Research detection kit NG22306013
for ovarian cancerfor BRAF mutationsfor KRAS mutations

Research detection kit - NG22306013 - SPACEGEN - for ovarian cancer / for BRAF mutations / for KRAS mutations
Research detection kit - NG22306013 - SPACEGEN - for ovarian cancer / for BRAF mutations / for KRAS mutations
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Characteristics

Applications
for research, for ovarian cancer
Tested parameter
for BRAF mutations, for KRAS mutations, for PIK3CA Gene, for BRCA mutations, for PTEN gene, for TP53 gene
Sample type
clinical, cell, tissue
Analysis mode
immunohistochemistry
Result display time

4 h

Description

Ovarian cancer is a malignant tumor that poses a serious threat to women's health. It ranks third in the incidence of malignant tumors in the female reproductive system, following cervical cancer and endometrial cancer, but has the highest mortality rate among female reproductive system malignancies. Ovarian cancer is often referred to as the "silent killer" because when symptoms appear and patients seek medical attention, about 70% of cases are already in advanced stages, resulting in low 5-year survival rates. The most common type of ovarian cancer is epithelial ovarian cancer, accounting for approximately 80% of cases. Epithelial ovarian cancer can be further categorized into serous carcinoma (70-80%), endometrioid carcinoma (10%), clear cell carcinoma (10%), mucinous carcinoma (3%), and other rare types (<5%) based on pathological characteristics. Research has shown that different types of ovarian cancer carry different mutated genes, which can assist in histopathological classification and be used clinically for ovarian cancer risk assessment, optimizing treatment plans, and supporting genetic screening. Furthermore, there is clinical evidence suggesting that molecular subtyping of ovarian cancer can be linked to individualized treatment, leading to improved patient survival rates. It has become an effective approach to guide ovarian cancer treatment. DETECTION SIGNIFICANCE 1.Prognostic Assessment: Ovarian cancer is highly heterogeneous. Accurately classify the tumor tissues and suggest the prognosis of patients according to the molecular characteristics of different tissue subtypes, assisted by morphology and immunohistochemistry.

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