Technology

Background of Transfection Technology

The conventional liquid-phase transfection, in which transfection reagent is added to pre-cultured cells on a device, is problematic in two respects: complicated protocols and; poor transfection efficiency.
To address these, the method of solid-phase transfection, which is designed to achieve transfection by merely culturing cells over genes affixed on solid support of a device, was developed in two main formats: the well format (Homma K et al. BBRC, 2001, 289, 1075-1081) and the microarray format (Ziauddin J and Sabatini DM Nature. 2001, 411, 107-110). However, while protocols are much simpler than its solution-supported counterpart, the solid-phase method was still far from perfect: transfection efficiency still remained poor with many cell strains, significantly limiting the methods practicality.

CytoPathfinder’s breakthrough technology

The innovative solid-phase transfection technology developed by Dr. Masato Miyake, a founding member of CytoPathfinder, dramatically boosts the efficiency of transfection through the use of an extracellular matrix protein* and other substances that accelerate transfection.
The ongoing development of transfection accelerators is expected to further broaden the variety of applicable cell strains, opening up new possibilities for transfection experiments to become a viable option for cells with poor transfection efficiency.
*Transfection acceleration via extracellular matrix protein is considered to be caused by the mechanism through which interaction between nucleus and cell membranes is enhanced by way of intracellular stress fiber induction as trigger. (Yoshikawa T, et. al., J. Control Release, 2004, 96, 227-232; Uchiyama E, et al., Neuroscience Lett., 2005, 378, 40-43)

Diagram of Transfection Array

Applicable cell strains(Example)

As shown below, solid-phase transfection is applicable to established cell lines, primary cells, and mesenchymal stem cells, and many more cell strains.
Moreover, for non-adherent cells, Kato K et al. demonstrated that plasmid DNA (or siRNA) deposited in a defined area on BAM (Biocompatible anchor for membrane)-modified slides was transfected into non-adherent K562 cells (Biotechniques, 2004, 37, 444-452). This suggests that Transfection Array™ is applicable to non-adherent cells as well as adherent ones.

Applicable Cells Source
Cell lines
Hela human cervix carcinoma
T-47D human breast cancer
SK-BR-3 human breast cancer
MCF7 human breast cancer
MDA-MB-231 human breast cancer
MDA-MB-453-S human breast cancer
HEK293, 293T human embryonic kidney
Caco2 adenocarcinoma, colon
HepG2 human hepatocellular carcinoma
NT2 (NTERA-2) human teratocarcinoma
SHSY5Y human neuroblastoma
NIH/3T3, 3T3-L1
PC-12
mouse embryonic fibroblast
rat pheochromocytoma
Normal cells rat brain cortex neuronal cells
primary mouse embryonic fibroblast (MEF)
Human breast cancer cells Mice Bearing human tumor xenografts
Stem cells human mesenchymal stem cell (hMSCs)
mouse neuronal stem cell

Transfection Technology and Applications in R&D Process

The principle of siRNA transfection technology is to silencing gene functions in cells by cutting off the nucleic chain at targeted position, resulting in a loss of function as depicted below. As this technology is applicable to a wide range of mammalian cells (cell line, primary cell, stem cell, iPS cell etc.), we could open the black box of the phenotypic changes of cells caused by a variety of stimulus and thoroughly understand the intracellular gene networks responsible for the changes.

Picture of siRNA transfection and its application in clinical development

Therefore, this technology could be used in every step of drug discovery and development process, such as,

  1. Target identification and validation
  2. Disease mechanism by exploring signaling pathway
  3. Identification of target genes responsible for MOA (mode of action) of a drug (Cellular Pharmacogenomics / Cellular PGx). Improve success rate of clinical study by facilitating PGx.
  4. siRNA medicine though there are number of failure cases reported in clinical trial (need efficient drug delivery system)

siRNA Image

From the view point of business and ROI (Return on Investment), iii) and iv) are assumed to be most attractive for pharma industries with lowest risk and shortest to market. CytoPathfinders recent acquisition of PGXIS was aiming a synergy of the combination of Cellular PGx and PGx in improving the success rate of clinical trials by identifying the genes of drug MOA. As the industrial average of success rate of Phase-I, II and III clinical study is 65%, 35% and 60% respectively, Phase-II step is obviously the process to be improved. Insufficient efficacy is the main reason of failure in Phase-II (52%) and Phase-III (72%). PGx is widely recognized to improve these steps by identifying subpopulation responding to the compounds. On the other hand, cellular PGx can explore the intracellular gene network playing critical role for drug to exert its efficacy by measuring the phenotypic changes in quantitative manner. The key to identify responsible genes for drug action is to narrow down the number of genes from whole genome ca. 23,000 genes. Thus selected genes will facilitate the conventional PGx analysis of clinical data in more confident and efficient manner. Once gene network for drug action is explored, it is applicable to design rational drug combination with existing one or NCEs for the sake of better treatment or conceive alternative indications from the accumulated database.
As the usual Phase-II study takes ca. 18-24 months and the cellular PGx for identifying genes responsible for MOAs takes ca. 6-12 months, drug candidate is better to be profiled before or at Phase-II stage in order to makes the PGx analysis fast and easy rather than spending time in complicated SNP analysis.

Combination of pharmacogenomics and cellular pharmacogenomics
in Phase-II clinical trial is the key to improve its success rate

Phase-II clinical trial Image

Genome-wide PGx depends on the size of well-defined patients population: If the populations is not large enough, readout of signals from the noises is not easy. Biological roles of genes (markers) identified for classification of sub-population are often unclear.

Cellular PGx can narrow down the gene network responsible for MOA of drug by silencing individual genes in genome-wide functional assay. Therefore, the combination of PGx and Cellular PGx is complementary to identify sub-populations responding / not responding to drug.

Genome-wide PGx depends on the size of well-defined patients population: If the populations is not large enough, readout of signals from the noises is not easy. Biological roles of genes (markers) identified for classification of sub-population are often unclear.
Cellular PGx can narrow down the gene network responsible for MOA of drug by silencing individual genes in genome-wide functional assay. Therefore, the combination of PGx and Cellular PGx is complementary to identify sub-populations responding / not responding to drug.
In contrast to the current PGx often using genetic markers to identify responder / non responder to a drug, cellular PGx enables us to clarify why patient responding to drug A and not to drug B by using patients primary cell, such as cancer biopsy sample. Other words, current PGx is to suggesting a drug to be prescribed to the responder but no help for non-responder in spite of the fact that the population of non-responder is much larger than responder. In case of current cancer drugs, Cellular PGx is expected play a critical role in drug discovery for larger market of non-responder either by alternative indication or combo-drug.
In order to profile a compound by three doses with druggable 7,000 genes (x4siRNA/gene) by using patients primary cell, most commonly used 384-well plate format requiring 3,000-5,000 cells/well are far from practice because of the huge number of cell requirement. In this regard, CytoPathfinders proprietary 1536-well plate format (300-500 cells/well) or 3456-well plate format (100-150 cells/well) are best fit for statistical analysis under limited cell resources.

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