The strategy and clinical relevance of in vitro models of MAP resistance in osteosarcoma: a systematic review

Abstract

Over the last 40 years osteosarcoma (OS) survival has stagnated with patients commonly resistant to neoadjuvant MAP chemotherapy involving high dose methotrexate, adriamycin (doxorubicin) and platinum (cisplatin). Due to the rarity of OS, the generation of relevant cell models as tools for drug discovery is paramount to tackling this issue. Four literature databases were systematically searched using pre-determined search terms to identify MAP resistant OS cell lines and patients. Drug exposure strategies used to develop cell models of resistance and the impact of these on the differential expression of resistance associated genes, proteins and non-coding RNAs are reported. A comparison to clinical studies in relation to chemotherapy response, relapse and metastasis was then made. The search retrieved 1891 papers of which 52 were relevant. Commonly, cell lines were derived from Caucasian patients with epithelial or fibroblastic subtypes. The strategy for model development varied with most opting for continuous over pulsed chemotherapy exposure. A diverse resistance level was observed between models (2.2–338 fold) with 63% of models exceeding clinically reported resistance levels which may affect the expression of chemoresistance factors. In vitro p-glycoprotein overexpression is a key resistance mechanism; however, from the available literature to date this does not translate to innate resistance in patients. The selection of models with a lower fold resistance may better reflect the clinical situation. A comparison of standardised strategies in models and variants should be performed to determine their impact on resistance markers. Clinical studies are required to determine the impact of resistance markers identified in vitro in poor responders to MAP treatment, specifically with respect to innate and acquired resistance. A shift from seeking disputed and undruggable mechanisms to clinically relevant resistance mechanisms may identify key resistance markers that can be targeted for patient benefit after a 40-year wait.

Augmented drug resistance of osteosarcoma cells within decalcified bone matrix scaffold: The role of glutamine metabolism

“…The ABC transporters‐related pathway was also profoundly enriched in HOS‐dBMS, indicating the enhanced drug resistance by 3D environmental cues (Figure 2G). By the heat map analysis (Figure 2H), we found that the expression of OS prognosis‐related biomarkers 15 including Tp53, Tnfrsf1b, Gnl3l, Sox9, Stat3, Igf2r and Igfbpl1 was upregulated, and Ass1 and Irf7 was downregulated, in HOS‐dBMS. Of these, Tp53 16 and IGF‐related receptors (Igf2r and Igfbpl1) 17 were indicative of high metastatic risk.…”

Targeting strategies for bone diseases: signaling pathways and clinical studies

“…Over the past 40 years, the survival of osteosarcoma has stagnated due to a common resistance to neoadjuvant MAP (methotrexate, adriamycin, and platinum) chemotherapy, and increasing genomic and functional studies of osteosarcoma have emerged, expecting to exploit new drug targets. 225 Among them, tumor-suppressor genes such as p53 (TP53), 226 retinoblastoma (RB), 227 PTEN 228 et al, were found to be the significant responsible genes in osteosarcoma genesis and its resistance, with recurrent somatic mutations and copy number alterations. Unfortunately, no therapies targeting these genes have been successfully established in the clinic for osteosarcoma thus far.…”

Cancer Drug Resistance: Targeting Proliferation or Programmed Cell Death

“…Importantly, the first question which arises for researchers is the choice of the most suitable model for the development of resistance. In general, there are two known in vitro alternatives: (1) the short treatment of cancer cells with low concentrations of a drug followed by a drug-free interval (pulse-selection method); and (2) the long-term (up to 6 months) incubation of tumor cells with high doses of anticancer agents [ 13 , 14 ]. Both models have their own characteristics.…”

“…Thus, this approach is considered to be a clinically relevant model. In this case, based on a comparison of IC50 values, an increase in resistance to anticancer agents is not too high (1.5–5-fold) [ 14 , 15 , 16 , 17 ]. Importantly, these data are in good consistency with resistant index for cancer cells derived from patients [ 13 ].…”

“…However, this approach does not correspond to the conditions when patients undergo anticancer therapy and may lead to artificial results being obtained. Nevertheless, both approaches are widely used in different investigations [ 11 , 14 , 15 , 18 , 19 ]. At the same time, despite the huge number of studies devoted to this topic, there is still a lack of understanding regarding which set of methods would allow the most complete information to be obtained about the mechanisms of resistance development [ 13 ].…”