In recent years, three-dimensional (3D) in vitro cell culture models have earned great attention, especiallyin the field of human cancer disease modelling research as they provide a promising alternative towardsthe conventional two-dimensional (2D) monolayer culture of cells with improved tissue organization. In2D cell culture systems, the complexity of cells on a planar surface does not accurately reflects the invivo cellular microenvironment. Cells propagated in 3D cell culture model, on the other hand, exhibitphysiologically relevant cell-to-cell interactions and cell-to-extracellular matrix (ECM) interactions,important in maintaining a normal homeostasis and specificity of tissues. This review gives an overviewon 2D models and their limitations, followed by 3D cell culture models, their advantages, drawbacks andchallenges in present perspectives. The review also highlights the dissimilarities of 2D and 3D modelsand the applicability of 3D models in current cancer research.

Background: The PLASMIC score is a convenient tool for predicting ADAMTS13 activity of ＜10%.Lactate dehydrogenase (LDH) is widely used as a marker of haemolysis in thrombotic thrombocytopenic purpura (TTP) monitoring, and could be used as a replacement marker for lysis. We aimed to validate the PLASMIC score in a multi-centre Asia Pacific region, and to explore whether LDH could be used as a replacement marker for lysis. Methods: Records of patients with thrombotic microangiopathy (TMA) were reviewed. Patients’ ADAMTS13 activity levels were obtained, along with clinical/laboratory findings relevant to the PLASMIC score. Both PLASMIC scores and PLASMIC-LDH scores, in which LDH replaced traditional lysis markers, were calculated. We generated a receiver operator characteristics (ROC) curve and compared the area under the curve values (AUC) to determine the predictive ability of each score. Results: 46 patients fulfilled the inclusion criteria, of which 34 had ADAMTS13 activity levels of ＜10%. When the patients were divided into intermediate-to-high risk (scores 5‒7) and low risk (scores 0‒4), the PLASMIC score showed a sensitivity of 97.1% and specificity of 58.3%, with a positive predictive value (PPV) of 86.8% and negative predictive value (NPV) of 87.5%. The PLASMIC-LDH score had a sensitivity of 97.1% and specificity of 33.3%, with a PPV of 80.5% and NPV of 80.0%. Conclusion Our study validated the utility of the PLASMIC score, and demonstrated PLASMIC-LDH as a reasonable alternative in the absence of traditional lysis markers, to help identify high-risk patients for treatment via plasma exchange.