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
Nature Reviews Genetics,2018
*2. High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq Using
Drop-Based
Microfluidics, May 22, Plos One, 2015.
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; 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
