Cancer Stem Cells (CD44+/CD24−), RAD6, DDB2 Immunohistochemistry Expression and IHC-UNEDO Scoring System As Predictor of Ovarian Cancer Chemoresistance

Autor: Sihombing, Unedo Hence Markus, Andrijono, Andrijono, Purwoto, Gatot, Gandamihardja, Supriadi, Harahap, Alida R., Rustamadji, Primariadewi, Kekalih, Aria, Widyawati, Retno, Fuady, Dzicky Rifqi
Zdroj: The Journal of Obstetrics and Gynecology of India; June 2024, Vol. 74 Issue: 3 p236-242, 7p
Abstrakt: Backgrounds: Ovarian cancer is a deadly women cancer with many chemoresistance after standard treatment. Ovarian cancer tissues’ CD44+/CD24−(CSCs), RAD6 overexpression and DDB2 underexpression are associated with chemoresistance, recurrence, and poor prognosis of the disease because of the existence of cancer stem cells (CSCs). We tried to analyze the expression of those three proteins while building a predictor scoring system to predict the ovarian cancer chemoresistance from the ovarian cancer tissue immunohistochemistry. Materials and Methods: We conducted a cohort study of 64 patients divided into two groups (32 patients in each group) at the Cipto Mangunkusumo, Tarakan, Dharmais, and Fatmawati Hospital which are located in Jakarta city, Indonesia. The patients underwent cytoreductive debulking and histopathological examination continued by six series of chemotherapy followed by six months of observation. We divided the groups into chemoresistant and chemosensitive by using Response Criteria in Solid Tumors (RECIST) criteria. Ovarian cancer tissue immunohistochemistry tests were then performed to count the CSCs, RAD6 and DDB2 expressions. Results: We found relationship between increased CSCs, RAD6 and reduced DDB2 (p< 0.05) expression in ovarian cancer tissue with the chemoresistance. A possible predictor scoring system named IHC-UNEDO scoring was built to aid the ovarian cancer chemoresistance prediction. Conclusions: The conclusion is that CSCs, RAD6 and DDB2 expressions are significantly associated with ovarian cancer chemoresistance, and IHC-UNEDO scoring should be considered as a tool to predict ovarian cancer chemoresistance.
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