인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Endometrial cancer (EC) rates are continuing to rise and it remains the most common gynecologic cancer in the US. Existing diagnostic methods are invasive and can cause pain and anxiety. Hence, there is a need for less invasive diagnostics for early EC detection. The study objective was to evaluate the utility of growth factors collected through minimally invasive cervicovaginal lavage (CVL) sampling as diagnostic and prognostic biomarkers for EC. CVL samples from 192 individuals undergoing hysterectomy for benign or malignant conditions were collected and used to quantify the concentrations of 19 growth and angiogenic factors using multiplex immunoassays. Patients were categorized based on disease groups: benign conditions (n = 108), endometrial hyperplasia (n = 18), and EC (n = 66). EC group was stratified into grade 1/2 endometrial endometrioid cancer (n = 53) and other EC subtypes (n = 13). Statistical associations were assessed using receiver operating characteristics, Spearman correlations and hierarchical clustering. Growth and angiogenic factors: angiopoietin-2, endoglin, fibroblast activation protein (FAP), melanoma inhibitory activity, and vascular endothelial growth factor-A (VEGF-A) were significantly (p < 0.0001) elevated in EC patients. A multivariate model combining 11 proteins with patient age and body mass index exhibited excellent discriminatory potential (area under curve = 0.918) for EC, with a specificity of 90.7% and a sensitivity of 87.8%. Moreover, angiopoietin-2, FAP and VEGF-A significantly (p < 0.05-0.001) associated with tumor grade, size, myometrial invasion, and mismatch repair status. Our results highlight the innovative use of growth and angiogenic factors collected through CVL sampling for the detecting endometrial cancer, showcasing not only their diagnostic potential but also their prognostic value.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.