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July 28, 2017

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Academia Sinica sets up STOML2 database to allow early diagnosis

TAIPEI, Taiwan -- Academia Sinica yesterday announced the establishment of the world's first STOML2 database that allows hospitals to diagnose colorectal cancer in its early stage.

Chen Yu-ru, the head of the Academia Sinica's Institute of Chemistry, said that her research team worked with Chang Gung Memorial Hospital to analyze both the normal as well as the cancerous tissues of 28 colorectal cancer patients.

Based on the research, Chen said that patients with high STOML2 content have a lower than five-year survival rate, and by using the STOML2 as a marker to analyze patients' blood, the accuracy rate in diagnosing colorectal cancer at its early stage can reach 69 percent.

According to Chen, only liver and prostate cancers can be diagnosed according to the changes of proteomics so far.

"Colorectal cancer has topped the rankings as the most common cancer in Taiwan, and the carcinoembryonic antigen (CEA) indication that is used on cancer patients now can only monitor the result of treatments on patients instead of diagnosing cancer at its early stage," said Chen.

However, Chen added that it will require over 100 cancer patients' samples after repeat examinations in order to make the database usable within four to five years.

According to Chen, by examining a patient's STOML2, it can also help evaluate which medical treatment is most suitable for each cancer patient.

Chen said that the reason why Taiwan can establish the world's first STOML2 database for colorectal cancer is that there is a national health insurance program that registers all information about patients.

According to Chen, many countries have regulations that restrict labs from receiving samples from cancer patients, which gives Taiwan an opportunity to establish the world's first STOML2 database.

Chen said that the research team hopes to apply this method of analysis in diagnosing other cancers and thus to create a database that contains information on proteomics that will help evaluate the cause of cancers, which will in turn greatly benefit the development of cancer treatments.

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