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Laboratory Introduction

Laboratory of Gynecological Oncology

Laboratory of Gynecological Oncology
The Laboratory of Gynecologic Oncology is located at the Cancer Research Institute, Seoul National University. Our laboratory mainly focuses on gynecologic malignancies-related researches under the leadership of Professor Yong Sang Song. We are studying the tumor microenvironment, drug resistance, clinical biomarker discovery of ovarian cancer by utilizing various experimental models and methods including organoids, multi-omics analysis and deep learning models. We have built a wide international multi-center network using a large number of clinical samples and data, enabling high-level brokerage research using big data. As of 2021, two full-time doctors, four doctoral students, and multi-institution joint research teams, led by Professor Song Yong-sang, are participating in research activities based on their respective specialties.
Related Researcher
송용상

Yong-Sang Song Professor

Research topics

(1) Tumor microenvironment in ovarian cancer - Tumor microenvironment plays a vital role in the resistance of anti-cancer drugs. Our lab is working on the ovarian cancer tumor microenvironment using clinical samples from Seoul National University Hospital. - Immune cells, fat stem cells (ASC), fibroblast, cancer stem cells (CSC) isolated from clinical samples, e.g., malignant ascites, cancer tissue, are used for multi-omics analysis. We are also studying exosomes secreted by cells under hypoxic conditions on metastasis and anti-cancer drug resistance of ovarian cancer. (2) Ovarian cancer organoid model - Various experimental models using ovarian spheroids and ovarian organoids have been built besides conventional 2D cell line culture models. Patient-derived ovarian cancer organoids can better mimic the in vivo microenvironment and well preserve the tumoral heterogeneity. (3) Multi-omics analysis for the development of diagnostic and predictive models - We are developing various algorithms and models using a variety of omics data (genomics, transcriptomics, proteomics, metagenomics) for cancer diagnosis, drug response monitoring and prognosis prediction using ovarian cancer patient clinical samples. In addition, in-depth analysis of intercellular interactions using single-cell sequencing is also being carried out. (4) Exosomes in liquid biopsy - Exosomes are emerging as crucial clinical biomarkers in liquid biopsy. Ascites and blood are the most representative and accessible sources for liquid biopsy of ovarian cancer. We are now studying exosomes derived from ascites and blood featuring miRNAs, proteomics and microbiomes to investigate significant clinical biomarkers in ovarian cancer diagnosis and prediction prognosis. (5) Obesity - The effect of phytochemicals on the differentiation of adipocyte-derived stem cells is also being investigated. Big data from NHI is now being used for various researches to explore risk factors for obesity, chronic diseases and cancer, etc.

Research goals
Our laboratory is conducting basic, clinical translational and clinical researches on cancer metastasis, drug resistance, targeted therapy etc. in ovarian cancer and aims to explore significant biomarkers and therapeutic targets with clinical applicational potential. We are keeping working on improving the survival and life quality of ovarian cancer patients.
Research achievements
Han Y, Kim B, Cho U, Park IS, Kim SI, Dhanasekaran DN, Tsang BK, Song YS. Mitochondrial fission causes cisplatin resistance under hypoxic conditions via ROS in ovarian cancer cells. Oncogene. 2019 Nov;38(45):7089-7105. doi: 10.1038/s41388-019-0949-5. Epub 2019 Aug 13. PMID: 31409904. Wang W, Han Y, Jo HA, Lee J, Song YS. Non-coding RNAs shuttled via exosomes reshape the hypoxic tumor microenvironment. J Hematol Oncol. 2020 Jun 5;13(1):67. doi: 10.1186/s13045-020-00893-3. PMID: 32503591; PMCID: PMC7275461. Wang W, Im J, Kim S, Jang S, Han Y, Yang KM, Kim SJ, Dhanasekaran DN, Song YS. ROS-Induced SIRT2 Upregulation Contributes to Cisplatin Sensitivity in Ovarian Cancer. Antioxidants (Basel). 2020 Nov 16;9(11):1137. doi: 10.3390/antiox9111137. PMID: 33207824; PMCID: PMC7698236. Han Y, Jo H, Cho JH, Dhanasekaran DN, Song YS. Resveratrol as a Tumor-Suppressive Nutraceutical Modulating Tumor Microenvironment and Malignant Behaviors of Cancer. Int J Mol Sci. 2019 Feb 20;20(4):925. doi: 10.3390/ijms20040925. PMID: 30791624; PMCID: PMC6412705. Kim SI, Jung M, Dan K, Lee S, Lee C, Kim HS, Chung HH, Kim JW, Park NH, Song YS, Han D, Lee M. Proteomic Discovery of Biomarkers to Predict Prognosis of High-Grade Serous Ovarian Carcinoma. Cancers (Basel). 2020 Mar 26;12(4):790. doi: 10.3390/cancers12040790. PMID: 32224886; PMCID: PMC7226362. Park Y, Pang K, Park J, Hong E, Lee J, Ooshima A, Kim HS, Cho JH, Han Y, Lee C, Song YS, Park KS, Yang KM, Kim SJ. Destablilization of TRAF6 by DRAK1 Suppresses Tumor Growth and Metastasis in Cervical Cancer Cells. Cancer Res. 2020 Jun 15;80(12):2537-2549. doi: 10.1158/0008-5472.CAN-19-3428. Epub 2020 Apr 7. PMID: 32265222. Asare-Werehene M, Communal L, Carmona E, Han Y, Song YS, Burger D, Mes-Masson AM, Tsang BK. Plasma Gelsolin Inhibits CD8+ T-cell Function and Regulates Glutathione Production to Confer Chemoresistance in Ovarian Cancer. Cancer Res. 2020 Sep 15;80(18):3959-3971. doi: 10.1158/0008-5472.CAN-20-0788. Epub 2020 Jul 8. PMID: 32641415. Kim SI, Kang N, Leem S, Yang J, Jo H, Lee M, Kim HS, Dhanasekaran DN, Kim YK, Park T, Song YS. Metagenomic Analysis of Serum Microbe-Derived Extracellular Vesicles and Diagnostic Models to Differentiate Ovarian Cancer and Benign Ovarian Tumor. Cancers (Basel). 2020 May 21;12(5):1309. doi: 10.3390/cancers12051309. PMID: 32455705; PMCID: PMC7281409. Kim SI, Lee M, Kim HS, Chung HH, Kim JW, Park NH, Song YS. Germline and Somatic BRCA1/2 Gene Mutational Status and Clinical Outcomes in Epithelial Peritoneal, Ovarian, and Fallopian Tube Cancer: Over a Decade of Experience in a Single Institution in Korea. Cancer Res Treat. 2020 Oct;52(4):1229-1241. doi: 10.4143/crt.2020.557. Epub 2020 Jul 27. PMID: 32718143; PMCID: PMC7577800. Kim SI, Song M, Hwangbo S, Lee S, Cho U, Kim JH, Lee M, Kim HS, Chung HH, Suh DS, Park T, Song YS. Development of Web-Based Nomograms to Predict Treatment Response and Prognosis of Epithelial Ovarian Cancer. Cancer Res Treat. 2019 Jul;51(3):1144-1155. doi: 10.4143/crt.2018.508. Epu
  • Han Y, Kim B, Cho U, Park IS, Kim SI, Dhanasekaran DN, Tsang BK, Song YS. Mitochondrial fission causes cisplatin resistance under hypoxic conditions via ROS in ovarian cancer cells. Oncogene. 2019 Nov;38(45):7089-7105. doi: 10.1038/s41388-019-0949-5. Epub 2019 Aug 13. PMID: 31409904.
  • Wang W, Han Y, Jo HA, Lee J, Song YS. Non-coding RNAs shuttled via exosomes reshape the hypoxic tumor microenvironment. J Hematol Oncol. 2020 Jun 5;13(1):67. doi: 10.1186/s13045-020-00893-3. PMID: 32503591; PMCID: PMC7275461.
  • Wang W, Im J, Kim S, Jang S, Han Y, Yang KM, Kim SJ, Dhanasekaran DN, Song YS. ROS-Induced SIRT2 Upregulation Contributes to Cisplatin Sensitivity in Ovarian Cancer. Antioxidants (Basel). 2020 Nov 16;9(11):1137. doi: 10.3390/antiox9111137. PMID: 33207824; PMCID: PMC7698236.
  • Han Y, Jo H, Cho JH, Dhanasekaran DN, Song YS. Resveratrol as a Tumor-Suppressive Nutraceutical Modulating Tumor Microenvironment and Malignant Behaviors of Cancer. Int J Mol Sci. 2019 Feb 20;20(4):925. doi: 10.3390/ijms20040925. PMID: 30791624; PMCID: PMC6412705.
  • Kim SI, Jung M, Dan K, Lee S, Lee C, Kim HS, Chung HH, Kim JW, Park NH, Song YS, Han D, Lee M. Proteomic Discovery of Biomarkers to Predict Prognosis of High-Grade Serous Ovarian Carcinoma. Cancers (Basel). 2020 Mar 26;12(4):790. doi: 10.3390/cancers12040790. PMID: 32224886; PMCID: PMC7226362.
  • Park Y, Pang K, Park J, Hong E, Lee J, Ooshima A, Kim HS, Cho JH, Han Y, Lee C, Song YS, Park KS, Yang KM, Kim SJ. Destablilization of TRAF6 by DRAK1 Suppresses Tumor Growth and Metastasis in Cervical Cancer Cells. Cancer Res. 2020 Jun 15;80(12):2537-2549. doi: 10.1158/0008-5472.CAN-19-3428. Epub 2020 Apr 7. PMID: 32265222.
  • Asare-Werehene M, Communal L, Carmona E, Han Y, Song YS, Burger D, Mes-Masson AM, Tsang BK. Plasma Gelsolin Inhibits CD8+ T-cell Function and Regulates Glutathione Production to Confer Chemoresistance in Ovarian Cancer. Cancer Res. 2020 Sep 15;80(18):3959-3971. doi: 10.1158/0008-5472.CAN-20-0788. Epub 2020 Jul 8. PMID: 32641415.
  • Kim SI, Kang N, Leem S, Yang J, Jo H, Lee M, Kim HS, Dhanasekaran DN, Kim YK, Park T, Song YS. Metagenomic Analysis of Serum Microbe-Derived Extracellular Vesicles and Diagnostic Models to Differentiate Ovarian Cancer and Benign Ovarian Tumor. Cancers (Basel). 2020 May 21;12(5):1309. doi: 10.3390/cancers12051309. PMID: 32455705; PMCID: PMC7281409.
  • Kim SI, Lee M, Kim HS, Chung HH, Kim JW, Park NH, Song YS. Germline and Somatic BRCA1/2 Gene Mutational Status and Clinical Outcomes in Epithelial Peritoneal, Ovarian, and Fallopian Tube Cancer: Over a Decade of Experience in a Single Institution in Korea. Cancer Res Treat. 2020 Oct;52(4):1229-1241. doi: 10.4143/crt.2020.557. Epub 2020 Jul 27. PMID: 32718143; PMCID: PMC7577800.
  • Kim SI, Song M, Hwangbo S, Lee S, Cho U, Kim JH, Lee M, Kim HS, Chung HH, Suh DS, Park T, Song YS. Development of Web-Based Nomograms to Predict Treatment Response and Prognosis of Epithelial Ovarian Cancer. Cancer Res Treat. 2019 Jul;51(3):1144-1155. doi: 10.4143/crt.2018.508. Epub 2018 Nov 20. PMID: 30453728; PMCID: PMC6639233.
  • Hwangbo S, Kim SI, Kim JH, Eoh KJ, Lee C, Kim YT, Suh DS, Park T, Song YS. Development of Machine Learning Models to Predict Platinum Sensitivity of High- Grade Serous Ovarian Carcinoma. Cancers (Basel). 2021 Apr 14;13(8):1875. doi: 10.3390/cancers13081875. PMID: 33919797; PMCID: PMC8070756.
  • Kim S, Han Y, Kim SI, Lee J, Jo H, Wang W, Cho U, Park WY, Rando TA, Dhanasekaran DN, Song YS. Computational modeling of malignant ascites reveals CCL5-SDC4 interaction in the immune microenvironment of ovarian cancer. Mol Carcinog. 2021 May;60(5):297-312. doi: 10.1002/mc.23289. Epub 2021 Mar 15. PMID: 33721368; PMCID: PMC8080545.
  • Kim SI, Lee S, Choi CH, Lee M, Suh DH, Kim HS, Kim K, Chung HH, No JH, Kim JW, Park NH, Song YS, Kim YB. Machine Learning Models to Predict Survival Outcomes According to the Surgical Approach of Primary Radical Hysterectomy in Patients with Early Cervical Cancer. Cancers (Basel). 2021 Jul 23;13(15):3709. doi: 10.3390/cancers13153709. PMID: 34359610; PMCID: PMC8345043.
  • Han Y, Park IS, Kim SI, Wang W, Yoo J, Jo H, Lee J, Seol A, Han KD, Song YS. Increasing serum gamma-glutamyltransferase level accompanies a rapid increase in the incidence of endometrial cancer in Korea: A nationwide cohort study. Gynecol Oncol. 2021 Jun;161(3):864-870. doi: 10.1016/j.ygyno.2021.03.024. Epub 2021 Mar 29. PMID: 33795129.
b 2018 Nov 20. PMID: 30453728; PMCID: PMC6639233. Hwangbo S, Kim SI, Kim JH, Eoh KJ, Lee C, Kim YT, Suh DS, Park T, Song YS. Development of Machine Learning Models to Predict Platinum Sensitivity of High- Grade Serous Ovarian Carcinoma. Cancers (Basel). 2021 Apr 14;13(8):1875. doi: 10.3390/cancers13081875. PMID: 33919797; PMCID: PMC8070756. Kim S, Han Y, Kim SI, Lee J, Jo H, Wang W, Cho U, Park WY, Rando TA, Dhanasekaran DN, Song YS. Computational modeling of malignant ascites reveals CCL5-SDC4 interaction in the immune microenvironment of ovarian cancer. Mol Carcinog. 2021 May;60(5):297-312. doi: 10.1002/mc.23289. Epub 2021 Mar 15. PMID: 33721368; PMCID: PMC8080545. Kim SI, Lee S, Choi CH, Lee M, Suh DH, Kim HS, Kim K, Chung HH, No JH, Kim JW, Park NH, Song YS, Kim YB. Machine Learning Models to Predict Survival Outcomes According to the Surgical Approach of Primary Radical Hysterectomy in Patients with Early Cervical Cancer. Cancers (Basel). 2021 Jul 23;13(15):3709. doi: 10.3390/cancers13153709. PMID: 34359610; PMCID: PMC8345043. Han Y, Park IS, Kim SI, Wang W, Yoo J, Jo H, Lee J, Seol A, Han KD, Song YS. Increasing serum gamma-glutamyltransferase level accompanies a rapid increase in the incidence of endometrial cancer in Korea: A nationwide cohort study. Gynecol Oncol. 2021 Jun;161(3):864-870. doi: 10.1016/j.ygyno.2021.03.024. Epub 2021 Mar 29. PMID: 33795129.
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