Standardization of human stem cell pluripotency using bioinformatics presentation 1
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After being induced, iPSC should be tested for their proficiency as an embryonic stem cell. This presentation provide a tool of one of the approaches used.
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surrounding non-transformed cells. It contains immune cells, signaling molecules,
stromal and extracellular matrix. Research has shown the TME is often associated
with tumor growth. However, the function and regulatory mechanism of each
constituent is still poorly understood. The presence of PD-L1 is a promising marker
to predict positive response for T cell checkpoint therapy. Current IHC methods to
measure PD-L1 are subjective and highly variable. A higher-throughput and
standardized method that can systematically measure gene expression of cells
present in the TME has emerged to be a more desirable solution.
We applied the OncomineTM Immune Response Research Assay to measure the
expression of 395 genes in non-small cell lung cancer (NSCLC) research samples
from 40 matched FFPE and fresh frozen sample types. This assay covers genes
involved in checkpoint pathway, T cell regulation, cytokine and interferon signaling
pathways, and markers of different tumor infiltrating lymphocyte (TIL) subsets, as
well as tumor markers. With an input requirement of 10 ng of total RNA, libraries
were generated, templated on the Ion ChefTM and sequenced on the Ion S5TM
System. Sequencing data was analyzed and mapped with Torrent Suite Software
and differential expression analysis was conducted with AffymetrixTM Transcriptome
Analysis Console.Encode jc 20130412
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium. Nature (6 September 2012)
A journal club presentation
JoB spike in manuscript 2014
This document discusses how normalization methods for gene expression measurements that assume equal cellular RNA content across experimental conditions can mask differences in total RNA yield per cell. The authors demonstrate that total RNA yield from Chinese Hamster Ovary (CHO) cells varies between experimental treatments and cell lines expressing recombinant proteins. They apply a normalization method using synthetic spike-in RNA standards added proportionally to cell number, which reveals differences in cellular RNA content and allows detection of global transcriptional amplification or repression. They use this method to assess gene expression in CHO cell lines of different sizes treated with cell cycle or mTOR inhibitors, or subjected to high osmolarity conditions. They find that a cell cycle inhibitor increases cell size and transcriptional amplification, an mTOR inhibitor causes
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Standardization of human stem cell pluripotency using bioinformatics presentation 1
- 1. Standardization of human stem cell pluripotency using bioinformatics A review paper in stem cell research & therapy Bader Al Alwan
- 2. In this review Technologies currently being used to produce standardized, high-quality stem cells Assays for pluripotency using bioinformatics and gene expression profiling A number of approaches that promise to improve unbiased prediction of utility of iPSCs and ESCs
- 3. Introduction Four TF (Oct4, KLf4, Sox2 and c-Myc) were sufficient to convert adult cells into iPSCs; Takahashi and Yamanaka. Then, a number of studies emerged illustrating the potency of these cells to differentiate into various progenitors. The generation of iPSCs raised: - Epigenetic and gene expression changes - Highly variable population of reprogramming states - Can generate inefficient and highly variable yield observed during iPSCs generation. How iPSCs behave in functional assays compared to ESCs, and how their quality and uniformity been efficiently tested?
- 4. Bioinformatic assays for pluripotency There has been a much progress in developing genome-wide assays and associated bioinformatic methods The global analysis of the epigenome Analysis of various non-coding RNAs
- 5. Gene Expression Profiling DNA microarray was the first method of global molecular analysis used PluriTest, an algorithm that construct bioinformatic models for assessing the quality of novel pluripotent stem cells only on DNA microarray gene expression measurement
- 6. Epigenetic Profiles Understanding the epigenetic landscape that is common to both systems (iPSCs & ESCs) and connect it to gene regulation - ChIP - Genome-wide methylation - Combining methylation mapping and gene expression signatures by algorithm
- 7. The Scorecard Approach An additional approach that combines gene expression and epigenetic measures with an in vitro differentiation assay - Comparison of DNA methylation and gene expression profiles with reference standard hESC - Testing each gene whether or not its DNA methylation and gene expression levels fall within the range observed among ES cell lines - Genes outside of this range are flagged - The number and identity of these outlier genes are tracked for each iPSC line - The results of the outlier detection are summarized as a “deviation scorecard”
- 9. Conclusion