James Noh, CEO
Seoul, South Korea
Hanyang University Website
A research team from Hanyang University in South Korea has developed a new technology for discovering therapeutic target genes for individual cancer patients with a genome-wide quantitative evaluation.
A research team from Hanyang University in South Korea has developed a new technology for discovering therapeutic target genes for individual cancer patients with a genome-wide quantitative evaluation. The team is seeking industrial partners for technical cooperation agreements to further development of the new diagnostic kits and bring it to the market.
Description of Technology
Anticancer drugs have been developed based on some select genes as the therapeutic target of general patients of specific cancer. However, the efficacy of the treatment tends to depend on the disease state of individual patients.
For the next level of personalized medicine, we provide two novel indicators of genomic states of individual cancer patients – the log-odds ratio of transcriptional states(LOR) and the genomic modular sample probability (MSP).
LOR reports a degree of transformation of the gene activity between cancerous tissue and normal tissue. For example, LORs were very low at most genes in mild cases of breast cancer but significantly larger at some particular genes in severe cases, where it is not probable to recognize the mild and severe cases with gene expression data ab initio. LORs of some oncogenes or tumor suppressor genes were highly deviated from the normal in severe cases but close to the normal in mild cases. Not only the degree of transformation of the gene activity varies with patients, but also the range of variation depends on genes. Therefore, therapeutic cancer targets can be discovered by a genome-wide analysis based on the disease characteristics of individual patients, rather than designated based on the general characteristics of cancer or cancer subtypes.
MSP reports a degree of transformation of a genomic module that defines the biological function in the genome. Each patient’s MSP pattern over genomic modules shows the disease characteristics of the patient. For example, in some severe cases of breast cancer was identified an extensive transformation of genomic modules for cell cycle regulation, those for the immune system, and those specifically activated in normal epithelial cells and stromal cells (Patient #4). Some other severe cases showed a minor transformation of the cell-cycle regulatory modules but a significant transformation of the other genomic modules (Patient #18). In contrast, most mild cases rarely showed a substantial transformation of any genomic module (Patient #41). The MSP datasets collected from a large group of patients are useful in classifying patients based on the genomic subtypes and can help with precision medicine.
MSPs of breast cancer patients
(A) Two severe case (Patient #4 and Patient #18) have different MSP patterns on genomic modules for cell cycle regulation.
Patient #4: severe case, ER (-)
Patient #18: severe case, ER (+)
Patient #41: mild case
Type of Business Relationship Sought
Out license, Partnership
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