Ovarian cancer 'Anti-cancer drug resistance prediction and treatment'Expected improvement of patient survival rate
Sep 09, 2024
Professor Song Yong-sang's team at Myongji Hospital developed the only way to predict the resistance of anticancer drugs in ovarian cancer patients and link them to practical treatment.
When anticancer drug resistance occurs, the therapeutic effect decreases, and it can lead to recurrence, metastasis, and side effects. Therefore, if a customized treatment plan is established by predicting different anticancer drug resistance for each patient, it is expected to change the treatment paradigm, such as increasing the treatment effect and reducing the cost with optimal drug selection.
The study (Tailored Chemistry: Innovative Deep-Learning Model Predicting Chemistry Response for High-Grade Serious Ovarian Carcinoma) was jointly conducted by Professor Song Yong-sang, Kim Hee-yeon, Cho Hyun-ah, Lee Ju-won, Seoul National University Professor Kim Se-ek, Professor Ahn Tae-jin of Handong University, and Dr. Ahn Eun-young's team, an international SCI journal, in the September issue of Clinical and Translational Medicine.
The study on predicting anticancer drug resistance was targeted at first-line adjuvant chemotherapy, which is platinum-based chemotherapy. The research team selected 31 important genes by analyzing three genetic data obtained from Korea, North America, and Europe, and analyzed resistance to anticancer drugs using AI analysis techniques, deep neural network models, and ensemble strategies.
As a result, we have developed a model with 85% predictive accuracy of anticancer drug resistance (100% resistance predictive sensitivity), which will provide a customized treatment plan with high treatment effect and minimal side effects for ovarian cancer patients.
In particular, major pathways included in genes such as TP53, E2F1, E2F4, HDAC1, HDAC2, and MYC1 are expected to play an important role in predicting the mechanism of chemical resistance, which will have a positive impact on the development of new drugs in the future.
Clinical trials will also be conducted based on the research. The clinical trial will focus on Professor Song Yong-sang of Myongji Hospital and Professor Kim Jae-hoon of Gangnam Severance Hospital. ▲ Professor Lee Yeon-ji of Myongji Hospital ▲ Professor Heo Soo-young of the Catholic University Medical School ▲ Professor Lim Myeong-cheol of the National Cancer Center ▲ Professor Lee Jae-kwan of Korea University Medical School ▲ Professor Lee Jung-won of Samsung Seoul Hospital ▲ Professor Roh Jae-hong of Bundang Seoul National University Hospital, Professor Seo Dong-hoon ▲ Professor Imaria of Seoul National University Hospital and Professor Kim Se-ik ▲ Professor Lee Jung-yoon of Severance Hospital ▲ Professor Park Jeong-ryeol of Hyundai.
In addition, precision medical device companies Foretell My Health (CEO Ahn Tae-jin, CTO Ahn Eun-yong) and Meteo Biotech (CEO Lee Choong-won, CTO Lee Soo-min) plan to improve clinical trial accuracy and lay the groundwork for realization of customized treatment by supporting CosmoSort technology that predicts immune treatment effects by analyzing liquid biopsy precision medical technology and cancer cell-immune cell interactions.
Professor Song Yong-sang, director of the Ovarian Cancer and Gynecological Cancer Center, said, "The development of diagnostic methods for resistance to ovarian cancer will be an important turning point and a new paradigm for early diagnosis and customized treatment of ovarian cancer. We expect such research and technological advancements to be not only a medical innovation, but also an opportunity to bring new hope to patients and their families."," he said.
When anticancer drug resistance occurs, the therapeutic effect decreases, and it can lead to recurrence, metastasis, and side effects. Therefore, if a customized treatment plan is established by predicting different anticancer drug resistance for each patient, it is expected to change the treatment paradigm, such as increasing the treatment effect and reducing the cost with optimal drug selection.
The study (Tailored Chemistry: Innovative Deep-Learning Model Predicting Chemistry Response for High-Grade Serious Ovarian Carcinoma) was jointly conducted by Professor Song Yong-sang, Kim Hee-yeon, Cho Hyun-ah, Lee Ju-won, Seoul National University Professor Kim Se-ek, Professor Ahn Tae-jin of Handong University, and Dr. Ahn Eun-young's team, an international SCI journal, in the September issue of Clinical and Translational Medicine.
The study on predicting anticancer drug resistance was targeted at first-line adjuvant chemotherapy, which is platinum-based chemotherapy. The research team selected 31 important genes by analyzing three genetic data obtained from Korea, North America, and Europe, and analyzed resistance to anticancer drugs using AI analysis techniques, deep neural network models, and ensemble strategies.
As a result, we have developed a model with 85% predictive accuracy of anticancer drug resistance (100% resistance predictive sensitivity), which will provide a customized treatment plan with high treatment effect and minimal side effects for ovarian cancer patients.
In particular, major pathways included in genes such as TP53, E2F1, E2F4, HDAC1, HDAC2, and MYC1 are expected to play an important role in predicting the mechanism of chemical resistance, which will have a positive impact on the development of new drugs in the future.
Clinical trials will also be conducted based on the research. The clinical trial will focus on Professor Song Yong-sang of Myongji Hospital and Professor Kim Jae-hoon of Gangnam Severance Hospital. ▲ Professor Lee Yeon-ji of Myongji Hospital ▲ Professor Heo Soo-young of the Catholic University Medical School ▲ Professor Lim Myeong-cheol of the National Cancer Center ▲ Professor Lee Jae-kwan of Korea University Medical School ▲ Professor Lee Jung-won of Samsung Seoul Hospital ▲ Professor Roh Jae-hong of Bundang Seoul National University Hospital, Professor Seo Dong-hoon ▲ Professor Imaria of Seoul National University Hospital and Professor Kim Se-ik ▲ Professor Lee Jung-yoon of Severance Hospital ▲ Professor Park Jeong-ryeol of Hyundai.
In addition, precision medical device companies Foretell My Health (CEO Ahn Tae-jin, CTO Ahn Eun-yong) and Meteo Biotech (CEO Lee Choong-won, CTO Lee Soo-min) plan to improve clinical trial accuracy and lay the groundwork for realization of customized treatment by supporting CosmoSort technology that predicts immune treatment effects by analyzing liquid biopsy precision medical technology and cancer cell-immune cell interactions.
Professor Song Yong-sang, director of the Ovarian Cancer and Gynecological Cancer Center, said, "The development of diagnostic methods for resistance to ovarian cancer will be an important turning point and a new paradigm for early diagnosis and customized treatment of ovarian cancer. We expect such research and technological advancements to be not only a medical innovation, but also an opportunity to bring new hope to patients and their families."," he said.
|
bellho@sportschosun.com
