研究興趣

Research Interest:

Recently, the gene expression profiles of stem cells in the lineage stages have been studied by whole genome amplification (WGA) or microarray analysis. Especially in the Embryonic Stem Cell (ESC), the pluripotent cells, has the ability to differentiate into all the derivatives of progenitor cells including the three germ layers. To further comprehend the mechanism of signaling pathways or specific markers under what switches among lineage stages, we can more easily manipulate the individual cell level to induce or reverse it, just known as the iPS. Base on the experimental and bioinformatics analysis, a lot of databases (StemDB, Stem BANCC, Euro-StemCell etc.) are established by collecting this big data for mining the responsive gene expression as a novel and specific biomarker, not only the Oct4, Sox2, Nanog, and need more other surface biomarkers. So one of my interest is to explore that 

     1. Which specific factors can affect the signal pathway for stem cell differention>

      2. Which specific biomarker can be expressed in the distinct progenitor cell type?

    To address this issue, how to combine the experimental and bioinformatics field to predict the new biomarkers or key connectors are still a challenge task. This critical study not only find the comprehensive analysis of gene expression, but also can be applied to tissue engineering in the regenerative medicine for clinical application, such as neural disorder or dementia. My previous work was similar to this related research that injected the neural stem cell to repair the brain injury area.

More than, if once “Single” stem cell can be isolated, subsequent expansion and manipulation in cell culture and experiments could provide the appropriate more information for the differentiation of various cell types. Thus according to this related issue, the multiple points of cell divergence between the differentiated and un-differentiated stage is the top topics to reveal the hidden secrets for stem cell signaling pathway. This prospective progress can also provide in the drug discovery and development of cell-based therapies to treat disease. Recently, developed CTC isolation techniques has also been applied in this area. Researchers discovered that breast cancer, prostate and colorectal cancers patients with fewer CTCs in their blood. Additional studies have analyzed the genetic mutations that the cells carry, comparing the mutations to those in a primary tumor or correlating the findings to a patient’s disease severity. Taken all together, the signal cell can also learn more about the biology of metastasis through CTC analysis that more explore the pharmacodynamic and predictive biomarker utility of CTCs in the future.

Reference 

*1. Single-cell genome sequencing: current sztazte of the science,17,175-188,
      Nature Reviews  Genetics,2018

*2. High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using Drop-Based
       Microfluidics, May 22, Plos One, 2015. 

*3. Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells, 
       May 21; 161(5) :1187-201, Cells, 2015.

*4. Single-cell transcriptomics enters the age of mass production. 

      May 21;58 (4) :563-4, Mol Cell, 2015.

*5. Circulating tumor cells, March 26, vol. 110 no. 13, PNAS, 2013.

*6. Circulating Tumor Cells, Advances in Basic Science and Clinical Applications, Richard 
      J. Cote and Ram H. Datar, Book, 2