m+Medelevator.RU
← Поиск публикаций
Nigerian journal of clinical practice · 2024

Potential of AKNA as a Predictive Biomarker for Ovarian Cancer and Its Relationship to Tumor Grading.

СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Rustamadji P, Wiyarta E, Miftahuzzakiyah M, Sukmawati D, Suryandari D A, Kodariah R

Аннотация

BACKGROUND: Ovarian cancer exhibits a significant prevalence and incidence on a global scale. Low-grade or high-grade epithelial-type ovarian cancer can be classified by using the dualistic model. Inflammation has been associated with AKNA protein by cancer researchers. The potential of AKNA as a cancer biomarker is supported by its significance and association with ovarian carcinoma. Uninvestigated is this enormous potential.

AIM: This study examines the correlation between AKNA expression in low-grade and high-grade ovarian tumors and its utility as a predictive biomarker for ovarian cancer.

METHODS: This study examined a total of thirty-one samples, which were classified into three groups: cyst, low-grade, and high-grade ovarian carcinoma. The departmental archive was accessed for the following information: age, tumor size, nuclear grade, mitosis, ovary volume, implant tumor status, lymph vascular invasion status, lymph node metastasis, and tumor-infiltrating lymphocyte. The expression of AKNA was determined using IHC staining. The information was collected and analyzed via analysis of variance.

RESULTS: The AKNA H-score shows the mean difference between all three groups (P < 0.001). Cysts had the highest AKNA expression, followed by low-grade and high-grade ovarian carcinoma.

CONCLUSION: Higher-grade ovarian cancer expressed less AKNA compared to cysts or low-grade forms of the disease. This considerable difference suggests that AKNA might predict ovarian cancer tumor grade.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты