Glioma-on-a-Chip Models

Abstract

Glioma, as an aggressive type of cancer, accounts for virtually 80% of malignant brain tumors. Despite advances in therapeutic approaches, the long-term survival of glioma patients is poor (it is usually fatal within 12–14 months). Glioma-on-chip platforms, with continuous perfusion, mimic in vivo metabolic functions of cancer cells for analytical purposes. This offers an unprecedented opportunity for understanding the underlying reasons that arise glioma, determining the most effective radiotherapy approach, testing different drug combinations, and screening conceivable side effects of drugs on other organs. Glioma-on-chip technologies can ultimately enhance the efficacy of treatments, promote the survival rate of patients, and pave a path for personalized medicine. In this perspective paper, we briefly review the latest developments of glioma-on-chip technologies, such as therapy applications, drug screening, and cell behavior studies, and discuss the current challenges as well as future research directions in this field.

Deep Learning-Enabled Technologies for Bioimage Analysis

“…Microfluidics allows for multiplexing biotechnological techniques and enabling applications ranging from single-cell analysis [60][61][62][63][64] to on-chip applications [65,66]. It is commonly used in biomedical and chemical research [67][68][69][70][71][72][73] to transcend traditional tech- Five popular deep CNNs for feature extraction and classification purposes are AlexNet, visual geometry group network (VGGNet), GoogLeNet, U-Net, and residual network (ResNet) [55].…”

“…Microfluidics allows for multiplexing biotechnological techniques and enabling applications ranging from single-cell analysis [60][61][62][63][64] to on-chip applications [65,66]. It is commonly used in biomedical and chemical research [67][68][69][70][71][72][73] to transcend traditional techniques with the capability of trapping, aligning, and manipulating single cells for cell combination [74], phenotyping [75][76][77], cell classification [78][79][80][81], and flow-based cytometry [82][83][84], cell capture [85,86], such as circulating tumor cells [87], and cell motility (e.g., sperm movement [88,89], mass [90], and volume sensing [91]).…”

Biomedical Applications of Magnetic Levitation

“…[122] Furthermore, 3D bioprinting is an emerging method for the rapid prototyping of perfusable, complex 3D bioconstructs (ranging from organ-on-chip to full-scale organs). [123][124][125][126] However, due to the high shear stress or intense light exposure, retaining cell viability during the printing process is challenging. [124,127] [115] Reproduced with permission.…”

“…[134] A number of viable methods to decrease the equilibrium time are the following: increasing the magnetic field strength, augmenting the concentration of the paramagnetic medium, decreasing the working temperature, reducing the distance traveled by the objects during levitation (i.e., smaller MagLev platforms), and gentle injection of objects into the medium to prevent dispersion. [134] In addition, the integration of MagLev with microfluidic chips [136][137][138][139][140][141] and multiplexed biomedical platforms [126,[142][143][144][145] enables the development of flow-assisted devices for real-time monitoring and continuous separation of samples.…”

Editorial for the Special Issue on Microfluidic Brain-on-a-Chip

“…Needless to say, these investigations will lead to novel therapeutics and diagnostics approaches as it is also clearly laid out by Ustun et al [ 33 ] in their contribution to brain tumor modeling on chips.…”