Release date: 2017-12-08
The research team of the Korea Advanced Institute of Science and Technology (KAIST) identified the genetic network principles of colon tumorigenesis. These principles will be used in the future to find molecular targets for effective anticancer drugs. Moreover, this research has attracted people's attention because of the use of systems biology, which is precisely the comprehensive research field of biotechnology (BT) and information technology (IT).
The research team led by Professor Kwang Hyun Cho of the KAIST Department of Biology and Brain Engineering successfully conducted the study; the researchers included Dr. Dongkwan Shin and student researchers Jonghoon Lee and Jeong Ryeol Gong. On November 2nd, Nature Communications magazine published the results of the study online.
Human cancer is caused by genetic mutations. The frequency of gene mutations varies by cancer type—for example, there are only about 10 mutations in leukemia and childhood cancer; but there are an average of 50 mutations in adult solid cancer; cancer caused by external factors even Contains hundreds of mutations (such as lung cancer).
Cancer researchers around the world are working to identify genetic mutations that are often found in patients, and to discover important cancer-inducing genes (called "drivers") that are used to develop targets for anticancer drugs. However, genetic mutations not only affect their own functions, but also affect other genes through interactions. Therefore, current treatments are limited to targeting a small number of cancer-inducing genes without further understanding of the gene network, so current drugs are only effective in a small number of patients and often lead to drug resistance.
Professor Cho's team used large-scale genomic data from cancer patients to establish mathematical models of the synergistic effects of multiple gene mutations in gene interaction networks. The model is based on the Cancer Genomic Atlas (TCGA) proposed by the International Union of Cancer Genome. The team successfully quantified the effects of gene network mutations on colon cancer patient populations through clinical features.
Moreover, the researchers used large-scale computer simulation analysis to identify key transition phenomena in the process of tumorigenesis, which is the first hidden genetic network principle identified. A critical phase transition is a phenomenon in which a substance suddenly changes through a phase transition. In the past, people were unable to determine whether there was a conversion phenomenon because it was difficult to track the sequence of a genetic mutation during tumorigenesis. The team used a system biology-based approach to find that if the known "driver gene" mutations follow closely, the colon cancer tumor formation will show a key transition phenomenon. Using a self-developed mathematical model, the research team may have developed a new anti-cancer targeted drug that is most effective in suppressing the effects of many genetic mutations found in cancer patients. In particular, researchers can not only evaluate "drivers" but also other "passenger genes" that are affected by genetic mutations in order to find the most effective drug targets.
Professor Cho said: "People know little about the role of many gene mutations in tumorigenesis," he continued. "In this study, systems biology methods first discovered the principles of gene networks, from a new perspective. The possibility of target recognition of anticancer drugs.†The study was funded by the Ministry of Science and ICT and the National Research Foundation of Korea (NRF).
Source: Korea Institute of Science and Technology
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