Bielack SS, Kempf-Bielack B, Delling G, Exner GU, Flege S, et al. (2002) Prognostic factors in high-grade osteosarcoma of the extremities or trunk: An analysis of 1,702 patients treated on neoadjuvant cooperative osteosarcoma study group protocols. J Clin Oncol 20(3): 776-790.
11. Bielack B, Bielack SS, Jürgens H, Branscheid D, Berdel WE, et al. (2005) Osteosarcoma relapse after combined modality therapy: an analysis of unselected patients in the Cooperative Osteosarcoma Study Group (COSS). J Clin Oncol 23(3): 559-568.
12. Link MP, Goorin AM, Miser AW, Green AA, Pratt CB, et al. (1986) The effect of adjuvant chemotherapy on relapse-free survival in patients with osteosarcoma of the extremity. N Engl J Med 314(25): 1600-1606.
13. Meyers PA, Healey JH, Chou AJ, Wexler LH, Merola PR, et al. (2011) Addition of pamidronate to chemotherapy for the treatment of osteosarcoma. Cancer 117(8): 1736-1744.
14. Misaghi A, Goldin A, Awad M, Kulidjian AA (2018) Osteosarcoma: a comprehensive review. SICOT J 4: 12.
15. Bishop MW, Janeway KA, Gorlick R (2016) Future directions in the treatment of osteosarcoma. Curr Opin Pediatr 28(1): 26-33.
16. Miller CW, Aslo A, Won A, Tan M, Lampkin B, et al. (1996) Alterations of the p53, Rb and MDM2 genes in osteosarcoma. J Cancer Res Clin Oncol 122(9): 559-565.
17. Benassi MS, Molendini L, Gamberi G, Ragazzini P, Sollazzo MR, et al. (1999) Alteration of pRb/p16/cdk4 regulation in human osteosarcoma. Int J Cancer 84(5): 489-493.
18. Smida J, Baumhoer D, Rosemann M, Walch A, Bielack S, et al. (2010) Genomic alterations and allelic imbalances are strong prognostic predictors in osteosarcoma. Clin Cancer Res 16(16): 4256-4267.
19. Pasic I, Shlien A, Durbin AD, Stavropoulos DJ, Baskin B, et al. (2010) Recurrent focal copy-number changes and loss of heterozygosity implicate two noncoding RNAs and one tumor suppressor gene at chromosome 3q13.31 in osteosarcoma. Cancer Res 70(1): 160-171.
20. van Dartel M, Cornelissen PW, Redeker S, Tarkkanen M, Knuutila S, et al. (2002) Amplification of 17p11.2 approximately p12, including PMP22, TOP3A, and MAPK7, in high-grade osteosarcoma. Cancer Genet Cytogenet 139(2): 91-96.
21. Li B, Ye Z (2014) Epigenetic alterations in osteosarcoma: promising targets. Mol Biol Rep 41(5): 3303-3315.
22. Oh JH, Kim HS, Kim HH, Kim WH, Lee SH (2006) Aberrant methylation of p14ARF gene correlates with poor survival in osteosarcoma. Clin Orthop Relat Res 442: 216-222.
23. Bennani-Baiti IM, MachadoI, Llombart BA, Kovar H (2012) Lysinespecific demethylase 1 (LSD1/KDM1A/AOF2/BHC110) is expressed and is an epigenetic drug target in chondrosarcoma, Ewing’s sarcoma, osteosarcoma, and rhabdomyosarcoma. Hum Pathol 43(8): 1300-1307.
24. Li JP, Liu LH, Li J, Chen Y, Jiang XW, et al. (2013) Microarray expression profile of long noncoding RNAs in human osteosarcoma. Biochem Biophys Res Commun 433(2): 200-206.
25. Kobayashi E, Hornicek FJ, Duan Z (2012) MicroRNA involvement in osteosarcoma. Sarcoma.
26. Cukierman E, Pankov R, Stevens DR, Yamada KM (2001) Taking cellmatrix adhesions to the third dimension. Science 294(5547): 1708- 1712.
27. Imamura Y, Mukohara T, Shimono Y, Funakoshi Y, Chayahara N, et al. (2015) Comparison of 2D- and 3D-culture models as drug-testing platforms in breast cancer. Oncol Rep 33(4): 1837-1843.
28. Wang M, Zhao J, Zhang L, Wei F, Lian Y, et al. (2017) Role of tumor microenvironment in tumorigenesis. J Cancer 8(5): 761-773.
29. Chen F, Zhuang X, Lin L, Yu P, Wang Y, et al. (2015) New horizons in tumor microenvironment biology: challenges and opportunities. BMC Med 13: 45.
30. Mroue R, Bissell MJ (2013) Three-dimensional cultures of mouse mammary epithelial cells. Methods Mol Biol 945: 221-250.
31. Lovitt CJ, Shelper TB, Avery VM (2014) Advanced cell culture techniques for cancer drug discovery. Biology (Basel) 3(2): 345-367.
32. Weigelt B, Ghajar CM, Bissell MJ (2014) The need for complex 3D culture models to unravel novel pathways and identify accurate biomarkers in breast cancer. Adv Drug Deliv Rev 69-70: 42-51.
33. Monteiro CF, Custódio CA, Mano JF (2019) Three-dimensional osteosarcoma models for advancing drug discovery and development. Advanced Therapeutics 2(3): 1800108.
34. De Luca A, Raimondi L, Salamanna F, Carina V, Costa V, et al. (2018) Relevance of 3d culture systems to study osteosarcoma environment. J Exp Clin Cancer Res 37(1): 2.
35. Caliari SR, Burdick JA (2016) A practical guide to hydrogels for cell culture. Nat Methods 13(5): 405-414.
36. Brigo L, Urciuolo A, Giulitti S, Della Giustina G, Tromayer M, et al. (2017) 3D high-resolution two-photon crosslinked hydrogel structures for biological studies. Acta Biomater 55: 373-384.
37. Jabbari E, Sarvestani SK, Daneshian L, Moeinzadeh S (2015) Optimum 3D matrix stiffness for maintenance of cancer stem cells is dependent on tissue origin of cancer cells. PLoS ONE 10(7): e0132377.
38. Arai K, Sakamoto R, Kubota D, Kondo T (2013) Proteomic approach toward molecular backgrounds of drug resistance of osteosarcoma cells in spheroid culture system. Proteomics 13(15): 2351-2360.
39. Rainusso N, Man TK, Lau CC, Hicks J, Shen JJ, et al. (2011) Identification and gene expression profiling of tumor-initiating cells isolated from human osteosarcoma cell lines in an orthotopic mouse model. Cancer Biol Ther 12(4): 278-287.
40. Guo X, Yu L, Zhang Z, Dai G, Gao T, et al. (2017) miR-335 negatively regulates osteosarcoma stem cell-like properties by targeting POU5F1. Cancer Cell Int 17: 29.
41. Pang LY, Gatenby EL, Kamida A, Whitelaw BA, Hupp TR, et al. (2014) Global gene expression analysis of canine osteosarcoma stem cells reveal a novel role for COX-2 in tumour initiation. PLoS ONE 9(1): e83144.
42. Martins SR, Lopes ÁO, do Carmo A, Paiva AA, Simões PC, et al. (2012) Therapeutic implications of an enriched cancer stem-like cell population in a human osteosarcoma cell line. BMC Cancer 12:139.
43. Charoen KM, Fallica B, Colson YL, Zaman MH, Grinstaff MW (2014) Embedded multicellular spheroids as a biomimetic 3D cancer model for evaluating drug and drug-device combinations. Biomaterials 35(7): 2264-2271.
44. Foty R (2011) A Simple hanging drop cell culture protocol for generation of 3D spheroids. J Vis Exp (51).
45. Rimann M, Laternser S, Gvozdenovic A, Muff R, Fuchs B, et al. (2014) An in vitro osteosarcoma 3D microtissue model for drug development. J Biotechnol 189: 129-135.
46. Chaddad H, Kuchler-Bopp S, Fuhrmann G, Gegout H, Ubeaud-Sequier G, et al. (2017) Combining 2D angiogenesis and 3D osteosarcoma microtissues to improve vascularization. Exp Cell Res 360(2): 138-145.
47. Baek N, Seo OW, Lee J, Hulme J, An SSA (2016) Real-time monitoring of cisplatin cytotoxicity on three-dimensional spheroid tumor cells. Drug Des Devel Ther 10: 2155-2165.
48. He H, Ni J, Huang J (2014) Molecular mechanisms of chemoresistance in osteosarcoma (Review). Oncol Lett 7(5): 1352-1362.
49. Kunz P, Fellenberg J, Moskovszky L, Sápi Z, Krenacs T, et al. (2015) Improved survival in osteosarcoma patients with atypical low vascularization. Ann Surg Oncol 22(2): 489-496.
50. Mantovani A, Allavena P, Sica A, Balkwill F (2008) Cancer-related inflammation. Nature 454(7203): 436-444.
51. Liu B, Huang Y, Sun Y, Zhang J, Yao Y, et al. (2016) Prognostic value of inflammation-based scores in patients with osteosarcoma. Scientific Reports 6: 39862
52. Duan DP, Dang XQ, Wang KZ, Wang YP, Zhang H, et al. (2012) The cyclooxygenase-2 inhibitor NS-398 inhibits proliferation and induces apoptosis in human osteosarcoma cells via downregulation of the survivin pathway. Oncol Rep 28(5): 1693-1700.
53. Nishimura A, Akeda K, Matsubara T, Kusuzaki K, Matsumine A, et al. (2011) Transfection of NF-κB decoy oligodeoxynucleotide suppresses pulmonary metastasis by murine osteosarcoma. Cancer Gene Ther 18(4): 250-259.
54. Tan PHS, Aung KZ, Toh SL, Goh JCH, Nathan SS (2011) Threedimensional porous silk tumor constructs in the approximation of in vivo osteosarcoma physiology. Biomaterials 32(26): 6131-6137.
55. Tan PHS, Chia SS, Toh SL, Goh JCH, Nathan SS (2014) The dominant role of IL-8 as an angiogenic driver in a three-dimensional physiological tumor construct for drug testing. Tissue Eng Part A 20(11-12): 1758- 1766.
56. Vogenberg FR, Barash CI, Pursel M (2010) Personalized medicine: part 1: evolution and development into theranostics. Pharmacy and Therapeutics 35(10): 560-576.