Biology subjects

Tsai, H.-F.

Publications and source records attributed to Tsai, H.-F..

3 recordsLinked to original sources

bioRxiv2020

Voltage-gated ion channels mediate the electrotaxis of glioblastoma cells in a hybrid PMMA/PDMS microdevice

Transformed astrocytes in the most aggressive form cause glioblastoma, the most common cancer in central nervous system with high mortality. The physiological electric field by neuronal local field potentials and tissue polarity may guide the infiltration of glioblastoma cells through the electrotaxis process. However, microenvironments with multiplex gradients are difficult to create. In this work, we have developed a hybrid microfluidic platform to study glioblastoma electrotaxis in controlled microenvironments with high through-put quantitative analysis by a machine learning-powered single cell tracking software. By equalizing the hydrostatic pressure difference between inlets and outlets of the microchannel, uniform single cells can be seeded reliably inside the microdevice. The electrotaxis of two glioblastoma models, T98G and U-251MG, require optimal laminin-containing extracellular matrix and exhibits opposite directional and electro-alignment tendencies. Calcium signaling is a key contributor in glioblastoma pathophysiology but its role in glioblastoma electrotaxis is still an open question. Anodal T98G electrotaxis and cathodal U-251MG electrotaxis require the presence of extracellular calcium cations. U-251MG electrotaxis is dependent on the P/Q-type voltage-gated calcium channel (VGCC) and T98G is dependent on the R-type VGCC. U-251MG and T98G electrotaxis are also mediated by A-type (rapidly inactivating) voltage-gated potassium channels and acid-sensing sodium channels. The involvement of multiple ion channels suggests that the glioblastoma electrotaxis is complex and patient-specific ion channel expression can be critical to develop personalized therapeutics to fight against cancer metastasis. The hybrid microfluidic design and machine learning-powered single cell analysis provide a simple and flexible platform for quantitative investigation of complicated biological systems.

cell biology↗

bioRxiv2019

Usiigaci: Instance-aware cell tracking in stain-free phase contrast microscopy enabled by machine learning

Stain-free, single-cell segmentation and tracking is tantamount to the holy grail of microscopic cell migration analysis. Phase contrast microscopy (PCM) images with cells at high density are notoriously difficult to segment accurately; thus, manual segmentation remains the de facto standard practice. In this work, we introduce Usiigaci, an all-in-one, semi-automated pipeline to segment, track, and visualize cell movement and morphological changes in PCM. Stain-free, instance-aware segmentation is accomplished using a mask regional convolutional neural network (Mask R-CNN). A Trackpy-based cell tracker with a graphical user interface is developed for cell tracking and data verification. The performance of Usiigaci is validated with electrotaxis of NIH/3T3 fibroblasts. Usiigaci provides highly accurate cell movement and morphological information for quantitative cell migration analysis.

bioinformatics↗

bioRxiv2018

Targeting BMI1 and MCL1 for Lung Adenocarcinoma Treatment

Lung cancer is the leading cause of cancer-associated death worldwide. Early metastasis and the recurrence remain major challenges for lung cancer treatment in clinic. Targeting the cancer stemness could be a potential strategy to restrain tumor progression. In the current study, we found that in lung adenocarcinoma (LAC), BMI1 and MCL1 play crucial roles in invasion, chemo-resistance, and tumor initiation. JNK signaling is a link between oncogenic pathway or environment stress to cancer stemness. The activation of JNK, either by EGFR or chemotherapy agent, stabilized BMI1 and MCL1 proteins through suppressing the expression of E3-ubiquitin ligase HUWE1. In lung cancer patient samples, high level of BMI1 is correlated with poor survival, and the expression of BMI1 is positively correlated with MCL1. A novel small-molecule BI-44 was synthesized, which effectively suppressed BMI1/MCL1 expression and inhibited tumor formation and progression in preclinical models. Targeting BMI1/MCL1 provides the basis for a new therapeutic approach in the treatment of LAC.

cancer biology↗