Browsing by Subject "cancer stem cells"

High-grade serous carcinoma (HGSC) is the most common and lethal subtype of ovarian cancer. To date, HGSC has typically been diagnosed late, and the survival rate is poor. Relapses are common despite standardised treatment options, and platinum-based chemotherapy resistance remains frequent. The tumours are generally heterogeneous, which makes HGSC complex. Molecular mechanisms of tumour initiation, progression and chemoresistance are insufficiently understood. Thus, efficacious treatment is challenging, and current options do not help some patients. In addition, a population of cancer cells having stem cell-like properties are suggested to play a role in tumour initiation, progression and chemoresistance. There is an urgent need to better understand prognostic biomarkers and treatment responses in HGSC. With diverse analytical methods, the treatment-unresponsive patients and their outcomes could be identified by predictive biomarkers. This thesis aimed to validate potential tissue biomarkers associated with cancer stem cells and poor prognosis in HGSC, evaluate the usability of the RNAscope technique and briefly review the hypotheses on cancer stem cells. Four putative biomarkers were studied: ALDH1A1, BMI1, MYC and SOX2. The RNAscope technique was used to detect and quantify the biomarker expression. Using diagnostic tumour tissue specimens from 95 patients allowed capturing the expression in situ. With comprehensive clinical information, we could test whether the biomarkers distinguished patients with similar background information but different outcomes. This thesis shows that BMI1 could be a potential prognostic biomarker in high-grade serous carcinoma. The results provide information about the expression patterns of previously identified potential HGSC stemness markers. Proteomics studies such as immunohistochemistry could provide complementary information. When the molecular mechanisms and prognostic markers are better understood, they will provide a promising opportunity to develop novel diagnostic methods for predicting the outcomes and deciding treatments for this complex disease.